storj/go.sum

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cloud.google.com/go v0.26.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw=
cloud.google.com/go v0.31.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw=
cloud.google.com/go v0.34.0/go.mod h1:aQUYkXzVsufM+DwF1aE+0xfcU+56JwCaLick0ClmMTw=
cloud.google.com/go v0.37.0/go.mod h1:TS1dMSSfndXH133OKGwekG838Om/cQT0BUHV3HcBgoo=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
cloud.google.com/go v0.38.0/go.mod h1:990N+gfupTy94rShfmMCWGDn0LpTmnzTp2qbd1dvSRU=
cloud.google.com/go v0.44.1/go.mod h1:iSa0KzasP4Uvy3f1mN/7PiObzGgflwredwwASm/v6AU=
cloud.google.com/go v0.44.2/go.mod h1:60680Gw3Yr4ikxnPRS/oxxkBccT6SA1yMk63TGekxKY=
cloud.google.com/go v0.45.1/go.mod h1:RpBamKRgapWJb87xiFSdk4g1CME7QZg3uwTez+TSTjc=
cloud.google.com/go v0.46.3/go.mod h1:a6bKKbmY7er1mI7TEI4lsAkts/mkhTSZK8w33B4RAg0=
cloud.google.com/go v0.110.2 h1:sdFPBr6xG9/wkBbfhmUz/JmZC7X6LavQgcrVINrKiVA=
cloud.google.com/go v0.110.2/go.mod h1:k04UEeEtb6ZBRTv3dZz4CeJC3jKGxyhl0sAiVVquxiw=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
cloud.google.com/go/bigquery v1.0.1/go.mod h1:i/xbL2UlR5RvWAURpBYZTtm/cXjCha9lbfbpx4poX+o=
cloud.google.com/go/compute v1.19.0 h1:+9zda3WGgW1ZSTlVppLCYFIr48Pa35q1uG2N1itbCEQ=
cloud.google.com/go/compute v1.19.0/go.mod h1:rikpw2y+UMidAe9tISo04EHNOIf42RLYF/q8Bs93scU=
cloud.google.com/go/compute/metadata v0.2.3 h1:mg4jlk7mCAj6xXp9UJ4fjI9VUI5rubuGBW5aJ7UnBMY=
cloud.google.com/go/compute/metadata v0.2.3/go.mod h1:VAV5nSsACxMJvgaAuX6Pk2AawlZn8kiOGuCv6gTkwuA=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
cloud.google.com/go/datastore v1.0.0/go.mod h1:LXYbyblFSglQ5pkeyhO+Qmw7ukd3C+pD7TKLgZqpHYE=
cloud.google.com/go/firestore v1.1.0/go.mod h1:ulACoGHTpvq5r8rxGJ4ddJZBZqakUQqClKRT5SZwBmk=
cloud.google.com/go/iam v0.13.0 h1:+CmB+K0J/33d0zSQ9SlFWUeCCEn5XJA0ZMZ3pHE9u8k=
cloud.google.com/go/longrunning v0.4.1 h1:v+yFJOfKC3yZdY6ZUI933pIYdhyhV8S3NpWrXWmg7jM=
cloud.google.com/go/profiler v0.3.1 h1:b5got9Be9Ia0HVvyt7PavWxXEht15B9lWnigdvHtxOc=
cloud.google.com/go/profiler v0.3.1/go.mod h1:GsG14VnmcMFQ9b+kq71wh3EKMZr3WRMgLzNiFRpW7tE=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
cloud.google.com/go/pubsub v1.0.1/go.mod h1:R0Gpsv3s54REJCy4fxDixWD93lHJMoZTyQ2kNxGRt3I=
cloud.google.com/go/storage v1.0.0/go.mod h1:IhtSnM/ZTZV8YYJWCY8RULGVqBDmpoyjwiyrjsg+URw=
cloud.google.com/go/storage v1.29.0 h1:6weCgzRvMg7lzuUurI4697AqIRPU1SvzHhynwpW31jI=
dmitri.shuralyov.com/app/changes v0.0.0-20180602232624-0a106ad413e3/go.mod h1:Yl+fi1br7+Rr3LqpNJf1/uxUdtRUV+Tnj0o93V2B9MU=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
dmitri.shuralyov.com/gpu/mtl v0.0.0-20190408044501-666a987793e9/go.mod h1:H6x//7gZCb22OMCxBHrMx7a5I7Hp++hsVxbQ4BYO7hU=
dmitri.shuralyov.com/html/belt v0.0.0-20180602232347-f7d459c86be0/go.mod h1:JLBrvjyP0v+ecvNYvCpyZgu5/xkfAUhi6wJj28eUfSU=
dmitri.shuralyov.com/service/change v0.0.0-20181023043359-a85b471d5412/go.mod h1:a1inKt/atXimZ4Mv927x+r7UpyzRUf4emIoiiSC2TN4=
dmitri.shuralyov.com/state v0.0.0-20180228185332-28bcc343414c/go.mod h1:0PRwlb0D6DFvNNtx+9ybjezNCa8XF0xaYcETyp6rHWU=
git.apache.org/thrift.git v0.0.0-20180902110319-2566ecd5d999/go.mod h1:fPE2ZNJGynbRyZ4dJvy6G277gSllfV2HJqblrnkyeyg=
2018-10-06 18:57:53 +01:00
github.com/BurntSushi/toml v0.3.1 h1:WXkYYl6Yr3qBf1K79EBnL4mak0OimBfB0XUf9Vl28OQ=
github.com/BurntSushi/toml v0.3.1/go.mod h1:xHWCNGjB5oqiDr8zfno3MHue2Ht5sIBksp03qcyfWMU=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/BurntSushi/xgb v0.0.0-20160522181843-27f122750802/go.mod h1:IVnqGOEym/WlBOVXweHU+Q+/VP0lqqI8lqeDx9IjBqo=
github.com/Masterminds/semver/v3 v3.1.1/go.mod h1:VPu/7SZ7ePZ3QOrcuXROw5FAcLl4a0cBrbBpGY/8hQs=
github.com/OneOfOne/xxhash v1.2.2/go.mod h1:HSdplMjZKSmBqAxg5vPj2TmRDmfkzw+cTzAElWljhcU=
github.com/VividCortex/ewma v1.2.0 h1:f58SaIzcDXrSy3kWaHNvuJgJ3Nmz59Zji6XoJR/q1ow=
github.com/VividCortex/ewma v1.2.0/go.mod h1:nz4BbCtbLyFDeC9SUHbtcT5644juEuWfUAUnGx7j5l4=
github.com/acarl005/stripansi v0.0.0-20180116102854-5a71ef0e047d h1:licZJFw2RwpHMqeKTCYkitsPqHNxTmd4SNR5r94FGM8=
github.com/acarl005/stripansi v0.0.0-20180116102854-5a71ef0e047d/go.mod h1:asat636LX7Bqt5lYEZ27JNDcqxfjdBQuJ/MM4CN/Lzo=
github.com/ajg/form v1.5.1 h1:t9c7v8JUKu/XxOGBU0yjNpaMloxGEJhUkqFRq0ibGeU=
github.com/ajg/form v1.5.1/go.mod h1:uL1WgH+h2mgNtvBq0339dVnzXdBETtL2LeUXaIv25UY=
github.com/alecthomas/template v0.0.0-20160405071501-a0175ee3bccc/go.mod h1:LOuyumcjzFXgccqObfd/Ljyb9UuFJ6TxHnclSeseNhc=
github.com/alecthomas/units v0.0.0-20151022065526-2efee857e7cf/go.mod h1:ybxpYRFXyAe+OPACYpWeL0wqObRcbAqCMya13uyzqw0=
github.com/alessio/shellescape v1.2.2 h1:8LnL+ncxhWT2TR00dfJRT25JWWrhkMZXneHVWnetDZg=
github.com/alessio/shellescape v1.2.2/go.mod h1:PZAiSCk0LJaZkiCSkPv8qIobYglO3FPpyFjDCtHLS30=
github.com/alicebob/gopher-json v0.0.0-20200520072559-a9ecdc9d1d3a h1:HbKu58rmZpUGpz5+4FfNmIU+FmZg2P3Xaj2v2bfNWmk=
github.com/alicebob/gopher-json v0.0.0-20200520072559-a9ecdc9d1d3a/go.mod h1:SGnFV6hVsYE877CKEZ6tDNTjaSXYUk6QqoIK6PrAtcc=
github.com/alicebob/miniredis/v2 v2.13.3 h1:kohgdtN58KW/r9ZDVmMJE3MrfbumwsDQStd0LPAGmmw=
github.com/alicebob/miniredis/v2 v2.13.3/go.mod h1:uS970Sw5Gs9/iK3yBg0l9Uj9s25wXxSpQUE9EaJ/Blg=
github.com/andybalholm/brotli v1.0.0 h1:7UCwP93aiSfvWpapti8g88vVVGp2qqtGyePsSuDafo4=
github.com/andybalholm/brotli v1.0.0/go.mod h1:loMXtMfwqflxFJPmdbJO0a3KNoPuLBgiu3qAvBg8x/Y=
github.com/anmitsu/go-shlex v0.0.0-20161002113705-648efa622239/go.mod h1:2FmKhYUyUczH0OGQWaF5ceTx0UBShxjsH6f8oGKYe2c=
github.com/antihax/optional v1.0.0/go.mod h1:uupD/76wgC+ih3iEmQUL+0Ugr19nfwCT1kdvxnR2qWY=
github.com/apache/thrift v0.12.0 h1:pODnxUFNcjP9UTLZGTdeh+j16A8lJbRvD3rOtrk/7bs=
github.com/apache/thrift v0.12.0/go.mod h1:cp2SuWMxlEZw2r+iP2GNCdIi4C1qmUzdZFSVb+bacwQ=
github.com/armon/circbuf v0.0.0-20150827004946-bbbad097214e/go.mod h1:3U/XgcO3hCbHZ8TKRvWD2dDTCfh9M9ya+I9JpbB7O8o=
github.com/armon/go-metrics v0.0.0-20180917152333-f0300d1749da/go.mod h1:Q73ZrmVTwzkszR9V5SSuryQ31EELlFMUz1kKyl939pY=
github.com/armon/go-radix v0.0.0-20180808171621-7fddfc383310/go.mod h1:ufUuZ+zHj4x4TnLV4JWEpy2hxWSpsRywHrMgIH9cCH8=
2018-10-06 18:57:53 +01:00
github.com/beorn7/perks v0.0.0-20180321164747-3a771d992973/go.mod h1:Dwedo/Wpr24TaqPxmxbtue+5NUziq4I4S80YR8gNf3Q=
github.com/beorn7/perks v1.0.0/go.mod h1:KWe93zE9D1o94FZ5RNwFwVgaQK1VOXiVxmqh+CedLV8=
github.com/bgentry/speakeasy v0.1.0/go.mod h1:+zsyZBPWlz7T6j88CTgSN5bM796AkVf0kBD4zp0CCIs=
github.com/bketelsen/crypt v0.0.3-0.20200106085610-5cbc8cc4026c/go.mod h1:MKsuJmJgSg28kpZDP6UIiPt0e0Oz0kqKNGyRaWEPv84=
2019-09-20 15:22:40 +01:00
github.com/blang/semver v3.5.1+incompatible h1:cQNTCjp13qL8KC3Nbxr/y2Bqb63oX6wdnnjpJbkM4JQ=
github.com/blang/semver v3.5.1+incompatible/go.mod h1:kRBLl5iJ+tD4TcOOxsy/0fnwebNt5EWlYSAyrTnjyyk=
github.com/bmizerany/assert v0.0.0-20160611221934-b7ed37b82869 h1:DDGfHa7BWjL4YnC6+E63dPcxHo2sUxDIu8g3QgEJdRY=
github.com/bmizerany/assert v0.0.0-20160611221934-b7ed37b82869/go.mod h1:Ekp36dRnpXw/yCqJaO+ZrUyxD+3VXMFFr56k5XYrpB4=
github.com/bmkessler/fastdiv v0.0.0-20190227075523-41d5178f2044 h1:8Rz0TcIbkvU+x53bDQgezQ3tbjrQSpZRr6h9JnR9lZU=
github.com/bmkessler/fastdiv v0.0.0-20190227075523-41d5178f2044/go.mod h1:OI0uaNyGvxANSxteY6/mFRZs9EcQGqK30Bd1wqQj9zQ=
github.com/boombuler/barcode v1.0.1-0.20190219062509-6c824513bacc h1:biVzkmvwrH8WK8raXaxBx6fRVTlJILwEwQGL1I/ByEI=
github.com/boombuler/barcode v1.0.1-0.20190219062509-6c824513bacc/go.mod h1:paBWMcWSl3LHKBqUq+rly7CNSldXjb2rDl3JlRe0mD8=
github.com/bradfitz/go-smtpd v0.0.0-20170404230938-deb6d6237625/go.mod h1:HYsPBTaaSFSlLx/70C2HPIMNZpVV8+vt/A+FMnYP11g=
github.com/bsm/ginkgo/v2 v2.7.0 h1:ItPMPH90RbmZJt5GtkcNvIRuGEdwlBItdNVoyzaNQao=
github.com/bsm/gomega v1.26.0 h1:LhQm+AFcgV2M0WyKroMASzAzCAJVpAxQXv4SaI9a69Y=
github.com/buger/jsonparser v0.0.0-20181115193947-bf1c66bbce23/go.mod h1:bbYlZJ7hK1yFx9hf58LP0zeX7UjIGs20ufpu3evjr+s=
github.com/calebcase/tmpfile v1.0.3 h1:BZrOWZ79gJqQ3XbAQlihYZf/YCV0H4KPIdM5K5oMpJo=
github.com/calebcase/tmpfile v1.0.3/go.mod h1:UAUc01aHeC+pudPagY/lWvt2qS9ZO5Zzof6/tIUzqeI=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/census-instrumentation/opencensus-proto v0.2.1/go.mod h1:f6KPmirojxKA12rnyqOA5BBL4O983OfeGPqjHWSTneU=
github.com/cespare/xxhash v1.1.0/go.mod h1:XrSqR1VqqWfGrhpAt58auRo0WTKS1nRRg3ghfAqPWnc=
github.com/cespare/xxhash/v2 v2.1.1/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs=
github.com/cespare/xxhash/v2 v2.2.0 h1:DC2CZ1Ep5Y4k3ZQ899DldepgrayRUGE6BBZ/cd9Cj44=
github.com/cespare/xxhash/v2 v2.2.0/go.mod h1:VGX0DQ3Q6kWi7AoAeZDth3/j3BFtOZR5XLFGgcrjCOs=
github.com/cheekybits/genny v1.0.0/go.mod h1:+tQajlRqAUrPI7DOSpB0XAqZYtQakVtB7wXkRAgjxjQ=
github.com/chzyer/logex v1.1.10/go.mod h1:+Ywpsq7O8HXn0nuIou7OrIPyXbp3wmkHB+jjWRnGsAI=
github.com/chzyer/readline v0.0.0-20180603132655-2972be24d48e/go.mod h1:nSuG5e5PlCu98SY8svDHJxuZscDgtXS6KTTbou5AhLI=
github.com/chzyer/test v0.0.0-20180213035817-a1ea475d72b1/go.mod h1:Q3SI9o4m/ZMnBNeIyt5eFwwo7qiLfzFZmjNmxjkiQlU=
github.com/client9/misspell v0.3.4/go.mod h1:qj6jICC3Q7zFZvVWo7KLAzC3yx5G7kyvSDkc90ppPyw=
2018-10-06 18:57:53 +01:00
github.com/cloudfoundry/gosigar v1.1.0 h1:V/dVCzhKOdIU3WRB5inQU20s4yIgL9Dxx/Mhi0SF8eM=
github.com/cloudfoundry/gosigar v1.1.0/go.mod h1:3qLfc2GlfmwOx2+ZDaRGH3Y9fwQ0sQeaAleo2GV5pH0=
github.com/cncf/udpa/go v0.0.0-20191209042840-269d4d468f6f/go.mod h1:M8M6+tZqaGXZJjfX53e64911xZQV5JYwmTeXPW+k8Sc=
github.com/cncf/udpa/go v0.0.0-20201120205902-5459f2c99403/go.mod h1:WmhPx2Nbnhtbo57+VJT5O0JRkEi1Wbu0z5j0R8u5Hbk=
github.com/cncf/udpa/go v0.0.0-20210930031921-04548b0d99d4/go.mod h1:6pvJx4me5XPnfI9Z40ddWsdw2W/uZgQLFXToKeRcDiI=
github.com/cncf/xds/go v0.0.0-20210805033703-aa0b78936158/go.mod h1:eXthEFrGJvWHgFFCl3hGmgk+/aYT6PnTQLykKQRLhEs=
github.com/cncf/xds/go v0.0.0-20210922020428-25de7278fc84/go.mod h1:eXthEFrGJvWHgFFCl3hGmgk+/aYT6PnTQLykKQRLhEs=
github.com/cncf/xds/go v0.0.0-20211011173535-cb28da3451f1/go.mod h1:eXthEFrGJvWHgFFCl3hGmgk+/aYT6PnTQLykKQRLhEs=
github.com/cockroachdb/apd v1.1.0/go.mod h1:8Sl8LxpKi29FqWXR16WEFZRNSz3SoPzUzeMeY4+DwBQ=
github.com/coreos/bbolt v1.3.2/go.mod h1:iRUV2dpdMOn7Bo10OQBFzIJO9kkE559Wcmn+qkEiiKk=
github.com/coreos/etcd v3.3.13+incompatible/go.mod h1:uF7uidLiAD3TWHmW31ZFd/JWoc32PjwdhPthX9715RE=
github.com/coreos/go-semver v0.3.0/go.mod h1:nnelYz7RCh+5ahJtPPxZlU+153eP4D4r3EedlOD2RNk=
github.com/coreos/go-systemd v0.0.0-20181012123002-c6f51f82210d/go.mod h1:F5haX7vjVVG0kc13fIWeqUViNPyEJxv/OmvnBo0Yme4=
github.com/coreos/go-systemd v0.0.0-20190321100706-95778dfbb74e/go.mod h1:F5haX7vjVVG0kc13fIWeqUViNPyEJxv/OmvnBo0Yme4=
github.com/coreos/go-systemd v0.0.0-20190719114852-fd7a80b32e1f/go.mod h1:F5haX7vjVVG0kc13fIWeqUViNPyEJxv/OmvnBo0Yme4=
github.com/coreos/pkg v0.0.0-20180928190104-399ea9e2e55f/go.mod h1:E3G3o1h8I7cfcXa63jLwjI0eiQQMgzzUDFVpN/nH/eA=
github.com/cpuguy83/go-md2man/v2 v2.0.0/go.mod h1:maD7wRr/U5Z6m/iR4s+kqSMx2CaBsrgA7czyZG/E6dU=
github.com/creack/pty v1.1.7/go.mod h1:lj5s0c3V2DBrqTV7llrYr5NG6My20zk30Fl46Y7DoTY=
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
2018-10-06 18:57:53 +01:00
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dgrijalva/jwt-go v3.2.0+incompatible/go.mod h1:E3ru+11k8xSBh+hMPgOLZmtrrCbhqsmaPHjLKYnJCaQ=
github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f h1:lO4WD4F/rVNCu3HqELle0jiPLLBs70cWOduZpkS1E78=
github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f/go.mod h1:cuUVRXasLTGF7a8hSLbxyZXjz+1KgoB3wDUb6vlszIc=
github.com/dgryski/go-sip13 v0.0.0-20181026042036-e10d5fee7954/go.mod h1:vAd38F8PWV+bWy6jNmig1y/TA+kYO4g3RSRF0IAv0no=
github.com/dsnet/try v0.0.3 h1:ptR59SsrcFUYbT/FhAbKTV6iLkeD6O18qfIWRml2fqI=
github.com/dustin/go-humanize v1.0.0/go.mod h1:HtrtbFcZ19U5GC7JDqmcUSB87Iq5E25KnS6fMYU6eOk=
github.com/envoyproxy/go-control-plane v0.9.0/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/envoyproxy/go-control-plane v0.9.1-0.20191026205805-5f8ba28d4473/go.mod h1:YTl/9mNaCwkRvm6d1a2C3ymFceY/DCBVvsKhRF0iEA4=
github.com/envoyproxy/go-control-plane v0.9.4/go.mod h1:6rpuAdCZL397s3pYoYcLgu1mIlRU8Am5FuJP05cCM98=
github.com/envoyproxy/go-control-plane v0.9.9-0.20201210154907-fd9021fe5dad/go.mod h1:cXg6YxExXjJnVBQHBLXeUAgxn2UodCpnH306RInaBQk=
github.com/envoyproxy/go-control-plane v0.9.10-0.20210907150352-cf90f659a021/go.mod h1:AFq3mo9L8Lqqiid3OhADV3RfLJnjiw63cSpi+fDTRC0=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/envoyproxy/protoc-gen-validate v0.1.0/go.mod h1:iSmxcyjqTsJpI2R4NaDN7+kN2VEUnK/pcBlmesArF7c=
github.com/fasthttp-contrib/websocket v0.0.0-20160511215533-1f3b11f56072/go.mod h1:duJ4Jxv5lDcvg4QuQr0oowTf7dz4/CR8NtyCooz9HL8=
2018-10-06 18:57:53 +01:00
github.com/fatih/color v1.7.0/go.mod h1:Zm6kSWBoL9eyXnKyktHP6abPY2pDugNf5KwzbycvMj4=
github.com/fatih/color v1.9.0 h1:8xPHl4/q1VyqGIPif1F+1V3Y3lSmrq01EabUW3CoW5s=
github.com/fatih/color v1.9.0/go.mod h1:eQcE1qtQxscV5RaZvpXrrb8Drkc3/DdQ+uUYCNjL+zU=
github.com/fatih/structs v1.1.0 h1:Q7juDM0QtcnhCpeyLGQKyg4TOIghuNXrkL32pHAUMxo=
github.com/fatih/structs v1.1.0/go.mod h1:9NiDSp5zOcgEDl+j00MP/WkGVPOlPRLejGD8Ga6PJ7M=
github.com/flynn/go-shlex v0.0.0-20150515145356-3f9db97f8568/go.mod h1:xEzjJPgXI435gkrCt3MPfRiAkVrwSbHsst4LCFVfpJc=
github.com/flynn/noise v1.0.0 h1:DlTHqmzmvcEiKj+4RYo/imoswx/4r6iBlCMfVtrMXpQ=
github.com/flynn/noise v1.0.0/go.mod h1:xbMo+0i6+IGbYdJhF31t2eR1BIU0CYc12+BNAKwUTag=
github.com/francoispqt/gojay v1.2.13/go.mod h1:ehT5mTG4ua4581f1++1WLG0vPdaA9HaiDsoyrBGkyDY=
2018-10-06 18:57:53 +01:00
github.com/fsnotify/fsnotify v1.4.7/go.mod h1:jwhsz4b93w/PPRr/qN1Yymfu8t87LnFCMoQvtojpjFo=
github.com/fsnotify/fsnotify v1.4.9/go.mod h1:znqG4EE+3YCdAaPaxE2ZRY/06pZUdp0tY4IgpuI1SZQ=
github.com/fsnotify/fsnotify v1.5.4 h1:jRbGcIw6P2Meqdwuo0H1p6JVLbL5DHKAKlYndzMwVZI=
github.com/fsnotify/fsnotify v1.5.4/go.mod h1:OVB6XrOHzAwXMpEM7uPOzcehqUV2UqJxmVXmkdnm1bU=
github.com/gavv/httpexpect v2.0.0+incompatible h1:1X9kcRshkSKEjNJJxX9Y9mQ5BRfbxU5kORdjhlA1yX8=
github.com/gavv/httpexpect v2.0.0+incompatible/go.mod h1:x+9tiU1YnrOvnB725RkpoLv1M62hOWzwo5OXotisrKc=
github.com/ghodss/yaml v1.0.0/go.mod h1:4dBDuWmgqj2HViK6kFavaiC9ZROes6MMH2rRYeMEF04=
github.com/gliderlabs/ssh v0.1.1/go.mod h1:U7qILu1NlMHj9FlMhZLlkCdDnU1DBEAqr0aevW3Awn0=
github.com/go-errors/errors v1.0.1/go.mod h1:f4zRHt4oKfwPJE5k8C9vpYG+aDHdBFUsgrm6/TyX73Q=
github.com/go-gl/glfw v0.0.0-20190409004039-e6da0acd62b1/go.mod h1:vR7hzQXu2zJy9AVAgeJqvqgH9Q5CA+iKCZ2gyEVpxRU=
github.com/go-kit/kit v0.8.0/go.mod h1:xBxKIO96dXMWWy0MnWVtmwkA9/13aqxPnvrjFYMA2as=
github.com/go-kit/log v0.1.0/go.mod h1:zbhenjAZHb184qTLMA9ZjW7ThYL0H2mk7Q6pNt4vbaY=
github.com/go-logfmt/logfmt v0.3.0/go.mod h1:Qt1PoO58o5twSAckw1HlFXLmHsOX5/0LbT9GBnD5lWE=
github.com/go-logfmt/logfmt v0.4.0/go.mod h1:3RMwSq7FuexP4Kalkev3ejPJsZTpXXBr9+V4qmtdjCk=
github.com/go-logfmt/logfmt v0.5.0/go.mod h1:wCYkCAKZfumFQihp8CzCvQ3paCTfi41vtzG1KdI/P7A=
github.com/go-oauth2/oauth2/v4 v4.4.2 h1:tWQlR5I4/qhWiyOME67BAFmo622yi+2mm7DMm8DpMdg=
github.com/go-oauth2/oauth2/v4 v4.4.2/go.mod h1:K4DemYzNwwYnIDOPdHtX/7SlO0AHdtlphsTgE7lA3PA=
github.com/go-session/session v3.1.2+incompatible/go.mod h1:8B3iivBQjrz/JtC68Np2T1yBBLxTan3mn/3OM0CyRt0=
github.com/go-stack/stack v1.8.0/go.mod h1:v0f6uXyyMGvRgIKkXu+yp6POWl0qKG85gN/melR3HDY=
github.com/go-task/slim-sprig v0.0.0-20210107165309-348f09dbbbc0 h1:p104kn46Q8WdvHunIJ9dAyjPVtrBPhSr3KT2yUst43I=
github.com/go-task/slim-sprig v0.0.0-20210107165309-348f09dbbbc0/go.mod h1:fyg7847qk6SyHyPtNmDHnmrv/HOrqktSC+C9fM+CJOE=
github.com/gofrs/uuid v4.0.0+incompatible/go.mod h1:b2aQJv3Z4Fp6yNu3cdSllBxTCLRxnplIgP/c0N/04lM=
github.com/gogo/protobuf v1.1.1/go.mod h1:r8qH/GZQm5c6nD/R0oafs1akxWv10x8SbQlK7atdtwQ=
github.com/gogo/protobuf v1.2.1/go.mod h1:hp+jE20tsWTFYpLwKvXlhS1hjn+gTNwPg2I6zVXpSg4=
github.com/gogo/protobuf v1.3.2 h1:Ov1cvc58UF3b5XjBnZv7+opcTcQFZebYjWzi34vdm4Q=
github.com/gogo/protobuf v1.3.2/go.mod h1:P1XiOD3dCwIKUDQYPy72D8LYyHL2YPYrpS2s69NZV8Q=
github.com/golang-jwt/jwt v3.2.1+incompatible h1:73Z+4BJcrTC+KczS6WvTPvRGOp1WmfEP4Q1lOd9Z/+c=
github.com/golang-jwt/jwt v3.2.1+incompatible/go.mod h1:8pz2t5EyA70fFQQSrl6XZXzqecmYZeUEB8OUGHkxJ+I=
2018-10-06 18:57:53 +01:00
github.com/golang/glog v0.0.0-20160126235308-23def4e6c14b/go.mod h1:SBH7ygxi8pfUlaOkMMuAQtPIUF8ecWP5IEl/CR7VP2Q=
github.com/golang/groupcache v0.0.0-20190129154638-5b532d6fd5ef/go.mod h1:cIg4eruTrX1D+g88fzRXU5OdNfaM+9IcxsU14FzY7Hc=
github.com/golang/groupcache v0.0.0-20200121045136-8c9f03a8e57e/go.mod h1:cIg4eruTrX1D+g88fzRXU5OdNfaM+9IcxsU14FzY7Hc=
github.com/golang/groupcache v0.0.0-20210331224755-41bb18bfe9da h1:oI5xCqsCo564l8iNU+DwB5epxmsaqB+rhGL0m5jtYqE=
github.com/golang/groupcache v0.0.0-20210331224755-41bb18bfe9da/go.mod h1:cIg4eruTrX1D+g88fzRXU5OdNfaM+9IcxsU14FzY7Hc=
github.com/golang/lint v0.0.0-20180702182130-06c8688daad7/go.mod h1:tluoj9z5200jBnyusfRPU2LqT6J+DAorxEvtC7LHB+E=
2018-10-06 18:57:53 +01:00
github.com/golang/mock v1.1.1/go.mod h1:oTYuIxOrZwtPieC+H1uAHpcLFnEyAGVDL/k47Jfbm0A=
github.com/golang/mock v1.2.0/go.mod h1:oTYuIxOrZwtPieC+H1uAHpcLFnEyAGVDL/k47Jfbm0A=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/golang/mock v1.3.1/go.mod h1:sBzyDLLjw3U8JLTeZvSv8jJB+tU5PVekmnlKIyFUx0Y=
github.com/golang/mock v1.4.4/go.mod h1:l3mdAwkq5BuhzHwde/uurv3sEJeZMXNpwsxVWU71h+4=
github.com/golang/mock v1.6.0 h1:ErTB+efbowRARo13NNdxyJji2egdxLGQhRaY+DUumQc=
github.com/golang/mock v1.6.0/go.mod h1:p6yTPP+5HYm5mzsMV8JkE6ZKdX+/wYM6Hr+LicevLPs=
2018-10-06 18:57:53 +01:00
github.com/golang/protobuf v1.2.0/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U=
github.com/golang/protobuf v1.3.1/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U=
github.com/golang/protobuf v1.3.2/go.mod h1:6lQm79b+lXiMfvg/cZm0SGofjICqVBUtrP5yJMmIC1U=
github.com/golang/protobuf v1.3.3/go.mod h1:vzj43D7+SQXF/4pzW/hwtAqwc6iTitCiVSaWz5lYuqw=
github.com/golang/protobuf v1.4.0-rc.1/go.mod h1:ceaxUfeHdC40wWswd/P6IGgMaK3YpKi5j83Wpe3EHw8=
github.com/golang/protobuf v1.4.0-rc.1.0.20200221234624-67d41d38c208/go.mod h1:xKAWHe0F5eneWXFV3EuXVDTCmh+JuBKY0li0aMyXATA=
github.com/golang/protobuf v1.4.0-rc.2/go.mod h1:LlEzMj4AhA7rCAGe4KMBDvJI+AwstrUpVNzEA03Pprs=
github.com/golang/protobuf v1.4.0-rc.4.0.20200313231945-b860323f09d0/go.mod h1:WU3c8KckQ9AFe+yFwt9sWVRKCVIyN9cPHBJSNnbL67w=
github.com/golang/protobuf v1.4.0/go.mod h1:jodUvKwWbYaEsadDk5Fwe5c77LiNKVO9IDvqG2KuDX0=
github.com/golang/protobuf v1.4.1/go.mod h1:U8fpvMrcmy5pZrNK1lt4xCsGvpyWQ/VVv6QDs8UjoX8=
github.com/golang/protobuf v1.4.2/go.mod h1:oDoupMAO8OvCJWAcko0GGGIgR6R6ocIYbsSw735rRwI=
github.com/golang/protobuf v1.4.3/go.mod h1:oDoupMAO8OvCJWAcko0GGGIgR6R6ocIYbsSw735rRwI=
github.com/golang/protobuf v1.5.0/go.mod h1:FsONVRAS9T7sI+LIUmWTfcYkHO4aIWwzhcaSAoJOfIk=
github.com/golang/protobuf v1.5.2/go.mod h1:XVQd3VNwM+JqD3oG2Ue2ip4fOMUkwXdXDdiuN0vRsmY=
github.com/golang/protobuf v1.5.3 h1:KhyjKVUg7Usr/dYsdSqoFveMYd5ko72D+zANwlG1mmg=
github.com/golang/protobuf v1.5.3/go.mod h1:XVQd3VNwM+JqD3oG2Ue2ip4fOMUkwXdXDdiuN0vRsmY=
github.com/google/btree v0.0.0-20180813153112-4030bb1f1f0c/go.mod h1:lNA+9X1NB3Zf8V7Ke586lFgjr2dZNuvo3lPJSGZ5JPQ=
github.com/google/btree v1.0.0/go.mod h1:lNA+9X1NB3Zf8V7Ke586lFgjr2dZNuvo3lPJSGZ5JPQ=
2018-10-06 18:57:53 +01:00
github.com/google/go-cmp v0.2.0/go.mod h1:oXzfMopK8JAjlY9xF4vHSVASa0yLyX7SntLO5aqRK0M=
github.com/google/go-cmp v0.3.0/go.mod h1:8QqcDgzrUqlUb/G2PQTWiueGozuR1884gddMywk6iLU=
github.com/google/go-cmp v0.3.1/go.mod h1:8QqcDgzrUqlUb/G2PQTWiueGozuR1884gddMywk6iLU=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/google/go-cmp v0.4.0/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
github.com/google/go-cmp v0.5.0/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
github.com/google/go-cmp v0.5.3/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/gNBxE=
github.com/google/go-cmp v0.5.9 h1:O2Tfq5qg4qc4AmwVlvv0oLiVAGB7enBSJ2x2DqQFi38=
github.com/google/go-cmp v0.5.9/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
github.com/google/go-github v17.0.0+incompatible/go.mod h1:zLgOLi98H3fifZn+44m+umXrS52loVEgC2AApnigrVQ=
github.com/google/go-querystring v1.0.0 h1:Xkwi/a1rcvNg1PPYe5vI8GbeBY/jrVuDX5ASuANWTrk=
github.com/google/go-querystring v1.0.0/go.mod h1:odCYkC5MyYFN7vkCjXpyrEuKhc/BUO6wN/zVPAxq5ck=
github.com/google/martian v2.1.0+incompatible/go.mod h1:9I4somxYTbIHy5NJKHRl3wXiIaQGbYVAs8BPL6v8lEs=
github.com/google/pprof v0.0.0-20181206194817-3ea8567a2e57/go.mod h1:zfwlbNMJ+OItoe0UupaVj+oy1omPYYDuagoSzA8v9mc=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/google/pprof v0.0.0-20190515194954-54271f7e092f/go.mod h1:zfwlbNMJ+OItoe0UupaVj+oy1omPYYDuagoSzA8v9mc=
github.com/google/pprof v0.0.0-20211108044417-e9b028704de0/go.mod h1:KgnwoLYCZ8IQu3XUZ8Nc/bM9CCZFOyjUNOSygVozoDg=
github.com/google/pprof v0.0.0-20221103000818-d260c55eee4c h1:lvddKcYTQ545ADhBujtIJmqQrZBDsGo7XIMbAQe/sNY=
github.com/google/pprof v0.0.0-20221103000818-d260c55eee4c/go.mod h1:dDKJzRmX4S37WGHujM7tX//fmj1uioxKzKxz3lo4HJo=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/google/renameio v0.1.0/go.mod h1:KWCgfxg9yswjAJkECMjeO8J8rahYeXnNhOm40UhjYkI=
github.com/google/s2a-go v0.1.4 h1:1kZ/sQM3srePvKs3tXAvQzo66XfcReoqFpIpIccE7Oc=
github.com/google/s2a-go v0.1.4/go.mod h1:Ej+mSEMGRnqRzjc7VtF+jdBwYG5fuJfiZ8ELkjEwM0A=
github.com/google/uuid v1.1.1/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/google/uuid v1.1.2/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/google/uuid v1.3.0 h1:t6JiXgmwXMjEs8VusXIJk2BXHsn+wx8BZdTaoZ5fu7I=
github.com/google/uuid v1.3.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/googleapis/enterprise-certificate-proxy v0.2.3 h1:yk9/cqRKtT9wXZSsRH9aurXEpJX+U6FLtpYTdC3R06k=
github.com/googleapis/enterprise-certificate-proxy v0.2.3/go.mod h1:AwSRAtLfXpU5Nm3pW+v7rGDHp09LsPtGY9MduiEsR9k=
github.com/googleapis/gax-go v2.0.0+incompatible/go.mod h1:SFVmujtThgffbyetf+mdk2eWhX2bMyUtNHzFKcPA9HY=
github.com/googleapis/gax-go/v2 v2.0.3/go.mod h1:LLvjysVCY1JZeum8Z6l8qUty8fiNwE08qbEPm1M08qg=
github.com/googleapis/gax-go/v2 v2.0.4/go.mod h1:0Wqv26UfaUD9n4G6kQubkQ+KchISgw+vpHVxEJEs9eg=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/googleapis/gax-go/v2 v2.0.5/go.mod h1:DWXyrwAJ9X0FpwwEdw+IPEYBICEFu5mhpdKc/us6bOk=
github.com/googleapis/gax-go/v2 v2.8.0 h1:UBtEZqx1bjXtOQ5BVTkuYghXrr3N4V123VKJK67vJZc=
github.com/googleapis/gax-go/v2 v2.8.0/go.mod h1:4orTrqY6hXxxaUL4LHIPl6lGo8vAE38/qKbhSAKP6QI=
github.com/gopherjs/gopherjs v0.0.0-20181017120253-0766667cb4d1 h1:EGx4pi6eqNxGaHF6qqu48+N2wcFQ5qg5FXgOdqsJ5d8=
github.com/gopherjs/gopherjs v0.0.0-20181017120253-0766667cb4d1/go.mod h1:wJfORRmW1u3UXTncJ5qlYoELFm8eSnnEO6hX4iZ3EWY=
github.com/gorilla/mux v1.8.0 h1:i40aqfkR1h2SlN9hojwV5ZA91wcXFOvkdNIeFDP5koI=
github.com/gorilla/mux v1.8.0/go.mod h1:DVbg23sWSpFRCP0SfiEN6jmj59UnW/n46BH5rLB71So=
github.com/gorilla/schema v1.2.0 h1:YufUaxZYCKGFuAq3c96BOhjgd5nmXiOY9NGzF247Tsc=
github.com/gorilla/schema v1.2.0/go.mod h1:kgLaKoK1FELgZqMAVxx/5cbj0kT+57qxUrAlIO2eleU=
github.com/gorilla/websocket v1.4.2 h1:+/TMaTYc4QFitKJxsQ7Yye35DkWvkdLcvGKqM+x0Ufc=
github.com/gorilla/websocket v1.4.2/go.mod h1:YR8l580nyteQvAITg2hZ9XVh4b55+EU/adAjf1fMHhE=
github.com/graphql-go/graphql v0.7.9 h1:5Va/Rt4l5g3YjwDnid3vFfn43faaQBq7rMcIZ0VnV34=
github.com/graphql-go/graphql v0.7.9/go.mod h1:k6yrAYQaSP59DC5UVxbgxESlmVyojThKdORUqGDGmrI=
github.com/gregjones/httpcache v0.0.0-20180305231024-9cad4c3443a7/go.mod h1:FecbI9+v66THATjSRHfNgh1IVFe/9kFxbXtjV0ctIMA=
github.com/grpc-ecosystem/go-grpc-middleware v1.0.0/go.mod h1:FiyG127CGDf3tlThmgyCl78X/SZQqEOJBCDaAfeWzPs=
github.com/grpc-ecosystem/go-grpc-prometheus v1.2.0/go.mod h1:8NvIoxWQoOIhqOTXgfV/d3M/q6VIi02HzZEHgUlZvzk=
github.com/grpc-ecosystem/grpc-gateway v1.5.0/go.mod h1:RSKVYQBd5MCa4OVpNdGskqpgL2+G+NZTnrVHpWWfpdw=
github.com/grpc-ecosystem/grpc-gateway v1.9.0/go.mod h1:vNeuVxBJEsws4ogUvrchl83t/GYV9WGTSLVdBhOQFDY=
github.com/grpc-ecosystem/grpc-gateway v1.16.0/go.mod h1:BDjrQk3hbvj6Nolgz8mAMFbcEtjT1g+wF4CSlocrBnw=
github.com/hashicorp/consul/api v1.1.0/go.mod h1:VmuI/Lkw1nC05EYQWNKwWGbkg+FbDBtguAZLlVdkD9Q=
github.com/hashicorp/consul/sdk v0.1.1/go.mod h1:VKf9jXwCTEY1QZP2MOLRhb5i/I/ssyNV1vwHyQBF0x8=
github.com/hashicorp/errwrap v1.0.0/go.mod h1:YH+1FKiLXxHSkmPseP+kNlulaMuP3n2brvKWEqk/Jc4=
github.com/hashicorp/go-cleanhttp v0.5.1/go.mod h1:JpRdi6/HCYpAwUzNwuwqhbovhLtngrth3wmdIIUrZ80=
github.com/hashicorp/go-immutable-radix v1.0.0/go.mod h1:0y9vanUI8NX6FsYoO3zeMjhV/C5i9g4Q3DwcSNZ4P60=
github.com/hashicorp/go-msgpack v0.5.3/go.mod h1:ahLV/dePpqEmjfWmKiqvPkv/twdG7iPBM1vqhUKIvfM=
github.com/hashicorp/go-multierror v1.0.0/go.mod h1:dHtQlpGsu+cZNNAkkCN/P3hoUDHhCYQXV3UM06sGGrk=
github.com/hashicorp/go-rootcerts v1.0.0/go.mod h1:K6zTfqpRlCUIjkwsN4Z+hiSfzSTQa6eBIzfwKfwNnHU=
github.com/hashicorp/go-sockaddr v1.0.0/go.mod h1:7Xibr9yA9JjQq1JpNB2Vw7kxv8xerXegt+ozgdvDeDU=
github.com/hashicorp/go-syslog v1.0.0/go.mod h1:qPfqrKkXGihmCqbJM2mZgkZGvKG1dFdvsLplgctolz4=
github.com/hashicorp/go-uuid v1.0.0/go.mod h1:6SBZvOh/SIDV7/2o3Jml5SYk/TvGqwFJ/bN7x4byOro=
github.com/hashicorp/go-uuid v1.0.1/go.mod h1:6SBZvOh/SIDV7/2o3Jml5SYk/TvGqwFJ/bN7x4byOro=
github.com/hashicorp/go.net v0.0.1/go.mod h1:hjKkEWcCURg++eb33jQU7oqQcI9XDCnUzHA0oac0k90=
2018-10-06 18:57:53 +01:00
github.com/hashicorp/golang-lru v0.5.0/go.mod h1:/m3WP610KZHVQ1SGc6re/UDhFvYD7pJ4Ao+sR/qLZy8=
github.com/hashicorp/golang-lru v0.5.1/go.mod h1:/m3WP610KZHVQ1SGc6re/UDhFvYD7pJ4Ao+sR/qLZy8=
2018-10-06 18:57:53 +01:00
github.com/hashicorp/hcl v1.0.0 h1:0Anlzjpi4vEasTeNFn2mLJgTSwt0+6sfsiTG8qcWGx4=
github.com/hashicorp/hcl v1.0.0/go.mod h1:E5yfLk+7swimpb2L/Alb/PJmXilQ/rhwaUYs4T20WEQ=
github.com/hashicorp/logutils v1.0.0/go.mod h1:QIAnNjmIWmVIIkWDTG1z5v++HQmx9WQRO+LraFDTW64=
github.com/hashicorp/mdns v1.0.0/go.mod h1:tL+uN++7HEJ6SQLQ2/p+z2pH24WQKWjBPkE0mNTz8vQ=
github.com/hashicorp/memberlist v0.1.3/go.mod h1:ajVTdAv/9Im8oMAAj5G31PhhMCZJV2pPBoIllUwCN7I=
github.com/hashicorp/serf v0.8.2/go.mod h1:6hOLApaqBFA1NXqRQAsxw9QxuDEvNxSQRwA/JwenrHc=
2018-10-06 18:57:53 +01:00
github.com/hpcloud/tail v1.0.0/go.mod h1:ab1qPbhIpdTxEkNHXyeSf5vhxWSCs/tWer42PpOxQnU=
github.com/ianlancetaylor/demangle v0.0.0-20210905161508-09a460cdf81d/go.mod h1:aYm2/VgdVmcIU8iMfdMvDMsRAQjcfZSKFby6HOFvi/w=
github.com/imkira/go-interpol v1.1.0 h1:KIiKr0VSG2CUW1hl1jpiyuzuJeKUUpC8iM1AIE7N1Vk=
github.com/imkira/go-interpol v1.1.0/go.mod h1:z0h2/2T3XF8kyEPpRgJ3kmNv+C43p+I/CoI+jC3w2iA=
github.com/inconshreveable/mousetrap v1.0.0 h1:Z8tu5sraLXCXIcARxBp/8cbvlwVa7Z1NHg9XEKhtSvM=
2018-10-06 18:57:53 +01:00
github.com/inconshreveable/mousetrap v1.0.0/go.mod h1:PxqpIevigyE2G7u3NXJIT2ANytuPF1OarO4DADm73n8=
github.com/jackc/chunkreader v1.0.0 h1:4s39bBR8ByfqH+DKm8rQA3E1LHZWB9XWcrz8fqaZbe0=
github.com/jackc/chunkreader v1.0.0/go.mod h1:RT6O25fNZIuasFJRyZ4R/Y2BbhasbmZXF9QQ7T3kePo=
github.com/jackc/chunkreader/v2 v2.0.0/go.mod h1:odVSm741yZoC3dpHEUXIqA9tQRhFrgOHwnPIn9lDKlk=
github.com/jackc/chunkreader/v2 v2.0.1 h1:i+RDz65UE+mmpjTfyz0MoVTnzeYxroil2G82ki7MGG8=
github.com/jackc/chunkreader/v2 v2.0.1/go.mod h1:odVSm741yZoC3dpHEUXIqA9tQRhFrgOHwnPIn9lDKlk=
github.com/jackc/pgconn v0.0.0-20190420214824-7e0022ef6ba3/go.mod h1:jkELnwuX+w9qN5YIfX0fl88Ehu4XC3keFuOJJk9pcnA=
github.com/jackc/pgconn v0.0.0-20190824142844-760dd75542eb/go.mod h1:lLjNuW/+OfW9/pnVKPazfWOgNfH2aPem8YQ7ilXGvJE=
github.com/jackc/pgconn v0.0.0-20190831204454-2fabfa3c18b7/go.mod h1:ZJKsE/KZfsUgOEh9hBm+xYTstcNHg7UPMVJqRfQxq4s=
github.com/jackc/pgconn v1.8.0/go.mod h1:1C2Pb36bGIP9QHGBYCjnyhqu7Rv3sGshaQUvmfGIB/o=
github.com/jackc/pgconn v1.9.0/go.mod h1:YctiPyvzfU11JFxoXokUOOKQXQmDMoJL9vJzHH8/2JY=
github.com/jackc/pgconn v1.9.1-0.20210724152538-d89c8390a530/go.mod h1:4z2w8XhRbP1hYxkpTuBjTS3ne3J48K83+u0zoyvg2pI=
github.com/jackc/pgconn v1.11.0 h1:HiHArx4yFbwl91X3qqIHtUFoiIfLNJXCQRsnzkiwwaQ=
github.com/jackc/pgconn v1.11.0/go.mod h1:4z2w8XhRbP1hYxkpTuBjTS3ne3J48K83+u0zoyvg2pI=
github.com/jackc/pgerrcode v0.0.0-20201024163028-a0d42d470451 h1:WAvSpGf7MsFuzAtK4Vk7R4EVe+liW4x83r4oWu0WHKw=
github.com/jackc/pgerrcode v0.0.0-20201024163028-a0d42d470451/go.mod h1:a/s9Lp5W7n/DD0VrVoyJ00FbP2ytTPDVOivvn2bMlds=
github.com/jackc/pgio v1.0.0 h1:g12B9UwVnzGhueNavwioyEEpAmqMe1E/BN9ES+8ovkE=
github.com/jackc/pgio v1.0.0/go.mod h1:oP+2QK2wFfUWgr+gxjoBH9KGBb31Eio69xUb0w5bYf8=
github.com/jackc/pgmock v0.0.0-20190831213851-13a1b77aafa2/go.mod h1:fGZlG77KXmcq05nJLRkk0+p82V8B8Dw8KN2/V9c/OAE=
github.com/jackc/pgmock v0.0.0-20201204152224-4fe30f7445fd/go.mod h1:hrBW0Enj2AZTNpt/7Y5rr2xe/9Mn757Wtb2xeBzPv2c=
github.com/jackc/pgmock v0.0.0-20210724152146-4ad1a8207f65/go.mod h1:5R2h2EEX+qri8jOWMbJCtaPWkrrNc7OHwsp2TCqp7ak=
github.com/jackc/pgpassfile v1.0.0 h1:/6Hmqy13Ss2zCq62VdNG8tM1wchn8zjSGOBJ6icpsIM=
github.com/jackc/pgpassfile v1.0.0/go.mod h1:CEx0iS5ambNFdcRtxPj5JhEz+xB6uRky5eyVu/W2HEg=
github.com/jackc/pgproto3 v1.1.0/go.mod h1:eR5FA3leWg7p9aeAqi37XOTgTIbkABlvcPB3E5rlc78=
github.com/jackc/pgproto3/v2 v2.0.0-alpha1.0.20190420180111-c116219b62db/go.mod h1:bhq50y+xrl9n5mRYyCBFKkpRVTLYJVWeCc+mEAI3yXA=
github.com/jackc/pgproto3/v2 v2.0.0-alpha1.0.20190609003834-432c2951c711/go.mod h1:uH0AWtUmuShn0bcesswc4aBTWGvw0cAxIJp+6OB//Wg=
github.com/jackc/pgproto3/v2 v2.0.0-rc3/go.mod h1:ryONWYqW6dqSg1Lw6vXNMXoBJhpzvWKnT95C46ckYeM=
github.com/jackc/pgproto3/v2 v2.0.0-rc3.0.20190831210041-4c03ce451f29/go.mod h1:ryONWYqW6dqSg1Lw6vXNMXoBJhpzvWKnT95C46ckYeM=
github.com/jackc/pgproto3/v2 v2.0.6/go.mod h1:WfJCnwN3HIg9Ish/j3sgWXnAfK8A9Y0bwXYU5xKaEdA=
github.com/jackc/pgproto3/v2 v2.1.1/go.mod h1:WfJCnwN3HIg9Ish/j3sgWXnAfK8A9Y0bwXYU5xKaEdA=
github.com/jackc/pgproto3/v2 v2.3.2 h1:7eY55bdBeCz1F2fTzSz69QC+pG46jYq9/jtSPiJ5nn0=
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github.com/jackc/pgservicefile v0.0.0-20200714003250-2b9c44734f2b/go.mod h1:vsD4gTJCa9TptPL8sPkXrLZ+hDuNrZCnj29CQpr4X1E=
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2018-10-06 18:57:53 +01:00
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github.com/onsi/ginkgo v1.16.5/go.mod h1:+E8gABHa3K6zRBolWtd+ROzc/U5bkGt0FwiG042wbpU=
github.com/onsi/ginkgo/v2 v2.2.0 h1:3ZNA3L1c5FYDFTTxbFeVGGD8jYvjYauHD30YgLxVsNI=
github.com/onsi/ginkgo/v2 v2.2.0/go.mod h1:MEH45j8TBi6u9BMogfbp0stKC5cdGjumZj5Y7AG4VIk=
github.com/onsi/gomega v1.7.1/go.mod h1:XdKZgCCFLUoM/7CFJVPcG8C1xQ1AJ0vpAezJrB7JYyY=
github.com/onsi/gomega v1.10.1/go.mod h1:iN09h71vgCQne3DLsj+A5owkum+a2tYe+TOCB1ybHNo=
github.com/onsi/gomega v1.13.0/go.mod h1:lRk9szgn8TxENtWd0Tp4c3wjlRfMTMH27I+3Je41yGY=
github.com/onsi/gomega v1.20.1 h1:PA/3qinGoukvymdIDV8pii6tiZgC8kbmJO6Z5+b002Q=
github.com/openzipkin/zipkin-go v0.1.1/go.mod h1:NtoC/o8u3JlF1lSlyPNswIbeQH9bJTmOf0Erfk+hxe8=
github.com/oschwald/maxminddb-golang v1.8.0 h1:Uh/DSnGoxsyp/KYbY1AuP0tYEwfs0sCph9p/UMXK/Hk=
github.com/oschwald/maxminddb-golang v1.8.0/go.mod h1:RXZtst0N6+FY/3qCNmZMBApR19cdQj43/NM9VkrNAis=
github.com/pascaldekloe/goe v0.0.0-20180627143212-57f6aae5913c/go.mod h1:lzWF7FIEvWOWxwDKqyGYQf6ZUaNfKdP144TG7ZOy1lc=
2018-10-06 18:57:53 +01:00
github.com/pelletier/go-toml v1.2.0/go.mod h1:5z9KED0ma1S8pY6P1sdut58dfprrGBbd/94hg7ilaic=
github.com/pelletier/go-toml v1.9.0 h1:NOd0BRdOKpPf0SxkL3HxSQOG7rNh+4kl6PHcBPFs7Q0=
github.com/pelletier/go-toml v1.9.0/go.mod h1:u1nR/EPcESfeI/szUZKdtJ0xRNbUoANCkoOuaOx1Y+c=
2018-10-06 18:57:53 +01:00
github.com/pkg/errors v0.8.0/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
2019-01-07 19:11:11 +00:00
github.com/pkg/errors v0.8.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
github.com/pkg/errors v0.9.1 h1:FEBLx1zS214owpjy7qsBeixbURkuhQAwrK5UwLGTwt4=
github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
github.com/pkg/sftp v1.10.1/go.mod h1:lYOWFsE0bwd1+KfKJaKeuokY15vzFx25BLbzYYoAxZI=
2018-10-06 18:57:53 +01:00
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/posener/complete v1.1.1/go.mod h1:em0nMJCgc9GFtwrmVmEMR/ZL6WyhyjMBndrE9hABlRI=
github.com/pquerna/otp v1.3.0 h1:oJV/SkzR33anKXwQU3Of42rL4wbrffP4uvUf1SvS5Xs=
github.com/pquerna/otp v1.3.0/go.mod h1:dkJfzwRKNiegxyNb54X/3fLwhCynbMspSyWKnvi1AEg=
github.com/prometheus/client_golang v0.8.0/go.mod h1:7SWBe2y4D6OKWSNQJUaRYU/AaXPKyh/dDVn+NZz0KFw=
github.com/prometheus/client_golang v0.9.1/go.mod h1:7SWBe2y4D6OKWSNQJUaRYU/AaXPKyh/dDVn+NZz0KFw=
github.com/prometheus/client_golang v0.9.3/go.mod h1:/TN21ttK/J9q6uSwhBd54HahCDft0ttaMvbicHlPoso=
github.com/prometheus/client_model v0.0.0-20180712105110-5c3871d89910/go.mod h1:MbSGuTsp3dbXC40dX6PRTWyKYBIrTGTE9sqQNg2J8bo=
github.com/prometheus/client_model v0.0.0-20190129233127-fd36f4220a90/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
github.com/prometheus/common v0.0.0-20180801064454-c7de2306084e/go.mod h1:daVV7qP5qjZbuso7PdcryaAu0sAZbrN9i7WWcTMWvro=
github.com/prometheus/common v0.0.0-20181113130724-41aa239b4cce/go.mod h1:daVV7qP5qjZbuso7PdcryaAu0sAZbrN9i7WWcTMWvro=
github.com/prometheus/common v0.4.0/go.mod h1:TNfzLD0ON7rHzMJeJkieUDPYmFC7Snx/y86RQel1bk4=
github.com/prometheus/procfs v0.0.0-20180725123919-05ee40e3a273/go.mod h1:c3At6R/oaqEKCNdg8wHV1ftS6bRYblBhIjjI8uT2IGk=
github.com/prometheus/procfs v0.0.0-20181005140218-185b4288413d/go.mod h1:c3At6R/oaqEKCNdg8wHV1ftS6bRYblBhIjjI8uT2IGk=
github.com/prometheus/procfs v0.0.0-20190507164030-5867b95ac084/go.mod h1:TjEm7ze935MbeOT/UhFTIMYKhuLP4wbCsTZCD3I8kEA=
github.com/prometheus/tsdb v0.7.1/go.mod h1:qhTCs0VvXwvX/y3TZrWD7rabWM+ijKTux40TwIPHuXU=
github.com/quic-go/qtls-go1-18 v0.2.0 h1:5ViXqBZ90wpUcZS0ge79rf029yx0dYB0McyPJwqqj7U=
github.com/quic-go/qtls-go1-18 v0.2.0/go.mod h1:moGulGHK7o6O8lSPSZNoOwcLvJKJ85vVNc7oJFD65bc=
github.com/quic-go/qtls-go1-19 v0.2.0 h1:Cvn2WdhyViFUHoOqK52i51k4nDX8EwIh5VJiVM4nttk=
github.com/quic-go/qtls-go1-19 v0.2.0/go.mod h1:ySOI96ew8lnoKPtSqx2BlI5wCpUVPT05RMAlajtnyOI=
github.com/quic-go/qtls-go1-20 v0.1.0 h1:d1PK3ErFy9t7zxKsG3NXBJXZjp/kMLoIb3y/kV54oAI=
github.com/quic-go/qtls-go1-20 v0.1.0/go.mod h1:JKtK6mjbAVcUTN/9jZpvLbGxvdWIKS8uT7EiStoU1SM=
github.com/quic-go/quic-go v0.32.0 h1:lY02md31s1JgPiiyfqJijpu/UX/Iun304FI3yUqX7tA=
github.com/quic-go/quic-go v0.32.0/go.mod h1:/fCsKANhQIeD5l76c2JFU+07gVE3KaA0FP+0zMWwfwo=
github.com/redis/go-redis/v9 v9.0.3 h1:+7mmR26M0IvyLxGZUHxu4GiBkJkVDid0Un+j4ScYu4k=
github.com/redis/go-redis/v9 v9.0.3/go.mod h1:WqMKv5vnQbRuZstUwxQI195wHy+t4PuXDOjzMvcuQHk=
github.com/rivo/uniseg v0.2.0/go.mod h1:J6wj4VEh+S6ZtnVlnTBMWIodfgj8LQOQFoIToxlJtxc=
github.com/rivo/uniseg v0.4.4 h1:8TfxU8dW6PdqD27gjM8MVNuicgxIjxpm4K7x4jp8sis=
github.com/rivo/uniseg v0.4.4/go.mod h1:FN3SvrM+Zdj16jyLfmOkMNblXMcoc8DfTHruCPUcx88=
github.com/rogpeppe/fastuuid v0.0.0-20150106093220-6724a57986af/go.mod h1:XWv6SoW27p1b0cqNHllgS5HIMJraePCO15w5zCzIWYg=
github.com/rogpeppe/fastuuid v1.2.0/go.mod h1:jVj6XXZzXRy/MSR5jhDC/2q6DgLz+nrA6LYCDYWNEvQ=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
github.com/rogpeppe/go-internal v1.3.0/go.mod h1:M8bDsm7K2OlrFYOpmOWEs/qY81heoFRclV5y23lUDJ4=
github.com/rogpeppe/go-internal v1.10.0 h1:TMyTOH3F/DB16zRVcYyreMH6GnZZrwQVAoYjRBZyWFQ=
github.com/rs/xid v1.2.1/go.mod h1:+uKXf+4Djp6Md1KODXJxgGQPKngRmWyn10oCKFzNHOQ=
github.com/rs/zerolog v1.13.0/go.mod h1:YbFCdg8HfsridGWAh22vktObvhZbQsZXe4/zB0OKkWU=
github.com/rs/zerolog v1.15.0/go.mod h1:xYTKnLHcpfU2225ny5qZjxnj9NvkumZYjJHlAThCjNc=
github.com/russross/blackfriday v1.5.2/go.mod h1:JO/DiYxRf+HjHt06OyowR9PTA263kcR/rfWxYHBV53g=
github.com/russross/blackfriday/v2 v2.0.1/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM=
github.com/ryanuber/columnize v0.0.0-20160712163229-9b3edd62028f/go.mod h1:sm1tb6uqfes/u+d4ooFouqFdy9/2g9QGwK3SQygK0Ts=
github.com/satori/go.uuid v1.2.0/go.mod h1:dA0hQrYB0VpLJoorglMZABFdXlWrHn1NEOzdhQKdks0=
github.com/sclevine/agouti v3.0.0+incompatible/go.mod h1:b4WX9W9L1sfQKXeJf1mUTLZKJ48R1S7H23Ji7oFO5Bw=
github.com/sean-/seed v0.0.0-20170313163322-e2103e2c3529/go.mod h1:DxrIzT+xaE7yg65j358z/aeFdxmN0P9QXhEzd20vsDc=
github.com/segmentio/backo-go v0.0.0-20200129164019-23eae7c10bd3 h1:ZuhckGJ10ulaKkdvJtiAqsLTiPrLaXSdnVgXJKJkTxE=
github.com/segmentio/backo-go v0.0.0-20200129164019-23eae7c10bd3/go.mod h1:9/Rh6yILuLysoQnZ2oNooD2g7aBnvM7r/fNVxRNWfBc=
github.com/sergi/go-diff v1.0.0/go.mod h1:0CfEIISq7TuYL3j771MWULgwwjU+GofnZX9QAmXWZgo=
github.com/sergi/go-diff v1.1.0 h1:we8PVUC3FE2uYfodKH/nBHMSetSfHDR6scGdBi+erh0=
github.com/sergi/go-diff v1.1.0/go.mod h1:STckp+ISIX8hZLjrqAeVduY0gWCT9IjLuqbuNXdaHfM=
github.com/shopspring/decimal v0.0.0-20180709203117-cd690d0c9e24/go.mod h1:M+9NzErvs504Cn4c5DxATwIqPbtswREoFCre64PpcG4=
github.com/shopspring/decimal v1.2.0 h1:abSATXmQEYyShuxI4/vyW3tV1MrKAJzCZ/0zLUXYbsQ=
github.com/shopspring/decimal v1.2.0/go.mod h1:DKyhrW/HYNuLGql+MJL6WCR6knT2jwCFRcu2hWCYk4o=
github.com/shurcooL/component v0.0.0-20170202220835-f88ec8f54cc4/go.mod h1:XhFIlyj5a1fBNx5aJTbKoIq0mNaPvOagO+HjB3EtxrY=
github.com/shurcooL/events v0.0.0-20181021180414-410e4ca65f48/go.mod h1:5u70Mqkb5O5cxEA8nxTsgrgLehJeAw6Oc4Ab1c/P1HM=
github.com/shurcooL/github_flavored_markdown v0.0.0-20181002035957-2122de532470/go.mod h1:2dOwnU2uBioM+SGy2aZoq1f/Sd1l9OkAeAUvjSyvgU0=
github.com/shurcooL/go v0.0.0-20180423040247-9e1955d9fb6e/go.mod h1:TDJrrUr11Vxrven61rcy3hJMUqaf/CLWYhHNPmT14Lk=
github.com/shurcooL/go-goon v0.0.0-20170922171312-37c2f522c041/go.mod h1:N5mDOmsrJOB+vfqUK+7DmDyjhSLIIBnXo9lvZJj3MWQ=
github.com/shurcooL/gofontwoff v0.0.0-20180329035133-29b52fc0a18d/go.mod h1:05UtEgK5zq39gLST6uB0cf3NEHjETfB4Fgr3Gx5R9Vw=
github.com/shurcooL/gopherjslib v0.0.0-20160914041154-feb6d3990c2c/go.mod h1:8d3azKNyqcHP1GaQE/c6dDgjkgSx2BZ4IoEi4F1reUI=
github.com/shurcooL/highlight_diff v0.0.0-20170515013008-09bb4053de1b/go.mod h1:ZpfEhSmds4ytuByIcDnOLkTHGUI6KNqRNPDLHDk+mUU=
github.com/shurcooL/highlight_go v0.0.0-20181028180052-98c3abbbae20/go.mod h1:UDKB5a1T23gOMUJrI+uSuH0VRDStOiUVSjBTRDVBVag=
github.com/shurcooL/home v0.0.0-20181020052607-80b7ffcb30f9/go.mod h1:+rgNQw2P9ARFAs37qieuu7ohDNQ3gds9msbT2yn85sg=
github.com/shurcooL/htmlg v0.0.0-20170918183704-d01228ac9e50/go.mod h1:zPn1wHpTIePGnXSHpsVPWEktKXHr6+SS6x/IKRb7cpw=
github.com/shurcooL/httperror v0.0.0-20170206035902-86b7830d14cc/go.mod h1:aYMfkZ6DWSJPJ6c4Wwz3QtW22G7mf/PEgaB9k/ik5+Y=
github.com/shurcooL/httpfs v0.0.0-20171119174359-809beceb2371/go.mod h1:ZY1cvUeJuFPAdZ/B6v7RHavJWZn2YPVFQ1OSXhCGOkg=
github.com/shurcooL/httpgzip v0.0.0-20180522190206-b1c53ac65af9/go.mod h1:919LwcH0M7/W4fcZ0/jy0qGght1GIhqyS/EgWGH2j5Q=
github.com/shurcooL/issues v0.0.0-20181008053335-6292fdc1e191/go.mod h1:e2qWDig5bLteJ4fwvDAc2NHzqFEthkqn7aOZAOpj+PQ=
github.com/shurcooL/issuesapp v0.0.0-20180602232740-048589ce2241/go.mod h1:NPpHK2TI7iSaM0buivtFUc9offApnI0Alt/K8hcHy0I=
github.com/shurcooL/notifications v0.0.0-20181007000457-627ab5aea122/go.mod h1:b5uSkrEVM1jQUspwbixRBhaIjIzL2xazXp6kntxYle0=
github.com/shurcooL/octicon v0.0.0-20181028054416-fa4f57f9efb2/go.mod h1:eWdoE5JD4R5UVWDucdOPg1g2fqQRq78IQa9zlOV1vpQ=
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github.com/shurcooL/sanitized_anchor_name v0.0.0-20170918181015-86672fcb3f95/go.mod h1:1NzhyTcUVG4SuEtjjoZeVRXNmyL/1OwPU0+IJeTBvfc=
github.com/shurcooL/sanitized_anchor_name v1.0.0/go.mod h1:1NzhyTcUVG4SuEtjjoZeVRXNmyL/1OwPU0+IJeTBvfc=
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github.com/sirupsen/logrus v1.2.0/go.mod h1:LxeOpSwHxABJmUn/MG1IvRgCAasNZTLOkJPxbbu5VWo=
github.com/sirupsen/logrus v1.4.1/go.mod h1:ni0Sbl8bgC9z8RoU9G6nDWqqs/fq4eDPysMBDgk/93Q=
github.com/sirupsen/logrus v1.4.2/go.mod h1:tLMulIdttU9McNUspp0xgXVQah82FyeX6MwdIuYE2rE=
github.com/smartystreets/assertions v0.0.0-20180927180507-b2de0cb4f26d h1:zE9ykElWQ6/NYmHa3jpm/yHnI4xSofP+UP6SpjHcSeM=
github.com/smartystreets/assertions v0.0.0-20180927180507-b2de0cb4f26d/go.mod h1:OnSkiWE9lh6wB0YB77sQom3nweQdgAjqCqsofrRNTgc=
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github.com/soheilhy/cmux v0.1.4/go.mod h1:IM3LyeVVIOuxMH7sFAkER9+bJ4dT7Ms6E4xg4kGIyLM=
github.com/sourcegraph/annotate v0.0.0-20160123013949-f4cad6c6324d/go.mod h1:UdhH50NIW0fCiwBSr0co2m7BnFLdv4fQTgdqdJTHFeE=
github.com/sourcegraph/syntaxhighlight v0.0.0-20170531221838-bd320f5d308e/go.mod h1:HuIsMU8RRBOtsCgI77wP899iHVBQpCmg4ErYMZB+2IA=
github.com/spacemonkeygo/monkit/v3 v3.0.0-20191108235033-eacca33b3037/go.mod h1:JcK1pCbReQsOsMKF/POFSZCq7drXFybgGmbc27tuwes=
github.com/spacemonkeygo/monkit/v3 v3.0.4/go.mod h1:JcK1pCbReQsOsMKF/POFSZCq7drXFybgGmbc27tuwes=
github.com/spacemonkeygo/monkit/v3 v3.0.18/go.mod h1:kj1ViJhlyADa7DiA4xVnTuPA46lFKbM7mxQTrXCuJP4=
github.com/spacemonkeygo/monkit/v3 v3.0.20-0.20230419135619-fb89f20752cb h1:kWLHxcYDcloMFEJMngxuKh8wcLl9RjjeAN2a9AtTtCg=
github.com/spacemonkeygo/monkit/v3 v3.0.20-0.20230419135619-fb89f20752cb/go.mod h1:kj1ViJhlyADa7DiA4xVnTuPA46lFKbM7mxQTrXCuJP4=
2018-10-06 18:57:53 +01:00
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go.etcd.io/bbolt v1.3.2/go.mod h1:IbVyRI1SCnLcuJnV2u8VeU0CEYM7e686BmAb1XKL+uU=
go.etcd.io/bbolt v1.3.5 h1:XAzx9gjCb0Rxj7EoqcClPD1d5ZBxZJk0jbuoPHenBt0=
go.etcd.io/bbolt v1.3.5/go.mod h1:G5EMThwa9y8QZGBClrRx5EY+Yw9kAhnjy3bSjsnlVTQ=
go.opencensus.io v0.18.0/go.mod h1:vKdFvxhtzZ9onBp9VKHK8z/sRpBMnKAsufL7wlDrCOA=
go.opencensus.io v0.21.0/go.mod h1:mSImk1erAIZhrmZN+AvHh14ztQfjbGwt4TtuofqLduU=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
go.opencensus.io v0.22.0/go.mod h1:+kGneAE2xo2IficOXnaByMWTGM9T73dGwxeWcUqIpI8=
go.opencensus.io v0.24.0 h1:y73uSU6J157QMP2kn2r30vwW1A2W2WFwSCGnAVxeaD0=
go.opencensus.io v0.24.0/go.mod h1:vNK8G9p7aAivkbmorf4v+7Hgx+Zs0yY+0fOtgBfjQKo=
go.opentelemetry.io/proto/otlp v0.7.0/go.mod h1:PqfVotwruBrMGOCsRd/89rSnXhoiJIqeYNgFYFoEGnI=
go.uber.org/atomic v1.3.2/go.mod h1:gD2HeocX3+yG+ygLZcrzQJaqmWj9AIm7n08wl/qW/PE=
go.uber.org/atomic v1.4.0/go.mod h1:gD2HeocX3+yG+ygLZcrzQJaqmWj9AIm7n08wl/qW/PE=
go.uber.org/atomic v1.5.0/go.mod h1:sABNBOSYdrvTF6hTgEIbc7YasKWGhgEQZyfxyTvoXHQ=
go.uber.org/atomic v1.6.0/go.mod h1:sABNBOSYdrvTF6hTgEIbc7YasKWGhgEQZyfxyTvoXHQ=
go.uber.org/atomic v1.7.0 h1:ADUqmZGgLDDfbSL9ZmPxKTybcoEYHgpYfELNoN+7hsw=
go.uber.org/atomic v1.7.0/go.mod h1:fEN4uk6kAWBTFdckzkM89CLk9XfWZrxpCo0nPH17wJc=
2018-10-06 18:57:53 +01:00
go.uber.org/multierr v1.1.0/go.mod h1:wR5kodmAFQ0UK8QlbwjlSNy0Z68gJhDJUG5sjR94q/0=
go.uber.org/multierr v1.3.0/go.mod h1:VgVr7evmIr6uPjLBxg28wmKNXyqE9akIJ5XnfpiKl+4=
go.uber.org/multierr v1.5.0/go.mod h1:FeouvMocqHpRaaGuG9EjoKcStLC43Zu/fmqdUMPcKYU=
go.uber.org/multierr v1.6.0 h1:y6IPFStTAIT5Ytl7/XYmHvzXQ7S3g/IeZW9hyZ5thw4=
go.uber.org/multierr v1.6.0/go.mod h1:cdWPpRnG4AhwMwsgIHip0KRBQjJy5kYEpYjJxpXp9iU=
go.uber.org/tools v0.0.0-20190618225709-2cfd321de3ee/go.mod h1:vJERXedbb3MVM5f9Ejo0C68/HhF8uaILCdgjnY+goOA=
go.uber.org/zap v1.9.1/go.mod h1:vwi/ZaCAaUcBkycHslxD9B2zi4UTXhF60s6SWpuDF0Q=
go.uber.org/zap v1.10.0/go.mod h1:vwi/ZaCAaUcBkycHslxD9B2zi4UTXhF60s6SWpuDF0Q=
go.uber.org/zap v1.13.0/go.mod h1:zwrFLgMcdUuIBviXEYEH1YKNaOBnKXsx2IPda5bBwHM=
go.uber.org/zap v1.14.1/go.mod h1:Mb2vm2krFEG5DV0W9qcHBYFtp/Wku1cvYaqPsS/WYfc=
go.uber.org/zap v1.16.0 h1:uFRZXykJGK9lLY4HtgSw44DnIcAM+kRBP7x5m+NpAOM=
go.uber.org/zap v1.16.0/go.mod h1:MA8QOfq0BHJwdXa996Y4dYkAqRKB8/1K1QMMZVaNZjQ=
go4.org v0.0.0-20180809161055-417644f6feb5/go.mod h1:MkTOUMDaeVYJUOUsaDXIhWPZYa1yOyC1qaOBpL57BhE=
golang.org/x/build v0.0.0-20190111050920-041ab4dc3f9d/go.mod h1:OWs+y06UdEOHN4y+MfF/py+xQ/tYqIWW03b70/CG9Rw=
golang.org/x/crypto v0.0.0-20180904163835-0709b304e793/go.mod h1:6SG95UA2DQfeDnfUPMdvaQW0Q7yPrPDi9nlGo2tz2b4=
golang.org/x/crypto v0.0.0-20181029021203-45a5f77698d3/go.mod h1:6SG95UA2DQfeDnfUPMdvaQW0Q7yPrPDi9nlGo2tz2b4=
golang.org/x/crypto v0.0.0-20181030102418-4d3f4d9ffa16/go.mod h1:6SG95UA2DQfeDnfUPMdvaQW0Q7yPrPDi9nlGo2tz2b4=
golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=
golang.org/x/crypto v0.0.0-20190313024323-a1f597ede03a/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=
golang.org/x/crypto v0.0.0-20190411191339-88737f569e3a/go.mod h1:WFFai1msRO1wXaEeE5yQxYXgSfI8pQAWXbQop6sCtWE=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/crypto v0.0.0-20190510104115-cbcb75029529/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20190605123033-f99c8df09eb5/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20190820162420-60c769a6c586/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/crypto v0.0.0-20191011191535-87dc89f01550/go.mod h1:yigFU9vqHzYiE8UmvKecakEJjdnWj3jj499lnFckfCI=
golang.org/x/crypto v0.0.0-20200221231518-2aa609cf4a9d/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
golang.org/x/crypto v0.0.0-20200622213623-75b288015ac9/go.mod h1:LzIPMQfyMNhhGPhUkYOs5KpL4U8rLKemX1yGLhDgUto=
golang.org/x/crypto v0.0.0-20201203163018-be400aefbc4c/go.mod h1:jdWPYTVW3xRLrWPugEBEK3UY2ZEsg3UU495nc5E+M+I=
golang.org/x/crypto v0.0.0-20210322153248-0c34fe9e7dc2/go.mod h1:T9bdIzuCu7OtxOm1hfPfRQxPLYneinmdGuTeoZ9dtd4=
golang.org/x/crypto v0.0.0-20210616213533-5ff15b29337e/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
golang.org/x/crypto v0.0.0-20210711020723-a769d52b0f97/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
golang.org/x/crypto v0.0.0-20210921155107-089bfa567519/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
golang.org/x/crypto v0.0.0-20220314234659-1baeb1ce4c0b/go.mod h1:IxCIyHEi3zRg3s0A5j5BB6A9Jmi73HwBIUl50j+osU4=
golang.org/x/crypto v0.0.0-20220525230936-793ad666bf5e/go.mod h1:IxCIyHEi3zRg3s0A5j5BB6A9Jmi73HwBIUl50j+osU4=
golang.org/x/crypto v0.7.0 h1:AvwMYaRytfdeVt3u6mLaxYtErKYjxA2OXjJ1HHq6t3A=
golang.org/x/crypto v0.7.0/go.mod h1:pYwdfH91IfpZVANVyUOhSIPZaFoJGxTFbZhFTx+dXZU=
golang.org/x/exp v0.0.0-20190121172915-509febef88a4/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/exp v0.0.0-20190306152737-a1d7652674e8/go.mod h1:CJ0aWSM057203Lf6IL+f9T1iT9GByDxfZKAQTCR3kQA=
golang.org/x/exp v0.0.0-20190510132918-efd6b22b2522/go.mod h1:ZjyILWgesfNpC6sMxTJOJm9Kp84zZh5NQWvqDGG3Qr8=
golang.org/x/exp v0.0.0-20190829153037-c13cbed26979/go.mod h1:86+5VVa7VpoJ4kLfm080zCjGlMRFzhUhsZKEZO7MGek=
golang.org/x/exp v0.0.0-20191030013958-a1ab85dbe136/go.mod h1:JXzH8nQsPlswgeRAPE3MuO9GYsAcnJvJ4vnMwN/5qkY=
golang.org/x/exp v0.0.0-20221205204356-47842c84f3db h1:D/cFflL63o2KSLJIwjlcIt8PR064j/xsmdEJL/YvY/o=
golang.org/x/exp v0.0.0-20221205204356-47842c84f3db/go.mod h1:CxIveKay+FTh1D0yPZemJVgC/95VzuuOLq5Qi4xnoYc=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/image v0.0.0-20190227222117-0694c2d4d067/go.mod h1:kZ7UVZpmo3dzQBMxlp+ypCbDeSB+sBbTgSJuh5dn5js=
golang.org/x/image v0.0.0-20190802002840-cff245a6509b/go.mod h1:FeLwcggjj3mMvU+oOTbSwawSJRM1uh48EjtB4UJZlP0=
golang.org/x/lint v0.0.0-20180702182130-06c8688daad7/go.mod h1:UVdnD1Gm6xHRNCYTkRU2/jEulfH38KcIWyp/GAMgvoE=
golang.org/x/lint v0.0.0-20181026193005-c67002cb31c3/go.mod h1:UVdnD1Gm6xHRNCYTkRU2/jEulfH38KcIWyp/GAMgvoE=
golang.org/x/lint v0.0.0-20190227174305-5b3e6a55c961/go.mod h1:wehouNa3lNwaWXcvxsM5YxQ5yQlVC4a0KAMCusXpPoU=
golang.org/x/lint v0.0.0-20190301231843-5614ed5bae6f/go.mod h1:UVdnD1Gm6xHRNCYTkRU2/jEulfH38KcIWyp/GAMgvoE=
golang.org/x/lint v0.0.0-20190313153728-d0100b6bd8b3/go.mod h1:6SW0HCj/g11FgYtHlgUYUwCkIfeOF89ocIRzGO/8vkc=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/lint v0.0.0-20190409202823-959b441ac422/go.mod h1:6SW0HCj/g11FgYtHlgUYUwCkIfeOF89ocIRzGO/8vkc=
golang.org/x/lint v0.0.0-20190909230951-414d861bb4ac/go.mod h1:6SW0HCj/g11FgYtHlgUYUwCkIfeOF89ocIRzGO/8vkc=
golang.org/x/lint v0.0.0-20190930215403-16217165b5de/go.mod h1:6SW0HCj/g11FgYtHlgUYUwCkIfeOF89ocIRzGO/8vkc=
golang.org/x/lint v0.0.0-20200302205851-738671d3881b h1:Wh+f8QHJXR411sJR8/vRBTZ7YapZaRvUcLFFJhusH0k=
golang.org/x/lint v0.0.0-20200302205851-738671d3881b/go.mod h1:3xt1FjdF8hUf6vQPIChWIBhFzV8gjjsPE/fR3IyQdNY=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/mobile v0.0.0-20190312151609-d3739f865fa6/go.mod h1:z+o9i4GpDbdi3rU15maQ/Ox0txvL9dWGYEHz965HBQE=
golang.org/x/mobile v0.0.0-20190719004257-d2bd2a29d028/go.mod h1:E/iHnbuqvinMTCcRqshq8CkpyQDoeVncDDYHnLhea+o=
golang.org/x/mod v0.0.0-20190513183733-4bf6d317e70e/go.mod h1:mXi4GBBbnImb6dmsKGUJ2LatrhH/nqhxcFungHvyanc=
golang.org/x/mod v0.1.0/go.mod h1:0QHyrYULN0/3qlju5TqG8bIK38QM8yzMo5ekMj3DlcY=
golang.org/x/mod v0.1.1-0.20191105210325-c90efee705ee/go.mod h1:QqPTAvyqsEbceGzBzNggFXnrqF1CaUcvgkdR5Ot7KZg=
golang.org/x/mod v0.2.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.3.0/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.4.2/go.mod h1:s0Qsj1ACt9ePp/hMypM3fl4fZqREWJwdYDEqhRiZZUA=
golang.org/x/mod v0.6.0-dev.0.20220106191415-9b9b3d81d5e3/go.mod h1:3p9vT2HGsQu2K1YbXdKPJLVgG5VJdoTa1poYQBtP1AY=
golang.org/x/mod v0.6.0-dev.0.20220419223038-86c51ed26bb4/go.mod h1:jJ57K6gSWd91VN4djpZkiMVwK6gcyfeH4XE8wZrZaV4=
golang.org/x/mod v0.8.0 h1:LUYupSeNrTNCGzR/hVBk2NHZO4hXcVaW1k4Qx7rjPx8=
golang.org/x/mod v0.8.0/go.mod h1:iBbtSCu2XBx23ZKBPSOrRkjjQPZFPuis4dIYUhu/chs=
golang.org/x/net v0.0.0-20180724234803-3673e40ba225/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20180826012351-8a410e7b638d/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
2018-10-06 18:57:53 +01:00
golang.org/x/net v0.0.0-20180906233101-161cd47e91fd/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20181023162649-9b4f9f5ad519/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20181029044818-c44066c5c816/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20181106065722-10aee1819953/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20181114220301-adae6a3d119a/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20181201002055-351d144fa1fc/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20181220203305-927f97764cc3/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20190108225652-1e06a53dbb7e/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20190213061140-3a22650c66bd/go.mod h1:mL1N/T3taQHkDXs73rZJwtUhF3w3ftmwwsq0BUmARs4=
golang.org/x/net v0.0.0-20190311183353-d8887717615a/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
golang.org/x/net v0.0.0-20190313220215-9f648a60d977/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
golang.org/x/net v0.0.0-20190404232315-eb5bcb51f2a3/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/net v0.0.0-20190501004415-9ce7a6920f09/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
golang.org/x/net v0.0.0-20190503192946-f4e77d36d62c/go.mod h1:t9HGtf8HONx5eT2rtn7q6eTqICYqUVnKs3thJo3Qplg=
golang.org/x/net v0.0.0-20190603091049-60506f45cf65/go.mod h1:HSz+uSET+XFnRR8LxR5pz3Of3rY3CfYBVs4xY44aLks=
golang.org/x/net v0.0.0-20190620200207-3b0461eec859/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20190813141303-74dc4d7220e7/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20190923162816-aa69164e4478/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20200226121028-0de0cce0169b/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
golang.org/x/net v0.0.0-20200324143707-d3edc9973b7e/go.mod h1:qpuaurCH72eLCgpAm/N6yyVIVM9cpaDIP3A8BGJEC5A=
golang.org/x/net v0.0.0-20200520004742-59133d7f0dd7/go.mod h1:qpuaurCH72eLCgpAm/N6yyVIVM9cpaDIP3A8BGJEC5A=
golang.org/x/net v0.0.0-20200625001655-4c5254603344/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
golang.org/x/net v0.0.0-20200707034311-ab3426394381/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
golang.org/x/net v0.0.0-20200822124328-c89045814202/go.mod h1:/O7V0waA8r7cgGh81Ro3o1hOxt32SMVPicZroKQ2sZA=
golang.org/x/net v0.0.0-20201021035429-f5854403a974/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
golang.org/x/net v0.0.0-20201110031124-69a78807bb2b/go.mod h1:sp8m0HH+o8qH0wwXwYZr8TS3Oi6o0r6Gce1SSxlDquU=
golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
golang.org/x/net v0.0.0-20210405180319-a5a99cb37ef4/go.mod h1:p54w0d4576C0XHj96bSt6lcn1PtDYWL6XObtHCRCNQM=
golang.org/x/net v0.0.0-20210428140749-89ef3d95e781/go.mod h1:OJAsFXCWl8Ukc7SiCT/9KSuxbyM7479/AVlXFRxuMCk=
golang.org/x/net v0.0.0-20211015210444-4f30a5c0130f/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y=
golang.org/x/net v0.0.0-20211112202133-69e39bad7dc2/go.mod h1:9nx3DQGgdP8bBQD5qxJ1jj9UTztislL4KSBs9R2vV5Y=
golang.org/x/net v0.0.0-20220526153639-5463443f8c37/go.mod h1:XRhObCWvk6IyKnWLug+ECip1KBveYUHfp+8e9klMJ9c=
golang.org/x/net v0.0.0-20220722155237-a158d28d115b/go.mod h1:XRhObCWvk6IyKnWLug+ECip1KBveYUHfp+8e9klMJ9c=
golang.org/x/net v0.9.0 h1:aWJ/m6xSmxWBx+V0XRHTlrYrPG56jKsLdTFmsSsCzOM=
golang.org/x/net v0.9.0/go.mod h1:d48xBJpPfHeWQsugry2m+kC02ZBRGRgulfHnEXEuWns=
2018-10-06 18:57:53 +01:00
golang.org/x/oauth2 v0.0.0-20180821212333-d2e6202438be/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
golang.org/x/oauth2 v0.0.0-20181017192945-9dcd33a902f4/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
golang.org/x/oauth2 v0.0.0-20181203162652-d668ce993890/go.mod h1:N/0e6XlmueqKjAGxoOufVs8QHGRruUQn6yWY3a++T0U=
golang.org/x/oauth2 v0.0.0-20190226205417-e64efc72b421/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/oauth2 v0.0.0-20190604053449-0f29369cfe45/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
golang.org/x/oauth2 v0.0.0-20200107190931-bf48bf16ab8d/go.mod h1:gOpvHmFTYa4IltrdGE7lF6nIHvwfUNPOp7c8zoXwtLw=
golang.org/x/oauth2 v0.7.0 h1:qe6s0zUXlPX80/dITx3440hWZ7GwMwgDDyrSGTPJG/g=
golang.org/x/oauth2 v0.7.0/go.mod h1:hPLQkd9LyjfXTiRohC/41GhcFqxisoUQ99sCUOHO9x4=
golang.org/x/perf v0.0.0-20180704124530-6e6d33e29852/go.mod h1:JLpeXjPJfIyPr5TlbXLkXWLhP8nz10XfvxElABhCtcw=
2018-10-06 18:57:53 +01:00
golang.org/x/sync v0.0.0-20180314180146-1d60e4601c6f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20181108010431-42b317875d0f/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20181221193216-37e7f081c4d4/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20190227155943-e225da77a7e6/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20190911185100-cd5d95a43a6e/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20201020160332-67f06af15bc9/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20210220032951-036812b2e83c/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20220722155255-886fb9371eb4/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.0.0-20220819030929-7fc1605a5dde/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sync v0.1.0 h1:wsuoTGHzEhffawBOhz5CYhcrV4IdKZbEyZjBMuTp12o=
golang.org/x/sync v0.1.0/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
golang.org/x/sys v0.0.0-20180823144017-11551d06cbcc/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20180830151530-49385e6e1522/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20180905080454-ebe1bf3edb33/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
2018-10-06 18:57:53 +01:00
golang.org/x/sys v0.0.0-20180909124046-d0be0721c37e/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20181026203630-95b1ffbd15a5/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20181029174526-d69651ed3497/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20181107165924-66b7b1311ac8/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20181116152217-5ac8a444bdc5/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190204203706-41f3e6584952/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
golang.org/x/sys v0.0.0-20190222072716-a9d3bda3a223/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/sys v0.0.0-20190312061237-fead79001313/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190316082340-a2f829d7f35f/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190403152447-81d4e9dc473e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190412213103-97732733099d/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190422165155-953cdadca894/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/sys v0.0.0-20190502145724-3ef323f4f1fd/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190507160741-ecd444e8653b/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190606165138-5da285871e9c/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190624142023-c5567b49c5d0/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190813064441-fde4db37ae7a/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20190904154756-749cb33beabd/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191005200804-aed5e4c7ecf9/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191026070338-33540a1f6037/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191120155948-bd437916bb0e/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20191224085550-c709ea063b76/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200116001909-b77594299b42/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200202164722-d101bd2416d5/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200223170610-d5e6a3e2c0ae/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200323222414-85ca7c5b95cd/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200519105757-fe76b779f299/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200625212154-ddb9806d33ae/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20200930185726-fdedc70b468f/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210112080510-489259a85091/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210330210617-4fbd30eecc44/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210423082822-04245dca01da/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210510120138-977fb7262007/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210514084401-e8d321eab015/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20211007075335-d3039528d8ac/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20211019181941-9d821ace8654/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220412211240-33da011f77ad/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220520151302-bc2c85ada10a/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220722155257-8c9f86f7a55f/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.7.0 h1:3jlCCIQZPdOYu1h8BkNvLz8Kgwtae2cagcG/VamtZRU=
golang.org/x/sys v0.7.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/term v0.0.0-20201117132131-f5c789dd3221/go.mod h1:Nr5EML6q2oocZ2LXRh80K7BxOlk5/8JxuGnuhpl+muw=
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
golang.org/x/term v0.0.0-20210927222741-03fcf44c2211/go.mod h1:jbD1KX2456YbFQfuXm/mYQcufACuNUgVhRMnK/tPxf8=
golang.org/x/term v0.7.0 h1:BEvjmm5fURWqcfbSKTdpkDXYBrUS1c0m8agp14W48vQ=
golang.org/x/term v0.7.0/go.mod h1:P32HKFT3hSsZrRxla30E9HqToFYAQPCMs/zFMBUFqPY=
2018-10-06 18:57:53 +01:00
golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/text v0.3.1-0.20180807135948-17ff2d5776d2/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
golang.org/x/text v0.3.2/go.mod h1:bEr9sfX3Q8Zfm5fL9x+3itogRgK3+ptLWKqgva+5dAk=
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.4/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.7/go.mod h1:u+2+/6zg+i71rQMx5EYifcz6MCKuco9NR6JIITiCfzQ=
golang.org/x/text v0.3.8/go.mod h1:E6s5w1FMmriuDzIBO73fBruAKo1PCIq6d2Q6DHfQ8WQ=
golang.org/x/text v0.9.0 h1:2sjJmO8cDvYveuX97RDLsxlyUxLl+GHoLxBiRdHllBE=
golang.org/x/text v0.9.0/go.mod h1:e1OnstbJyHTd6l/uOt8jFFHp6TRDWZR/bV3emEE/zU8=
golang.org/x/time v0.0.0-20180412165947-fbb02b2291d2/go.mod h1:tRJNPiyCQ0inRvYxbN9jk5I+vvW/OXSQhTDSoE431IQ=
golang.org/x/time v0.0.0-20181108054448-85acf8d2951c/go.mod h1:tRJNPiyCQ0inRvYxbN9jk5I+vvW/OXSQhTDSoE431IQ=
golang.org/x/time v0.0.0-20190308202827-9d24e82272b4/go.mod h1:tRJNPiyCQ0inRvYxbN9jk5I+vvW/OXSQhTDSoE431IQ=
golang.org/x/time v0.0.0-20200630173020-3af7569d3a1e h1:EHBhcS0mlXEAVwNyO2dLfjToGsyY4j24pTs2ScHnX7s=
golang.org/x/time v0.0.0-20200630173020-3af7569d3a1e/go.mod h1:tRJNPiyCQ0inRvYxbN9jk5I+vvW/OXSQhTDSoE431IQ=
golang.org/x/tools v0.0.0-20180221164845-07fd8470d635/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20180828015842-6cd1fcedba52/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20181030000716-a0a13e073c7b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20190114222345-bf090417da8b/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/tools v0.0.0-20190226205152-f727befe758c/go.mod h1:9Yl7xja0Znq3iFh3HoIrodX9oNMXvdceNzlUR8zjMvY=
golang.org/x/tools v0.0.0-20190311212946-11955173bddd/go.mod h1:LCzVGOaR6xXOjkQ3onu1FJEFr0SW1gC7cKk1uF8kGRs=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/tools v0.0.0-20190312151545-0bb0c0a6e846/go.mod h1:LCzVGOaR6xXOjkQ3onu1FJEFr0SW1gC7cKk1uF8kGRs=
golang.org/x/tools v0.0.0-20190312170243-e65039ee4138/go.mod h1:LCzVGOaR6xXOjkQ3onu1FJEFr0SW1gC7cKk1uF8kGRs=
golang.org/x/tools v0.0.0-20190328211700-ab21143f2384/go.mod h1:LCzVGOaR6xXOjkQ3onu1FJEFr0SW1gC7cKk1uF8kGRs=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/tools v0.0.0-20190425150028-36563e24a262/go.mod h1:RgjU9mgBXZiqYHBnxXauZ1Gv1EHHAz9KjViQ78xBX0Q=
golang.org/x/tools v0.0.0-20190425163242-31fd60d6bfdc/go.mod h1:RgjU9mgBXZiqYHBnxXauZ1Gv1EHHAz9KjViQ78xBX0Q=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/tools v0.0.0-20190506145303-2d16b83fe98c/go.mod h1:RgjU9mgBXZiqYHBnxXauZ1Gv1EHHAz9KjViQ78xBX0Q=
golang.org/x/tools v0.0.0-20190524140312-2c0ae7006135/go.mod h1:RgjU9mgBXZiqYHBnxXauZ1Gv1EHHAz9KjViQ78xBX0Q=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/tools v0.0.0-20190606124116-d0a3d012864b/go.mod h1:/rFqwRUd4F7ZHNgwSSTFct+R/Kf4OFW1sUzUTQQTgfc=
golang.org/x/tools v0.0.0-20190621195816-6e04913cbbac/go.mod h1:/rFqwRUd4F7ZHNgwSSTFct+R/Kf4OFW1sUzUTQQTgfc=
golang.org/x/tools v0.0.0-20190628153133-6cdbf07be9d0/go.mod h1:/rFqwRUd4F7ZHNgwSSTFct+R/Kf4OFW1sUzUTQQTgfc=
golang.org/x/tools v0.0.0-20190816200558-6889da9d5479/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20190823170909-c4a336ef6a2f/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/tools v0.0.0-20190911174233-4f2ddba30aff/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20191012152004-8de300cfc20a/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20191029041327-9cc4af7d6b2c/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20191029190741-b9c20aec41a5/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20191112195655-aa38f8e97acc/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20191119224855-298f0cb1881e/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
golang.org/x/tools v0.0.0-20200103221440-774c71fcf114/go.mod h1:TB2adYChydJhpapKDTa4BR/hXlZSLoq2Wpct/0txZ28=
golang.org/x/tools v0.0.0-20200130002326-2f3ba24bd6e7/go.mod h1:TB2adYChydJhpapKDTa4BR/hXlZSLoq2Wpct/0txZ28=
golang.org/x/tools v0.0.0-20200619180055-7c47624df98f/go.mod h1:EkVYQZoAsY45+roYkvgYkIh4xh/qjgUK9TdY2XT94GE=
golang.org/x/tools v0.0.0-20201224043029-2b0845dc783e/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
golang.org/x/tools v0.0.0-20210106214847-113979e3529a/go.mod h1:emZCQorbCU4vsT4fOWvOPXz4eW1wZW4PmDk9uLelYpA=
golang.org/x/tools v0.1.1/go.mod h1:o0xws9oXOQQZyjljx8fwUC0k7L1pTE6eaCbjGeHmOkk=
golang.org/x/tools v0.1.10/go.mod h1:Uh6Zz+xoGYZom868N8YTex3t7RhtHDBrE8Gzo9bV56E=
golang.org/x/tools v0.1.12/go.mod h1:hNGJHUnrk76NpqgfD5Aqm5Crs+Hm0VOH/i9J2+nxYbc=
golang.org/x/tools v0.6.0 h1:BOw41kyTf3PuCW1pVQf8+Cyg8pMlkYB1oo9iJ6D/lKM=
golang.org/x/tools v0.6.0/go.mod h1:Xwgl3UAJ/d3gWutnCtw505GrjyAbvKui8lOU390QaIU=
golang.org/x/xerrors v0.0.0-20190410155217-1f06c39b4373/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20190513163551-3ee3066db522/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191011141410-1b5146add898/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20200804184101-5ec99f83aff1/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
golang.org/x/xerrors v0.0.0-20220517211312-f3a8303e98df/go.mod h1:K8+ghG5WaK9qNqU5K3HdILfMLy1f3aNYFI/wnl100a8=
golang.org/x/xerrors v0.0.0-20220907171357-04be3eba64a2 h1:H2TDz8ibqkAF6YGhCdN3jS9O0/s90v0rJh3X/OLHEUk=
google.golang.org/api v0.0.0-20180910000450-7ca32eb868bf/go.mod h1:4mhQ8q/RsB7i+udVvVy5NUi08OU8ZlA0gRVgrF7VFY0=
google.golang.org/api v0.0.0-20181030000543-1d582fd0359e/go.mod h1:4mhQ8q/RsB7i+udVvVy5NUi08OU8ZlA0gRVgrF7VFY0=
google.golang.org/api v0.1.0/go.mod h1:UGEZY7KEX120AnNLIHFMKIo4obdJhkp2tPbaPlQx13Y=
google.golang.org/api v0.4.0/go.mod h1:8k5glujaEP+g9n7WNsDg8QP6cUVNI86fCNMcbazEtwE=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
google.golang.org/api v0.7.0/go.mod h1:WtwebWUNSVBH/HAw79HIFXZNqEvBhG+Ra+ax0hx3E3M=
google.golang.org/api v0.8.0/go.mod h1:o4eAsZoiT+ibD93RtjEohWalFOjRDx6CVaqeizhEnKg=
google.golang.org/api v0.9.0/go.mod h1:o4eAsZoiT+ibD93RtjEohWalFOjRDx6CVaqeizhEnKg=
google.golang.org/api v0.13.0/go.mod h1:iLdEw5Ide6rF15KTC1Kkl0iskquN2gFfn9o9XIsbkAI=
google.golang.org/api v0.118.0 h1:FNfHq9Z2GKULxu7cEhCaB0wWQHg43UpomrrN+24ZRdE=
google.golang.org/api v0.118.0/go.mod h1:76TtD3vkgmZ66zZzp72bUUklpmQmKlhh6sYtIjYK+5E=
google.golang.org/appengine v1.1.0/go.mod h1:EbEs0AVv82hx2wNQdGPgUI5lhzA/G0D9YwlJXL52JkM=
google.golang.org/appengine v1.2.0/go.mod h1:xpcJRLb0r/rnEns0DIKYYv+WjYCduHsrkT7/EB5XEv4=
google.golang.org/appengine v1.3.0/go.mod h1:xpcJRLb0r/rnEns0DIKYYv+WjYCduHsrkT7/EB5XEv4=
google.golang.org/appengine v1.4.0/go.mod h1:xpcJRLb0r/rnEns0DIKYYv+WjYCduHsrkT7/EB5XEv4=
google.golang.org/appengine v1.5.0/go.mod h1:xpcJRLb0r/rnEns0DIKYYv+WjYCduHsrkT7/EB5XEv4=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
google.golang.org/appengine v1.6.1/go.mod h1:i06prIuMbXzDqacNJfV5OdTW448YApPu5ww/cMBSeb0=
google.golang.org/appengine v1.6.6/go.mod h1:8WjMMxjGQR8xUklV/ARdw2HLXBOI7O7uCIDZVag1xfc=
google.golang.org/appengine v1.6.7 h1:FZR1q0exgwxzPzp/aF+VccGrSfxfPpkBqjIIEq3ru6c=
google.golang.org/appengine v1.6.7/go.mod h1:8WjMMxjGQR8xUklV/ARdw2HLXBOI7O7uCIDZVag1xfc=
2018-10-06 18:57:53 +01:00
google.golang.org/genproto v0.0.0-20180817151627-c66870c02cf8/go.mod h1:JiN7NxoALGmiZfu7CAH4rXhgtRTLTxftemlI0sWmxmc=
google.golang.org/genproto v0.0.0-20180831171423-11092d34479b/go.mod h1:JiN7NxoALGmiZfu7CAH4rXhgtRTLTxftemlI0sWmxmc=
google.golang.org/genproto v0.0.0-20181029155118-b69ba1387ce2/go.mod h1:JiN7NxoALGmiZfu7CAH4rXhgtRTLTxftemlI0sWmxmc=
google.golang.org/genproto v0.0.0-20181202183823-bd91e49a0898/go.mod h1:7Ep/1NZk928CDR8SjdVbjWNpdIf6nzjE3BTgJDr2Atg=
google.golang.org/genproto v0.0.0-20190306203927-b5d61aea6440/go.mod h1:VzzqZJRnGkLBvHegQrXjBqPurQTc5/KpmUdxsrq26oE=
google.golang.org/genproto v0.0.0-20190307195333-5fe7a883aa19/go.mod h1:VzzqZJRnGkLBvHegQrXjBqPurQTc5/KpmUdxsrq26oE=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
google.golang.org/genproto v0.0.0-20190418145605-e7d98fc518a7/go.mod h1:VzzqZJRnGkLBvHegQrXjBqPurQTc5/KpmUdxsrq26oE=
google.golang.org/genproto v0.0.0-20190425155659-357c62f0e4bb/go.mod h1:VzzqZJRnGkLBvHegQrXjBqPurQTc5/KpmUdxsrq26oE=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
google.golang.org/genproto v0.0.0-20190502173448-54afdca5d873/go.mod h1:VzzqZJRnGkLBvHegQrXjBqPurQTc5/KpmUdxsrq26oE=
google.golang.org/genproto v0.0.0-20190801165951-fa694d86fc64/go.mod h1:DMBHOl98Agz4BDEuKkezgsaosCRResVns1a3J2ZsMNc=
google.golang.org/genproto v0.0.0-20190819201941-24fa4b261c55/go.mod h1:DMBHOl98Agz4BDEuKkezgsaosCRResVns1a3J2ZsMNc=
google.golang.org/genproto v0.0.0-20190911173649-1774047e7e51/go.mod h1:IbNlFCBrqXvoKpeg0TB2l7cyZUmoaFKYIwrEpbDKLA8=
google.golang.org/genproto v0.0.0-20191108220845-16a3f7862a1a/go.mod h1:n3cpQtvxv34hfy77yVDNjmbRyujviMdxYliBSkLhpCc=
google.golang.org/genproto v0.0.0-20200513103714-09dca8ec2884/go.mod h1:55QSHmfGQM9UVYDPBsyGGes0y52j32PQ3BqQfXhyH3c=
google.golang.org/genproto v0.0.0-20200526211855-cb27e3aa2013/go.mod h1:NbSheEEYHJ7i3ixzK3sjbqSGDJWnxyFXZblF3eUsNvo=
google.golang.org/genproto v0.0.0-20230410155749-daa745c078e1 h1:KpwkzHKEF7B9Zxg18WzOa7djJ+Ha5DzthMyZYQfEn2A=
google.golang.org/genproto v0.0.0-20230410155749-daa745c078e1/go.mod h1:nKE/iIaLqn2bQwXBg8f1g2Ylh6r5MN5CmZvuzZCgsCU=
google.golang.org/grpc v1.14.0/go.mod h1:yo6s7OP7yaDglbqo1J04qKzAhqBH6lvTonzMVmEdcZw=
google.golang.org/grpc v1.16.0/go.mod h1:0JHn/cJsOMiMfNA9+DeHDlAU7KAAB5GDlYFpa9MZMio=
google.golang.org/grpc v1.17.0/go.mod h1:6QZJwpn2B+Zp71q/5VxRsJ6NXXVCE5NRUHRo+f3cWCs=
google.golang.org/grpc v1.19.0/go.mod h1:mqu4LbDTu4XGKhr4mRzUsmM4RtVoemTSY81AxZiDr8c=
google.golang.org/grpc v1.20.1/go.mod h1:10oTOabMzJvdu6/UiuZezV6QK5dSlG84ov/aaiqXj38=
google.golang.org/grpc v1.21.1/go.mod h1:oYelfM1adQP15Ek0mdvEgi9Df8B9CZIaU1084ijfRaM=
google.golang.org/grpc v1.23.0/go.mod h1:Y5yQAOtifL1yxbo5wqy6BxZv8vAUGQwXBOALyacEbxg=
google.golang.org/grpc v1.25.1/go.mod h1:c3i+UQWmh7LiEpx4sFZnkU36qjEYZ0imhYfXVyQciAY=
google.golang.org/grpc v1.27.0/go.mod h1:qbnxyOmOxrQa7FizSgH+ReBfzJrCY1pSN7KXBS8abTk=
google.golang.org/grpc v1.33.1/go.mod h1:fr5YgcSWrqhRRxogOsw7RzIpsmvOZ6IcH4kBYTpR3n0=
google.golang.org/grpc v1.33.2/go.mod h1:JMHMWHQWaTccqQQlmk3MJZS+GWXOdAesneDmEnv2fbc=
google.golang.org/grpc v1.36.0/go.mod h1:qjiiYl8FncCW8feJPdyg3v6XW24KsRHe+dy9BAGRRjU=
google.golang.org/grpc v1.45.0/go.mod h1:lN7owxKUQEqMfSyQikvvk5tf/6zMPsrK+ONuO11+0rQ=
google.golang.org/grpc v1.55.0 h1:3Oj82/tFSCeUrRTg/5E/7d/W5A1tj6Ky1ABAuZuv5ag=
google.golang.org/grpc v1.55.0/go.mod h1:iYEXKGkEBhg1PjZQvoYEVPTDkHo1/bjTnfwTeGONTY8=
google.golang.org/protobuf v0.0.0-20200109180630-ec00e32a8dfd/go.mod h1:DFci5gLYBciE7Vtevhsrf46CRTquxDuWsQurQQe4oz8=
google.golang.org/protobuf v0.0.0-20200221191635-4d8936d0db64/go.mod h1:kwYJMbMJ01Woi6D6+Kah6886xMZcty6N08ah7+eCXa0=
google.golang.org/protobuf v0.0.0-20200228230310-ab0ca4ff8a60/go.mod h1:cfTl7dwQJ+fmap5saPgwCLgHXTUD7jkjRqWcaiX5VyM=
google.golang.org/protobuf v1.20.1-0.20200309200217-e05f789c0967/go.mod h1:A+miEFZTKqfCUM6K7xSMQL9OKL/b6hQv+e19PK+JZNE=
google.golang.org/protobuf v1.21.0/go.mod h1:47Nbq4nVaFHyn7ilMalzfO3qCViNmqZ2kzikPIcrTAo=
google.golang.org/protobuf v1.22.0/go.mod h1:EGpADcykh3NcUnDUJcl1+ZksZNG86OlYog2l/sGQquU=
google.golang.org/protobuf v1.23.0/go.mod h1:EGpADcykh3NcUnDUJcl1+ZksZNG86OlYog2l/sGQquU=
google.golang.org/protobuf v1.23.1-0.20200526195155-81db48ad09cc/go.mod h1:EGpADcykh3NcUnDUJcl1+ZksZNG86OlYog2l/sGQquU=
google.golang.org/protobuf v1.25.0/go.mod h1:9JNX74DMeImyA3h4bdi1ymwjUzf21/xIlbajtzgsN7c=
google.golang.org/protobuf v1.26.0-rc.1/go.mod h1:jlhhOSvTdKEhbULTjvd4ARK9grFBp09yW+WbY/TyQbw=
google.golang.org/protobuf v1.26.0/go.mod h1:9q0QmTI4eRPtz6boOQmLYwt+qCgq0jsYwAQnmE0givc=
google.golang.org/protobuf v1.27.1/go.mod h1:9q0QmTI4eRPtz6boOQmLYwt+qCgq0jsYwAQnmE0givc=
google.golang.org/protobuf v1.30.0 h1:kPPoIgf3TsEvrm0PFe15JQ+570QVxYzEvvHqChK+cng=
google.golang.org/protobuf v1.30.0/go.mod h1:HV8QOd/L58Z+nl8r43ehVNZIU/HEI6OcFqwMG9pJV4I=
gopkg.in/alecthomas/kingpin.v2 v2.2.6/go.mod h1:FMv+mEhP44yOT+4EoQTLFTRgOQ1FBLkstjWtayDeSgw=
2018-10-06 18:57:53 +01:00
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20180628173108-788fd7840127/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20190902080502-41f04d3bba15/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c/go.mod h1:JHkPIbrfpd72SG/EVd6muEfDQjcINNoR0C8j2r3qZ4Q=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
gopkg.in/errgo.v2 v2.1.0/go.mod h1:hNsd1EY+bozCKY1Ytp96fpM3vjJbqLJn88ws8XvfDNI=
2018-10-06 18:57:53 +01:00
gopkg.in/fsnotify.v1 v1.4.7/go.mod h1:Tz8NjZHkW78fSQdbUxIjBTcgA1z1m8ZHf0WmKUhAMys=
gopkg.in/inconshreveable/log15.v2 v2.0.0-20180818164646-67afb5ed74ec/go.mod h1:aPpfJ7XW+gOuirDoZ8gHhLh3kZ1B08FtV2bbmy7Jv3s=
gopkg.in/inf.v0 v0.9.1/go.mod h1:cWUDdTG/fYaXco+Dcufb5Vnc6Gp2YChqWtbxRZE0mXw=
gopkg.in/ini.v1 v1.51.0/go.mod h1:pNLf8WUiyNEtQjuu5G5vTm06TEv9tsIgeAvK8hOrP4k=
gopkg.in/ini.v1 v1.62.0 h1:duBzk771uxoUuOlyRLkHsygud9+5lrlGjdFBb4mSKDU=
gopkg.in/ini.v1 v1.62.0/go.mod h1:pNLf8WUiyNEtQjuu5G5vTm06TEv9tsIgeAvK8hOrP4k=
gopkg.in/resty.v1 v1.12.0/go.mod h1:mDo4pnntr5jdWRML875a/NmxYqAlA73dVijT2AXvQQo=
gopkg.in/segmentio/analytics-go.v3 v3.1.0 h1:UzxH1uaGZRpMKDhJyBz0pexz6yUoBU3x8bJsRk/HV6U=
gopkg.in/segmentio/analytics-go.v3 v3.1.0/go.mod h1:4QqqlTlSSpVlWA9/9nDcPw+FkM2yv1NQoYjUbL9/JAw=
gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7 h1:uRGJdciOHaEIrze2W8Q3AKkepLTh2hOroT7a+7czfdQ=
2018-10-06 18:57:53 +01:00
gopkg.in/tomb.v1 v1.0.0-20141024135613-dd632973f1e7/go.mod h1:dt/ZhP58zS4L8KSrWDmTeBkI65Dw0HsyUHuEVlX15mw=
gopkg.in/yaml.v2 v2.0.0-20170812160011-eb3733d160e7/go.mod h1:JAlM8MvJe8wmxCU4Bli9HhUf9+ttbYbLASfIpnQbh74=
2018-10-06 18:57:53 +01:00
gopkg.in/yaml.v2 v2.2.1/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.2.2/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.2.3/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.2.4/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.3.0/go.mod h1:hI93XBmqTisBFMUTm0b8Fm+jr3Dg1NNxqwp+5A1VGuI=
gopkg.in/yaml.v2 v2.4.0 h1:D8xgwECY7CYvx+Y2n4sBz93Jn9JRvxdiyyo8CTfuKaY=
gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.0-20200615113413-eeeca48fe776/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
grpc.go4.org v0.0.0-20170609214715-11d0a25b4919/go.mod h1:77eQGdRu53HpSqPFJFmuJdjuHRquDANNeA4x7B8WQ9o=
honnef.co/go/tools v0.0.0-20180728063816-88497007e858/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
honnef.co/go/tools v0.0.0-20190102054323-c2f93a96b099/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
honnef.co/go/tools v0.0.0-20190106161140-3f1c8253044a/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
honnef.co/go/tools v0.0.0-20190418001031-e561f6794a2a/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
honnef.co/go/tools v0.0.0-20190523083050-ea95bdfd59fc/go.mod h1:rf3lG4BRIbNafJWhAfAdb/ePZxsR/4RtNHQocxwk9r4=
honnef.co/go/tools v0.0.1-2019.2.3 h1:3JgtbtFHMiCmsznwGVTUWbgGov+pVqnlf1dEJTNAXeM=
pkg/process: Now that we are trying to identify the root cause of the satellite load limitations (i.e. currently the satellite has a max ability of 400 rps for uploads and we need this to be higher), we are using the golang diagnostic tools to collect insight into what the bottlenecks are. We currently have a debug endpoint to gather some cpu and mem data, but it could be useful to have continuous profiling. GCP stackdriver has support for continuous profiling so lets set that up and see if it is helpful to gather more data. This PR adds support for [GCP continuous profiler](https://cloud.google.com/profiler) which allows enabling continuous cpu/mem profiling and the stats are sent to stackdriver in google cloud console. To enable the continuous profiling for a storj component, do the following: - prereq: the workload must be running in GKE and have Stackdriver Profiling IAM role permissions - provide the config flag `debug.profilename` in the config.yaml file for the workload (i.e. satellite api process, etc). The profilename should be the workload name, for example "satellite-api". - once the above config flag is provided, the profiler will be initialized and profiling stats will automatically be sent to GCP project where the workload is running and viewable in the Stackdriver Profile page in the console The current implementation assumes the workload is running in GKE, however if we find if useful we can add support to enable this from anywhere. But for simplicity, its configured this way assuming the main goal is to enable in production systems. Change-Id: Ibf8ebe2df7bf06fdd4951ee6a1e48854dd36ad47
2020-02-25 16:46:12 +00:00
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