currently production uses a different application suffix for gc
services, so chronograf can distinguish between gc processes and core
processes, but it'd be nice to be a bit more consistent with repairers
and api servers
Change-Id: Icb96fed006c59d7afd730317d35636a6e4573b58
Currently storj-sim relies on the log lines to be exactly the same,
when they change it cannot find the necessary information from log.
Change-Id: Ia039915ef3375a7cf60f107b2c05c958de15b6d5
uuid.UUID implements driver.Value so it can be directly used as a
scannable result.
Replace uses of dbutil.BytesToUUID with uuid.FromBytes.
Change-Id: I51a670185ceb3cc2199d5aa2b76bc3fc191ca8fe
Previous split to a storj.io/private repository broke tag-release.sh
script. This is the minimal temporary fix to make things work.
This links the build information to specified variables and sets them
inline. This approach, of course, is very fragile.
Change-Id: I73db2305e6c304146e5a14b13f1d917881a7455c
* debug
* traces
* cfgstruct
* process
Package `storj/private/version` will be removed as a separate change.
Change-Id: Iadc40faa782e6225513b28218952f02d9c240a9f
We are not generating identity for gateway during setup anymore, its
generated on-fly by libuplink. With this change we can remove
`--identity-dir` from gateway.
Change-Id: I63298115d4399564b2f29541b8dc16e3b3acdcf2
The admission/v3 protocol now supports arbitrary key/value headers to be
included in each packet of metrics. This commit creates support for
this, so the lua config file can declare a filter taking into account
the key/value headers.
Change-Id: I41de8c018d33304ccf46ec221ae689d55c5fb1ee
Previously, we were simply discarding rows from the repair queue when
they couldn't be repaired (either because the overlay said too many
nodes were down, or because we failed to download enough pieces).
Now, such segments will be put into the irreparableDB for further
and (hopefully) more focused attention.
This change also better differentiates some error cases from Repair()
for monitoring purposes.
Change-Id: I82a52a6da50c948ddd651048e2a39cb4b1e6df5c
New API has limited number of options to configure at the moment. We
should remove unused flags from Uplink CLI and add if needed in the
future.
Change-Id: Icf3f3dadd43cb61a3b408b02d0762aef34425dbf
On satellite, remove all references to free_bandwidth column in nodes table.
On storage node, remove references to AllocatedBandwidth and MinimumBandwidth and mark as deprecated.
Protobuf message, NodeCapacity, is left intact for backwards compatibility.
Once this is released to all satellites, we can drop the column from the DB.
Change-Id: I2ff6c6537fc9008a0c5588e951afea58ede85838
By using a require for storj.io/storj it will make the import
unambiguous. This means it is possible to have a module name
storj.io/storj/cmd/gateway.
Change-Id: I98439cbbaf433ae31309b7f80a19ced896018f65
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
The code to generate monkit.lock has a bug where it doesn't take
ScopeNamed into account and assumes the package. Since the downgrade
file was created from monkit.lock, we also assumed the package, so
we were downgrading to the wrong metric.
No other places call ScopeNamed that would cause a problem.
Change-Id: If9fbbd971a7d755f5de33ed20b8a6bcc95670ee3
This peer will contain our administrative panels.
It's completely separated from our other satellite
processes because it allows better control for restricting
access to it.
Change-Id: Ifca473bee82ff6c680b346918ba32b835a7a6847
In case the endpoint doesn't start, it might end up indefinitely
waiting for it to come up stalling jenkins.
Change-Id: Ib10bf1a25461e7532ec56ca705178bc9a7f85d12
this commit updates our monkit dependency to the v3 version where
it outputs in an influx style. this makes discovery much easier
as many tools are built to look at it this way.
graphite and rothko will suffer some due to no longer being a tree
based on dots. hopefully time will exist to update rothko to
index based on the new metric format.
it adds an influx output for the statreceiver so that we can
write to influxdb v1 or v2 directly.
Change-Id: Iae9f9494a6d29cfbd1f932a5e71a891b490415ff
Currently we risk losing pending bandwidth rollup writes even on a clean
shutdown. This change ensures that all pending writes are actually
written to the db when shutting down the satellite.
Change-Id: Ideab62fa9808937d3dce9585c52405d8c8a0e703
Setup command of uplink has to create the configuration directory just
before saving the configuration file for making it more robust than
creating in the initial state of the process.
When creating the directory at the beginning of the process leaves the
possibility to delete such directory during the setup process and leads
to a failure.
Ticket https://storjlabs.atlassian.net/browse/V3-3545
Change-Id: I30db0175e23a597e9675d267b4d7e25d5d4c5119
storagenode database preflight check.
Disable preflight database check by default, and have the option to
enable it. This will allow us to enable it once it is definitely
working.
Also change the name of the config flag for preflight time sync.
Change-Id: Ie2e20f9e25dcb38794eafa7e1505e7c6ff287c99
for storagenode
Ensure that database schema matches latest test migration schema before
allowing the node to start up.
Ensure minimal read/write functionality for each storagenode database
before allowing the node to start up.
This will eliminate many unhandled audit errors we are seeing.
Change-Id: Ic0e628b04a9c35b7a8243f6a81d4683918170ba9
this commit introduces the reported_serials table. its purpose is
to allow for blind writes into it as nodes report in so that we have
minimal contention. in order to continue to accurately account for
used bandwidth, though, we cannot immediately add the settled amount.
if we did, we would have to give up on blind writes.
the table's primary key is structured precisely so that we can quickly
find expired orders and so that we maximally benefit from rocksdb
path prefix compression. we do this by rounding the expires at time
forward to the next day, effectively giving us storagenode petnames
for free. and since there's no secondary index or foreign key
constraints, this design should use significantly less space than
the current used_serials table while also reducing contention.
after inserting the orders into the table, we have a chore that
periodically consumes all of the expired orders in it and inserts
them into the existing rollups tables. this is as if we changed
the nodes to report as the order expired rather than as soon as
possible, so the belief in correctness of the refactor is higher.
since we are able to process large batches of orders (typically
a day's worth), we can use the code to maximally batch inserts into
the rollup tables to make inserts as friendly as possible to
cockroach.
Change-Id: I25d609ca2679b8331979184f16c6d46d4f74c1a6
JIRA: https://storjlabs.atlassian.net/browse/V3-3499
The `uplink share` command does not print the restricted API key and the
restricted encryption access anymore.
Change-Id: Ie4ebe0b27067ee00af97c775f4e06f558b894fe2
