Alpha=1 and beta=0 are the expected first values for any alpha/beta
reputation system we are using in the codebase. So we are removing the
configurability of these values.
Change-Id: Ic61861b8ea5047fa1438ea6609b1d0048bf0abc3
We want to increase our throughput for downtime estimation. This commit
adds the ability to reach out to multiple nodes concurrently for downtime
estimation. The number of concurrent routines is determined by a new config
flag, EstimationConcurrencyLimit. It also increases the default
EstimationBatchSize to 1000.
Change-Id: I800ce7ec1035885afa194c3c3f64eedd4f6f61eb
BeginObject response
We want to control inline segment size and segment size on satellite
side. We need to return such information to uplink like with redundancy
scheme.
Change-Id: If04b0a45a2757a01c0cc046432c115f475e9323c
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
* add script for easy rolling upgrade test local execution
* remove unneeded binaries building for rolling upgrade and versions
tests
* unify build process for Jenkins and local execution for rolling
upgrade and versions tests
Change-Id: Ic11211b83f3f447494bbd5827d2af77ea4b20dfe
Add flag to satellite repairer, "InMemoryRepair" that allows the
satellite to decide whether to download the entire segment being
repaired into memory (this is what the satellite already does), or to
download it into temporary files on disk that will be read from in the
upload phase of repair.
This should help with handling high repair traffic on satellites that
cannot afford to spend 64mb of memory per repair worker.
Updates tests to test repair for both in memory and to disk.
Change-Id: Iddf591e165621497c98533d45bfea3c28b08a194
this is going to make all the tests slower but it is what it is
test-sim-aws.sh is removed because it was moved to storj/gateway repo.
Change-Id: I10727e747a4c3740b1c9054ce7d17313b4fa310b
1. only run release tags that don't contain 'rc'
2. install gateway version that's the same as satellite
3. update gateway access to contain satellite id
Change-Id: I8ca1418302c3aafdf0c4eaaf8361422a1eec2bd4
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
This new repair timeout (configured as TotalTimeout) will include both
the time to download pieces and the time to upload pieces, as well as
the time to pop the segment from the repair queue.
This is a move from Github PR #3645.
Change-Id: I47d618f57285845d8473fcd285f7d9be9b4318c8
This change adds two new tables to process orders as fast as we used
to but in an asynchronous manner and with hopefully less storage
usage. This should help scale on cockroach, but limits us to one
worker. It lays the groundwork for the order processing pipeline to
be queue rather than database driven.
For more details, see the added fast billing changes blueprint.
It also fixes the orders db so that all the timestamps that are
passed to columns that do not contain a time zone are converted to
UTC at the last possible opportunity, making it less likely to use
the APIs incorrectly. We really should migrate to include timezones
on all of our timestamp columns.
Change-Id: Ibfda8e7a3d5972b7798fb61b31ff56419c64ea35
