This should reduce potential spikes in the number of established connections in the following cases:
- when the connection establishing procedure becomes temporarily slow
- after a temporary spike in the rate of ConnPool.Get() calls
See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2552
Previously ScrapeConfig.clone() was improperly copying promauth.Secret fields -
their contents was replaced with `<secret>` value.
This led to inability to use passwords and secrets in `-promscrape.config` file.
The bug has been introduced in v1.77.0 in the commit 67b10896d2
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2551
* {lib/promscrape,app/vmagent}: adds sigv4 support for vmagent remoteWrite
moves aws related code into separate lib from lib/promscrape
it allows to write data from vmagent to the AWS managed prometheus (cortex)
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1287
* Apply suggestions from code review
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/{storage,flagutil} - Add option for snapshot autoremoval
- add prometheus-like duration as command flag
- add option to delete stale snapshots
- update duration.go flag to re-use own code
* wip
* lib/flagutil: re-use Duration.Set() call in NewDuration
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* Export "null" in jsonl instead of NaN
The NaN appeared because of staleness markers that were added for compatibility. I think it's better to use json `null`, implemented here.
Also maybe it also makes sense to add a flag like `?skip-staleness-markers=true` to `/export`, to skip nulls at all?
* Update app/vmselect/prometheus/export.qtpl
* app/vmselect/prometheus/export.qtpl.go: `make quicktemplate-gen`
* docs/CHANGELOG.md: document the change
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
This should prevent from `duplicate time series` errors when executing the following query:
kube_pod_container_resource_requests{resource="cpu"} * on (namespace,pod) group_left() (kube_pod_status_phase{phase=~"Pending|Running"}==1)
where `kube_pod_status_phase{phase=~"Pending|Running"}==1` filters out diplicate time series
Reduce the number of memory allocations in this function. This improves its performance by up to 50%.
This should improve service discovery speed when big number of potential targets with big number of meta-labels
are generated by service discovery.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2270
* lib/promscrape: adds job restart method
it must restart only ScrapeConfig with changed content
this change greatly reduce time, that needed for job restart
and it should decrease possible data loss when config frequently changed at kubernetes based deployments
Apply suggestions from code review
Co-authored-by: Roman Khavronenko <roman@victoriametrics.com>
* wip
Co-authored-by: Roman Khavronenko <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
The following actions are taken:
- Increase the TLS hashdshake timeout from 5 seconds to 10 seconds
- Increase dial timeout from 5 seconds to 30 seconds
- Specify DialContext instead of Dial in http.Transport. This allows properly handling
the Context arg during dialing the remote storage
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1699
Some of the releases could negatively affect performance for a limited
period of time due to some changes in core. Update details are meant to
warn users about expected changes in peformance after the update.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* fixes jwt token parse with correct base64Url decoding
it must be applied according to jwt RFC that requires token to be URL safe
added slow path for decoding tokens with std base64 decoding
adds error logging for vmgateway
* docs/CHANGELOG.md: document the bugfix
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/discovery/consul: update services on the watcher's start
Previously, watcher's start was only initing goroutines for discovery
but not waiting for the first iteration to end. It means first Consul
discovery wasn't returning discovered targets until the next iteration.
The change makes the watcher's start blocking until we get first discovery
iteration done and all registries updated.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* vmalert: remove workarounds for consul SD
Now when consul SD lib properly updates services
on the first start, we don't need workarounds in vmalert.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* lib/discovery/consul: update after review
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/index: reduce read/write load after indexDB rotation
IndexDB in VM is responsible for storing TSID - ID's used for identifying
time series. The index is stored on disk and used by both ingestion and read path.
IndexDB is stored separately to data parts and is global for all stored data.
It can't be deleted partially as VM deletes data parts. Instead, indexDB is
rotated once in `retention` interval.
The rotation procedure means that `current` indexDB becomes `previous`,
and new freshly created indexDB struct becomes `current`. So in any time,
VM holds indexDB for current and previous retention periods.
When time series is ingested or queried, VM checks if its TSID is present
in `current` indexDB. If it is missing, it checks the `previous` indexDB.
If TSID was found, it gets copied to the `current` indexDB. In this way
`current` indexDB stores only series which were active during the retention
period.
To improve indexDB lookups, VM uses a cache layer called `tsidCache`. Both
write and read path consult `tsidCache` and on miss the relad lookup happens.
When rotation happens, VM resets the `tsidCache`. This is needed for ingestion
path to trigger `current` indexDB re-population. Since index re-population
requires additional resources, every index rotation event may cause some extra
load on CPU and disk. While it may be unnoticeable for most of the cases,
for systems with very high number of unique series each rotation may lead
to performance degradation for some period of time.
This PR makes an attempt to smooth out resource usage after the rotation.
The changes are following:
1. `tsidCache` is no longer reset after the rotation;
2. Instead, each entry in `tsidCache` gains a notion of indexDB to which
they belong;
3. On ingestion path after the rotation we check if requested TSID was
found in `tsidCache`. Then we have 3 branches:
3.1 Fast path. It was found, and belongs to the `current` indexDB. Return TSID.
3.2 Slow path. It wasn't found, so we generate it from scratch,
add to `current` indexDB, add it to `tsidCache`.
3.3 Smooth path. It was found but does not belong to the `current` indexDB.
In this case, we add it to the `current` indexDB with some probability.
The probability is based on time passed since the last rotation with some threshold.
The more time has passed since rotation the higher is chance to re-populate `current` indexDB.
The default re-population interval in this PR is set to `1h`, during which entries from
`previous` index supposed to slowly re-populate `current` index.
The new metric `vm_timeseries_repopulated_total` was added to identify how many TSIDs
were moved from `previous` indexDB to the `current` indexDB. This metric supposed to
grow only during the first `1h` after the last rotation.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/promscrape: support prometheus-like duration in scrape configs
The change allows to specify duration values like `1d`, `1w`
for fields `scrape_interval`, `scrape_timeout`, etc.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/817#issuecomment-1033384766
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* lib/blockcache: make linter happy
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* lib/promscrape: support prometheus-like duration in scrape configs
* add support for extra fields `scrape_align_interval` and `scrape_offset`;
* support Prometheus duration parsing for `__scrape_interval__`
and `__scrape_duration__` labels;
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
* wip
* docs/CHANGELOG.md: document the feature
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* fixes service discovery for kubernetes
now it must take in account all pods that belong to the discovered endpoint and endpointslice
adds simple test for endpoints
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2134
* wip
* docs/CHANGELOG.md: document the change
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* adds CGO build for arm64
it must improve performance for arm64 based deployments of vmstorage and
vmsingle for 15-20%
it depends on gozstd package update for correct musl gozstd vendoring
* typo fixes
* docs/CHANGELOG.md: document the change
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* Mention about the ability to configure vmalert notifiers via files in docs/CHANGELOG.md
* Mention about the ability to use Consul service discovery for vmalert notifiers in docs/CHANGELOG.md
* Run `make docs-sync` in order to sync app/vmalert/README.md to docs/vmalert.md
This metric shows the number of CPU cores available to the process.
This allows creating alerting rules on CPU saturation with the following query:
rate(process_cpu_seconds_total[5m]) / process_cpu_cores_available > 0.9
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2107
This adds more optimization cases for https://utcc.utoronto.ca/~cks/space/blog/sysadmin/PrometheusLabelNonOptimization
For example:
* Multi-level transform functions. For example, abs(round(foo{a="b"})) + bar{x="y"}
is now optimized to abs(round(foo{a="b",x="y"})) + bar{a="b",x="y"}
* Binary operations with `on()`, `without()`, `group_left()` and `group_right()` modifiers.
For example, foo{a="b"} on (a) + bar is now optimized to foo{a="b"} on (a) + bar{a="b"}
* Multi-level binary operations. For example, foo{a="b"} + bar{x="y"} + baz{z="q"}
is now optimized to foo{a="b",x="y",z="q"} + bar{a="b",x="y",z="q"} + baz{a="b",x="y",z="q"}
* Aggregate functions. For example, sum(foo{a="b"}) by (c) + bar{c="d"}
is now optimized to sum(foo{a="b",c="d"}) by (c) + bar{c="d"}
