This commits adds storage part and cluster RPC methods for metrics metadata.
Key concepts:
* vmstorage persists metadata in-memory only.
* vmstorage evicts metadata records older than 1 hour.
* vmstorage stores only the last value of metadata for time series
metric name.
* vminsert opens an additional TCP connection to the vmstorage for
metadata write requests.
* vmselect doesn't support `limit_per_metric_name`.
This feature is available optional and must be enabled via flag - `-enableMetadata` provided to vminsert/vmsingle.
Fixes github.com/VictoriaMetrics/VictoriaMetrics/issues/2974
- Rename WriteRequestUnmarshaller to WriteRequestUnmarshaler
- Add a description to WriteRequestUnmarshaler struct
Review comments
b98e592752 (r163365472)
Follow up on
b98e592752
The prompb and prompbmarshal share exactly the same models and provide
marshal and unmarshale capabilities for them. This creates duplication
(changes in one model has to be made in another, case with metadata) and
confusion where for example you compare same looking models but golang
says they are not the same (because of the type).
This commit merge prompbmarshal logic into prompb so the rest of the
code is aligned on prompb models.
Moves samplesPool and labelsPool to WriteRequestUnmarshaller.
Make WriteRequest struct clean from unmarshal logic.
The benchmark shows no significant changes:
$benchstat prompbmarshal.bench prompb2.bench
goos: darwin
goarch: arm64
pkg: github.com/VictoriaMetrics/VictoriaMetrics/lib/prompb
cpu: Apple M1 Pro
│ prompbmarshal.bench │ prompb2.bench │
│ sec/op │ sec/op vs base │
WriteRequestUnmarshalProtobuf-10 189.2µ ± 5% 190.8µ ± 8% ~ (p=0.579 n=10)
WriteRequestMarshalProtobuf-10 145.3µ ± 7% 143.6µ ± 2% ~ (p=0.143 n=10)
geomean 165.8µ 165.5µ -0.14%
│ prompbmarshal.bench │ prompb2.bench │
│ B/s │ B/s vs base │
WriteRequestUnmarshalProtobuf-10 50.42Mi ± 5% 49.99Mi ± 8% ~ (p=0.593 n=10)
WriteRequestMarshalProtobuf-10 65.64Mi ± 7% 66.39Mi ± 2% ~ (p=0.143 n=10)
geomean 57.53Mi 57.61Mi +0.14%
│ prompbmarshal.bench │ prompb2.bench │
│ B/op │ B/op vs base │
WriteRequestUnmarshalProtobuf-10 27.70Ki ± 4% 26.90Ki ± 7% ~ (p=0.190 n=10)
WriteRequestMarshalProtobuf-10 3.267Ki ± 12% 3.273Ki ± 12% ~ (p=0.971 n=10)
geomean 9.514Ki 9.383Ki -1.38%
│ prompbmarshal.bench │ prompb2.bench │
│ allocs/op │ allocs/op vs base │
WriteRequestUnmarshalProtobuf-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=10) ¹
WriteRequestMarshalProtobuf-10 0.000 ± 0% 0.000 ± 0% ~ (p=1.000 n=10) ¹
geomean ² +0.00% ²
¹ all samples are equal
² summaries must be >0 to compute geomean
### Describe Your Changes
Fix many spelling errors and some grammar, including misspellings in
filenames.
The change also fixes a typo in metric `vm_mmaped_files` to `vm_mmapped_files`.
While this is a breaking change, this metric isn't used in alerts or dashboards.
So it seems to have low impact on users.
The change also deprecates `cspell` as it is much heavier and less usable.
---------
Co-authored-by: Andrii Chubatiuk <achubatiuk@victoriametrics.com>
Co-authored-by: Andrii Chubatiuk <andrew.chubatiuk@gmail.com>
This reverts commit 5a3abfa041.
Reason for revert: exemplars aren't in wide use because they have numerous issues which prevent their adoption (see below).
Adding support for examplars into VictoriaMetrics introduces non-trivial code changes. These code changes need to be supported forever
once the release of VictoriaMetrics with exemplar support is published. That's why I don't think this is a good feature despite
that the source code of the reverted commit has an excellent quality. See https://docs.victoriametrics.com/goals/ .
Issues with Prometheus exemplars:
- Prometheus still has only experimental support for exemplars after more than three years since they were introduced.
It stores exemplars in memory, so they are lost after Prometheus restart. This doesn't look like production-ready feature.
See 0a2f3b3794/content/docs/instrumenting/exposition_formats.md (L153-L159)
and https://prometheus.io/docs/prometheus/latest/feature_flags/#exemplars-storage
- It is very non-trivial to expose exemplars alongside metrics in your application, since the official Prometheus SDKs
for metrics' exposition ( https://prometheus.io/docs/instrumenting/clientlibs/ ) either have very hard-to-use API
for exposing histograms or do not have this API at all. For example, try figuring out how to expose exemplars
via https://pkg.go.dev/github.com/prometheus/client_golang@v1.19.1/prometheus .
- It looks like exemplars are supported for Histogram metric types only -
see https://pkg.go.dev/github.com/prometheus/client_golang@v1.19.1/prometheus#Timer.ObserveDurationWithExemplar .
Exemplars aren't supported for Counter, Gauge and Summary metric types.
- Grafana has very poor support for Prometheus exemplars. It looks like it supports exemplars only when the query
contains histogram_quantile() function. It queries exemplars via special Prometheus API -
https://prometheus.io/docs/prometheus/latest/querying/api/#querying-exemplars - (which is still marked as experimental, btw.)
and then displays all the returned exemplars on the graph as special dots. The issue is that this doesn't work
in production in most cases when the histogram_quantile() is calculated over thousands of histogram buckets
exposed by big number of application instances. Every histogram bucket may expose an exemplar on every timestamp shown on the graph.
This makes the graph unusable, since it is litterally filled with thousands of exemplar dots.
Neither Prometheus API nor Grafana doesn't provide the ability to filter out unneeded exemplars.
- Exemplars are usually connected to traces. While traces are good for some
I doubt exemplars will become production-ready in the near future because of the issues outlined above.
Alternative to exemplars:
Exemplars are marketed as a silver bullet for the correlation between metrics, traces and logs -
just click the exemplar dot on some graph in Grafana and instantly see the corresponding trace or log entry!
This doesn't work as expected in production as shown above. Are there better solutions, which work in production?
Yes - just use time-based and label-based correlation between metrics, traces and logs. Assign the same `job`
and `instance` labels to metrics, logs and traces, so you can quickly find the needed trace or log entry
by these labes on the time range with the anomaly on metrics' graph.
This code adds Exemplars to VMagent and the promscrape parser adhering
to OpenMetrics Specifications. This will allow forwarding of exemplars
to Prometheus and other third party apps that support OpenMetrics specs.
---------
Signed-off-by: Ted Possible <ted_possible@cable.comcast.com>
