Also reduce CPU usage when applying `series_limit` to scrape targets with constant set of metrics.
The main idea is to perform the calculations on scrape_series_added and series_limit
only if the set of metrics exposed by the target has been changed.
Scrape targets rarely change the set of exposed metrics,
so this optimization should reduce CPU usage in general case.
The number of series per target can be limited with the following options:
* Global limit with `-promscrape.maxSeriesPerTarget` command-line option.
* Per-target limit with `max_series: N` option in `scrape_config` section.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1561
Store the scraped response body instead of storing the parsed and relabeld metrics.
This should reduce memory usage, since the response body takes less memory than the parsed and relabeled metrics.
This is especially true for Kubernetes service discovery, which adds many long labels for all the scraped metrics.
This should also reduce CPU usage, since the marshaling of the parsed
and relabeld metrics has been substituted by response body copying.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1526
This option allows reducing CPU usage a bit when VictoriaMetrics is used
for collecting and processing non-Prometheus data. For example, InfluxDB line protocol, Graphite, OpenTSDB, CSV, etc.
This option can be useful when vmagent consumes too much additional memory
for staleness markers functionality and when staleness markers aren't needed.
* feature: Add multitenant for vmagent
* Minor fix
* Fix rcs index out of range
* Minor fix
* Fix multi Init
* Fix multi Init
* Fix multi Init
* Add default multi
* Adjust naming
* Add TenantInserted metrics
* Add TenantInserted metrics
* fix: remove unused metrics for vmagent
* fix: remove unused metrics for vmagent
Co-authored-by: mghader <marc.ghader@ubisoft.com>
Co-authored-by: Sebastian YEPES <syepes@gmail.com>
* new feature: relabel logging
Use scrape_configs[x].relabel_debug = true to log metric names inkl.
labels before and after relabeling. After relabeling related metrics
get dropped, i.e. not submitted to servers.
* vminsert wants relabel logging, too.
Do not cache too big byte buffers and too big writeRequestCtx objects,
since it is cheaper to re-create them instead of wasting RAM for their caching.
This reverts 7f6f350ee1
See the description for `sample_limit` option from Prometheus docs:
Per-scrape limit on number of scraped samples that will be accepted.
If more than this number of samples are present after metric relabeling
the entire scrape will be treated as failed. 0 means no limit.
https://prometheus.io/docs/prometheus/latest/configuration/configuration/#scrape_config
These metrics may result in big number of time series when vmagent scrapes thousands of targets and these targets constantly changes.
* It is better using `up == 0` query for determining failing targets.
* It is better using the following query for determining targets with exceeded limit on the number of metrics:
scrape_samples_scraped > 0 if up == 0
These metrics could be useful for determining imporperly working scrape targets.
Note that these metrics are exported only for failing scrape targets. They aren't exposed for normally working targets.
* adds proxy_url support,
adds proxy_url to the dockerswarm, eureka, kubernetes and consul service discovery,
adds proxy_url to the scrape_config for targets scrapping,
http based proxy is supported atm,
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/503
* fixes imports
Show also original labels for duplicate targets in error message in order to simplify debugging the issue.
Now `/targets` endpoint accepts optional `show_original_labels=1` query arg, which shows original labels for each target.
This may simplify debugging for target relabeling.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/651
The previous basis on `cap(sw.labels)` doesn't work anymore after 7785869ccc ,
because `sw.labels` may be reset multiple times when processing big number of rows.
Previously targets with big number of metrics and/or labels could generated too big buffers,
which then could be re-used when scraping targets with small number of metrics.
This resulted in memory waste.
Now big buffers are used only for targets with big number of metrics / labels,
while small buffers are used for targets with small number of metrics / labels.
