Chapter 13. Troubleshooting monitoring issues
Find troubleshooting steps for common issues with core platform and user-defined project monitoring.
13.2. Determining why Prometheus is consuming a lot of disk space
Developers can create labels to define attributes for metrics in the form of key-value pairs. The number of potential key-value pairs corresponds to the number of possible values for an attribute. An attribute that has an unlimited number of potential values is called an unbound attribute. For example, a customer_id
attribute is unbound because it has an infinite number of possible values.
Every assigned key-value pair has a unique time series. The use of many unbound attributes in labels can result in an exponential increase in the number of time series created. This can impact Prometheus performance and can consume a lot of disk space.
You can use the following measures when Prometheus consumes a lot of disk:
- Check the time series database (TSDB) status using the Prometheus HTTP API for more information about which labels are creating the most time series data. Doing so requires cluster administrator privileges.
- Check the number of scrape samples that are being collected.
Reduce the number of unique time series that are created by reducing the number of unbound attributes that are assigned to user-defined metrics.
NoteUsing attributes that are bound to a limited set of possible values reduces the number of potential key-value pair combinations.
- Enforce limits on the number of samples that can be scraped across user-defined projects. This requires cluster administrator privileges.
Prerequisites
-
You have access to the cluster as a user with the
cluster-admin
cluster role. -
You have installed the OpenShift CLI (
oc
).
Procedure
-
In the Administrator perspective, navigate to Observe
Metrics. Enter a Prometheus Query Language (PromQL) query in the Expression field. The following example queries help to identify high cardinality metrics that might result in high disk space consumption:
By running the following query, you can identify the ten jobs that have the highest number of scrape samples:
topk(10, max by(namespace, job) (topk by(namespace, job) (1, scrape_samples_post_metric_relabeling)))
By running the following query, you can pinpoint time series churn by identifying the ten jobs that have created the most time series data in the last hour:
topk(10, sum by(namespace, job) (sum_over_time(scrape_series_added[1h])))
Investigate the number of unbound label values assigned to metrics with higher than expected scrape sample counts:
- If the metrics relate to a user-defined project, review the metrics key-value pairs assigned to your workload. These are implemented through Prometheus client libraries at the application level. Try to limit the number of unbound attributes referenced in your labels.
- If the metrics relate to a core OpenShift Container Platform project, create a Red Hat support case on the Red Hat Customer Portal.
Review the TSDB status using the Prometheus HTTP API by following these steps when logged in as a cluster administrator:
Get the Prometheus API route URL by running the following command:
$ HOST=$(oc -n openshift-monitoring get route prometheus-k8s -ojsonpath={.status.ingress[].host})
Extract an authentication token by running the following command:
$ TOKEN=$(oc whoami -t)
Query the TSDB status for Prometheus by running the following command:
$ curl -H "Authorization: Bearer $TOKEN" -k "https://$HOST/api/v1/status/tsdb"
Example output
"status": "success","data":{"headStats":{"numSeries":507473, "numLabelPairs":19832,"chunkCount":946298,"minTime":1712253600010, "maxTime":1712257935346},"seriesCountByMetricName": [{"name":"etcd_request_duration_seconds_bucket","value":51840}, {"name":"apiserver_request_sli_duration_seconds_bucket","value":47718}, ...
13.3. Resolving the KubePersistentVolumeFillingUp alert firing for Prometheus
As a cluster administrator, you can resolve the KubePersistentVolumeFillingUp
alert being triggered for Prometheus.
The critical alert fires when a persistent volume (PV) claimed by a prometheus-k8s-*
pod in the openshift-monitoring
project has less than 3% total space remaining. This can cause Prometheus to function abnormally.
There are two KubePersistentVolumeFillingUp
alerts:
-
Critical alert: The alert with the
severity="critical"
label is triggered when the mounted PV has less than 3% total space remaining. -
Warning alert: The alert with the
severity="warning"
label is triggered when the mounted PV has less than 15% total space remaining and is expected to fill up within four days.
To address this issue, you can remove Prometheus time-series database (TSDB) blocks to create more space for the PV.
Prerequisites
-
You have access to the cluster as a user with the
cluster-admin
cluster role. -
You have installed the OpenShift CLI (
oc
).
Procedure
List the size of all TSDB blocks, sorted from oldest to newest, by running the following command:
$ oc debug <prometheus_k8s_pod_name> -n openshift-monitoring \1 -c prometheus --image=$(oc get po -n openshift-monitoring <prometheus_k8s_pod_name> \2 -o jsonpath='{.spec.containers[?(@.name=="prometheus")].image}') \ -- sh -c 'cd /prometheus/;du -hs $(ls -dt */ | grep -Eo "[0-9|A-Z]{26}")'
Example output
308M 01HVKMPKQWZYWS8WVDAYQHNMW6 52M 01HVK64DTDA81799TBR9QDECEZ 102M 01HVK64DS7TRZRWF2756KHST5X 140M 01HVJS59K11FBVAPVY57K88Z11 90M 01HVH2A5Z58SKT810EM6B9AT50 152M 01HV8ZDVQMX41MKCN84S32RRZ1 354M 01HV6Q2N26BK63G4RYTST71FBF 156M 01HV664H9J9Z1FTZD73RD1563E 216M 01HTHXB60A7F239HN7S2TENPNS 104M 01HTHMGRXGS0WXA3WATRXHR36B
Identify which and how many blocks could be removed, then remove the blocks. The following example command removes the three oldest Prometheus TSDB blocks from the
prometheus-k8s-0
pod:$ oc debug prometheus-k8s-0 -n openshift-monitoring \ -c prometheus --image=$(oc get po -n openshift-monitoring prometheus-k8s-0 \ -o jsonpath='{.spec.containers[?(@.name=="prometheus")].image}') \ -- sh -c 'ls -latr /prometheus/ | egrep -o "[0-9|A-Z]{26}" | head -3 | \ while read BLOCK; do rm -r /prometheus/$BLOCK; done'
Verify the usage of the mounted PV and ensure there is enough space available by running the following command:
$ oc debug <prometheus_k8s_pod_name> -n openshift-monitoring \1 --image=$(oc get po -n openshift-monitoring <prometheus_k8s_pod_name> \2 -o jsonpath='{.spec.containers[?(@.name=="prometheus")].image}') -- df -h /prometheus/
The following example output shows the mounted PV claimed by the
prometheus-k8s-0
pod that has 63% of space remaining:Example output
Starting pod/prometheus-k8s-0-debug-j82w4 ... Filesystem Size Used Avail Use% Mounted on /dev/nvme0n1p4 40G 15G 40G 37% /prometheus Removing debug pod ...