Workshop

Monitor Storage

5 minutes

In this step, we’ll configure the Prometheus receiver to monitor the storage.

What storage do Cisco AI PODs utilize?

Cisco AI PODs have a number of different storage options, including Pure Storage, VAST, and NetApp.

The workshop will focus on Pure Storage.

How do we capture Pure Storage metrics?

Cisco AI PODs that utilize Pure Storage also use a technology called Portworx, which provides persistent storage for Kubernetes.

Portworx includes a metrics endpoint that we can scrape using the Prometheus receiver.

Capture Storage Metrics with Prometheus

Let’s modify the OpenTelemetry collector configuration to scrape Portworx metrics with the Prometheus receiver.

To do so, let’s add an additional Prometheus receiver creator section to the otel-collector-values.yaml file. Add it after the receiver_creator/weaviate section but before the pipelines section:

yaml 
      receiver_creator/storage:
        # Name of the extensions to watch for endpoints to start and stop.
        watch_observers: [ k8s_observer ]
        receivers:
          prometheus/portworx:
            config:
              config:
                scrape_configs:
                  - job_name: portworx-metrics
                    static_configs:
                      - targets:
                          - '`endpoint`:17001'
                          - '`endpoint`:17018'
            rule: type == "pod" && labels["app"] == "portworx-metrics-sim"

We’ll need to ensure that Portworx metrics are added to the filter/metrics_to_be_included filter processor configuration as well:

yaml 
    processors:
      filter/metrics_to_be_included:
        metrics:
          # Include only metrics used in charts and detectors
          include:
            match_type: strict
            metric_names:
              - DCGM_FI_DEV_FB_FREE
              - ...
              - px_cluster_cpu_percent
              - px_cluster_disk_total_bytes
              - px_cluster_disk_utilized_bytes
              - px_cluster_status_nodes_offline
              - px_cluster_status_nodes_online
              - px_volume_read_latency_seconds
              - px_volume_reads_total
              - px_volume_readthroughput
              - px_volume_write_latency_seconds
              - px_volume_writes_total
              - px_volume_writethroughput

Note: add just the new metrics starting with px_cluster_cpu_percent

We’ll need to add a new metrics pipeline for Portworx metrics as well. Add the following to the bottom of the file:

yaml 
        metrics/storage:
          exporters:
            - signalfx
          processors:
            - memory_limiter
            - filter/metrics_to_be_included
            - batch
            - resourcedetection
            - resource
          receivers:
            - receiver_creator/storage

Take a moment to compare the contents of your modified otel-collector-values.yaml file with the otel-collector-values-with-portworx.yaml file.Remember that indentation is important for yaml files, and needs to be precise:

bash 
diff otel-collector-values.yaml otel-collector-values-with-portworx.yaml

Update your file if needed to ensure the contents match.

Don’t restart the collector yet

Because restarting the collector in an OpenShift environment takes 3 minutes per node, we’ll wait until we’ve completed all configuration changes before initiating a restart.
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