tencent cloud

Feedback

Streamlining Monitoring Metrics

Last updated: 2022-06-10 19:32:52

    Overview

    This document describes how to streamline the TMP collection metrics to avoid unnecessary expenses.

    Prerequisites

    Before configuring monitoring collection items, you need to perform the following operations:

    Streamlining Metrics

    Streamlining metrics in the console

    TMP offers more than 100 free basic monitoring metrics as listed in Free Metrics in Pay-as-You-Go Mode.

    1. Log in to the TKE console and select TMP on the left sidebar.
    2. On the instance list page, select the target instance to enter its details page.
    3. On the Cluster Monitoring page, click Data Collection Configuration on the right of the cluster to enter the collection configuration list page.
    4. You can add or remove targets of basic metrics on the productized page. Click Metric Details on the right.
    5. The following shows whether the metrics are free. If you select a metric, it will be collected. We recommend you deselect paid metrics to avoid additional costs. Only metrics for basic monitoring are free of charge. For more information on free metrics, see Free Metrics in Pay-as-You-Go Mode. For more information on paid metrics, see Pay-as-You-Go.

    Streamlining metrics through YAML

    Currently, TMP is billed by the number of monitoring data points. We recommend you optimize your collection configuration to collect only required metrics and filter out unnecessary ones. This will save costs and reduce the overall reported data volume. For more information on the billing mode and Tencent Cloud resource usage, see here.

    The following describes how to add filters for ServiceMonitors, PodMonitors, and RawJobs to streamline custom metrics.

    1. Log in to the TKE console and select TMP on the left sidebar.

    2. On the instance list page, select the target instance to enter its details page.

    3. On the Cluster Monitoring page, click Data Collection Configuration on the right of the cluster to enter the collection configuration list page.

    4. Click on the right of the instance to view the metric details.

      A ServiceMonitor and a PodMonitor use the same filtering fields, and this document uses a ServiceMonitor as an example.
      Sample for ServiceMonitor:

      apiVersion: monitoring.coreos.com/v1
      kind: ServiceMonitor
      metadata:
      labels:
      app.kubernetes.io/name: kube-state-metrics
      app.kubernetes.io/version: 1.9.7
      name: kube-state-metrics
      namespace: kube-system
      spec:
      endpoints:
      - bearerTokenSecret:
       key: ""
      interval: 15s # This parameter is the collection frequency. You can increase it to reduce the data storage costs. For example, you can set it to `300s` for less important metrics, which can reduce the amount of monitoring data collected by 20 times.
      port: http-metrics
      scrapeTimeout: 15s # This parameter is the collection timeout period. TMP configuration requires that this value not exceed the collection interval, i.e., `scrapeTimeout` <= `interval`.
      jobLabel: app.kubernetes.io/name
      namespaceSelector: {}
      selector:
      matchLabels:
       app.kubernetes.io/name: kube-state-metrics
      

      To collect kube_node_info and kube_node_role metrics, you need to add the metricRelabelings field to the Endpoint list of the ServiceMonitor. Note that it is metricRelabelings but not relabelings.
      Sample for adding metricRelabelings:
      apiVersion: monitoring.coreos.com/v1
      kind: ServiceMonitor
      metadata:
      labels:
      app.kubernetes.io/name: kube-state-metrics
      app.kubernetes.io/version: 1.9.7
      name: kube-state-metrics
      namespace: kube-system
      spec:
      endpoints:
      - bearerTokenSecret:
       key: ""
      interval: 15s # This parameter is the collection frequency. You can increase it to reduce the data storage costs. For example, you can set it to `300s` for less important metrics, which can reduce the amount of monitoring data collected by 20 times.
      port: http-metrics
      scrapeTimeout: 15s
      # The following four lines are added:
      metricRelabelings: # Each collected item is subject to the following processing.
      - sourceLabels: ["__name__"] # The name of the label to be detected. `__name__` indicates the name of the metric or any label that comes with the item.
       regex: kube_node_info|kube_node_role # Whether the above label satisfies this regex. Here, `__name__` should satisfy the requirements of `kube_node_info` or `kube_node_role`.
       action:  keep # Keep the item if it meets the above conditions; otherwise, drop it.
      jobLabel: app.kubernetes.io/name
      namespaceSelector: {}
      selector:
      

    5. Click OK.

    Blocking certain targets

    Blocking the monitoring of the entire namespace

    TMP will manage all the ServiceMonitors and PodMonitors in a cluster by default after the cluster is associated. If you want to block the monitoring under a namespace, you can label it with tps-skip-monitor: "true" as instructed in Labels and Selectors.

    Blocking certain targets

    TMP collects monitoring data by creating CRD resources of ServiceMonitor and PodMonitor types in your cluster. If you want to block the collection of the specified ServiceMonitor and PodMonitor resources, you can label these CRD resources with tps-skip-monitor: "true" as instructed in Labels and Selectors.

    Contact Us

    Contact our sales team or business advisors to help your business.

    Technical Support

    Open a ticket if you're looking for further assistance. Our Ticket is 7x24 avaliable.

    7x24 Phone Support