Advanced configuration

This page covers advanced setting. A default installation of Obcerv does not require changes to the settings described here.

Note: For sample scenarios in installing the Obcerv instance, see Parameters file for the Obcerv instance.

Resource settings

For each Obcerv workload there is a resources parameter that defines the resource requests and limits for the pods in that workload. We recommend setting these parameters for all applications, otherwise some pods may consume all available resources on your Kubernetes cluster.

The provided configuration examples have baseline resources and limits set for all workloads. They can be altered as needed, for example:

      memory: "1Gi"
      cpu: "500m"
      memory: "2Gi"
      cpu: "1"

Timescale volume sizing

By setting certain parameters, you can control the sizing and distribution of persistent data volumes for Timescale. The following are sample values:

- dataDiskSize: "50Gi"
- timeseriesDiskCount: 4
- timeseriesDiskSize: "10Ti"

There are two types of data stored in Timescale: timeseries data and non-timeseries data. By default, all data is stored on the data volume which is sized by the dataDiskSize parameter, while the timeseriesDiskCount parameter is set to 0. However, Timeseries data can be stored on isolated volumes that may use a different storage class and can be scaled when more storage is needed.

When the timeseriesDiskCount parameter is set to greater than 0, all timeseries data is distributed among the timeseries data volumes, each of which has a size defined by the timeseriesDiskSize parameter. This is helpful when there are constraints on the maximum volume sizes set by a cloud provider (for example, when AWS has a max volume size of 16Ti).

To calculate the total disk volume size utilised by Timescale, use the following formula:

dataDiskSize + (timeseriesDiskSize * timeseriesDiskCount)

Timescale retention settings

To adjust metric data retention, update the timescale.retention parameter. The values are in the format of <number><time>, such as: 5d or 45m. The time format options are:

- m  (minutes)
- h  (hours)
- d  (days)
- mo (months)
- y  (years)
      chunkSize: 3h
      retention: 60d
      compressAfter: 3h

Kafka retention settings

The kafka.defaultRetentionMillis parameter controls how long data is retained in Kafka topics, which defaults to 21600000 (6 hours).

Timescale and Kafka on reserved nodes

For larger deployments, you may want to run Timescale and/or Kafka on reserved Kubernetes nodes. This can be achieved using Kubernetes labels and taints on the nodes and tolerations and nodeSelector on the workloads.

The following example shows how to deploy Timescale on reserved nodes:

  1. Add a label to the Timescale nodes in the manifest or using kubectl:

    instancegroup: timescale-nodes
  2. Add a taint to the Timescale nodes in the manifest or using kubectl:

  3. Set the following in your parameters file:

         enabled: true
         clusterSize: 3
       maxConnections: 100
       dataDiskSize: 100Gi
       walDiskSize: 50Gi
           memory: "12Gi"
           cpu: "3"
           memory: "12Gi"
           cpu: "12"
       compressAfter: 1h
           chunkSize: 2d
           retention: 2y
           chunkSize: 20m
           retention: 60d
  4. (Optional) In order for Obcerv to collect pod logs from the reserved nodes, the following tolerations are required so that the logs agent can run on these nodes:

        # must match the tainted node setting 
        - key: dedicated
          operator: Equal
          value: timescale-nodes
          effect: NoSchedule
        - key: dedicated
          operator: Equal
          value: kafka-nodes
          effect: NoSchedule
["Obcerv"] ["User Guide", "Technical Reference"]

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