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Sumo Logic

Collect MongoDB Logs and Metrics for Kubernetes environments

Configure collection of logs and metrics for the Sumo Logic app for MongoDB, in a non-Kubernetes environment.

In a Kubernetes environment, we use the Telegraf Operator, which is packaged with our Kubernetes collection. You can learn more about it here.The diagram below illustrates how data is collected from MongoDB in a Kubernetes environment. In the architecture shown below, there are four services that make up the metric collection pipeline: Telegraf, Prometheus, Fluentd and FluentBit.

The first service in the pipeline is Telegraf. Telegraf collects metrics from MongoDB. Note that we’re running Telegraf in each pod we want to collect metrics from as a sidecar deployment for example, Telegraf runs in the same pod as the containers it monitors. Telegraf uses the MongoDB input plugin to obtain metrics. (For simplicity, the diagram doesn’t show the input plugins.) The injection of the Telegraf sidecar container is done by the Telegraf Operator. We also have Fluentbit that collects logs written to standard out and forwards them to FluentD, which in turn sends all the logs and metrics data to a Sumo Logic HTTP Source.

Follow the below instructions to set up the metric collection:

  1. Configure Metrics Collection

    1. Setup Kubernetes Collection with the Telegraf operator

    2. Add annotations on your MongoDB pods

  2. Configure Logs Collection

    1. Configure logging in MongoDB.

    2. Add labels on your MongoDB pods to capture logs from standard output.

    3. Collecting MongoDB Logs from a Log file.

Prerequisites

It’s assumed that you are using the latest helm chart version if not upgrade using the instructions here.

Step 1 Configure Metrics Collection

This section explains the steps to collect MongoDB metrics from a Kubernetes environment.

In a Kubernetes environment, we use the Telegraf Operator, which is packaged with our Kubernetes collection. You can learn more on this here. Follow the steps listed below to collect metrics from a Kubernetes environment:

  1. Setup Kubernetes Collection with the Telegraf Operator.

  2. Add annotations on your MongoDB pods

On your MongoDB Pods, add the following annotations:

annotations:
  telegraf.influxdata.com/class: sumologic-prometheus
  prometheus.io/scrape: "true"
  prometheus.io/port: "9273"
  telegraf.influxdata.com/inputs: |+
[[inputs.mongodb]]
  servers = ["mongodb://<username-CHANGEME>:<password-CHANGEME>@127.0.0.1:27017"]
  gather_perdb_stats = true
  gather_col_stats = true
  [inputs.mongodb.tags]
    environment="kubernetes"
    component="database"
    db_system="mongodb"
    db_cluster="mongodb_on_k8s"

Please enter values for the following parameters (marked in bold above):

  • telegraf.influxdata.com/inputs - This contains the required configuration for the Telegraf MongoDB Input plugin. Please refer to this doc for more information on configuring the MongoDB input plugin for Telegraf. Note: As telegraf will be run as a sidecar the host should always be localhost.

    • In the input plugins section - [inputs.MongoDB]:

      • servers - The URL to the MongoDB server. This can be a comma-separated list to connect to multiple MongoDB servers. Please see this doc for more information on additional parameters for configuring the MongoDB input plugin for Telegraf.

    • In the tags section - [inputs.MongoDB.tags]:

      • environment - This is the deployment environment where the MongoDB cluster identified by the value of servers resides. For example: dev, prod or qa. While this value is optional we highly recommend setting it. 

      • db_cluster - Enter a name to identify this MongoDB cluster. This cluster name will be shown in the Sumo Logic dashboards. 

Here’s an explanation for additional values set by this configuration that we request you please do not modify as they will cause the Sumo Logic apps to not function correctly.

  • telegraf.influxdata.com/class: sumologic-prometheus - This instructs the Telegraf operator what output to use. This should not be changed.

  • prometheus.io/scrape: "true" - This ensures our Prometheus will scrape the metrics.

  • prometheus.io/port: "9273" - This tells prometheus what ports to scrape on. This should not be changed.

  • telegraf.influxdata.com/inputs

    • In the tags section i.e.  [inputs.mongodb.tags]

      • component: “database” - This value is used by Sumo Logic apps to identify application components. 

      • db_system: “mongodb” - This value identifies the database system.

For all other parameters please see this doc for more properties that can be configured in the Telegraf agent globally.

  1. Sumo Logic Kubernetes collection will automatically start collecting metrics from the pods having the labels and annotations defined in the previous step. 

  2. Verify metrics in Sumo Logic.

Step 2 Configure Logs Collection

This section explains the steps to collect MongoDB logs from a Kubernetes environment.

  1. Add labels on your MongoDB pods to capture logs from standard output.

Make sure that the logs from MongoDB are sent to stdout. For more details see this doc.

Follow the instructions below to capture MongoDB logs from stdout on Kubernetes.

  1. Apply following labels to the MongoDB pods:

 labels:
    environment: "prod"
    component: "database"
    db_system: "mongodb"
    db_cluster: "mongodb_prod_cluster01”

Enter in values for the following parameters (marked in bold above):

  • environment. This is the deployment environment where the MongoDB cluster identified by the value of servers resides. For example: dev, prod or qa. While this value is optional we highly recommend setting it.
  • db_cluster. Enter a name to identify this MongoDB cluster. This cluster name will be shown in the Sumo Logic dashboards.

Here’s an explanation for additional values set by this configuration that we request you do not modify as they will cause the Sumo Logic apps to not function correctly.

  • component: “database”. This value is used by Sumo Logic apps to identify application components.
  • db_system: “mongodb”. This value identifies the database system.

For all other parameters see this doc for more properties that can be configured in the Telegraf agent globally.

  1. (Optional) Collecting MongoDB Logs from a Log File

Follow the  steps below to capture MongoDB logs from a log file on Kubernetes.

  1. Determine the location of the MongoDB log file on Kubernetes. This can be determined from the MongoDB.conf for your MongoDB cluster along with the mounts on the MongoDB pods.

  2. Install the Sumo Logic tailing sidecar operator.

  3. Add the following annotation in addition to the existing annotations.

annotations:
  tailing-sidecar: sidecarconfig;<mount>:<path_of_MongoDB_log_file>/<MongoDB_log_file_name>

Example:

annotations:
  tailing-sidecar: sidecarconfig;data:/mongo-prim-data/MongoDB.log
  1. Make sure that the MongoDB pods are running and annotations are applied by using the command: kubectl describe pod <MongoDB_pod_name>

  2. Sumo Logic Kubernetes collection will automatically start collecting logs from the pods having the annotations defined above. 

  1. Add an FER to normalize the fields in Kubernetes environments

Labels created in Kubernetes environments automatically are prefixed with pod_labels. To normalize these for our app to work, we need to create a Field Extraction Rule if not already created for Database Application Components. To do so:

  1. Go to Manage Data > Logs > Field Extraction Rules.

  2. Click the + Add button on the top right of the table.

  3. The following form appears:

  1. Enter the following options:

  • Rule Name. Enter the name as App Observability - Database.

  • Applied At. Choose Ingest Time

  • Scope. Select Specific Data

    • Scope: Enter the following keyword search expression:
      pod_labels_environment=* pod_labels_component=database     pod_labels_db_system=* pod_labels_db_cluster=*

  • Parse Expression.Enter the following parse expression:

| if (!isEmpty(pod_labels_environment), pod_labels_environment, "") as environment
| pod_labels_component as component
| pod_labels_db_system as db_system
| pod_labels_db_cluster as db_cluster
  1. Click Save to create the rule.