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InfluxDB

InfluxDB is an open source time series database platform that enables users to collect, process, and analyze data to optimize their infrastructure.

Scope of Support​

Currently, Nobl9 does not support the InfluxQL query language. You can retrieve the metrics using the Flux query language.

Nobl9 does not support full Flux query validation. The validation is performed on the following parameters:

  • bucket name
  • params.n9time_start
  • params.n9time_stop

Authentication​

When configuring a Nobl9 Agent or Direct connection to InfluxDB, you need to provide the API Token and Organization ID.

You can create the API Token using the InfluxDB user interface (UI), the command-line interface (CLI), or the InfluxDB API. For detailed instructions, refer to the Create an API Token | InfluxDB Documentation.

You can get your Organization ID from:

  • The URL in the InfluxDB UI by looking for the orgs value, for example, http://localhost:8086/orgs/03a2bbf46249a000/...
  • The Organization Settings in InfluxDB’s UI
    • Click the organization name icon in your InfluxDB panel and go to the Organization Settings. You can copy the Organization ID to the clipboard.

For more details, refer to the View Organizations | InfluxDB Documentation.

Adding InfluxDB as a Data Source in the UI​

To add InfluxDB as a data source in Nobl9 using the Agent or Direct connection method, follow these steps:

  1. Navigate to Integrations > Sources.

  2. Click the plus button button.

  3. Click the InfluxDB icon.

  4. Choose a configuration method (Direct or Agent), then configure the source as described below.

InfluxDB Direct​

Direct Configuration in the UI​

A Direct connection to InfluxDB requires users to enter their credentials which Nobl9 stores safely. To set up this type of connection:

  1. Enter an InfluxDB URL (mandatory).
    This is the Cluster URL which you can get by clicking the Account settings icon in the InfluxDB panel, and navigating to the Organization Settings. You can also copy and paste it from the address line of your browser after logging in to your InfluxDB account.

  2. Enter your InfluxDB API Token (mandatory).
    For more details, refer to the Create an API Token | InfluxDB Documentation.

  3. Enter your InfluxDB Organization ID (mandatory).
    For more details, refer to the Authentication section above.

  4. Select a Project (mandatory).
    Specifying a project is helpful when multiple users are spread across multiple teams or projects. When the Project field is left blank, a default value appears.

  5. Enter a Display name (optional).
    You can enter a friendly name with spaces in this field.

  6. Enter a Name (mandatory).
    The name is mandatory and can only contain lowercase, alphanumeric characters and dashes (for example, my-project-name). This field is populated automatically when you enter a display name, but you can edit the result.

  7. Enter a Description (optional).
    Here you can add details such as who is responsible for the integration (team/owner) and the purpose of creating it.

  8. Click the Add Data Source button.

InfluxDB Agent​

Agent Configuration in the UI​

Follow the instructions below to set up an Agent connection. Refer to the section above for the descriptions of the fields.

  1. Add the InfluxDB URL to connect to your data source.

  2. Select a Project (mandatory).

  3. Enter a Display name (optional).

  4. Enter a Name (mandatory).

  5. Enter a Description (optional).

  6. Click the Add Data Source button.

Deploying the InfluxDB Agent​

When you add the data source, Nobl9 automatically generates a Kubernetes configuration and a Docker command line for you to use to deploy the Agent. Both of these are available in the web UI, under the Agent Configuration section. Be sure to swap in your credentials (e.g., replace <INFLUXDB_API_TOKEN> and <INFLUXDB_ORG_ID> with your organization’s credentials). For more information, refer to the Authentication section above.

If you use Kubernetes, you can apply the supplied YAML config file to a Kubernetes cluster to deploy the Agent.

# DISCLAIMER: This deployment description contains only the fields necessary for the purpose of this demo.
# It is not a ready-to-apply k8s deployment description, and the client_id and client_secret are only exemplary values.

apiVersion: v1
kind: Secret
metadata:
  name: nobl9-agent-{organization}-{project}-{name}
  namespace: default
type: Opaque
stringData:
  influxdb_api_token: <INFLUXDB_API_TOKEN>
  influxdb_org_id: <INFLUXDB_ORG_ID>
  client_id: {client_id}
  client_secret: {client_secret}
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nobl9-agent-{organization}-{project}-{name}
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      nobl9-agent-name: {name}
      nobl9-agent-project: {project}
      nobl9-agent-organization: {organization}
  template:
    metadata:
      labels:
        nobl9-agent-name: {name}
        nobl9-agent-project: {project}
        nobl9-agent-organization: {organization}
    spec:
      containers:
        - name: agent-container
          image: nobl9/agent:{agent_version}
          resources:
            requests:
              memory: "350Mi"
              cpu: "0.1"
          env:
            - name: N9_CLIENT_ID
              valueFrom:
                secretKeyRef:
                  key: client_id
                  name: nobl9-agent-{organization}-{project}-{name}
            - name: INFLUXDB_API_TOKEN
              valueFrom:
                secretKeyRef:
                  key: influxdb_api_token
                  name: nobl9-agent-{organization}-{project}-{name}
            - name: INFLUXDB_ORG_ID
              valueFrom:
                secretKeyRef:
                  key: influxdb_org_id
                  name: nobl9-agent-{organization}-{project}-{name}
            - name: N9_INTAKE_URL
              value: "https://dev-bdw-nobl9.nobl9.dev/api/input"
            - name: N9_CLIENT_SECRET
              valueFrom:
                secretKeyRef:
                  key: client_secret
                  name: nobl9-agent-{organization}-{project}-{name}
            - name: N9_AUTH_SERVER
              value: "{auth_server}"
            - name: N9_OKTA_ORG_URL
              value: "https://accounts.nobl9.dev"

Creating SLOs with InfluxDB​

Creating SLO in the UI​

Follow the instructions below to create an SLO with InfluxDB in the UI:

  1. Navigate to Service Level Objectives.

  2. Click the plus button button.

  3. In step 1 of the SLO wizard, select the Service the SLO will be associated with.

  4. In step 2, select InfluxDB as the Data Source for your SLO, then specify the Metric. You can choose either a Threshold Metric, where a single time series is evaluated against a threshold or a Ratio Metric, which allows you to enter two time series to compare (for example, a count of good requests and total requests).

  • Paste the Flux query in the Query, or Good Query and Total Query fields for the metric you selected. An InfluxDB query must contain:

    • A bucket value that points to a bucket in your organization that you want to query. A bucket is a named location where time series data is stored in InfluxDB. For more details, refer to Manage Buckets in InfluxDB | InfluxDB Documentation.
    • params.n9time_start and params.n9time_stop placeholders that define the time range of the query. Append the following line to your query: range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop)). Do not add a time frame to the query, as Nobl9 appends the query times as needed.

    For more information on the Flux query language, refer to the Get Started with Flux | InfluxDB Documentation.

  • The following are query examples:

    • Threshold Metric
      Query:

      'from(bucket: "integrations")
      |> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
      |> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
      |> filter(fn: (r) => r["_measurement"] == "internal_write")
      |> filter(fn: (r) => r["_field"] == "write_time_ns")'

    • Ratio Metric
      Good Query:

      'from(bucket: "integrations")
      |> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
      |> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
      |> filter(fn: (r) => r["_measurement"] == "internal_write")
      |> filter(fn: (r) => r["_field"] == "write_time_ns")'

      Total Query:

      'from(bucket: "integrations")
      |> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
      |> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
      |> filter(fn: (r) => r["_measurement"] == "internal_write")
      |> filter(fn: (r) => r["_field"] == "write_time_ns")'

  1. In step 3 of the SLO Wizard, define a Time Window for the SLO.

  2. In step 4, specify the Error Budget Calculation Method and your Objective(s).

  3. In step 5, add a Name, Description, and other details about your SLO. You can also select Alert Policies and Labels on this screen.

  4. When you’re done, click Create SLO.

SLOs using InfluxDB - YAML samples​

Here’s an example of InfluxDB using rawMetric (Threshold Metric):

apiVersion: n9/v1alpha
  kind: SLO
  metadata:
    displayName: influxdb-calendar-occurrences-threshold
    name: influxdb-calendar-occurrences-threshold
    project: influxdb
  spec:
    budgetingMethod: Occurrences
    description: ""
    indicator:
      metricSource:
        name: influxdb
      rawMetric:
        influxdb:
          query: 'from(bucket: "integrations")
            |> range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop))
            |> aggregateWindow(every: 15s, fn: mean, createEmpty: false)
            |> filter(fn: (r) => r["_measurement"] == "internal_write")
            |> filter(fn: (r) => r["_field"] == "write_time_ns")'
    service: influxdb-service
    objectives:
      - target: 0.8
        op: lte
        displayName: average
        value: 300000000
      - target: 0.5
        op: lte
        displayName: so-so
        value: 250000000
    timeWindows:
      - calendar:
          startTime: "2020-11-14 12:10:00"
          timeZone: Etc/UTC
        count: 1
        isRolling: false
        unit: Day

Notes:

  • query:

    • query - must contain range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop)) placeholders and a bucket name.

    • aggregateWindow () - applies an aggregate or selector function to fixed windows of time. If you need to aggregate points when there are more than 4 points per minute, group the data using this function.

    • yield () - a function that indicates what input data will be provided as a result of the query. yield() is required when using multiple sources in a query. Each query result is then identified by the name provided to the yield().

    • For more information, refer to the Flux universe package | InfluxDB Documentation.

Querying the InfluxDB Server​

Nobl9 queries the InfluxDB server leveraging the /api/v2/query REST API on a per-minute basis with a maximum resolution of 4 data points.

InfluxDB API Rate Limits​

The API Rate Limits applies to the point density for the Agent. If the point density fetched from database per 1 minute is greater than 4, an error occurs. Then, you must rewrite the query with point aggregation.

InfluxDB API Reference | InfluxDB Documentation

Create an API Token | InfluxDB Documentation

View Organizations | InfluxDB Documentation

Influx Query Language | InfluxDB Documentation

Get Started with Flux | InfluxDB Documentation

Flux universe package | InfluxDB Documentation

Manage Buckets | InfluxDB Documentation

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