Skip to main content

InfluxDB

Reading time: 0 minute(s) (0 words)

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

InfluxDB parameters and supported features in Nobl9
General support:
Release channel: Stable, Beta
Connection method: Agent, Direct
Replay and SLI Analyzer: Not supported
Event logs: Supported
Query checker: Not supported
Query parameters retrieval: Not supported
Timestamp cache persistence: Supported
Query parameters:
Query interval: 1 min
Query delay: 1 min
Jitter: 15 sec
Timeout: 60 sec
Agent details and minimum required versions for supported features:
Plugin name: n9influxdb
Query delay environment variable: INFLUXDB_QUERY_DELAY
Timestamp cache persistence: 0.65.0
Additional notes:
No support for InfluxQL.
Write queries in Flux instead. Flux queries are only validated against bucket name, params.n9time_start, params.n9time_stop

Creating SLOs with InfluxDB​

Nobl9 Web​

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

  1. Navigate to Service Level Objectives.

  2. Click .

  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).

    1. Choose the Data Count Method for your ratio metric:
    • Non-incremental: counts incoming metric values one-by-one. So the resulting SLO graph is pike-shaped.
    • Incremental: counts the incoming metric values incrementally, adding every next value to previous values. It results in a constantly increasing SLO graph.

  5. 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 the Manage Buckets in InfluxDB | InfluxDB documentation.

    • params.n9time_start and params.n9time_stop placeholders that define the time range of the query.

      • When generating a Flux query in the InfluxDB UI, replace InfluxDB v.timeRangeStart and v.timeRangeStop variables with Nobl9 params.n9time_start and params.n9time_stop placeholders. For more information, refer to the Predefined dashboard variables | InfluxDB documentation.

      • When creating a Flux query in the Nobl9 UI, append the query with range(start: time(v: params.n9time_start), stop: time(v: params.n9time_stop)) function. For query examples, refer to the section below.

note

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.

SLI values for good and total
When choosing the query for the ratio SLI (countMetrics), keep in mind that the values ​​resulting from that query for both good and total:
  • Must be positive.
  • While we recommend using integers, fractions are also acceptable.
    • If using fractions, we recommend them to be larger than 1e-4 = 0.0001.
  • Shouldn't be larger than 1e+20.
  1. In step 3 of the SLO wizard, define a Time Window for the SLO.

  • Rolling time windows are better for tracking the recent user experience of a service.

  • Calendar-aligned windows are best suited for SLOs that are intended to map to business metrics measured on a calendar-aligned basis, such as every calendar month or every quarter.

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

    • Occurrences method counts good attempts against the count of total attempts.
    • Time Slicesmethod measures how many good minutes were achieved (when a system operates within defined boundaries) during a time window.
    • You can define up to 12 objectives for an SLO.

    See the use case example and the SLO calculations guide for more information on the error budget calculation methods.

  2. In step 5, add the Display name, Name, and other settings for your SLO:

    • Create a composite SLO
    • Set notification on data, if this option is available for your data source.
      When activated, Nobl9 notifies you if your SLO hasn't received data or received incomplete data for more than 15 minutes.
    • Add alert policies, labels, and links, if required.
      You can add up to 20 links per SLO.

  3. Click Create SLO.

sloctl​

Sample InfluxDB threshold SLO
apiVersion: n9/v1alpha
kind: SLO
metadata:
  name: api-server-slo
  displayName: API Server SLO
  project: default
  labels:
    area:
      - latency
      - slow-check
    env:
      - prod
      - dev
    region:
      - us
      - eu
    team:
      - green
      - sales
  annotations:
    area: latency
    env: prod
    region: us
    team: sales
spec:
  description: Example InfluxDB SLO
  indicator:
    metricSource:
      name: influx-d-b
      project: default
      kind: Agent
  budgetingMethod: Occurrences
  objectives:
    - displayName: Good response (200)
      value: 200
      name: ok
      target: 0.95
      rawMetric:
        query:
          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")
      op: lte
      primary: true
  service: api-server
  timeWindows:
    - unit: Month
      count: 1
      isRolling: false
      calendar:
        startTime: 2022-12-01T00:00:00.000Z
        timeZone: UTC
  alertPolicies:
    - fast-burn-5x-for-last-10m
  attachments:
    - url: https://docs.nobl9.com
      displayName: Nobl9 Documentation
  anomalyConfig:
    noData:
      alertMethods:
        - name: slack-notification
          project: default

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.

Query examples​

The following are Flux 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")'

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 apply to the point density for the agent. If the point density fetched from database per one minute is greater than 4, an error occurs. Then, you must rewrite the query with point aggregation.

For a more in-depth look, consult additional resources:
InfluxDB API referenceInfluxDB docsCreate an API tokenInfluxDB docsView organizationsInfluxDB docsInflux query languageInfluxDB docsGet started with FluxInfluxDB docsFlux universe packageInfluxDB docsManage bucketsInfluxDB docsPredefined dashboard variablesInfluxDB docsAgent metricsAgentCreating SLOs via TerraformTerraformCreating agents via TerraformTerraform
Last updated on
On this page