Skip to main content

Datadog

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

Datadog is a cloud-scale application observability solution that monitors servers, databases, tools, and services. Nobl9 connects with Datadog to collect SLI measurements and compare them to SLO targets. Nobl9 can activate processes and notifications when the error budget burn rate is too high or has been surpassed because it calculates error budgets of acceptable thresholds.

Users can pass business context through monitoring data, developing and measuring reliability targets, and aligning activities against the error budget's priorities using Nobl9 integration with Datadog.

Datadog parameters and supported features in Nobl9
General support:
Release channel: Stable, Beta
Connection method: Agent, Direct
Replay and SLI Analyzer: Historical data limit 30 days
Event logs: Supported
Query checker: Supported
Query parameters retrieval: Supported
Timestamp cache persistence: Supported
Query parameters:
Query interval: 2 min
Query delay: 1 min
Jitter: 15 sec
Timeout: 30 sec
Agent details and minimum required versions for supported features:
Plugin name: n9datadog
Query delay environment variable: DATADOG_QUERY_DELAY
Replay and SLI Analyzer: 0.65.0
Query parameters retrieval: 0.73.2
Timestamp cache persistence: 0.65.0

Creating SLOs with Datadog​

Nobl9 Web​

Follow the instructions below to create your SLOs with Datadog in the Nobl9 Web application.

  1. Navigate to Service Level Objectives.
  2. Click .
  3. Select a Service.
    It will be the location for your SLO in Nobl9.
  4. Select your Datadog data source.
  5. Modify Period for Historical Data Retrieval, if necessary.
    • This value defines how far back in the past your data will be retrieved when replaying your SLO based on Datadog.
    • A longer period can extend the data loading time for your SLO.
    • Must be a positive whole number up to the maximum period value you've set when adding the Datadog data source.

    Non-editable Replay period
    Non-editable Replay period indicates that the maximum period for historical data retrieval set for your Datadog data source is set to zero.
    Adjust the data source settings to create the SLO with Replay.
  6. Metric refers to the way of calculating and interpreting calculate and interpret data from your data source.
    • Threshold metric is defined by a single numerical value (the threshold) that separates satisfactory performance from unsatisfactory performance. It's represented by a single time series evaluated against the threshold.
    • Ratio metric expresses the performance as a fraction or proportion, typically by dividing the number of successful events by the total number of potential events (successes + failures). It's represented by two-time series for comparison for good events and total events.
      For ratio metrics, select the Data count method.

      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. Specify Query using the Datadog syntax.

    Click to open query samples
    Threshold metric
    avg:trace.http.request.duration{service:my-service}.as_count()
    Ratio metric, numerator
    avg:trace.http.request.hits.by_http_status{service:my-service,!http.status_class:5xx}.as_count()
    Ratio metric, denominator
    avg:trace.http.request.hits.by_http_status{service:my-service}.as_count()
  1. Define the Time window for your SLO:
  2. Configure the Error budget calculation method and Objectives:
    • Occurrences method counts good attempts against the count of total attempts.
    • Time Slices method 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.

      • Similar threshold values for objectives
      To use similar threshold values for different objectives in your SLO, we recommend differentiating them by setting varying decimal points for each objective.
      For example, if you want to use threshold value 1 for two objectives, set it to 1.0000001 for the first objective and to 1.0000002 for the second one.
  3. Add the Display name, Name, and other settings for your SLO:
    • Name identifies your SLO in Nobl9. After you save the SLO, its name becomes read-only.
      Use only lowercase letters, numbers, and dashes.
    • Select No data anomaly alert to receive notifications when your SLO stops reporting data for a specified period:
      • Choose up to five supported Alert methods.
      • Specify the delay period before Nobl9 sends an alert about the missing data.
        From 5 minutes to 31 days. Default: 15 minutes
    • Add alert policies, labels, and links, if required.
      Limits per SLO: 20 alert policies or links, 30 labels.
  4. Click CREATE SLO.

    5. SLO configuration use case
    Check the SLO configuration use case for a real-life SLO example.

YAML​

Sample Datadog 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 Datadog SLO
  indicator:
    metricSource:
      name: datadog
      project: default
      kind: Agent
  budgetingMethod: Occurrences
  objectives:
    - displayName: Good response (200)
      value: 200
      name: ok
      target: 0.95
      rawMetric:
        query:
          datadog:
            query: avg:trace.http.request.duration{*}
      op: lte
      primary: true
  service: api-server
  timeWindows:
    - unit: Month
      count: 1
      isRolling: false
      calendar:
        startTime: '2022-12-01 00:00:00'
        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
      alertAfter: 1h
Click to open field reference
FieldTypeDescription
apiVersion
mandatory
stringAPI version. Use n9/v1alpha
kind
mandatory
stringThe resource type. Use SLO
Metadata
metadata.name
mandatory
stringName identifier for the SLO. Use only lowercase alphanumeric characters
metadata.displayNamestringUser-friendly SLO name
metadata.project
mandatory
stringThe name identifier of the project where you need to host your SLO
metadata.labelsobject (map: string[])Grouping labels for filtering or viewing
metadata.annotationsobject (map: string)Flat string annotations
Spec
spec.descriptionstringSLO description
spec.indicator.metricSource.name
mandatory
stringData source name
spec.indicator.metricSource.project
mandatory
stringProject containing the data source
spec.indicator.metricSource.kind
mandatory
stringData source connection method. Can be Agent or Direct
spec.budgetingMethod
mandatory
enumError budget calculation method. Can be Occurrences or Time slices
spec.objectives
mandatory
arrayYour SLO objective definition, up to 12 objectives per SLO.
spec.objectives[].displayNamestringUser-friendly objective name
spec.objectives[].value
mandatory
numberData point values that is considered "good" (e.g., 200.0).
In SLOs with two or more objectives, keep each objective's value unique.
In ratio (count) metrics, value is retained for legacy purposes.
spec.objectives[].name
mandatory
stringName identifier for this objective
spec.objectives[].op
mandatory
string (enum)Operator for objective. One of:
lte (less than or equal to)
lt (less than)
gte (greater than or equal to)
gt (greater than)
spec.objectives[].target
mandatory
floatThe percentage of the good minutes or occurrences that must meet the desired performance (e.g., is the target is 0.95, the good performance is expected to be observed in at least 95% of the time window)
spec.objectives[].rawMetric/.countMetric
mandatory
objectThe metric type indicator. Set:
rawMetric for a threshold metric
countMetric for a ratio metric.
A ratio metric requires the additional fields:
countMetric.incremental (boolean) the data count method
countMetric.good/.bad and countMetric.total a numerator and denominator queries
spec.objectives[].countMetric.incremental
mandatory
booleanThe data count method for a ratio (countMetric) metric type
spec.objectives[].primarybooleanThe indicator of a primary SLO objective
spec.service
mandatory
stringThe name identifier of a service to host this SLO. The service must exist in the project specified in metadata.project
spec.timeWindows
mandatory
arrayDefines SLO time window for error budget calculation. Set:
isRolling: true for the rolling time window type
isRolling: false for the calendar-aligned type
spec.timeWindows.unit
mandatory
integerThe time window units. One of:
Day | Hour | Minute for the rolling time window
Year | Quarter | Month | Week | Day for the calendar-aligned time window
spec.timeWindows.count
mandatory
integerThe number of units in a time window
spec.timeWindows.startTimestringMandatory for calendar-aligned time windows. Date and time in the format YYYY-MM-DDTHH:mm:ss
spec.timeWindows.timeZonestringMandatory for calendar-aligned time-windows. A valid IANA Time Zone Database name
spec.timeWindows.isRolling
mandatory
boolean
true for the rolling time window type
false for the calendar-aligned type
spec.alertPoliciesarrayThe name identifiers of alert policies to be linked to this SLO (must be from the same project as the SLO). Up to 20 alert policies per SLO.
spec.attachmentsarrayLinks to any additional attributes of this SLO
spec.anomalyConfigobjectSettings for a manual no data anomaly detection rule
spec.noData.alertMethodsarrayList of alert methods for no-data anomaly. Up to five alert methods per SLO. Every alert method must have the name and project fields
spec.noData.alertAfterstringWaiting time before sending a no-data notification. Must be 5m to 31d.
Default: 15m
Source-specific fields
datadog.query
mandatory
stringA Datadog query

Query requirements and recommendations​

  1. Your Datadog query must return only one time series.
    Grouping metrics result in multiple time series and is not supported.
  • Incorrect query: avg:system.load.1{*} by {host}
    A query with metric grouping returns multiple time series
  • Correct query: avg:system.load.1{*}
    The same query without metric grouping returns a single time series
  1. Avoid using rollup functions in queries.

The Nobl9 agent uses enforced rollup to ensure your SLI calculations are accurate. For this reason, we recommend avoiding the .rollup() and .moving_rollup() functions in your queries.

Using these functions can interfere with the Nobl9 data collection process and skew data points, which can lead to inaccurate error budget calculations.

Querying Datadog and API rate limits​

Nobl9 retrieves SLI data (an SLI represents a single time series) from Datadog's Query Timeseries API. To operate efficiently within Datadog's rate limits, Nobl9 optimizes how it sends requests.

Table: Key parameters

ParameterDetails
Query frequencyEvery two minutes
Datadog API default rate limit1600 requests per hour (per organization)
Retrieved SLI baselineMinimum of 52 SLIs per two-minute interval (with no batching)
Nobl9's optimization strategyBatches queries into single 1024-character requests; sends identical queries once per cycle

The number of SLIs per interval depends on query length and batching efficiency.

If you require a higher rate limit, contact your Datadog representative.

Ensure query correctness

An incorrect query can cause processing delays for all other queries in the same batch. To avoid this, we recommend verifying your queries are correct before saving the SLO.

Check out these related guides and references:
Adding Datadog as a data sourceAdding data sourcesNobl9 integration with DatadogDatadog documentationRollup interval: Enforced vs customDatadog documentationRate limitsDatadog documentationQuery timeseries APIDatadog documentationCreating SLOs via TerraformTerraform
On this page