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Datadog

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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: Supported
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:
Environment variable: DATADOG_QUERY_DELAY
Plugin name: n9datadog
Replay and SLI Analyzer: 0.65.0
Maximum historical data retrieval period: 30 days
Query parameters retrieval: 0.73.2
Timestamp cache persistence: 0.65.0

Authentication​

To deploy the Nobl9 agent, provide an API Key and Application Key with the DD_API_KEY and DD_APPLICATION_KEY environment variables. Alternatively, you can pass credentials using a local configuration file with the api_key and application_key keys under the n9datadog section.

Learn how to obtain API and Application Keys.

Authorization scope requirements

To connect to Datadog, the Nobl9 agent scrapes the /api/v1/query endpoint that requires the timeseries_query authorization scope. Make sure your application has access to this scope before you connect to Datadog.

Learn more about Query timeseries data across multiple products.

Adding Datadog as a data source​

To ensure data transmission between Nobl9 and Datadog, it may be necessary to list Nobl9 IP addresses as trusted.

💻ip allowlist
IP addresses to include in your allowlist for secure access:

If you're using app.nobl9.com instance:
  • 18.159.114.21
  • 18.158.132.186
  • 3.64.154.26
If you're using us1.nobl9.com instance:
  • 34.121.54.120
  • 34.123.193.191
  • 34.134.71.10
  • 35.192.105.150
  • 35.225.248.37
  • 35.226.78.175
  • 104.198.44.161

You can add Datadog as the data source using the direct or agent connection methods.

Direct connection method​

Direct connection to Datadog requires entering your Datadog credentials.

Nobl9 Web​

  1. Navigate to Integrations > Sources.
  2. Click .
  3. Click the required Source button.
  4. Choose Direct.
  1. Select one of the following Release Channels:
    • The stable channel is fully tested by the Nobl9 team. It represents the final product; however, this channel does not contain all the new features of a beta release. Use it to avoid crashes and other limitations.
    • The beta channel is under active development. Here, you can check out new features and improvements without the risk of affecting any viable SLOs. Remember that features in this channel can change.

  2. Enter the Datadog Site for connection.
    It is a Datadog SaaS instance that corresponds to one of Datadog's available locations:

    • datadoghq.com (formerly referred to as com),
    • us3.datadoghq.com
    • us5.datadoghq.com
    • datadoghq.eu (formerly referred to as eu),
    • ddog-gov.com,
    • ap1.datadoghq.com

  3. Enter your Datadog API Key and Application Key.

  1. Select a Project.
    Specifying a project is helpful when multiple users are spread across multiple teams or projects. When the Project field is left blank, Nobl9 uses the default project.
  2. Enter a Display Name.
    You can enter a user-friendly name with spaces in this field.
  3. Enter a Name.
    The name is mandatory and can only contain lowercase, alphanumeric characters, and dashes (for example, my-project-1). Nobl9 duplicates the display name here, transforming it into the supported format, but you can edit the result.
  4. Enter a Description.
    Here you can add details such as who is responsible for the integration (team/owner) and the purpose of creating it.
  5. Specify the Query delay to set a customized delay for queries when pulling the data from the data source.
    • The default value in Datadog integration for Query delay is 1 minute.
    info
    Changing the Query delay may affect your SLI data. For more details, check the Query delay documentation.
  6. Enter a Maximum Period for Historical Data Retrieval.
    • This value defines how far back in the past your data will be retrieved when replaying your SLO based on this data source.
    • The maximum period value depends on the data source.
      Find the maximum value for your data source.
    • A greater period can extend the loading time when creating an SLO.
      • The value must be a positive integer.
  7. Enter a Default Period for Historical Data Retrieval.
    • It is used by SLOs connected to this data source.
    • The value must be a positive integer or 0.
    • By default, this value is set to 0. When you set it to >0, you will create SLOs with Replay.
  8. Click Add Data Source.

sloctl​

Create a configuration YAML file using the provided sample. Then, run sloctl apply specifying the path to your configuration file.

apiVersion: n9/v1alpha
kind: Direct
metadata:
  name: datadog-data-source
  # All displayName fields are optional
  displayName: Datadog data source
  # The name identifier of the project you want to locate your data source in
  project: my-project
spec:
  # All descriptions are optional
  description: My Datadog data source connected using the direct method
  releaseChannel: stable
  datadog:
    site: datadoghq.com
    apiKey: "[secret]"
    applicationKey: "[secret]"
  logCollectionEnabled: false # boolean, defaults to 'false'. Set to true if you'd like your source to collect logs. Available for data sources connected using the direct method only. Reach out to support@nobl9.com to activate it.
  historicalDataRetrieval:
    maxDuration:
      value: 30
      unit: Day
    defaultDuration:
      value: 15
      unit: Day
  queryDelay:
    value: 2
    unit: Minute
FieldTypeDescription
queryDelay.unit
mandatory
enumSpecifies the unit for the query delay. Possible values: Second | Minute.
• Check query delay documentation for default unit of query delay for each source.
queryDelay.value
mandatory
numericSpecifies the value for the query delay.
• Must be a number less than 1440 minutes (24 hours).
• Check query delay documentation for default unit of query delay for each source.
logCollectionEnabled
optional
booleanOptional. Defaults to false. Set to true if you'd like your direct to collect event logs. Contact us to activate it.
releaseChannel
mandatory
enumSpecifies the release channel. Accepted values: beta | stable.
Source-specific fields
datadog.site
mandatory
stringDatadog SaaS instance that corresponds to one of Datadog's available locations:
• datadoghq.com (formerly referred to as `COM`)
• us3.datadoghq.com
• us5.datadoghq.com
• datadoghq.eu (formerly referred to as `EU`)
• ddog-gov.com
• ap1.datadoghq.com
datadog.apiKey
mandatory
string, secretSee authentication section above for more details.
datadog.applicationKey
mandatory
string, secretSee authentication section above for more details.
Replay-related fields
historicalDataRetrieval
optional
n/aOptional structure related to configuration related to Replay.
❗ Use only with supported sources.
• If omitted, Nobl9 uses the default values of value: 0 and unit: Day for maxDuration and defaultDuration.
maxDuration.value
optional
numericSpecifies the maximum duration for historical data retrieval. Must be integer ≥ 0. See Replay documentation for values of max duration per data source.
maxDuration.unit
optional
enumSpecifies the unit for the maximum duration of historical data retrieval. Accepted values: Minute | Hour | Day.
defaultDuration.value
optional
numericSpecifies the default duration for historical data retrieval. Must be integer ≥ 0 and ≤ maxDuration.
defaultDuration.unit
optional
enumSpecifies the unit for the default duration of historical data retrieval. Accepted values: Minute | Hour | Day.

Agent connection method​

For the agent connection method, credentials aren't required. With this method, you must deploy your Datadog agent to activate data collection.

Nobl9 Web​

  1. Navigate to Integrations > Sources.
  2. Click .
  3. Click the required Source button.
  4. Choose Agent.
  1. Select one of the following Release Channels:
    • The stable channel is fully tested by the Nobl9 team. It represents the final product; however, this channel does not contain all the new features of a beta release. Use it to avoid crashes and other limitations.
    • The beta channel is under active development. Here, you can check out new features and improvements without the risk of affecting any viable SLOs. Remember that features in this channel can change.

  2. Enter the Datadog Site for connection.
    It is a Datadog SaaS instance that corresponds to one of Datadog's available locations:

    • datadoghq.com (formerly referred to as com),
    • us3.datadoghq.com
    • us5.datadoghq.com
    • datadoghq.eu (formerly referred to as eu),
    • ddog-gov.com,
    • ap1.datadoghq.com
  1. Select a Project.
    Specifying a project is helpful when multiple users are spread across multiple teams or projects. When the Project field is left blank, Nobl9 uses the default project.
  2. Enter a Display Name.
    You can enter a user-friendly name with spaces in this field.
  3. Enter a Name.
    The name is mandatory and can only contain lowercase, alphanumeric characters, and dashes (for example, my-project-1). Nobl9 duplicates the display name here, transforming it into the supported format, but you can edit the result.
  4. Enter a Description.
    Here you can add details such as who is responsible for the integration (team/owner) and the purpose of creating it.
  5. Specify the Query delay to set a customized delay for queries when pulling the data from the data source.
    • The default value in Datadog integration for Query delay is 1 minute.
    info
    Changing the Query delay may affect your SLI data. For more details, check the Query delay documentation.
  6. Enter a Maximum Period for Historical Data Retrieval.
    • This value defines how far back in the past your data will be retrieved when replaying your SLO based on this data source.
    • The maximum period value depends on the data source.
      Find the maximum value for your data source.
    • A greater period can extend the loading time when creating an SLO.
      • The value must be a positive integer.
  7. Enter a Default Period for Historical Data Retrieval.
    • It is used by SLOs connected to this data source.
    • The value must be a positive integer or 0.
    • By default, this value is set to 0. When you set it to >0, you will create SLOs with Replay.
  8. Click Add Data Source.

sloctl​

Create a configuration YAML file using the provided sample. Then, run sloctl apply specifying the path to your configuration file.

apiVersion: n9/v1alpha
kind: Agent
metadata:
  name: datadog-data-source
  # All displayName fields are optional
  displayName: Datadog data source
  # The name identifier of the project you want to locate your data source in
  project: my-project
spec:
  # All descriptions are optional
  description: My Datadog data source connected using the direct method
  releaseChannel: stable
  datadog:
    site: datadoghq.com
  historicalDataRetrieval:
    maxDuration:
      value: 30
      unit: Day
    defaultDuration:
      value: 15
      unit: Day
  queryDelay:
    value: 2
    unit: Minute
FieldTypeDescription
queryDelay.unit
mandatory
enumSpecifies the unit for the query delay. Possible values: Second | Minute.
• Check query delay documentation for default unit of query delay for each source.
queryDelay.value
mandatory
numericSpecifies the value for the query delay.
• Must be a number less than 1440 minutes (24 hours).
• Check query delay documentation for default unit of query delay for each source.
releaseChannel
mandatory
enumSpecifies the release channel. Accepted values: beta | stable.
Source-specific fields
datadog.site
mandatory
stringDatadog SaaS instance that corresponds to one of Datadog's available locations:
• datadoghq.com (formerly referred to as `com`)
• us3.datadoghq.com
• us5.datadoghq.com
• datadoghq.eu (formerly referred to as `eu`)
• ddog-gov.com
• ap1.datadoghq.com
Replay-related fields
historicalDataRetrieval
optional
n/aOptional structure related to configuration related to Replay.
❗ Use only with supported sources.
• If omitted, Nobl9 uses the default values of value: 0 and unit: Day for maxDuration and defaultDuration.
maxDuration.value
optional
numericSpecifies the maximum duration for historical data retrieval. Must be integer ≥ 0. See Replay documentation for values of max duration per data source.
maxDuration.unit
optional
enumSpecifies the unit for the maximum duration of historical data retrieval. Accepted values: Minute | Hour | Day.
defaultDuration.value
optional
numericSpecifies the default duration for historical data retrieval. Must be integer ≥ 0 and ≤ maxDuration.
defaultDuration.unit
optional
enumSpecifies the unit for the default duration of historical data retrieval. Accepted values: Minute | Hour | Day.

You can deploy only one agent per YAML file using sloctl apply.

Agent deployment​

When you add a data source, Nobl9 automatically generates a Kubernetes configuration and a Docker command line for agent deployment. To find them, go to your data source details > Agent Configuration.

Copy the required configuration and apply it to deploy the agent. Use you actual credentials instead of the placeholders (e.g., replace the <DATADOG_API_KEY> and <DATADOG_APPLICATION_KEY> with your organization keys).

Apply the copies YAML configuration to your Kubernetes cluster:

apiVersion: v1
kind: Secret
metadata:
  name: datadog-data-source
  namespace: my-namespace
type: Opaque
stringData:
  datadog_api_key: "<DATADOG_API_KEY>"
  datadog_application_key: "<DATADOG_APPLICATION_KEY>"
  client_id: "unique_client_id"
  client_secret: "unique_client_secret"
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: datadog-data-source
  namespace: my-namespace
spec:
  replicas: 1
  selector:
    matchLabels:
      nobl9-agent-name: "datadog-data-source"
      nobl9-agent-project: "my-project"
      nobl9-agent-organization: "my-organization"
  template:
    metadata:
      labels:
        nobl9-agent-name: "datadog-data-source"
        nobl9-agent-project: "my-project"
        nobl9-agent-organization: "my-organization"
    spec:
      containers:
        - name: agent-container
          image: nobl9/agent:0.82.2
          resources:
            requests:
              memory: "350Mi"
              cpu: "0.1"
          env:
            - name: N9_CLIENT_ID
              valueFrom:
                secretKeyRef:
                  key: client_id
                  name: datadog-data-source
            - name: N9_CLIENT_SECRET
              valueFrom:
                secretKeyRef:
                  key: client_secret
                  name: datadog-data-source
            - name: DD_API_KEY
              valueFrom:
                secretKeyRef:
                  key: datadog_api_key
                  name: datadog-data-source
            - name: DD_APPLICATION_KEY
              valueFrom:
                secretKeyRef:
                  key: datadog_application_key
                  name: datadog-data-source
            # The N9_METRICS_PORT is a variable specifying the port to which the /metrics and /health endpoints are exposed.
            # The 9090 is the default value and can be changed.
            # If you don’t want the metrics to be exposed, comment out or delete the N9_METRICS_PORT variable.
            - name: N9_METRICS_PORT
              value: "9090"

Creating SLOs with Datadog​

Nobl9 Web​

Follow the instructions below to create your SLOs with Datadog in the UI:

  1. Navigate to Service Level Objectives.

  2. Click .

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

  4. In step 2, select Datadog as the Data Source for your SLO.

  5. Modify Period for Historical Data Retrieval, when 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.

  6. Select the metric type:

    • A Threshold metric where a single time series is evaluated against a threshold.
    • A Ratio metric that allows you to enter two-time series for comparison.
        • For the ratio metric, select the Data Count Method:
      • 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.

  7. Enter a Query or Good Query and Total Query for the metric you selected.

      A sample threshold metric for Datadog:

    • avg:trace.http.request.duration{service:my-service}.as_count()

      A sample ratio metric for Datadog:

    • Good avg:trace.http.request.hits.by_http_status{service:my-service,!http.status_class:5xx}.as_count()
    • Total avg:trace.http.request.hits.by_http_status{service:my-service}.as_count()

    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. 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.
      Learn more about threshold value uniqueness.
  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.
    • Create Composite SLO: with this option selected, you create a composite SLO 1.0. Composite SLOs 1.0 are deprecated. They're fully operable; however, we encourage you to create new composite SLOs 2.0.
      You can create composite SLOs 2.0 with sloctl using the provided template. Alternatively, you can create a composite SLO 2.0 with Nobl9 Terraform provider.
    • Set Notifications on data. With it, Nobl9 will notify you in the cases when SLO won't be reporting data or report incomplete data for more than 15 minutes.
    • Add alert policies, labels, and links, if required.
      Up to 20 items of each type per SLO is allowed.
  4. Click CREATE SLO.

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

sloctl​

Here’s an example of Datadog using a rawMetric (threshold metric):

- apiVersion: n9/v1alpha
  kind: SLO
  metadata:
    name: my-datadog-threshold-slo
    # All displayName fields are optional
    displayName: My Datadog threshold SLO
    # The name identifier of the project you intend to locate your SLO in
    project: my-project
    # Labels, annotations: optional
    labels:
      area:
      - latency
      team:
      - sales
    annotations:
      area: latency
      team: sales
  spec:
    # All descriptions are optional
    description: My sample Datadog threshold SLO
    indicator:
      metricSource:
        # The name indicator of the data source for your SLO.
        name: datadog-data-source
        # The name indicator of the project holding your data source.
        project: my-project
        # Enum: Agent | Direct, mandatory. The connection method you used to add your data source.
        kind: Agent
    # Enum: Occurrences | Timeslices, mandatory. The budgeting method for your SLO.
    budgetingMethod: Occurrences
    objectives:
    - displayName: My objective
      value: 200.0
      name: my-objective
      target: 0.95
      rawMetric:
        query:
          datadog:
            query: avg:trace.http.request.duration{*}
      # Enum: lte (less than or equal to) | lt (less than) | gte (greater than or equal to) | gt (greater than).
      # The operator to compare incoming data against your threshold.
      op: lte
      # Boolean, mandatory. The primary objective indicator of your SLO.
      primary: true
    service: my-service
    # Mandatory. The time window for your SLO. Can be rolling or calendar-aligned.
    timeWindows:
    - unit: Month
      count: 1
      isRolling: false
      calendar:
        startTime: 2022-12-01 00:00:00
        timeZone: UTC
    # Alert policies, attachments, and anomalyConfig are optional.
    # Make sure you have alert policies and alert methods created before adding them to your SLO.
    alertPolicies:
    - my-alert-policy
    attachments:
    - url: https://{my-url}.com
      displayName: My URL attached to this SLO
    anomalyConfig:
      noData:
        alertMethods:
        - name: my-alert-method
          project: my-project

Important notes:

Learn more about Datadog queries.

warning

Queries to Datadog must return only one time series.

Example:

❌ Grouping metrics will often result in a multiple time series:

  • avg:system.load.1{*} by {host}
Image 1: Sample query with grouping metrics

✔ Same query without grouping

  • avg:system.load.1{*}
Image 2: Same query without grouping metrics
Rollup functions

Try avoiding the .rollup() or .moving_rollup() functions in your queries.

The Nobl9 agent uses enforced rollup described in the Rollup Interval: Enforced vs Custom to control the number of points returned from the queries. Using .rollup() or .moving_rollup() can affect the number of returned points or the way they are aggregated. This fact, in conjunction with the time range of each query by the Nobl9 agent can skew the calculated error budgets.

Learn more about Rollup.

Querying the Datadog server and API rate limits​

The Nobl9 agent leverages the Query Timeseries API parameters at a two-minute interval.

Requests to Datadog APIs are rate limited. The following is applied:

  • The default rate limit for the Query Timeseries API call is 1600 per hour per organization.
  • Nobl9 batches queries to Datadog into single 1024-character requests, including commas. Identical queries are sent only once to prevent redundancy.

For this reason, the amount of SLIs per interval depends on query length. With no batching, sending one query per API request, Nobl9 sends 52 SLIs per two-minute interval minimum (where an SLI represents a single time series).

When you need greater limits, refer to your Datadog contact.

Ensure query correctness

An incorrect query can occasionally cause delays for all queries in that batch. Identifying the problematic query may take time, leading to temporary processing delays.

For a more in-depth look, consult additional resources:
Nobl9 integration with datadogDatadog documentationRollup interval: Enforced vs customDatadog documentationRate limitsDatadog documentationQuery timeseries APIDatadog documentationAgent metricsAgentCreating SLOs via TerraformTerraformCreating agents via TerraformTerraform
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