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Elasticsearch

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Elasticsearch is a distributed search and storage solution used for log analytics, full-text search, security intelligence, business analytics, and operational intelligence use cases. This integration supports histogram aggregate queries that return either a single value or a single pair stored in n9-val field, any filtering or matches can be applied as long as the output follows the mentioned format.

Elasticsearch parameters and supported features in Nobl9
General support:
Release channel: Stable, Beta
Connection method: Agent
Replay and SLI Analyzer: Replay only
Event logs: Not supported
Query checker: Not supported
Query parameters retrieval: Supported
Timestamp cache persistence: Supported
Query parameters:
Query interval: 1 min
Query delay: 1 min
Jitter: 15 sec
Timeout: 30 sec
Agent details and minimum required versions for supported features:
Environment variable: ES_QUERY_DELAY, ELASTICSEARCH_CUSTOM_AUTHORIZATION_HEADER, N9_ELASTIC_SEARCH_MAX_BUCKETS
Plugin name: n9elasticsearch
Replay and SLI Analyzer: 0.85.0-beta
Maximum historical data retrieval period: 30 days
Query parameters retrieval: 0.73.2
Timestamp cache persistence: 0.65.0
Additional notes:
Support for Elasticsearch v7.9.1

Authentication​

The Nobl9 agent calls the Elasticsearch Get API. For this, an authorization token is required. The token can be obtained from the Kibana control panel.

Learn about API keys in Elasticsearch.

Custom authorization header​

As an alternative to the token, you can provide a custom authorization header with the ELASTICSEARCH_CUSTOM_AUTHORIZATION_HEADER environment variable when deploying your Elasticsearch agent.

Adding Elasticsearch as a data source​

To ensure data transmission between Nobl9 and Elasticsearch, 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 the Elasticsearch data source using the agent connection method.

Nobl9 Web​

Follow the instructions below to configure your Elasticsearch agent:

  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. Add the URL to connect to your data source.
    The URL must point to the Elasticsearch app. If you are using Elastic Cloud, the URL can be obtained from here. Select your deployment, open the deployment details, and copy the Elasticsearch endpoint.

  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 Elasticsearch 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​

Sample YAML configuration for adding Elasticsearch with the agent connection method
apiVersion: n9/v1alpha
kind: Agent
metadata:
  name: elasticsearch
  displayName: Elasticsearch Agent
  project: default
spec:
  description: Example Elasticsearch Agent
  releaseChannel: stable
  elasticsearch:
    url: http://elasticsearch-main.elasticsearch:9200
  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
elasticsearch.url
mandatory
stringMust point to the Elasticsearch application.
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.
warning

You can deploy only one agent in one YAML file by using the sloctl apply command.

Agent deployment​

When you add a data source, Nobl9 automatically generates a Kubernetes configuration and a Docker command line for deploying the agent.

To access these configurations, go to the Integrations section on the Nobl9 Web. Open your data source details and find the required configuration under the Agent Configuration tab.

agent configuration
Elasticsearch agent configuration

Be sure to swap in your credentials (e.g., replace the <ELASTICSEARCH_TOKEN> with your organization key).

To deploy the agent using Kubernetes, apply the YAML configuration file generated to a Kubernetes cluster. Here is a sample command with the essential fields included. An Elasticsearch token is used for authorization (lines 44-48):

Sample Kubernetes configuration for agent deployment (token)
apiVersion: v1
kind: Secret
metadata:
  name: nobl9-agent-my-org-my-project-elasticsearch-data-source
  namespace: default
type: Opaque
stringData:
  elasticsearch_token: "<ELASTICSEARCH_TOKEN>"
  client_id: "<UNIQUE_CLIENT_ID>"
  client_secret: "<UNIQUE_CLIENT_SECRET>"
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: nobl9-agent-my-org-my-project-elasticsearch-data-source
  namespace: default
spec:
  replicas: 1
  selector:
    matchLabels:
      nobl9-agent-name: "elasticsearch-data-source"
      nobl9-agent-project: "my-project"
      nobl9-agent-organization: "my-org"
  template:
    metadata:
      labels:
        nobl9-agent-name: "elasticsearch-data-source"
        nobl9-agent-project: "my-project"
        nobl9-agent-organization: "my-org"
    spec:
      containers:
        - name: agent-container
          image: nobl9/agent:0.88.0-beta
          resources:
            requests:
              memory: "700Mi"
              cpu: "0.2"
          env:
            - name: N9_CLIENT_ID
              valueFrom:
                secretKeyRef:
                  key: client_id
                  name: nobl9-agent-my-org-my-project-elasticsearch-data-source
            - name: ELASTICSEARCH_TOKEN
              valueFrom:
                secretKeyRef:
                  key: elasticsearch_token
                  name: nobl9-agent-my-org-my-project-elasticsearch-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 Elasticsearch​

Nobl9 Web​

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

  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 Elasticsearch data source.
  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 Elasticsearch.
    • 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 Elasticsearch data source.
  6. Select the Metric type:
    • Threshold metric: a single time series is evaluated against a threshold.
    • Ratio metric: two-time series for comparison for good events and total events.
      For ratio metrics, select the Data count method: incremental or non-incremental.

  1. Enter a Query or Query for good counter and Query for total counter for the metric you selected.
    For examples of queries, refer to the section below.

    For details on Elasticsearch queries, refer to the Scope of support for Elasticsearch Queries section.

    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 Elasticsearch using a rawMetric (threshold metric):

Sample Elasticsearch threshold metric SLO
- apiVersion: n9/v1alpha
  kind: SLO
  metadata:
    name: api-server-slo
    # Optional
    #displayName: API Server SLO
    project: default
    # Labels and annotations are optional
    #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 Elasticsearch SLO
    indicator:
      metricSource:
        name: elasticsearch
        project: default
        kind: Agent
    budgetingMethod: Occurrences
    objectives:
      - displayName: Good response (200)
        value: 200.0
        name: ok
        target: 0.95
        rawMetric:
          query:
            elasticsearch:
              index: apm-7.13.3-transaction
              query: |-
                {
                  "query": {
                    "bool": {
                      "must": [
                        {
                          "match": {
                            "service.name": "api-server"
                          }
                        },
                        {
                          "match": {
                            "transaction.result": "HTTP 2xx"
                          }
                        }
                      ],
                      "filter": [
                        {
                          "range": {
                            "@timestamp": {
                              "gte": "{{.BeginTime}}",
                              "lte": "{{.EndTime}}"
                            }
                          }
                        }
                      ]
                    }
                  },
                  "size": 0,
                  "aggs": {
                    "resolution": {
                      "date_histogram": {
                        "field": "@timestamp",
                        "fixed_interval": "{{.Resolution}}",
                        "min_doc_count": 0,
                        "extended_bounds": {
                          "min": "{{.BeginTime}}",
                          "max": "{{.EndTime}}"
                        }
                      },
                      "aggs": {
                        "n9-val": {
                          "avg": {
                            "field": "transaction.duration.us"
                          }
                        }
                      }
                    }
                  }
                }
        op: lte
        primary: true
    service: api-server
    timeWindows:
      - unit: Month
        count: 1
        isRolling: false
        calendar:
          startTime: 2022-12-01 00:00:00
          timeZone: UTC
    # Alert policies and anomaly notifications are optional
    #alertPolicies:
    #  - fast-burn-5x-for-last-10m
    #attachments:
    #  - url: https://docs.nobl9.com
    #    displayName: Nobl9 Documentation
    #anomalyConfig:
    #  noData:
    #    alertMethods:
    #      - name: slack-notification
    #        project: default

Elasticsearch queries scope of support​

When you use data from Elastic APM, the document timestamp can be provided either with "field": "@timestamp" or other, depending on the schema used.

Learn more about query requirements and options in Elasticsearch:

For the Nobl9 agent, queries must meet the following requirements:

  • The search results must be a time series
  • The aggs.resolution object must hold the following:
    • date_histogram to provide the timestamps
    • aggs.n9-val to provide the value(s)
Sample Elasticsearch query with the resolution, date_histogram, and n9-val objects
{
  "aggs": {
    "resolution": {
      "date_histogram": {
        "field": "@timestamp",
        "fixed_interval": "{{.Resolution}}",
        "min_doc_count": 0,
        "extended_bounds": {
          "min": "{{.BeginTime}}",
          "max": "{{.EndTime}}"
        }
      },
      "aggs": {
        "n9-val": {
          "avg": {
            "field": "transaction.duration.us"
          }
        }
      }
    }
  }
}

  1. Date Histogram Aggregation

    • We recommend using date_histogram with fixed_interval and passing the {{.Resolution}} placeholder as the interval value. With it, the Nobl9 agent can control data resolution.
    • fixed_interval in the query must be no longer than one minute: Nobl9 agent queries your data source every one minute for a 1-minute time range.

  2. Date Histogram Aggregation Fixed Intervals

    • "field": "@timestamp" must match the field used in the filter query.
    • Use extended_bounds with the "{{.BeginTime}}", "{{.EndTime}}" placeholders as a filter query.
    Placeholder usage

    {{.BeginTime}} and {{.EndTime}} are mandatory placeholders and must be included in the query. If you use filter and aggregations parameters in your query, {{.BeginTime}} and {{.EndTime}} are required for both parameters.

    The Nobl9 agent replaces these placeholders with the correct time range values.

  3. Metrics Aggregations

    • n9-val must be a metric aggregation.

    • single value metric aggregation is used as the value of the time series.

    • multi-value metric aggregation first returns a non-null value and is used as the value of the time series. In the following example, the null values are skipped.

      "aggs": {
          "n9-val": {
              ...
          }
      }

  4. elasticsearch.index is the index name when the query completes.

Querying the Elasticsearch server​

Nobl9 calls Elasticsearch Get API every minute and retrieves data points from the previous minute to the present time point. The number of data points is dependent on how much data the customer has stored.

Elasticsearch API rate limits​

For aggregation and analysis, Elasticsearch uses buckets. Each bucket collects a set of documents that match a given criterion.

The default API rate limit in Elasticsearch is 65,536 buckets for aggregate queries; however, the actual number of buckets depends on the target cluster configuration.

To configure the API rate limits within the Nobl9 agent, provide the N9_ELASTIC_SEARCH_MAX_BUCKETS environment variable. The Nobl9 agent uses its value to determine the resolution duration when registering data while replaying SLOs. The higher the value, the more data Replay will request.

To configure rate limits at the level of your Elasticsearch cluster, set the required value for the search.max_buckets parameter.

Learn more about search settings in Elasticsearch.

For a more in-depth look, consult additional resources:
Sending more data points than expectedTroubleshootingElasticsearch authenticationElasticsearch docsElasticsearch get APIElasticsearch docsElasticsearch APMElasticsearch docsBoolean queryElasticsearch docsQuery and filter contextElasticsearch docsFilter aggregationElasticsearch docsRange queryElasticsearch docsElasticsearch indexElasticsearch docsSearch SettingsElasticsearch docsAgent metricsAgentCreating SLOs via TerraformTerraformCreating agents via TerraformTerraform
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