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Azure monitor

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Azure Monitor is a monitoring solution that collects and aggregates data for further interpretation and response.

Nobl9 integration with Azure Monitor supports collecting Azure Monitor metrics, including Application Insights. With it, Nobl9 users can retrieve metrics and build SLOs based on them.

Scope of support​

caution

Ensure the metrics you use support a one-minute (1-minute) aggregation window (time grain).

Authentication​

To set up the Nobl9 direct connection, you must provide your Azure application's client ID and client secret. For this:

  1. Register an Azure application.
  2. Assign your Azure application the Monitoring Reader role for the Azure resources you want to read metrics from.
    This role meets the Nobl9 requirements for metric collection.
  3. Grant your application the Microsoft.Resources/subscriptions/resourceGroups/read permission.
    It enables resource and metric autocompletion during SLO creation.

You can also use sloctl. This way, you can configure SLOs for your Azure Cloud application without the resource and metric autocompletion.

Azure IAM

We recommend granting the Monitoring Reader role on the subscription or resource group level rather than a specific resource. A broader scope provides a more comprehensive choice of subscriptions, resource groups, resources, and metrics in the Nobl9 platform.

Adding Azure Monitor as a data source​

You can add the Azure Monitor data source using the direct or agent connection methods. For both methods, start with these steps:

  1. Navigate to Integrations > Sources.
  2. Click .
    The Data Source wizard opens.
  3. Select Azure Monitor.

Azure Monitor direct​

Direct configuration in the UI​

  1. Click Direct.
  2. Enter your Azure Tenant ID.
    It is an 8-4-4-4-12-character code containing digits 0-9 and letters Aa-Ff.
  3. Enter your Azure Client ID.
  4. Enter your Azure Client Secret.
Azure application ID

To retrieve Azure application's client ID and client secret, find your required application under App Registrations within the Azure Portal.

  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 Azure Monitor integration for Query delay is 5 minutes.
    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.
    • The value for the maximum period of data retrieval depends on the data source. Check the Replay documentation for details.
    • 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.

Direct using CLI - YAML​

The YAML for setting up a direct connection to Azure Monitor looks like this:

apiVersion: n9/v1alpha
kind: Direct
metadata:
  name: azure-monitor
  displayName: Azure Monitor
  project: azure-monitor
spec:
  description: Direct integration with Azure Monitor
  sourceOf:
    - Metrics
  queryDelay:
      unit: Minute
      value: 5 # For current operation, must be a number from 5 to 1440 minutes (24 hours)
  logCollectionEnabled: false
  releaseChannel: beta # For Azure monitor, the only accepted value is beta
  azureMonitor:
    tenantID: <YOUR_AZURE_TENANT_ID>
    clientID: <YOUR_AZURE_APPLICATION_CLIENT_ID>
    clientSecret: <YOUR_AZURE_APPLICATION_CLIENT_SECRET>
  historicalDataRetrieval:
    maxDuration:
      value: 30
      unit: Day
    defaultDuration:
      value: 0
      unit: Day
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. Beta functionality available only through direct release channel. Reach out to support@nobl9.com to activate it.
releaseChannel
mandatory
enumSpecifies the release channel. Accepted values: beta | stable.
Source-specific fields
azureMonitor.tennantID
mandatory
string, secretIt's the identifier of your Microsoft Entra tenant.
azureMonitor.clientID
mandatory
stringSee authentication section above for more details.
azureMonitor.clientSecret
mandatory
stringSee 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.

Azure Monitor agent​

Agent configuration in the UI​

  1. Click Agent.
  2. Enter your Azure Tenant ID.
    It is an 8-4-4-4-12-character code containing digits 0-9 and letters Aa-Ff.
  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 Azure Monitor integration for Query delay is 5 minutes.
    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.
    • The value for the maximum period of data retrieval depends on the data source. Check the Replay documentation for details.
    • 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.

Agent using CLI - YAML​

The YAML for setting up an agent connection to Azure Monitor is as follows:

apiVersion: n9/v1alpha
kind: Agent
metadata:
  name: azure-monitor
  displayName: Azure Monitor
  project: azure-monitor
spec:
  description: Azure Monitor agent
  sourceOf:
    - Metrics
  releaseChannel: beta
  queryDelay:
      unit: Minute
      value: 5 # numeric, must be a number from 5 to 1440 minutes (24 hours)
  azureMonitor:
    tenantId: <YOUR_AZURE_AD_TENANT_ID>
  historicalDataRetrieval:
      maxDuration:
        value: 30
        unit: Day
      defaultDuration:
        value: 0
        unit: Day
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
azureMonitor.tennantID
mandatory
string, secretIt's the identifier of your Microsoft Entra tenant.
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.

Deploying Azure Monitor 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 the <YOUR_AZURE_APPLICATION_CLIENT_ID> and <YOUR_AZURE_APPLICATION_CLIENT_SECRET> with your client ID and client secret).

If you use Kubernetes, you can apply the supplied YAML config file to a Kubernetes cluster to deploy the agent. The agent facilitates Nobl9 to import your service metrics.

# 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-nobl9-azure-agent
   namespace: default
type: Opaque
stringData:
   azure_client_id: "<YOUR_AZURE_APPLICATION_CLIENT_ID>"
   azure_client_secret: "<YOUR_AZURE_APPLICATION_CLIENT_SECRET>"
   client_id: "<UNIQUE_CLIENT_ID>"
   client_secret: "<UNIQUE_CLIENT_SECRET>"
---
apiVersion: apps/v1
kind: Deployment
metadata:
   name: nobl9-agent-nobl9-azure-agent
   namespace: default
spec:
   replicas: 1
   selector:
      matchLabels:
         nobl9-agent-name: "azure-agent"
         nobl9-agent-project: "default"
         nobl9-agent-organization: "nobl9"
   template:
      metadata:
         labels:
            nobl9-agent-name: "azure-agent"
            nobl9-agent-project: "default"
            nobl9-agent-organization: "nobl9"
      spec:
         containers:
            - name: agent-container
              image: nobl9/agent:0.74.0-beta
              resources:
                 requests:
                    memory: "700Mi"
                    cpu: "0.2"
              env:
                 - name: N9_CLIENT_ID
                   valueFrom:
                      secretKeyRef:
                         key: client_id
                         name: nobl9-agent-nobl9-azure-agent
                 - name: N9_AZURE_MONITOR_CLIENT_ID
                   valueFrom:
                      secretKeyRef:
                         key: azure_client_id
                         name: nobl9-agent-nobl9-azure-agent
                 - name: N9_AZURE_MONITOR_CLIENT_SECRET
                   valueFrom:
                      secretKeyRef:
                         key: azure_client_secret
                         name: nobl9-agent-nobl9-azure-agent
                 - name: N9_CLIENT_SECRET
                   valueFrom:
                      secretKeyRef:
                         key: client_secret
                         name: nobl9-agent-nobl9-azure-agent
                 - name: N9_AUTH_SERVER
                   value: "<UNIQUE_VALUE>"
                 - name: N9_METRICS_PORT
                   value: "9090"
                 - name: N9_DIAGNOSTIC_QUERY_LOG_SAMPLE_INTERVAL_MINUTES
                   value: "10"

Important notes:

  • The N9_METRICS_PORT is a variable specifying the port to which the /metrics and /health endpoints are exposed.
  • 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.
  • N9_DIAGNOSTIC_QUERY_LOG_SAMPLE_INTERVAL_MINUTES sets the frequency of log emission for SLI Analyzer. The default value is 10. To deactivate log emission, set this value to 0.

Creating SLOs with Azure Monitor​

Nobl9 integration with Azure Monitor supports Azure Monitor Metrics and Azure Monitor Logs data types. For the both data types, you can create threshold metric and ratio good or bad over total metrics.

These methods are available in the UI and by applying YAML via sloctl.

Creating SLOs in the UI​

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

  1. Navigate to Service Level Objectives.

  2. Click .
    The SLO wizard opens.

Step 1

Select your Service the SLO will be associated with.

Step 2

  1. Select your Azure Monitor integration as the Data Source for your SLO.

  2. Modify the Period for Historical Data Retrieval, when necessary.
    By default, the historical data for Azure Monitor is retrieved for the 7-day period. You can extend this period up to the value you've set when adding the Azure Monitor data source.

  3. Select the Data Type:

Azure Monitor Metrics to capture numeric data from your monitored resources.

  1. Specify the Resource you need to collect metrics for.
    Set the path to your required resource using the Subscription, Resource Group, and Resource fields. Make sure your selected resource holds the metrics you need to collect.
  2. Select Namespace in the list of available, when required.
    It's a way Azure Monitor groups similar metrics together.
  3. Configure Metric:

    1. 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. You can choose one of the following metric types:

        • Good metric, meaning a ratio of good requests and total requests.
        • Bad metric, meaning a ratio of bad requests and total requests.
    2. 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.
    3. Select the Metric Name in the list of available metrics.
      When you cannot find the required metric name in the list or the list displays No matching data, check if your selected resource holds the metric you need.

    4. Choose metric Aggregation to determine processing of the incoming data.

        The following aggregations are available:
      • Sum: the sum of all datapoints in an aggregation window
      • Average: the average of datapoints per aggregation window. Usually, it's Sum/Count
      • Maximum: the greatest datapoint value in an aggregation window
      • Minimum: the lowest datapoint value in an aggregation window
      • Count: the number of datapoints in an aggregation window. This type considers only how many data points are received, instead of datapoint values

    5. Select Dimensions if any are applied to your chosen metric in Azure.
      You can select the Value in the list or enter the required one. Make sure your entered value is up to 255 characters (ASCII only)

Step 3

Define a Time Window for the SLO.

Step 4

Specify the Error Budget Calculation Method and your Objective(s).

Step 5

Add a Name, Description, and other details about your SLO. You can also select Alert Policies and Labels on this screen.

Click Create SLO.

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.

SLOs using Azure Monitor - YAML samples​

Azure Monitor Metrics SLOs​

Here’s an example of Azure Monitor Metrics using a rawMetric (the threshold metric):

apiVersion: n9/v1alpha
kind: SLO
metadata:
   name: metrics-threshold
   project: azure-monitor
spec:
   budgetingMethod: Occurrences
   description: "The time taken by the my-app client to send requests, in ms. The metric for the SLO uses Application Insights, therefore metricNamespace is provided."
   indicator:
      metricSource:
         kind: Direct
         name: azure-monitor-direct
         service: azure-monitor-service
   objectives:
      - displayName: Fatal
        name: objective-1
        op: lte
        rawMetric:
           query:
              azureMonitor:
                 dataType: metrics
                 resourceID: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/<PROVIDER_NAMESPACE>/<PROVIDER_TYPE>/my-app
                 metricName: "random_get AvgDurationMs"
                 metricNamespace: azure.applicationinsights
           aggregation: Avg
           value: 1
           target: 0.5
      - displayName: Poor
        name: objective-2
        op: lte
        rawMetric:
           query:
              azureMonitor:
                 dataType: metrics
                 resourceID: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/<PROVIDER_NAMESPACE>/<PROVIDER_TYPE>/my-app
                 metricName: "random_get AvgDurationMs"
                 metricNamespace: azure.applicationinsights
           aggregation: Avg
           value: 0.5
           target: 0.6
      - displayName: Good
        name: objective-3
        op: lte
        rawMetric:
           query:
              azureMonitor:
                 dataType: metrics
                 resourceID: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/<PROVIDER_NAMESPACE>/<PROVIDER_TYPE>/my-app
                 metricName: "random_get AvgDurationMs"
                 metricNamespace: azure.applicationinsights
           aggregation: Avg
           value: 0.4
           target: 0.7
      - displayName: Excellent
        name: objective-4
        op: lte
        rawMetric:
           query:
              azureMonitor:
                 dataType: metrics
                 resourceID: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/<PROVIDER_NAMESPACE>/<PROVIDER_TYPE>/my-app
                 metricName: "random_get AvgDurationMs"
                 metricNamespace: azure.applicationinsights
           aggregation: Avg
           value: 0.3
           target: 0.8
      - displayName: Perfect
        name: objective-5
        op: lte
        rawMetric:
           query:
              azureMonitor:
                 dataType: metrics
                 resourceID: /subscriptions/<SUBSCRIPTION_ID>/resourceGroups/<RESOURCE_GROUP>/providers/<PROVIDER_NAMESPACE>/<PROVIDER_TYPE>/my-app
                 metricName: "random_get AvgDurationMs"
                 metricNamespace: azure.applicationinsights
           aggregation: Avg
           value: 0.2
           target: 0.9
   timeWindows:
      - count: 1
        isRolling: true
        unit: Hour

Azure Monitor Logs SLOs​

Here’s an example of Azure Monitor Logs using a rawMetric (the threshold metric):

- apiVersion: n9/v1alpha
    kind: SLO
    metadata:
        name: logs-threshold
        project: azure-monitor
    spec:
        alertPolicies: []
        budgetingMethod: Occurrences
        createdAt: "2023-12-11T13:57:05Z"
        description: ""
        indicator:
            metricSource:
                kind: Direct
                name: azure-monitor-direct
                project: azure-monitor-direct
        objectives:
            - displayName: "Objective 1"
            name: "objective-1"
            op: lt
            rawMetric:
                query:
                    azureMonitor:
                        dataType: logs
                        kqlQuery: |-
                            AppRequests
                            | where AppRoleName == "my-app"
                            | summarize n9_value = avg(DurationMs) by bin(TimeGenerated, 15s)
                            | project n9_time = TimeGenerated, n9_value
                        workspace:
                            resourceGroup: <RESOURCE_GROUP>
                            subscriptionId: <SUBSCRIPTION_ID>
                            workspaceId: <WORKSPACE_ID>
            target: 0.01
            value: 1
        service: azure-monitor-service
        timeWindows:
            - count: 28
            isRolling: true
            period:
                begin: "2023-11-14T12:20:35Z"
                end: "2023-12-12T12:20:35Z"
            unit: Day

Querying the Azure Monitor API​

The Nobl9 agent leverages the Azure Monitor Data Plane API to get data.

Agent metrics

Creating SLOs via Terraform

Creating agents via Terraform

Register an Azure application | Azure documentation

How to find a tenant ID | Azure documentation

Monitoring Reader | Azure documentation

Azure Monitor Metrics overview | Azure documentation

Azure Monitor Logs overview | Azure documentation

Best practices for Kusto Query Language queries | Azure documentation

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