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04 - Logging and Monitoring (Dedicated)

Capture structured logs, query telemetry, and validate operational visibility.

Prerequisites

  • You completed 03 - Configuration.
  • Your function app $APP_NAME is deployed and running with Application Insights connected.

What You'll Build

  • Emit structured application logs from Node.js HTTP functions.
  • Query Application Insights traces to verify telemetry ingestion.
  • Use az webapp log tail for real-time log streaming on Dedicated plans.

Infrastructure Context

Plan: Dedicated (B1) | Monitoring: Application Insights (auto-created) | Log streaming: az webapp log tail

Application Insights is auto-created with the same name as the function app. On Dedicated plans, real-time log streaming uses az webapp log tail (not az functionapp log tail, which does not exist).

flowchart TD
    FA[Function App\nDedicated B1] -->|Telemetry SDK| AI[Application Insights\nfunc-ndded-04100022]
    FA -->|stdout/stderr| LOGS[Log Stream\naz webapp log tail]

    subgraph MONITORING["Observability"]
        AI
        LOGS
        KQL[KQL Queries\ntraces / requests]
    end

    AI --> KQL

    style FA fill:#ff8c00,color:#fff
    style MONITORING fill:#E3F2FD,stroke:#1976D2
    style AI fill:#FFF3E0

Steps

  1. Review the logging function.

    The reference app includes src/functions/logLevels.js which emits structured logs at different severity levels:

    const { app } = require('@azure/functions');

app.http('logLevels', {
    methods: ['GET'],
    route: 'loglevels',
    handler: async (_request, context) => {
        context.log('Info-level message from logLevels');
        context.warn('Warning-level message from logLevels');
        context.error('Error-level message from logLevels');
        return { status: 200, jsonBody: { logged: true } };
    }
});

  2. Generate telemetry by invoking endpoints.

    curl --request GET "https://$APP_NAME.azurewebsites.net/api/health"
curl --request GET "https://$APP_NAME.azurewebsites.net/api/hello/Monitor"
curl --request GET "https://$APP_NAME.azurewebsites.net/api/info"

    Telemetry ingestion delay

    Application Insights has a 2–5 minute ingestion delay for new data. Wait at least 3 minutes after invoking endpoints before querying traces.

  3. Query Application Insights traces.

    App Insights name

    The Application Insights resource is auto-created with the same name as the function app (func-ndded-04100022), not $APP_NAME-ai. Use --app "$APP_NAME" for queries.

    az monitor app-insights query \
  --app "$APP_NAME" \
  --resource-group "$RG" \
  --analytics-query "traces | where timestamp > ago(30m) | project timestamp, message, severityLevel | take 20" \
  --output json
    CLI element Explanation
    Command(s) az monitor app-insights query
    Key flags --app, --resource-group, --analytics-query, --output
    Variables $APP_NAME, $RG
    Expected result Azure CLI returns the requested resource data; verify names, IDs, status fields, or metric values match the scenario.

    Expected output (abridged):

    {
  "tables": [
    {
      "name": "PrimaryResult",
      "columns": [
        { "name": "timestamp", "type": "datetime" },
        { "name": "message", "type": "string" },
        { "name": "severityLevel", "type": "int" }
      ],
      "rows": [
        ["2026-04-09T16:03:51.569Z", "Node.js v20 reached EOL on 2026-04...", 3],
        ["2026-04-09T16:03:51.731Z", "Using the AzureStorage storage provider.", 1],
        ["2026-04-09T16:03:54.950Z", "Initializing Warmup Extension.", 1],
        ["2026-04-09T16:04:20.575Z", "Handled hello for Monitor", 1]
      ]
    }
  ]
}

    How to read this

    • severityLevel: 1 = Information, 2 = Warning, 3 = Error
    • Runtime startup messages appear first, followed by your function logs
    • The Node.js EOL warning (severity 3) is expected for Node.js 20 deployments

  4. Stream real-time logs (Dedicated plan).

    az functionapp log tail does not exist

    As of Azure CLI 2.83.0, az functionapp log tail is not a valid command. On Dedicated plans, use az webapp log tail instead, which works because Dedicated Function Apps run on App Service infrastructure.

    az webapp log tail \
  --name "$APP_NAME" \
  --resource-group "$RG"
    CLI element Explanation
    Command(s) az webapp log tail
    Key flags --name, --resource-group
    Variables $APP_NAME, $RG
    Expected result Azure CLI completes successfully and returns JSON, table, or no output depending on the command; verify the next documented check before continuing.

    Then in another terminal, trigger a request:

    curl --request GET "https://$APP_NAME.azurewebsites.net/api/hello/LogTest"

    Expected log stream output:

    2026-04-09T16:10:11  Connected!
2026-04-09T16:10:19  [Information] Executing 'Functions.helloHttp'
2026-04-09T16:10:19  [Information] Handled hello for LogTest
2026-04-09T16:10:19  [Information] Executed 'Functions.helloHttp' (Succeeded, Duration=12ms)

  5. Query request performance metrics.

    az monitor app-insights query \
  --app "$APP_NAME" \
  --resource-group "$RG" \
  --analytics-query "requests | where timestamp > ago(30m) | project timestamp, name, resultCode, duration | take 10" \
  --output json
    CLI element Explanation
    Command(s) az monitor app-insights query
    Key flags --app, --resource-group, --analytics-query, --output
    Variables $APP_NAME, $RG
    Expected result Azure CLI returns the requested resource data; verify names, IDs, status fields, or metric values match the scenario.

Verification

The query result proves telemetry ingestion is active for your Function App. Verify:

  • traces table contains your function log messages
  • requests table shows HTTP invocations with status codes and durations
  • az webapp log tail streams real-time logs (not az functionapp log tail)

See Also

Sources