Configure local metrics and logs for Azure API Management self-hosted gateway

This article provides details for configuring local metrics and logs for the self-hosted gateway deployed on a Kubernetes cluster. For configuring cloud metrics and logs, see this article.

The self-hosted gateway supports StatsD, which has become a unifying protocol for metrics collection and aggregation. This section walks through the steps for deploying StatsD to Kubernetes, configuring the gateway to emit metrics via StatsD, and using Prometheus to monitor the metrics.

The following sample YAML configuration deploys StatsD and Prometheus to the Kubernetes cluster where a self-hosted gateway is deployed. It also creates a Service for each. The self-hosted gateway then publishes metrics to the StatsD Service. We'll access the Prometheus dashboard via its Service.

apiVersion: v1
kind: ConfigMap
metadata:
  name: sputnik-metrics-config
data:
  statsd.yaml: ""
  prometheus.yaml: |
    global:
      scrape_interval:     3s
      evaluation_interval: 3s
    scrape_configs:
      - job_name: 'prometheus'
        static_configs:
          - targets: ['localhost:9090']
      - job_name: 'test_metrics'
        static_configs:
          - targets: ['localhost:9102']
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: sputnik-metrics
spec:
  replicas: 1
  selector:
    matchLabels:
      app: sputnik-metrics
  template:
    metadata:
      labels:
        app: sputnik-metrics
    spec:
      containers:
      - name: sputnik-metrics-statsd
        image: prom/statsd-exporter
        ports:
        - name: tcp
          containerPort: 9102
        - name: udp
          containerPort: 8125
          protocol: UDP
        args:
          - --statsd.mapping-config=/tmp/statsd.yaml
          - --statsd.listen-udp=:8125
          - --web.listen-address=:9102
        volumeMounts:
          - mountPath: /tmp
            name: sputnik-metrics-config-files
      - name: sputnik-metrics-prometheus
        image: prom/prometheus
        ports:
        - name: tcp
          containerPort: 9090
        args:
          - --config.file=/tmp/prometheus.yaml
        volumeMounts:
          - mountPath: /tmp
            name: sputnik-metrics-config-files
      volumes:
        - name: sputnik-metrics-config-files
          configMap:
            name: sputnik-metrics-config
---
apiVersion: v1
kind: Service
metadata:
  name: sputnik-metrics-statsd
spec:
  type: NodePort
  ports:
  - name: udp
    port: 8125
    targetPort: 8125
    protocol: UDP
  selector:
    app: sputnik-metrics
---
apiVersion: v1
kind: Service
metadata:
  name: sputnik-metrics-prometheus
spec:
  type: LoadBalancer
  ports:
  - name: http
    port: 9090
    targetPort: 9090
  selector:
    app: sputnik-metrics

Save the configurations to a file named metrics.yaml. Use the following command to deploy everything to the cluster:

kubectl apply -f metrics.yaml

Once the deployment finishes, run the following command to check the Pods are running. Your pod name will be different.

kubectl get pods
NAME                                   READY   STATUS    RESTARTS   AGE
sputnik-metrics-f6d97548f-4xnb7        2/2     Running   0          1m

Run the below command to check the services are running. Take a note of the CLUSTER-IP and PORT of the StatsD Service, which we use later. You can visit the Prometheus dashboard using its EXTERNAL-IP and PORT.

kubectl get services
NAME                         TYPE           CLUSTER-IP    EXTERNAL-IP     PORT(S)                      AGE
sputnik-metrics-prometheus   LoadBalancer   10.0.252.72   13.89.141.90    9090:32663/TCP               18h
sputnik-metrics-statsd       NodePort       10.0.41.179   <none>          8125:32733/UDP               18h

Now that both StatsD and Prometheus are deployed, we can update the configurations of the self-hosted gateway to start emitting metrics through StatsD. The feature can be enabled or disabled using the telemetry.metrics.local key in the ConfigMap of the self-hosted gateway Deployment with additional options. The following are the available options:

Here's a sample configuration:

apiVersion: v1
kind: ConfigMap
metadata:
    name: contoso-gateway-environment
data:
    config.service.endpoint: "<self-hosted-gateway-management-endpoint>"
    telemetry.metrics.local: "statsd"
    telemetry.metrics.local.statsd.endpoint: "10.0.41.179:8125"
    telemetry.metrics.local.statsd.sampling: "1"
    telemetry.metrics.local.statsd.tag-format: "dogStatsD"

Update the YAML file of the self-hosted gateway deployment with the above configurations and apply the changes using the below command:

kubectl apply -f <file-name>.yaml

To pick up the latest configuration changes, restart the gateway deployment using the below command:

kubectl rollout restart deployment/<deployment-name>

Now we have everything deployed and configured, the self-hosted gateway should report metrics via StatsD. Prometheus then picks up the metrics from StatsD. Go to the Prometheus dashboard using the EXTERNAL-IP and PORT of the Prometheus Service.

Make some API calls through the self-hosted gateway, if everything is configured correctly, you should be able to view below metrics:

The self-hosted gateway outputs logs to stdout and stderr by default. You can easily view the logs using the following command:

kubectl logs <pod-name>

If your self-hosted gateway is deployed in Azure Kubernetes Service, you can enable Azure Monitor for containers to collect stdout and stderr from your workloads and view the logs in Log Analytics.

The self-hosted gateway also supports many protocols including localsyslog, rfc5424, and journal. The following table summarizes all the options supported.

Here's a sample configuration of local logging:

    apiVersion: v1
    kind: ConfigMap
    metadata:
        name: contoso-gateway-environment
    data:
        config.service.endpoint: "<self-hosted-gateway-management-endpoint>"
        telemetry.logs.std: "text"
        telemetry.logs.local.localsyslog.endpoint: "/dev/log"
        telemetry.logs.local.localsyslog.facility: "7"

• We only support up to 3072 bytes of request/response payload for local diagnostics. Anything above, may break JSON format due to chunking.

When using local syslog as a destination for logs, the runtime needs to allow streaming logs to the destination. For Kubernetes, a volume needs to be mounted which that matches the destination.

Given the following configuration:

apiVersion: v1
kind: ConfigMap
metadata:
    name: contoso-gateway-environment
data:
    config.service.endpoint: "<self-hosted-gateway-management-endpoint>"
    telemetry.logs.local: localsyslog
    telemetry.logs.local.localsyslog.endpoint: /dev/log

You can easily start streaming logs to that local syslog endpoint:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: contoso-deployment
  labels:
    app: contoso
spec:
  replicas: 1
  selector:
    matchLabels:
      app: contoso
  template:
    metadata:
      labels:
        app: contoso
    spec:
      containers:
        name: azure-api-management-gateway
        image: mcr.microsoft.com/azure-api-management/gateway:2.5.0
        imagePullPolicy: IfNotPresent
        envFrom:
        - configMapRef:
            name: contoso-gateway-environment
        # ... redacted ...
+       volumeMounts:
+       - mountPath: /dev/log
+         name: logs
+     volumes:
+     - hostPath:
+         path: /dev/log
+         type: Socket
+       name: logs

When configuring to use local syslog on Azure Kubernetes Service, you can choose two ways to explore the logs:

• Connect & explore logs on the worker nodes

You can easily consume them by getting access to the worker nodes:

1. Create an SSH connection to the node (docs)
2. Logs can be found under host/var/log/syslog

For example, you can filter all syslogs to just the ones from the self-hosted gateway:

$ cat host/var/log/syslog | grep "apimuser"
May 15 05:54:20 aks-agentpool-43853532-vmss000000 apimuser[8]: Timestamp=2023-05-15T05:54:20.0445178Z, isRequestSuccess=True, totalTime=290, category=GatewayLogs, callerIpAddress=141.134.132.243, timeGenerated=2023-05-15T05:54:20.0445178Z, region=Repro, correlationId=aaaa0000-bb11-2222-33cc-444444dddddd, method=GET, url="http://20.126.242.200/echo/resource?param1\=sample", backendResponseCode=200, responseCode=200, responseSize=628, cache=none, backendTime=287, apiId=echo-api, operationId=retrieve-resource, apimSubscriptionId=master, clientProtocol=HTTP/1.1, backendProtocol=HTTP/1.1, apiRevision=1, backendMethod=GET, backendUrl="http://echoapi.chinacloudapp.cn/api/resource?param1\=sample"
May 15 05:54:21 aks-agentpool-43853532-vmss000000 apimuser[8]: Timestamp=2023-05-15T05:54:21.1189171Z, isRequestSuccess=True, totalTime=150, category=GatewayLogs, callerIpAddress=141.134.132.243, timeGenerated=2023-05-15T05:54:21.1189171Z, region=Repro, correlationId=bbbb1111-cc22-3333-44dd-555555eeeeee, method=GET, url="http://20.126.242.200/echo/resource?param1\=sample", backendResponseCode=200, responseCode=200, responseSize=628, cache=none, backendTime=148, apiId=echo-api, operationId=retrieve-resource, apimSubscriptionId=master, clientProtocol=HTTP/1.1, backendProtocol=HTTP/1.1, apiRevision=1, backendMethod=GET, backendUrl="http://echoapi.chinacloudapp.cn/api/resource?param1\=sample"

• Learn about the observability capabilities of the Azure API Management gateways.
• Learn more about the Azure API Management self-hosted gateway.
• Learn about configuring and persisting logs in the cloud.