Logging with Fluentd
- Before you begin
- Setup Fluentd
  - Example Fluentd, Elasticsearch, Kibana Stack
- Configure Istio
- View the new logs
- Cleanup
- 相关内容

Logging with Fluentd

This task shows how to configure Istio to create custom log entriesand send them to a Fluentd daemon. Fluentdis an open source log collector that supports many dataoutputs and has a pluggablearchitecture. One popular logging backend isElasticsearch, andKibana as a viewer. At theend of this task, a new log stream will be enabled sending logs to anexample Fluentd / Elasticsearch / Kibana stack.

The Bookinfo sample application is usedas the example application throughout this task.

Before you begin

Install Istio in your cluster and deploy anapplication. This task assumes that Mixer is setup in a default configuration(—configDefaultNamespace=istio-system). If you use a differentvalue, update the configuration and commands in this task to match the value.

Setup Fluentd

In your cluster, you may already have a Fluentd daemon set running,such the add-on describedhereandhere,or something specific to your cluster provider. This is likelyconfigured to send logs to an Elasticsearch system or loggingprovider.

You may use these Fluentd daemons, or any other Fluentd daemon youhave set up, as long as they are listening for forwarded logs, andIstio’s Mixer is able to connect to them. In order for Mixer toconnect to a running Fluentd daemon, you may need to add aservicefor Fluentd. The Fluentd configuration to listen for forwarded logsis:

<source>
  type forward
</source>

The full details of connecting Mixer to all possible Fluentdconfigurations is beyond the scope of this task.

Example Fluentd, Elasticsearch, Kibana Stack

For the purposes of this task, you may deploy the example stackprovided. This stack includes Fluentd, Elasticsearch, and Kibana in anon production-ready set ofServicesandDeploymentsall in a newNamespacecalled logging.

Save the following as logging-stack.yaml.

# Logging Namespace. All below are a part of this namespace.
apiVersion: v1
kind: Namespace
metadata:
  name: logging
---
# Elasticsearch Service
apiVersion: v1
kind: Service
metadata:
  name: elasticsearch
  namespace: logging
  labels:
    app: elasticsearch
spec:
  ports:
  - port: 9200
    protocol: TCP
    targetPort: db
  selector:
    app: elasticsearch
---
# Elasticsearch Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: elasticsearch
  namespace: logging
  labels:
    app: elasticsearch
spec:
  replicas: 1
  selector:
    matchLabels:
      app: elasticsearch
  template:
    metadata:
      labels:
        app: elasticsearch
      annotations:
        sidecar.istio.io/inject: "false"
    spec:
      containers:
      - image: docker.elastic.co/elasticsearch/elasticsearch-oss:6.1.1
        name: elasticsearch
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: discovery.type
            value: single-node
        ports:
        - containerPort: 9200
          name: db
          protocol: TCP
        - containerPort: 9300
          name: transport
          protocol: TCP
        volumeMounts:
        - name: elasticsearch
          mountPath: /data
      volumes:
      - name: elasticsearch
        emptyDir: {}
---
# Fluentd Service
apiVersion: v1
kind: Service
metadata:
  name: fluentd-es
  namespace: logging
  labels:
    app: fluentd-es
spec:
  ports:
  - name: fluentd-tcp
    port: 24224
    protocol: TCP
    targetPort: 24224
  - name: fluentd-udp
    port: 24224
    protocol: UDP
    targetPort: 24224
  selector:
    app: fluentd-es
---
# Fluentd Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: fluentd-es
  namespace: logging
  labels:
    app: fluentd-es
spec:
  replicas: 1
  selector:
    matchLabels:
      app: fluentd-es
  template:
    metadata:
      labels:
        app: fluentd-es
      annotations:
        sidecar.istio.io/inject: "false"
    spec:
      containers:
      - name: fluentd-es
        image: gcr.io/google-containers/fluentd-elasticsearch:v2.0.1
        env:
        - name: FLUENTD_ARGS
          value: --no-supervisor -q
        resources:
          limits:
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 200Mi
        volumeMounts:
        - name: config-volume
          mountPath: /etc/fluent/config.d
      terminationGracePeriodSeconds: 30
      volumes:
      - name: config-volume
        configMap:
          name: fluentd-es-config
---
# Fluentd ConfigMap, contains config files.
kind: ConfigMap
apiVersion: v1
data:
  forward.input.conf: |-
    # Takes the messages sent over TCP
    <source>
      type forward
    </source>
  output.conf: |-
    <match **>
       type elasticsearch
       log_level info
       include_tag_key true
       host elasticsearch
       port 9200
       logstash_format true
       # Set the chunk limits.
       buffer_chunk_limit 2M
       buffer_queue_limit 8
       flush_interval 5s
       # Never wait longer than 5 minutes between retries.
       max_retry_wait 30
       # Disable the limit on the number of retries (retry forever).
       disable_retry_limit
       # Use multiple threads for processing.
       num_threads 2
    </match>
metadata:
  name: fluentd-es-config
  namespace: logging
---
# Kibana Service
apiVersion: v1
kind: Service
metadata:
  name: kibana
  namespace: logging
  labels:
    app: kibana
spec:
  ports:
  - port: 5601
    protocol: TCP
    targetPort: ui
  selector:
    app: kibana
---
# Kibana Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kibana
  namespace: logging
  labels:
    app: kibana
spec:
  replicas: 1
  selector:
    matchLabels:
      app: kibana
  template:
    metadata:
      labels:
        app: kibana
      annotations:
        sidecar.istio.io/inject: "false"
    spec:
      containers:
      - name: kibana
        image: docker.elastic.co/kibana/kibana-oss:6.1.1
        resources:
          # need more cpu upon initialization, therefore burstable class
          limits:
            cpu: 1000m
          requests:
            cpu: 100m
        env:
          - name: ELASTICSEARCH_URL
            value: http://elasticsearch:9200
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP
---

Create the resources:

$ kubectl apply -f logging-stack.yaml
namespace "logging" created
service "elasticsearch" created
deployment "elasticsearch" created
service "fluentd-es" created
deployment "fluentd-es" created
configmap "fluentd-es-config" created
service "kibana" created
deployment "kibana" created

Configure Istio

Now that there is a running Fluentd daemon, configure Istio with a newlog type, and send those logs to the listening daemon. Apply aYAML file with configuration for the log stream thatIstio will generate and collect automatically:

Zip

$ kubectl apply -f @samples/bookinfo/telemetry/fluentd-istio.yaml@

If you use Istio 1.1.2 or prior, please use the following configuration instead:

Zip

$ kubectl apply -f @samples/bookinfo/telemetry/fluentd-istio-crd.yaml@

Notice that the address: "fluentd-es.logging:24224" line in thehandler configuration is pointing to the Fluentd daemon we setup in theexample stack.

View the new logs

Send traffic to the sample application.

For theBookinfosample, visit http://$GATEWAY_URL/productpage in your web browseror issue the following command:

$ curl http://$GATEWAY_URL/productpage

In a Kubernetes environment, setup port-forwarding for Kibana byexecuting the following command:

$ kubectl -n logging port-forward $(kubectl -n logging get pod -l app=kibana -o jsonpath='{.items[0].metadata.name}') 5601:5601 &

Leave the command running. Press Ctrl-C to exit when done accessing the Kibana UI.

Navigate to the Kibana UI and click the “Set up index patterns” in the top right.
Use * as the index pattern, and click “Next step.”.
Select @timestamp as the Time Filter field name, and click “Create index pattern.”
Now click “Discover” on the left menu, and start exploring the logs generated

Cleanup

Remove the new telemetry configuration:

Zip

$ kubectl delete -f @samples/bookinfo/telemetry/fluentd-istio.yaml@

If you are using Istio 1.1.2 or prior:

Zip

$ kubectl delete -f @samples/bookinfo/telemetry/fluentd-istio-crd.yaml@

Remove the example Fluentd, Elasticsearch, Kibana stack:

$ kubectl delete -f logging-stack.yaml

Remove any kubectl port-forward processes that may still be running:

$ killall kubectl

If you are not planning to explore any follow-on tasks, refer to theBookinfo cleanup instructionsto shutdown the application.

Logging with Fluentd

Logging with Fluentd

Before you begin

Setup Fluentd

Example Fluentd, Elasticsearch, Kibana Stack

Configure Istio

View the new logs

Cleanup

相关内容