Logging with Fluentd
This task shows how to configure Istio to create custom log entries and send them to a Fluentd daemon. Fluentd is an open source log collector that supports many data outputs and has a pluggable architecture. One popular logging backend is Elasticsearch, and Kibana as a viewer. At the end of this task, a new log stream will be enabled sending logs to an example Fluentd / Elasticsearch / Kibana stack.
The Bookinfo sample application is used as the example application throughout this task.
Before you begin
- Install Istio in your cluster and deploy an
application. This task assumes that Mixer is setup in a default configuration
(
--configDefaultNamespace=istio-system). If you use a different value, 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 described here and here, or something specific to your cluster provider. This is likely configured to send logs to an Elasticsearch system or logging provider.
You may use these Fluentd daemons, or any other Fluentd daemon you have set up, as long as they are listening for forwarded logs, and Istio’s Mixer is able to connect to them. In order for Mixer to connect to a running Fluentd daemon, you may need to add a service for Fluentd. The Fluentd configuration to listen for forwarded logs is:
<source>
type forward
</source>
The full details of connecting Mixer to all possible Fluentd configurations is beyond the scope of this task.
Example Fluentd, Elasticsearch, Kibana Stack
For the purposes of this task, you may deploy the example stack
provided. This stack includes Fluentd, Elasticsearch, and Kibana in a
non production-ready set of
Services
and
Deployments
all in a new
Namespace
called 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 new log type, and send those logs to the listening daemon. Apply a YAML file with configuration for the log stream that Istio will generate and collect automatically:
$ kubectl apply -f @samples/bookinfo/telemetry/fluentd-istio.yaml@
Notice that the address: "fluentd-es.logging:24224" line in the
handler configuration is pointing to the Fluentd daemon we setup in the
example stack.
View the new logs
Send traffic to the sample application.
For the Bookinfo sample, visit
http://$GATEWAY_URL/productpagein your web browser or issue the following command:$ curl http://$GATEWAY_URL/productpageIn a Kubernetes environment, setup port-forwarding for Kibana by executing 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
@timestampas 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:
$ kubectl delete -f @samples/bookinfo/telemetry/fluentd-istio.yaml@If you are using Istio 1.1.2 or prior:
$ kubectl delete -f @samples/bookinfo/telemetry/fluentd-istio-crd.yaml@Remove the example Fluentd, Elasticsearch, Kibana stack:
$ kubectl delete -f logging-stack.yamlRemove any
kubectl port-forwardprocesses that may still be running:$ killall kubectlIf you are not planning to explore any follow-on tasks, refer to the Bookinfo cleanup instructions to shutdown the application.