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Is it Observable?

Prometheus Logo

K8s and Loging with Loki

Loki Logo

Repository containing the files for the Episode 2 of Is it Observable : K8s and Loki

This repository showcase the usage of the Loki by using GKE with :

  • the HipsterShop

Prerequisite

The following tools need to be install on your machine :

  • jq
  • kubectl
  • git
  • gcloud ( if you are using GKE)
  • Helm

1.Create a Google Cloud Platform Project

PROJECT_ID="<your-project-id>"
gcloud services enable container.googleapis.com --project ${PROJECT_ID}
gcloud services enable monitoring.googleapis.com \
cloudtrace.googleapis.com \
clouddebugger.googleapis.com \
cloudprofiler.googleapis.com \
--project ${PROJECT_ID}

2.Create a GKE cluster

ZONE=us-central1-b
gcloud containr clusters create isitobservable \
--project=${PROJECT_ID} --zone=${ZONE} \
--machine-type=e2-standard-2 --num-nodes=4

3.Clone Github repo

git clone https://github.com/isItObservable/Episode2--Kubernetes-Loki
cd Episode2--Kubernetes-Loki

4. Deploy Prometheus

HipsterShop

cd hipstershop
./setup.sh

Prometheus ( already done during Episde 1)

helm install prometheus stable/prometheus-operator

Expose Grafana

kubectl get svc
kubectl edit svc prometheus-grafana

change to type NodePort

apiVersion: v1
kind: Service
metadata:
  annotations:
    meta.helm.sh/release-name: prometheus
    meta.helm.sh/release-namespace: default
  labels:
    app.kubernetes.io/instance: prometheus
    app.kubernetes.io/managed-by: Helm
    app.kubernetes.io/name: grafana
    app.kubernetes.io/version: 7.0.3
    helm.sh/chart: grafana-5.3.0
  name: prometheus-grafana
  namespace: default
  resourceVersion: "89873265"
  selfLink: /api/v1/namespaces/default/services/prometheus-grafana
spec:
  clusterIP: IPADRESSS
  externalTrafficPolicy: Cluster
  ports:
  - name: service
    nodePort: 30806
    port: 80
    protocol: TCP
    targetPort: 3000
  selector:
    app.kubernetes.io/instance: prometheus
    app.kubernetes.io/name: grafana
  sessionAffinity: None
  type: NodePort
status:
  loadBalancer: {}

Deploy the ingress by making sure to replace the service name of your grafan

cd ..\grafana
kubectl apply -f ingress.yaml

Get the login user and password of Grafana

  • For the password :
kubectl get secret --namespace default prometheus-grafana -o jsonpath="{.data.admin-password}" | base64 --decode
  • For the login user:
kubectl get secret --namespace default prometheus-grafana -o jsonpath="{.data.admin-user}" | base64 --decode

Get the ip adress of your Grafana

kubectl get ingress grafana-ingress -ojson | jq  '.status.loadBalancer.ingress[].ip'

Install Loki with Promtail

helm repo add loki https://grafana.github.io/loki/charts
helm repo update
helm upgrade --install loki loki/loki-stack

Configure Grafana

In order to build a dashboard with data stored in Loki,we first need to add a new DataSource. In grafana, goto Configuration/Add data source.

grafana add datasource

Select the source Loki , and configure the url to interact with it.

Remember Grafana is hosted in the same namesapce as Loki. So you can simply refer the loki service :

grafana add datasource

explore the data provided by Loki in Grafana

In grafana select Explore on the main menu Select the datasource Loki . IN the dropdow menu select the label produc -> hipster-shop

grafana explore

Let's build a query

Loki has a specific query langage allow you to filter, transform the data and event plot a metric from your logs in a graph. Similar to Prometheus you need to :

  • filter using labels : {app="frontend",product="hipster-shop" ,stream="stdout"} we are here only looking at the logs from hipster-shop , app frontend and on the logs pushed in sdout.
  • transform using | for example :
{job="fluent-bit",namespace="hipster-shop",stream="stdout"} | json | http_resp_took_ms >10

the first | specify to Grafana to use the json parser that will extract all the json properties as labels. the second | will filter the logs on the new labels created by the json parser. In this example we want to only get the logs where the attribute http.resp.took.ms is above 10ms ( the json parser is replace . by _)

We can then extract on field to plot it using all the various functions available in Grafana

if i want to plot the response time over time i could use the function :

avg(avg_over_time({job="fluent-bit",namespace="hipster-shop",stream="stdout"} | json | http_resp_took_ms >10 | __error__ != "JSONParserErr"|unwrap http_resp_took_ms  [30s])) by (pod)