Overview
In this lab, you will explore how to use Managed Service for Prometheus in a self-deployed data collection mode. You can also utilize managed data collection as well.
With self-deployed data collections, you manage your Prometheus installation as usual. The only difference from upstream Prometheus is that you run the Managed Service for Prometheus drop-in replacement binary instead of the upstream Prometheus binary.
You can find more information on considerations to make when choosing a managed vs. self-managed data collection at the following documentation link: Data collection with Managed Service for Prometheus.
Deploy the Managed Service for Prometheus
Create a self managed data collection for scraping metrics
Understand considerations to make when using managed vs. self-managed data collections
Utilize Grafana to query Prometheus metrics data
ketan_patel@cloudshell:~ (new-user-learning)$ kubectl -n gmp-test apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/prometheus-engine/v0.4.3-gke.0/examples/example-app.yaml
deployment.apps/prom-example created
ketan_patel@cloudshell:~ (new-user-learning)$ kubectl -n gmp-test apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/prometheus-engine/v0.4.3-gke.0/examples/prometheus.yaml
clusterrole.rbac.authorization.k8s.io/gmp-test:prometheus-test created
clusterrolebinding.rbac.authorization.k8s.io/gmp-test:prometheus-test created
service/prometheus-test created
statefulset.apps/prometheus-test created
configmap/prometheus-test created
ketan_patel@cloudshell:~ (new-user-learning)$ kubectl -n gmp-test get pod
NAME READY STATUS RESTARTS AGE
helloworld-gke-5f574446d7-97gx7 1/1 Running 0 80m
prom-example-7987cfb88f-6wnq2 1/1 Running 0 54s
prom-example-7987cfb88f-bv5f5 1/1 Running 0 54s
prom-example-7987cfb88f-thsqv 1/1 Running 0 54s
prometheus-test-0 2/2 Running 1 (11s ago) 20s
ketan_patel@cloudshell:~ (new-user-learning)$ export PROJECT_ID=$(gcloud config get-value project)
Your active configuration is: [cloudshell-533]
ketan_patel@cloudshell:~ (new-user-learning)$ curl https://raw.githubusercontent.com/GoogleCloudPlatform/prometheus-engine/v0.4.3-gke.0/examples/frontend.yaml |
sed "s/\$PROJECT_ID/$PROJECT_ID/" | kubectl apply -n gmp-test -f -
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 1514 100 1514 0 0 8096 0 --:--:-- --:--:-- --:--:-- 8096
deployment.apps/frontend created
service/frontend created
ketan_patel@cloudshell:~ (new-user-learning)$ kubectl -n gmp-test port-forward svc/frontend 9090
Forwarding from 127.0.0.1:9090 -> 9090
Handling connection for 9090
Handling connection for 9090
ketan_patel@cloudshell:~/kube-prometheus (new-user-learning)$ kubectl -n gmp-test apply -f https://raw.githubusercontent.com/GoogleCloudPlatform/prometheus-engine/v0.4.3-gke.0/examples/grafana.yaml
deployment.apps/grafana created
service/grafana created
ketan_patel@cloudshell:~/kube-prometheus (new-user-learning)$ kubectl -n gmp-test port-forward svc/grafana 3001:3000
error: unable to forward port because pod is not running. Current status=Pending
ketan_patel@cloudshell:~/kube-prometheus (new-user-learning)$ kubectl get pods -n gmp-test
NAME READY STATUS RESTARTS AGE
frontend-694bd6ff76-2wcr5 1/1 Running 0 8m17s
frontend-694bd6ff76-qp4bs 1/1 Running 0 8m17s
grafana-9fdc4b86b-22wwr 1/1 Running 0 31s
helloworld-gke-5f574446d7-97gx7 1/1 Running 0 90m
prom-example-7987cfb88f-6wnq2 1/1 Running 0 10m
prom-example-7987cfb88f-bv5f5 1/1 Running 0 10m
prom-example-7987cfb88f-thsqv 1/1 Running 0 10m
prometheus-test-0 2/2 Running 1 (9m42s ago) 9m51s
ketan_patel@cloudshell:~/kube-prometheus (new-user-learning)$ kubectl -n gmp-test port-forward svc/grafana 3001:3000
Forwarding from 127.0.0.1:3001 -> 3000
Handling connection for 3001
Handling connection for 3001
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