events2prom collects events and aggregates them in memory to publish metrics in the Prometheus exposition format. It allows enabling and disabling aggregations in runtime and can support high dimensional cases.
Note: This is an experimental project, no stability guarantees.
$ docker run -it -p 6677:6677 -p 6678:6678/udp \
-v "${PWD}/examples/config/events2prom.yaml":/events2prom.yaml \
public.ecr.aws/q1p8v8z2/events2prom \
-config /events2prom.yaml
2021/11/08 13:27:17 Listening to admin server at ":6677"...
2021/11/08 13:27:17 Enabled collection: "request_count_by_pod"
2021/11/08 13:27:17 Enabled collection: "request_latency_ms"
2021/11/08 13:27:17 Listening events at [::]:6678, let's 🧹...
Then, run the example to generate events:
$ docker run -it --network host public.ecr.aws/q1p8v8z2/events2prom-example
Open http://127.0.0.1:6677/metrics to see the aggregated metrics.
# HELP request_count_by_pod Request count by pod
# TYPE request_count_by_pod counter
request_count_by_pod{pod="pod-1e0"} 1337
request_count_by_pod{pod="pod-1ff"} 1278
request_count_by_pod{pod="pod-def"} 1280
# HELP request_latency_ms Request latency in ms distribution
# TYPE request_latency_ms histogram
request_latency_ms_bucket{pod="pod-1e0",le="0"} 3
request_latency_ms_bucket{pod="pod-1e0",le="100"} 333
request_latency_ms_bucket{pod="pod-1e0",le="200"} 683
request_latency_ms_bucket{pod="pod-1e0",le="300"} 991
request_latency_ms_bucket{pod="pod-1e0",le="+Inf"} 991
request_latency_ms_sum{pod="pod-1e0"} 268975
request_latency_ms_count{pod="pod-1e0"} 991
request_latency_ms_bucket{pod="pod-1ff",le="0"} 5
request_latency_ms_bucket{pod="pod-1ff",le="100"} 328
request_latency_ms_bucket{pod="pod-1ff",le="200"} 661
request_latency_ms_bucket{pod="pod-1ff",le="300"} 978
request_latency_ms_bucket{pod="pod-1ff",le="+Inf"} 978
request_latency_ms_sum{pod="pod-1ff"} 250721
request_latency_ms_count{pod="pod-1ff"} 978
request_latency_ms_bucket{pod="pod-def",le="0"} 1
request_latency_ms_bucket{pod="pod-def",le="100"} 324
request_latency_ms_bucket{pod="pod-def",le="200"} 640
request_latency_ms_bucket{pod="pod-def",le="300"} 984
request_latency_ms_bucket{pod="pod-def",le="+Inf"} 984
request_latency_ms_sum{pod="pod-def"} 254033
request_latency_ms_count{pod="pod-def"} 984
Run the following to install events2prom on a Kubernetes cluster. See the config file to edit the config:
$ kubectl apply -f ./examples/config/k8s.yaml
Run an example program to produce events2prom events:
$ kubectl apply -f ./examples/config/example-app-k8s.yaml
Run the following command to ensure both events2prom and example application is running:
$ kubectl get pods -n events2prom
NAME READY STATUS RESTARTS AGE
events2prom-7gmr8 1/1 Running 0 5m31s
events2prom-97vw6 1/1 Running 0 5m3s
events2prom-dp9z4 1/1 Running 0 5m22s
events2prom-dvwbn 1/1 Running 0 5m17s
events2prom-example-47zq6 1/1 Running 0 32s
events2prom-example-6dr8c 1/1 Running 0 32s
events2prom-example-k4b76 1/1 Running 0 32s
events2prom-example-ltkqx 1/1 Running 0 32s
events2prom-example-s5lgq 1/1 Running 0 32s
events2prom-sxtpc 1/1 Running 0 4m58s
events2prom will run as a DaemonSet and will publish Prometheus metrics. Run Prometheus to scrape the events2prom output.