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# kube-prometheus
This repository collects Kubernetes manifests, dashboards, and alerting rules
combined with documentation and scripts to provide single-command deployments
of end-to-end Kubernetes cluster monitoring.
## Prerequisites
First, you need a running Kubernetes cluster. If you don't have one, follow the
instructions of [bootkube](https://github.com/kubernetes-incubator/bootkube) or
[minikube](https://github.com/kubernetes/minikube). Some sample contents of this
repository are adapted to work with a [multi-node setup](https://github.com/kubernetes-incubator/bootkube/tree/master/hack/multi-node)
using [bootkube](https://github.com/kubernetes-incubator/bootkube).
## Monitoring Kubernetes
The manifests used here use the [Prometheus Operator](https://github.com/coreos/prometheus-operator),
which manages Prometheus servers and their configuration in a cluster. With a single command we can install
* The Operator itself
* The Prometheus [node_exporter](https://github.com/prometheus/node_exporter)
* [kube-state-metrics](https://github.com/kubernetes/kube-state-metrics)
* The [Prometheus specification](https://github.com/coreos/prometheus-operator/blob/master/Documentation/prometheus.md) based on which the Operator deploys a Prometheus setup
* A Prometheus configuration covering monitoring of all Kubernetes core components and exporters
* A default set of alerting rules on the cluster component's health
* A Grafana instance serving dashboards on cluster metrics
* A three node highly available Alertmanager cluster
Simply run:
```bash
export KUBECONFIG=<path> # defaults to "~/.kube/config"
hack/cluster-monitoring/deploy
```
After all pods are ready, you can reach:
* Prometheus UI on node port `30900`
* Alertmanager UI on node port `30903`
* Grafana on node port `30902`
To tear it all down again, run:
```bash
hack/cluster-monitoring/teardown
```
## Monitoring custom services
The example manifests in [/manifests/examples/example-app](/manifests/examples/example-app)
deploy a fake service exposing Prometheus metrics. They additionally define a new Prometheus
server and a [`ServiceMonitor`](https://github.com/coreos/prometheus-operator/blob/master/Documentation/service-monitor.md),
which specifies how the example service should be monitored.
The Prometheus Operator will deploy and configure the desired Prometheus instance and continiously
manage its life cycle.
```bash
hack/example-service-monitoring/deploy
```
After all pods are ready you can reach the Prometheus server on node port `30100` and observe
how it monitors the service as specified. Same as before, this Prometheus server automatically
discovers the Alertmanager cluster deployed in the [Monitoring Kubernetes](#Monitoring-Kubernetes)
section.
Teardown:
```bash
hack/example-service-monitoring/teardown
```
## Dashboarding
The provided manifests deploy a Grafana instance serving dashboards provided via a ConfigMap.
To modify, delete, or add dashboards, the `grafana-dashboards` ConfigMap must be modified.
Currently, Grafana does not support serving dashboards from static files. Instead, the `grafana-watcher`
sidecar container aims to emulate the behavior, by keeping the Grafana database always in sync
with the provided ConfigMap. Hence, the Grafana pod is effectively stateless.
This allows managing dashboards via `git` etc. and easily deploying them via CD pipelines.
In the future, a separate Grafana operator will support gathering dashboards from multiple
ConfigMaps based on label selection.
## Roadmap
* Grafana Operator that dynamically discovers and deploys dashboards from ConfigMaps
* KPM/Helm packages to easily provide production-ready cluster-monitoring setup (essentially contents of `hack/cluster-monitoring`)
* Add meta-monitoring to default cluster monitoring setup
* Build out the provided dashboards and alerts for cluster monitoring to have full coverage of all system aspects
## Monitoring other Cluster Components
Discovery of API servers and kubelets works the same across all clusters.
Depending on a cluster's setup several other core components, such as etcd or the
scheduler, may be deployed in different ways.
The easiest integration point is for the cluster operator to provide headless services
of all those components to provide a common interface of discovering them. With that
setup they will automatically be discovered by the provided Prometheus configuration.
For the `kube-scheduler` and `kube-controller-manager` there are headless
services prepared, simply add them to your running cluster:
```bash
kubectl -n kube-system create manifests/k8s/
```
> Hint: if you use this for a cluster not created with bootkube, make sure you
> populate an endpoints object with the address to your `kube-scheduler` and
> `kube-controller-manager`, or adapt the label selectors to match your setup.
Aside from Kubernetes specific components, etcd is an important part of a
working cluster, but is typically deployed outside of it. This monitoring
setup assumes that it is made visible from within the cluster through a headless
service as well.
> Note that minikube hides some components like etcd so to see the extend of
> this setup we recommend setting up a [local cluster using bootkube](https://github.com/kubernetes-incubator/bootkube/tree/master/hack/multi-node).
An example for bootkube's multi-node vagrant setup is [here](/manifests/etcd/etcd-bootkube-vagrant-multi.yaml).
> Hint: this is merely an example for a local setup. The addresses will have to
> be adapted for a setup, that is not a single etcd bootkube created cluster.
With that setup the headless services provide endpoint lists consumed by
Prometheus to discover the endpoints as targets:
```bash
$ kubectl get endpoints --all-namespaces
NAMESPACE NAME ENDPOINTS AGE
default kubernetes 172.17.4.101:443 2h
kube-system kube-controller-manager-prometheus-discovery 10.2.30.2:10252 1h
kube-system kube-scheduler-prometheus-discovery 10.2.30.4:10251 1h
monitoring etcd-k8s 172.17.4.51:2379 1h
```
## Other Documentation
[Install Docs for a cluster created with KOPS on AWS](docs/KOPSonAWS.md)

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assets/grafana/kubernetes-pods-dashboard.json Normal file
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@ -0,0 +1,409 @@
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880
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@ -0,0 +1,880 @@
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assets/grafana/prometheus-datasource.json Normal file
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{
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121
assets/prometheus/rules/etcd2.rules Normal file
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### General cluster availability ###
# alert if another failed peer will result in an unavailable cluster
ALERT InsufficientPeers
IF count(up{job="etcd-k8s"} == 0) > (count(up{job="etcd-k8s"}) / 2 - 1)
FOR 3m
LABELS {
severity = "critical"
}
ANNOTATIONS {
summary = "Etcd cluster small",
description = "If one more etcd peer goes down the cluster will be unavailable",
}
### HTTP requests alerts ###
# alert if more than 1% of requests to an HTTP endpoint have failed with a non 4xx response
ALERT HighNumberOfFailedHTTPRequests
IF sum by(method) (rate(etcd_http_failed_total{job="etcd-k8s", code!~"4[0-9]{2}"}[5m]))
/ sum by(method) (rate(etcd_http_received_total{job="etcd-k8s"}[5m])) > 0.01
FOR 10m
LABELS {
severity = "warning"
}
ANNOTATIONS {
summary = "a high number of HTTP requests are failing",
description = "{{ $value }}% of requests for {{ $labels.method }} failed on etcd instance {{ $labels.instance }}",
}
# alert if more than 5% of requests to an HTTP endpoint have failed with a non 4xx response
ALERT HighNumberOfFailedHTTPRequests
IF sum by(method) (rate(etcd_http_failed_total{job="etcd-k8s", code!~"4[0-9]{2}"}[5m]))
/ sum by(method) (rate(etcd_http_received_total{job="etcd-k8s"}[5m])) > 0.05
FOR 5m
LABELS {
severity = "critical"
}
ANNOTATIONS {
summary = "a high number of HTTP requests are failing",
description = "{{ $value }}% of requests for {{ $labels.method }} failed on etcd instance {{ $labels.instance }}",
}
# alert if 50% of requests get a 4xx response
ALERT HighNumberOfFailedHTTPRequests
IF sum by(method) (rate(etcd_http_failed_total{job="etcd-k8s", code=~"4[0-9]{2}"}[5m]))
/ sum by(method) (rate(etcd_http_received_total{job="etcd-k8s"}[5m])) > 0.5
FOR 10m
LABELS {
severity = "critical"
}
ANNOTATIONS {
summary = "a high number of HTTP requests are failing",
description = "{{ $value }}% of requests for {{ $labels.method }} failed with 4xx responses on etcd instance {{ $labels.instance }}",
}
# alert if the 99th percentile of HTTP requests take more than 150ms
ALERT HTTPRequestsSlow
IF histogram_quantile(0.99, rate(etcd_http_successful_duration_second_bucket[5m])) > 0.15
FOR 10m
LABELS {
severity = "warning"
}
ANNOTATIONS {
summary = "slow HTTP requests",
description = "on ectd instance {{ $labels.instance }} HTTP requests to {{ $label.method }} are slow",
}
### File descriptor alerts ###
instance:fd_utilization = process_open_fds / process_max_fds
# alert if file descriptors are likely to exhaust within the next 4 hours
ALERT FdExhaustionClose
IF predict_linear(instance:fd_utilization[1h], 3600 * 4) > 1
FOR 10m
LABELS {
severity = "warning"
}
ANNOTATIONS {
summary = "file descriptors soon exhausted",
description = "{{ $labels.job }} instance {{ $labels.instance }} will exhaust in file descriptors soon",
}
# alert if file descriptors are likely to exhaust within the next hour
ALERT FdExhaustionClose
IF predict_linear(instance:fd_utilization[10m], 3600) > 1
FOR 10m
LABELS {
severity = "critical"
}
ANNOTATIONS {
summary = "file descriptors soon exhausted",
description = "{{ $labels.job }} instance {{ $labels.instance }} will exhaust in file descriptors soon",
}
### etcd proposal alerts ###
# alert if there are several failed proposals within an hour
ALERT HighNumberOfFailedProposals
IF increase(etcd_server_proposal_failed_total{job="etcd"}[1h]) > 5
LABELS {
severity = "warning"
}
ANNOTATIONS {
summary = "a high number of failed proposals within the etcd cluster are happening",
description = "etcd instance {{ $labels.instance }} has seen {{ $value }} proposal failures within the last hour",
}
### etcd disk io latency alerts ###
# alert if 99th percentile of fsync durations is higher than 500ms
ALERT HighFsyncDurations
IF histogram_quantile(0.99, rate(etcd_wal_fsync_durations_seconds_bucket[5m])) > 0.5
FOR 10m
LABELS {
severity = "warning"
}
ANNOTATIONS {
summary = "high fsync durations",
description = "ectd instance {{ $labels.instance }} fync durations are high",
}

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# NOTE: These rules were kindly contributed by the SoundCloud engineering team.
### Container resources ###
cluster_namespace_controller_pod_container:spec_memory_limit_bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_spec_memory_limit_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:spec_cpu_shares =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_spec_cpu_shares{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:cpu_usage:rate =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
irate(
container_cpu_usage_seconds_total{container_name!=""}[5m]
),
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_usage:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_usage_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_working_set:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_working_set_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_rss:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_rss{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_cache:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_cache{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:disk_usage:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_disk_usage_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_pagefaults:rate =
sum by (cluster,namespace,controller,pod_name,container_name,scope,type) (
label_replace(
irate(
container_memory_failures_total{container_name!=""}[5m]
),
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_oom:rate =
sum by (cluster,namespace,controller,pod_name,container_name,scope,type) (
label_replace(
irate(
container_memory_failcnt{container_name!=""}[5m]
),
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
### Cluster resources ###
cluster:memory_allocation:percent =
100 * sum by (cluster) (
container_spec_memory_limit_bytes{pod_name!=""}
) / sum by (cluster) (
machine_memory_bytes
)
cluster:memory_used:percent =
100 * sum by (cluster) (
container_memory_usage_bytes{pod_name!=""}
) / sum by (cluster) (
machine_memory_bytes
)
cluster:cpu_allocation:percent =
100 * sum by (cluster) (
container_spec_cpu_shares{pod_name!=""}
) / sum by (cluster) (
container_spec_cpu_shares{id="/"} * on(cluster,instance) machine_cpu_cores
)
cluster:node_cpu_use:percent =
100 * sum by (cluster) (
rate(node_cpu{mode!="idle"}[5m])
) / sum by (cluster) (
machine_cpu_cores
)
### API latency ###
# Raw metrics are in microseconds. Convert to seconds.
cluster_resource_verb:apiserver_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(
0.99,
sum by(le,cluster,job,resource,verb) (apiserver_request_latencies_bucket)
) / 1e6
cluster_resource_verb:apiserver_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(
0.9,
sum by(le,cluster,job,resource,verb) (apiserver_request_latencies_bucket)
) / 1e6
cluster_resource_verb:apiserver_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(
0.5,
sum by(le,cluster,job,resource,verb) (apiserver_request_latencies_bucket)
) / 1e6
### Scheduling latency ###
cluster:scheduler_e2e_scheduling_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(0.99,sum by (le,cluster) (scheduler_e2e_scheduling_latency_microseconds_bucket)) / 1e6
cluster:scheduler_e2e_scheduling_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(0.9,sum by (le,cluster) (scheduler_e2e_scheduling_latency_microseconds_bucket)) / 1e6
cluster:scheduler_e2e_scheduling_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(0.5,sum by (le,cluster) (scheduler_e2e_scheduling_latency_microseconds_bucket)) / 1e6
cluster:scheduler_scheduling_algorithm_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(0.99,sum by (le,cluster) (scheduler_scheduling_algorithm_latency_microseconds_bucket)) / 1e6
cluster:scheduler_scheduling_algorithm_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(0.9,sum by (le,cluster) (scheduler_scheduling_algorithm_latency_microseconds_bucket)) / 1e6
cluster:scheduler_scheduling_algorithm_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(0.5,sum by (le,cluster) (scheduler_scheduling_algorithm_latency_microseconds_bucket)) / 1e6
cluster:scheduler_binding_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(0.99,sum by (le,cluster) (scheduler_binding_latency_microseconds_bucket)) / 1e6
cluster:scheduler_binding_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(0.9,sum by (le,cluster) (scheduler_binding_latency_microseconds_bucket)) / 1e6
cluster:scheduler_binding_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(0.5,sum by (le,cluster) (scheduler_binding_latency_microseconds_bucket)) / 1e6
ALERT K8SNodeDown
IF up{job="kubelet"} == 0
FOR 1h
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Kubelet cannot be scraped",
description = "Prometheus could not scrape a {{ $labels.job }} for more than one hour",
}
ALERT K8SNodeNotReady
IF kube_node_status_ready{condition="true"} == 0
FOR 1h
LABELS {
service = "k8s",
severity = "warning",
}
ANNOTATIONS {
summary = "Node status is NotReady",
description = "The Kubelet on {{ $labels.node }} has not checked in with the API, or has set itself to NotReady, for more than an hour",
}
ALERT K8SManyNodesNotReady
IF
count by (cluster) (kube_node_status_ready{condition="true"} == 0) > 1
AND
(
count by (cluster) (kube_node_status_ready{condition="true"} == 0)
/
count by (cluster) (kube_node_status_ready{condition="true"})
) > 0.2
FOR 1m
LABELS {
service = "k8s",
severity = "critical",
}
ANNOTATIONS {
summary = "Many K8s nodes are Not Ready",
description = "{{ $value }} K8s nodes (more than 10% of cluster {{ $labels.cluster }}) are in the NotReady state.",
}
ALERT K8SKubeletNodeExporterDown
IF up{job="node-exporter"} == 0
FOR 15m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Kubelet node_exporter cannot be scraped",
description = "Prometheus could not scrape a {{ $labels.job }} for more than one hour.",
}
ALERT K8SKubeletDown
IF absent(up{job="kubelet"}) or count by (cluster) (up{job="kubelet"} == 0) / count by (cluster) (up{job="kubelet"}) > 0.1
FOR 1h
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "Many Kubelets cannot be scraped",
description = "Prometheus failed to scrape more than 10% of kubelets, or all Kubelets have disappeared from service discovery.",
}
ALERT K8SApiserverDown
IF up{job="kubernetes"} == 0
FOR 15m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "API server unreachable",
description = "An API server could not be scraped.",
}
# Disable for non HA kubernetes setups.
ALERT K8SApiserverDown
IF absent({job="kubernetes"}) or (count by(cluster) (up{job="kubernetes"} == 1) < count by(cluster) (up{job="kubernetes"}))
FOR 5m
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "API server unreachable",
description = "Prometheus failed to scrape multiple API servers, or all API servers have disappeared from service discovery.",
}
ALERT K8SSchedulerDown
IF absent(up{job="kube-scheduler"}) or (count by(cluster) (up{job="kube-scheduler"} == 1) == 0)
FOR 5m
LABELS {
service = "k8s",
severity = "critical",
}
ANNOTATIONS {
summary = "Scheduler is down",
description = "There is no running K8S scheduler. New pods are not being assigned to nodes.",
}
ALERT K8SControllerManagerDown
IF absent(up{job="kube-controller-manager"}) or (count by(cluster) (up{job="kube-controller-manager"} == 1) == 0)
FOR 5m
LABELS {
service = "k8s",
severity = "critical",
}
ANNOTATIONS {
summary = "Controller manager is down",
description = "There is no running K8S controller manager. Deployments and replication controllers are not making progress.",
}
ALERT K8SConntrackTableFull
IF 100*node_nf_conntrack_entries / node_nf_conntrack_entries_limit > 50
FOR 10m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Number of tracked connections is near the limit",
description = "The nf_conntrack table is {{ $value }}% full.",
}
ALERT K8SConntrackTableFull
IF 100*node_nf_conntrack_entries / node_nf_conntrack_entries_limit > 90
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "Number of tracked connections is near the limit",
description = "The nf_conntrack table is {{ $value }}% full.",
}
# To catch the conntrack sysctl de-tuning when it happens
ALERT K8SConntrackTuningMissing
IF node_nf_conntrack_udp_timeout > 10
FOR 10m
LABELS {
service = "k8s",
severity = "warning",
}
ANNOTATIONS {
summary = "Node does not have the correct conntrack tunings",
description = "Nodes keep un-setting the correct tunings, investigate when it happens.",
}
ALERT K8STooManyOpenFiles
IF 100*process_open_fds{job=~"kubelet|kubernetes"} / process_max_fds > 50
FOR 10m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "{{ $labels.job }} has too many open file descriptors",
description = "{{ $labels.node }} is using {{ $value }}% of the available file/socket descriptors.",
}
ALERT K8STooManyOpenFiles
IF 100*process_open_fds{job=~"kubelet|kubernetes"} / process_max_fds > 80
FOR 10m
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "{{ $labels.job }} has too many open file descriptors",
description = "{{ $labels.node }} is using {{ $value }}% of the available file/socket descriptors.",
}
# Some verbs excluded because they are expected to be long-lasting:
# WATCHLIST is long-poll, CONNECT is `kubectl exec`.
ALERT K8SApiServerLatency
IF histogram_quantile(
0.99,
sum without (instance,node,resource) (apiserver_request_latencies_bucket{verb!~"CONNECT|WATCHLIST|WATCH"})
) / 1e6 > 1.0
FOR 10m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Kubernetes apiserver latency is high",
description = "99th percentile Latency for {{ $labels.verb }} requests to the kube-apiserver is higher than 1s.",
}
ALERT K8SApiServerEtcdAccessLatency
IF etcd_request_latencies_summary{quantile="0.99"} / 1e6 > 1.0
FOR 15m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Access to etcd is slow",
description = "99th percentile latency for apiserver to access etcd is higher than 1s.",
}
ALERT K8SKubeletTooManyPods
IF kubelet_running_pod_count > 100
LABELS {
service = "k8s",
severity = "warning",
}
ANNOTATIONS {
summary = "Kubelet is close to pod limit",
description = "Kubelet {{$labels.instance}} is running {{$value}} pods, close to the limit of 110",
}

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# Adding kube-prometheus to [KOPS](https://github.com/kubernetes/kops) on AWS 1.5.x
## Prerequisites
A running Kubernetes cluster created with [KOPS](https://github.com/kubernetes/kops).
These instructions have currently been tested with **topology=public** on AWS with KOPS 1.5.1 and Kubernetes 1.5.x
## Open AWS Security Groups:
1. Open port 9100 on the masters security group to the nodes security group
1. Open ports 10250-10252 on the masters security group to the nodes security group.
Example script below requires $AWS\_DEFAULT_PROFILE and [$NAME](https://github.com/kubernetes/kops/blob/master/docs/aws.md#prepare-local-environment)
```bash
MASTER_SG=$(aws --profile ${AWS_DEFAULT_PROFILE} ec2 describe-security-groups --filters "Name=tag:Name,Values=masters.$NAME" --query "SecurityGroups[*].GroupId[]" --output=text)
NODES_SG=$(aws --profile ${AWS_DEFAULT_PROFILE} ec2 describe-security-groups --filters "Name=tag:Name,Values=nodes.$NAME" --query "SecurityGroups[*].GroupId[]" --output=text)
aws --profile ${AWS_DEFAULT_PROFILE} ec2 authorize-security-group-ingress --group-id $MASTER_SG --protocol tcp --port 9100 --source-group $NODES_SG
aws --profile ${AWS_DEFAULT_PROFILE} ec2 authorize-security-group-ingress --group-id $MASTER_SG --protocol tcp --port 10250-10252 --source-group $NODES_SG
```
## Adding kube-prometheus
Following the instructions in the [README](https://github.com/coreos/kube-prometheus/blob/master/README.md):
Example:
```bash
git clone -b master https://github.com/coreos/kube-prometheus.git kube-prometheus-temp;
cd kube-prometheus-temp
./hack/cluster-monitoring/deploy
kubectl -n kube-system create -f manifests/k8s/self-hosted/
cd -
rm -rf kube-prometheus-temp
```

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#!/usr/bin/env bash
if [ -z "${KUBECONFIG}" ]; then
export KUBECONFIG=~/.kube/config
fi
if [ -z "${NAMESPACE}" ]; then
NAMESPACE=monitoring
fi
kubectl create namespace "$NAMESPACE"
kctl() {
kubectl --namespace "$NAMESPACE" "$@"
}
kctl apply -f manifests/prometheus-operator.yaml
# Wait for TPRs to be ready.
printf "Waiting for Operator to register third party objects..."
until kctl get servicemonitor > /dev/null 2>&1; do sleep 1; printf "."; done
until kctl get prometheus > /dev/null 2>&1; do sleep 1; printf "."; done
until kctl get alertmanager > /dev/null 2>&1; do sleep 1; printf "."; done
echo "done!"
kctl apply -f manifests/exporters
kctl apply -f manifests/grafana
kctl apply -f manifests/prometheus/prometheus-k8s-rules.yaml
kctl apply -f manifests/prometheus/prometheus-k8s-service.yaml
kctl apply -f manifests/alertmanager/alertmanager-config.yaml
kctl apply -f manifests/alertmanager/alertmanager-service.yaml
# `kubectl apply` is currently not working for third party resources so we are
# using `kubectl create` here for the time being.
# (https://github.com/kubernetes/kubernetes/issues/29542)
kctl create -f manifests/prometheus/prometheus-k8s-servicemonitors.yaml
kctl create -f manifests/prometheus/prometheus-k8s.yaml
kctl create -f manifests/alertmanager/alertmanager.yaml

6
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#!/usr/bin/env bash
hack/cluster-monitoring/deploy
awk 'FNR==1{print "---"}1' manifests/k8s/minikube/*.yaml | sed s/MINIKUBE_IP/`minikube ip`/g | kubectl --namespace=kube-system apply -f -

6
hack/cluster-monitoring/minikube-teardown Executable file
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#!/usr/bin/env bash
hack/cluster-monitoring/teardown
kubectl --namespace=kube-system delete -f manifests/k8s/minikube

6
hack/cluster-monitoring/self-hosted-deploy Executable file
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#!/usr/bin/env bash
hack/cluster-monitoring/deploy
kubectl --namespace=kube-system apply -f manifests/k8s/self-hosted

6
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#!/usr/bin/env bash
hack/cluster-monitoring/teardown
kubectl --namespace=kube-system delete -f manifests/k8s/self-hosted

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#!/usr/bin/env bash
if [ -z "${KUBECONFIG}" ]; then
export KUBECONFIG=~/.kube/config
fi
if [ -z "${NAMESPACE}" ]; then
NAMESPACE=monitoring
fi
kctl() {
kubectl --namespace "$NAMESPACE" "$@"
}
kctl delete -f manifests/exporters
kctl delete -f manifests/grafana
kctl delete -f manifests/prometheus
kctl delete -f manifests/alertmanager
# Hack: wait a bit to let the controller delete the deployed Prometheus server.
sleep 5
kctl delete -f manifests/prometheus-operator.yaml

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#!/usr/bin/env bash
if [ -z "${KUBECONFIG}" ]; then
KUBECONFIG=~/.kube/config
fi
if [ -z "${NAMESPACE}" ]; then
NAMESPACE=default
fi
kubectl --namespace "$NAMESPACE" --kubeconfig="$KUBECONFIG" apply -f manifests/examples/example-app/prometheus-frontend-svc.yaml
kubectl --namespace "$NAMESPACE" --kubeconfig="$KUBECONFIG" apply -f manifests/examples/example-app/example-app.yaml
# `kubectl apply` is currently not working for third party resources so we are
# using `kubectl create` here for the time being.
# (https://github.com/kubernetes/kubernetes/issues/29542)
kubectl --namespace "$NAMESPACE" --kubeconfig="$KUBECONFIG" create -f manifests/examples/example-app/prometheus-frontend.yaml
kubectl --namespace "$NAMESPACE" --kubeconfig="$KUBECONFIG" create -f manifests/examples/example-app/servicemonitor-frontend.yaml

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#!/usr/bin/env bash
if [ -z "${KUBECONFIG}" ]; then
KUBECONFIG=~/.kube/config
fi
if [ -z "${NAMESPACE}" ]; then
NAMESPACE=default
fi
kubectl --namespace "$NAMESPACE" --kubeconfig="$KUBECONFIG" delete -f manifests/examples/example-app

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#!/bin/bash
# Generate Alert Rules ConfigMap
kubectl create configmap --dry-run=true prometheus-k8s-rules --from-file=assets/prometheus/rules/ -oyaml > manifests/prometheus/prometheus-k8s-rules.yaml
# Generate Dashboard ConfigMap
kubectl create configmap --dry-run=true grafana-dashboards --from-file=assets/grafana/ -oyaml > manifests/grafana/grafana-dashboards.yaml

50
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#!/bin/bash -eu
# Intended usage:
# * Edit dashboard in Grafana (you need to login first with admin/admin
# login/password).
# * Save dashboard in Grafana to check is specification is correct.
# Looks like this is the only way to check is dashboard specification
# has error.
# * Download dashboard specification as JSON file in Grafana:
# Share -> Export -> Save to file.
# * Wrap dashboard specification to make it digestable by kube-prometheus:
# ./hack/scripts/wrap-dashboard.sh Nodes-1488465802729.json
# * Replace dashboard specification:
# mv Nodes-1488465802729.json assets/grafana/node-dashboard.json
# * Regenerate Grafana configmap:
# ./hack/scripts/generate-configmaps.sh
# * Apply new configmap:
# kubectl -n monitoring apply -f manifests/grafana/grafana-cm.yaml
if [ "$#" -ne 1 ]; then
echo "Usage: $0 path-to-dashboard.json"
exit 1
fi
json=$1
temp=$(tempfile -m 0644)
cat >> $temp <<EOF
{
"dashboard":
EOF
cat $json >> $temp
cat >> $temp <<EOF
,
"inputs": [
{
"name": "DS_PROMETHEUS",
"pluginId": "prometheus",
"type": "datasource",
"value": "prometheus"
}
],
"overwrite": true
}
EOF
mv $temp $json

18
manifests/alertmanager/alertmanager-config.yaml Normal file
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apiVersion: v1
kind: ConfigMap
metadata:
name: alertmanager-main
data:
alertmanager.yaml: |-
global:
resolve_timeout: 5m
route:
group_by: ['job']
group_wait: 30s
group_interval: 5m
repeat_interval: 12h
receiver: 'webhook'
receivers:
- name: 'webhook'
webhook_configs:
- url: 'http://alertmanagerwh:30500/'

14
manifests/alertmanager/alertmanager-service.yaml Normal file
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@ -0,0 +1,14 @@
apiVersion: v1
kind: Service
metadata:
name: alertmanager-main
spec:
type: NodePort
ports:
- name: web
nodePort: 30903
port: 9093
protocol: TCP
targetPort: web
selector:
alertmanager: main

9
manifests/alertmanager/alertmanager.yaml Normal file
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apiVersion: "monitoring.coreos.com/v1alpha1"
kind: "Alertmanager"
metadata:
name: "main"
labels:
alertmanager: "main"
spec:
replicas: 3
version: v0.5.1

28
manifests/etcd/etcd-bootkube-gce.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: etcd-k8s
labels:
k8s-app: etcd
spec:
type: ClusterIP
clusterIP: None
ports:
- name: api
port: 2379
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: etcd-k8s
labels:
k8s-app: etcd
subsets:
- addresses:
- ip: 10.142.0.2
nodeName: 10.142.0.2
ports:
- name: api
port: 2379
protocol: TCP

28
manifests/etcd/etcd-bootkube-vagrant-multi.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: etcd-k8s
labels:
k8s-app: etcd
spec:
type: ClusterIP
clusterIP: None
ports:
- name: api
port: 2379
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: etcd-k8s
labels:
k8s-app: etcd
subsets:
- addresses:
- ip: 172.17.4.51
nodeName: 172.17.4.51
ports:
- name: api
port: 2379
protocol: TCP

34
manifests/examples/example-app/example-app.yaml Normal file
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kind: Service
apiVersion: v1
metadata:
name: example-app
labels:
tier: frontend
spec:
selector:
app: example-app
ports:
- name: web
protocol: TCP
port: 8080
targetPort: web
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: example-app
spec:
replicas: 4
template:
metadata:
labels:
app: example-app
version: 1.1.3
spec:
containers:
- name: example-app
image: quay.io/fabxc/prometheus_demo_service
ports:
- name: web
containerPort: 8080
protocol: TCP

14
manifests/examples/example-app/prometheus-frontend-svc.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: prometheus-frontend
spec:
type: NodePort
ports:
- name: web
nodePort: 30100
port: 9090
protocol: TCP
targetPort: web
selector:
prometheus: prometheus-frontend

24
manifests/examples/example-app/prometheus-frontend.yaml Normal file
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apiVersion: monitoring.coreos.com/v1alpha1
kind: Prometheus
metadata:
name: prometheus-frontend
namespace: default
labels:
prometheus: frontend
spec:
version: v1.5.2
serviceMonitorSelector:
matchLabels:
tier: frontend
resources:
requests:
# 2Gi is default, but won't schedule if you don't have a node with >2Gi
# memory. Modify based on your target and time-series count for
# production use. This value is mainly meant for demonstration/testing
# purposes.
memory: 400Mi
alerting:
alertmanagers:
- namespace: monitoring
name: alertmanager-main
port: web

13
manifests/examples/example-app/servicemonitor-frontend.yaml Normal file
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apiVersion: monitoring.coreos.com/v1alpha1
kind: ServiceMonitor
metadata:
name: frontend
labels:
tier: frontend
spec:
selector:
matchLabels:
tier: frontend
endpoints:
- port: web
interval: 10s

25
manifests/exporters/kube-state-metrics-deployment.yaml Normal file
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apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: kube-state-metrics
spec:
replicas: 1
template:
metadata:
labels:
app: kube-state-metrics
spec:
containers:
- name: kube-state-metrics
image: gcr.io/google_containers/kube-state-metrics:v0.4.1
ports:
- name: metrics
containerPort: 8080
resources:
requests:
memory: 30Mi
cpu: 100m
limits:
memory: 50Mi
cpu: 200m

18
manifests/exporters/kube-state-metrics-service.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
labels:
app: kube-state-metrics
k8s-app: kube-state-metrics
annotations:
alpha.monitoring.coreos.com/non-namespaced: "true"
name: kube-state-metrics
spec:
ports:
- name: http-metrics
port: 8080
targetPort: metrics
protocol: TCP
selector:
app: kube-state-metrics

45
manifests/exporters/node-exporter-daemonset.yaml Normal file
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apiVersion: extensions/v1beta1
kind: DaemonSet
metadata:
name: node-exporter
spec:
template:
metadata:
labels:
app: node-exporter
name: node-exporter
spec:
hostNetwork: true
hostPID: true
containers:
- image: quay.io/prometheus/node-exporter:v0.13.0
args:
- "-collector.procfs=/host/proc"
- "-collector.sysfs=/host/sys"
name: node-exporter
ports:
- containerPort: 9100
hostPort: 9100
name: scrape
resources:
requests:
memory: 30Mi
cpu: 100m
limits:
memory: 50Mi
cpu: 200m
volumeMounts:
- name: proc
readOnly: true
mountPath: /host/proc
- name: sys
readOnly: true
mountPath: /host/sys
volumes:
- name: proc
hostPath:
path: /proc
- name: sys
hostPath:
path: /sys

17
manifests/exporters/node-exporter-service.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
labels:
app: node-exporter
k8s-app: node-exporter
name: node-exporter
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 9100
protocol: TCP
selector:
app: node-exporter

2984
manifests/grafana/grafana-dashboards.yaml Normal file
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56
manifests/grafana/grafana-deployment.yaml Normal file
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apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: grafana
spec:
replicas: 1
template:
metadata:
labels:
app: grafana
spec:
containers:
- name: grafana
image: grafana/grafana:4.1.1
env:
- name: GF_AUTH_BASIC_ENABLED
value: "true"
- name: GF_AUTH_ANONYMOUS_ENABLED
value: "true"
volumeMounts:
- name: grafana-storage
mountPath: /var/grafana-storage
ports:
- name: web
containerPort: 3000
resources:
requests:
memory: 100Mi
cpu: 100m
limits:
memory: 300Mi
cpu: 300m
- name: grafana-watcher
image: quay.io/coreos/grafana-watcher:latest
args:
- '--watch-dir=/var/grafana-dashboards'
- '--grafana-url=http://admin:admin@localhost:3000'
volumeMounts:
- name: grafana-dashboards
mountPath: /var/grafana-dashboards
resources:
requests:
memory: "16Mi"
cpu: "50m"
limits:
memory: "32Mi"
cpu: "100m"
volumeMounts:
- name: grafana-dashboards
mountPath: /var/grafana-dashboards
volumes:
- name: grafana-storage
emptyDir: {}
- name: grafana-dashboards
configMap:
name: grafana-dashboards

15
manifests/grafana/grafana-service.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: grafana
labels:
app: grafana
spec:
type: NodePort
ports:
- name: web
port: 3000
protocol: TCP
nodePort: 30902
selector:
app: grafana

28
manifests/k8s/minikube/kube-controller-manager.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: kube-controller-manager-prometheus-discovery
labels:
k8s-app: kube-controller-manager
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10252
targetPort: 10252
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: kube-controller-manager-prometheus-discovery
labels:
k8s-app: kube-controller-manager
subsets:
- addresses:
- ip: MINIKUBE_IP
ports:
- name: http-metrics
port: 10252
protocol: TCP

28
manifests/k8s/minikube/kube-scheduler.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: kube-scheduler-prometheus-discovery
labels:
k8s-app: kube-scheduler
spec:
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10251
targetPort: 10251
protocol: TCP
---
apiVersion: v1
kind: Endpoints
metadata:
name: kube-scheduler-prometheus-discovery
labels:
k8s-app: kube-scheduler
subsets:
- addresses:
- ip: MINIKUBE_IP
ports:
- name: http-metrics
port: 10251
protocol: TCP

16
manifests/k8s/self-hosted/kube-controller-manager.yaml Normal file
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@ -0,0 +1,16 @@
apiVersion: v1
kind: Service
metadata:
name: kube-controller-manager-prometheus-discovery
labels:
k8s-app: kube-controller-manager
spec:
selector:
k8s-app: kube-controller-manager
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10252
targetPort: 10252
protocol: TCP

20
manifests/k8s/self-hosted/kube-dns.yaml Normal file
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apiVersion: v1
kind: Service
metadata:
name: kube-dns-prometheus-discovery
labels:
k8s-app: kube-dns
spec:
selector:
k8s-app: kube-dns
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics-skydns
port: 10055
targetPort: 10055
protocol: TCP
- name: http-metrics-dnsmasq
port: 10054
targetPort: 10054
protocol: TCP

16
manifests/k8s/self-hosted/kube-scheduler.yaml Normal file
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@ -0,0 +1,16 @@
apiVersion: v1
kind: Service
metadata:
name: kube-scheduler-prometheus-discovery
labels:
k8s-app: kube-scheduler
spec:
selector:
k8s-app: kube-scheduler
type: ClusterIP
clusterIP: None
ports:
- name: http-metrics
port: 10251
targetPort: 10251
protocol: TCP

26
manifests/prometheus-operator.yaml Normal file
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apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: prometheus-operator
labels:
operator: prometheus
spec:
replicas: 1
template:
metadata:
labels:
operator: prometheus
spec:
containers:
- name: prometheus-operator
image: quay.io/coreos/prometheus-operator:v0.6.0
args:
- "--kubelet-object=kube-system/kubelet"
- "--config-reloader-image=quay.io/coreos/configmap-reload:v0.0.1"
resources:
requests:
cpu: 100m
memory: 50Mi
limits:
cpu: 200m
memory: 300Mi

447
manifests/prometheus/prometheus-k8s-rules.yaml Normal file
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apiVersion: v1
data:
etcd2.rules: "### General cluster availability ###\n\n# alert if another failed
peer will result in an unavailable cluster\nALERT InsufficientPeers\n IF count(up{job=\"etcd-k8s\"}
== 0) > (count(up{job=\"etcd-k8s\"}) / 2 - 1)\n FOR 3m\n LABELS {\n severity
= \"critical\"\n }\n ANNOTATIONS {\n summary = \"Etcd cluster small\",\n
\ description = \"If one more etcd peer goes down the cluster will be unavailable\",\n
\ }\n\n### HTTP requests alerts ###\n\n# alert if more than 1% of requests to
an HTTP endpoint have failed with a non 4xx response\nALERT HighNumberOfFailedHTTPRequests\n
\ IF sum by(method) (rate(etcd_http_failed_total{job=\"etcd-k8s\", code!~\"4[0-9]{2}\"}[5m]))\n
\ / sum by(method) (rate(etcd_http_received_total{job=\"etcd-k8s\"}[5m])) >
0.01\n FOR 10m\n LABELS {\n severity = \"warning\"\n }\n ANNOTATIONS {\n
\ summary = \"a high number of HTTP requests are failing\",\n description
= \"{{ $value }}% of requests for {{ $labels.method }} failed on etcd instance
{{ $labels.instance }}\",\n }\n\n# alert if more than 5% of requests to an HTTP
endpoint have failed with a non 4xx response\nALERT HighNumberOfFailedHTTPRequests\n
\ IF sum by(method) (rate(etcd_http_failed_total{job=\"etcd-k8s\", code!~\"4[0-9]{2}\"}[5m]))
\n / sum by(method) (rate(etcd_http_received_total{job=\"etcd-k8s\"}[5m]))
> 0.05\n FOR 5m\n LABELS {\n severity = \"critical\"\n }\n ANNOTATIONS
{\n summary = \"a high number of HTTP requests are failing\",\n description
= \"{{ $value }}% of requests for {{ $labels.method }} failed on etcd instance
{{ $labels.instance }}\",\n }\n\n# alert if 50% of requests get a 4xx response\nALERT
HighNumberOfFailedHTTPRequests\n IF sum by(method) (rate(etcd_http_failed_total{job=\"etcd-k8s\",
code=~\"4[0-9]{2}\"}[5m]))\n / sum by(method) (rate(etcd_http_received_total{job=\"etcd-k8s\"}[5m]))
> 0.5\n FOR 10m\n LABELS {\n severity = \"critical\"\n }\n ANNOTATIONS
{\n summary = \"a high number of HTTP requests are failing\",\n description
= \"{{ $value }}% of requests for {{ $labels.method }} failed with 4xx responses
on etcd instance {{ $labels.instance }}\",\n }\n\n# alert if the 99th percentile
of HTTP requests take more than 150ms\nALERT HTTPRequestsSlow\n IF histogram_quantile(0.99,
rate(etcd_http_successful_duration_second_bucket[5m])) > 0.15\n FOR 10m\n LABELS
{\n severity = \"warning\"\n }\n ANNOTATIONS {\n summary = \"slow HTTP
requests\",\n description = \"on ectd instance {{ $labels.instance }} HTTP
requests to {{ $label.method }} are slow\",\n }\n\n### File descriptor alerts
###\n\ninstance:fd_utilization = process_open_fds / process_max_fds\n\n# alert
if file descriptors are likely to exhaust within the next 4 hours\nALERT FdExhaustionClose\n
\ IF predict_linear(instance:fd_utilization[1h], 3600 * 4) > 1\n FOR 10m\n LABELS
{\n severity = \"warning\"\n }\n ANNOTATIONS {\n summary = \"file descriptors
soon exhausted\",\n description = \"{{ $labels.job }} instance {{ $labels.instance
}} will exhaust in file descriptors soon\",\n }\n\n# alert if file descriptors
are likely to exhaust within the next hour\nALERT FdExhaustionClose\n IF predict_linear(instance:fd_utilization[10m],
3600) > 1\n FOR 10m\n LABELS {\n severity = \"critical\"\n }\n ANNOTATIONS
{\n summary = \"file descriptors soon exhausted\",\n description = \"{{
$labels.job }} instance {{ $labels.instance }} will exhaust in file descriptors
soon\",\n }\n\n### etcd proposal alerts ###\n\n# alert if there are several failed
proposals within an hour\nALERT HighNumberOfFailedProposals\n IF increase(etcd_server_proposal_failed_total{job=\"etcd\"}[1h])
> 5\n LABELS {\n severity = \"warning\"\n }\n ANNOTATIONS {\n summary
= \"a high number of failed proposals within the etcd cluster are happening\",\n
\ description = \"etcd instance {{ $labels.instance }} has seen {{ $value }}
proposal failures within the last hour\",\n }\n\n### etcd disk io latency alerts
###\n\n# alert if 99th percentile of fsync durations is higher than 500ms\nALERT
HighFsyncDurations\n IF histogram_quantile(0.99, rate(etcd_wal_fsync_durations_seconds_bucket[5m]))
> 0.5\n FOR 10m\n LABELS {\n severity = \"warning\"\n }\n ANNOTATIONS {\n
\ summary = \"high fsync durations\",\n description = \"ectd instance {{
$labels.instance }} fync durations are high\",\n }\n"
kubernetes.rules: |+
# NOTE: These rules were kindly contributed by the SoundCloud engineering team.
### Container resources ###
cluster_namespace_controller_pod_container:spec_memory_limit_bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_spec_memory_limit_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:spec_cpu_shares =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_spec_cpu_shares{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:cpu_usage:rate =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
irate(
container_cpu_usage_seconds_total{container_name!=""}[5m]
),
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_usage:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_usage_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_working_set:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_working_set_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_rss:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_rss{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_cache:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_memory_cache{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:disk_usage:bytes =
sum by (cluster,namespace,controller,pod_name,container_name) (
label_replace(
container_disk_usage_bytes{container_name!=""},
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_pagefaults:rate =
sum by (cluster,namespace,controller,pod_name,container_name,scope,type) (
label_replace(
irate(
container_memory_failures_total{container_name!=""}[5m]
),
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
cluster_namespace_controller_pod_container:memory_oom:rate =
sum by (cluster,namespace,controller,pod_name,container_name,scope,type) (
label_replace(
irate(
container_memory_failcnt{container_name!=""}[5m]
),
"controller", "$1",
"pod_name", "^(.*)-[a-z0-9]+"
)
)
### Cluster resources ###
cluster:memory_allocation:percent =
100 * sum by (cluster) (
container_spec_memory_limit_bytes{pod_name!=""}
) / sum by (cluster) (
machine_memory_bytes
)
cluster:memory_used:percent =
100 * sum by (cluster) (
container_memory_usage_bytes{pod_name!=""}
) / sum by (cluster) (
machine_memory_bytes
)
cluster:cpu_allocation:percent =
100 * sum by (cluster) (
container_spec_cpu_shares{pod_name!=""}
) / sum by (cluster) (
container_spec_cpu_shares{id="/"} * on(cluster,instance) machine_cpu_cores
)
cluster:node_cpu_use:percent =
100 * sum by (cluster) (
rate(node_cpu{mode!="idle"}[5m])
) / sum by (cluster) (
machine_cpu_cores
)
### API latency ###
# Raw metrics are in microseconds. Convert to seconds.
cluster_resource_verb:apiserver_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(
0.99,
sum by(le,cluster,job,resource,verb) (apiserver_request_latencies_bucket)
) / 1e6
cluster_resource_verb:apiserver_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(
0.9,
sum by(le,cluster,job,resource,verb) (apiserver_request_latencies_bucket)
) / 1e6
cluster_resource_verb:apiserver_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(
0.5,
sum by(le,cluster,job,resource,verb) (apiserver_request_latencies_bucket)
) / 1e6
### Scheduling latency ###
cluster:scheduler_e2e_scheduling_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(0.99,sum by (le,cluster) (scheduler_e2e_scheduling_latency_microseconds_bucket)) / 1e6
cluster:scheduler_e2e_scheduling_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(0.9,sum by (le,cluster) (scheduler_e2e_scheduling_latency_microseconds_bucket)) / 1e6
cluster:scheduler_e2e_scheduling_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(0.5,sum by (le,cluster) (scheduler_e2e_scheduling_latency_microseconds_bucket)) / 1e6
cluster:scheduler_scheduling_algorithm_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(0.99,sum by (le,cluster) (scheduler_scheduling_algorithm_latency_microseconds_bucket)) / 1e6
cluster:scheduler_scheduling_algorithm_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(0.9,sum by (le,cluster) (scheduler_scheduling_algorithm_latency_microseconds_bucket)) / 1e6
cluster:scheduler_scheduling_algorithm_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(0.5,sum by (le,cluster) (scheduler_scheduling_algorithm_latency_microseconds_bucket)) / 1e6
cluster:scheduler_binding_latency:quantile_seconds{quantile="0.99"} =
histogram_quantile(0.99,sum by (le,cluster) (scheduler_binding_latency_microseconds_bucket)) / 1e6
cluster:scheduler_binding_latency:quantile_seconds{quantile="0.9"} =
histogram_quantile(0.9,sum by (le,cluster) (scheduler_binding_latency_microseconds_bucket)) / 1e6
cluster:scheduler_binding_latency:quantile_seconds{quantile="0.5"} =
histogram_quantile(0.5,sum by (le,cluster) (scheduler_binding_latency_microseconds_bucket)) / 1e6
ALERT K8SNodeDown
IF up{job="kubelet"} == 0
FOR 1h
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Kubelet cannot be scraped",
description = "Prometheus could not scrape a {{ $labels.job }} for more than one hour",
}
ALERT K8SNodeNotReady
IF kube_node_status_ready{condition="true"} == 0
FOR 1h
LABELS {
service = "k8s",
severity = "warning",
}
ANNOTATIONS {
summary = "Node status is NotReady",
description = "The Kubelet on {{ $labels.node }} has not checked in with the API, or has set itself to NotReady, for more than an hour",
}
ALERT K8SManyNodesNotReady
IF
count by (cluster) (kube_node_status_ready{condition="true"} == 0) > 1
AND
(
count by (cluster) (kube_node_status_ready{condition="true"} == 0)
/
count by (cluster) (kube_node_status_ready{condition="true"})
) > 0.2
FOR 1m
LABELS {
service = "k8s",
severity = "critical",
}
ANNOTATIONS {
summary = "Many K8s nodes are Not Ready",
description = "{{ $value }} K8s nodes (more than 10% of cluster {{ $labels.cluster }}) are in the NotReady state.",
}
ALERT K8SKubeletNodeExporterDown
IF up{job="node-exporter"} == 0
FOR 15m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Kubelet node_exporter cannot be scraped",
description = "Prometheus could not scrape a {{ $labels.job }} for more than one hour.",
}
ALERT K8SKubeletDown
IF absent(up{job="kubelet"}) or count by (cluster) (up{job="kubelet"} == 0) / count by (cluster) (up{job="kubelet"}) > 0.1
FOR 1h
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "Many Kubelets cannot be scraped",
description = "Prometheus failed to scrape more than 10% of kubelets, or all Kubelets have disappeared from service discovery.",
}
ALERT K8SApiserverDown
IF up{job="kubernetes"} == 0
FOR 15m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "API server unreachable",
description = "An API server could not be scraped.",
}
# Disable for non HA kubernetes setups.
ALERT K8SApiserverDown
IF absent({job="kubernetes"}) or (count by(cluster) (up{job="kubernetes"} == 1) < count by(cluster) (up{job="kubernetes"}))
FOR 5m
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "API server unreachable",
description = "Prometheus failed to scrape multiple API servers, or all API servers have disappeared from service discovery.",
}
ALERT K8SSchedulerDown
IF absent(up{job="kube-scheduler"}) or (count by(cluster) (up{job="kube-scheduler"} == 1) == 0)
FOR 5m
LABELS {
service = "k8s",
severity = "critical",
}
ANNOTATIONS {
summary = "Scheduler is down",
description = "There is no running K8S scheduler. New pods are not being assigned to nodes.",
}
ALERT K8SControllerManagerDown
IF absent(up{job="kube-controller-manager"}) or (count by(cluster) (up{job="kube-controller-manager"} == 1) == 0)
FOR 5m
LABELS {
service = "k8s",
severity = "critical",
}
ANNOTATIONS {
summary = "Controller manager is down",
description = "There is no running K8S controller manager. Deployments and replication controllers are not making progress.",
}
ALERT K8SConntrackTableFull
IF 100*node_nf_conntrack_entries / node_nf_conntrack_entries_limit > 50
FOR 10m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Number of tracked connections is near the limit",
description = "The nf_conntrack table is {{ $value }}% full.",
}
ALERT K8SConntrackTableFull
IF 100*node_nf_conntrack_entries / node_nf_conntrack_entries_limit > 90
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "Number of tracked connections is near the limit",
description = "The nf_conntrack table is {{ $value }}% full.",
}
# To catch the conntrack sysctl de-tuning when it happens
ALERT K8SConntrackTuningMissing
IF node_nf_conntrack_udp_timeout > 10
FOR 10m
LABELS {
service = "k8s",
severity = "warning",
}
ANNOTATIONS {
summary = "Node does not have the correct conntrack tunings",
description = "Nodes keep un-setting the correct tunings, investigate when it happens.",
}
ALERT K8STooManyOpenFiles
IF 100*process_open_fds{job=~"kubelet|kubernetes"} / process_max_fds > 50
FOR 10m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "{{ $labels.job }} has too many open file descriptors",
description = "{{ $labels.node }} is using {{ $value }}% of the available file/socket descriptors.",
}
ALERT K8STooManyOpenFiles
IF 100*process_open_fds{job=~"kubelet|kubernetes"} / process_max_fds > 80
FOR 10m
LABELS {
service = "k8s",
severity = "critical"
}
ANNOTATIONS {
summary = "{{ $labels.job }} has too many open file descriptors",
description = "{{ $labels.node }} is using {{ $value }}% of the available file/socket descriptors.",
}
# Some verbs excluded because they are expected to be long-lasting:
# WATCHLIST is long-poll, CONNECT is `kubectl exec`.
ALERT K8SApiServerLatency
IF histogram_quantile(
0.99,
sum without (instance,node,resource) (apiserver_request_latencies_bucket{verb!~"CONNECT|WATCHLIST|WATCH"})
) / 1e6 > 1.0
FOR 10m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Kubernetes apiserver latency is high",
description = "99th percentile Latency for {{ $labels.verb }} requests to the kube-apiserver is higher than 1s.",
}
ALERT K8SApiServerEtcdAccessLatency
IF etcd_request_latencies_summary{quantile="0.99"} / 1e6 > 1.0
FOR 15m
LABELS {
service = "k8s",
severity = "warning"
}
ANNOTATIONS {
summary = "Access to etcd is slow",
description = "99th percentile latency for apiserver to access etcd is higher than 1s.",
}
ALERT K8SKubeletTooManyPods
IF kubelet_running_pod_count > 100
LABELS {
service = "k8s",
severity = "warning",
}
ANNOTATIONS {
summary = "Kubelet is close to pod limit",
description = "Kubelet {{$labels.instance}} is running {{$value}} pods, close to the limit of 110",
}
kind: ConfigMap
metadata:
creationTimestamp: null
name: prometheus-k8s-rules

14
manifests/prometheus/prometheus-k8s-service.yaml Normal file
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@ -0,0 +1,14 @@
apiVersion: v1
kind: Service
metadata:
name: prometheus-k8s
spec:
type: NodePort
ports:
- name: web
nodePort: 30900
port: 9090
protocol: TCP
targetPort: web
selector:
prometheus: k8s

69
manifests/prometheus/prometheus-k8s-servicemonitors.yaml Normal file
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apiVersion: monitoring.coreos.com/v1alpha1
kind: ServiceMonitor
metadata:
name: kube-apiserver
labels:
k8s-apps: https
spec:
jobLabel: provider
selector:
matchLabels:
component: apiserver
provider: kubernetes
namespaceSelector:
matchNames:
- default
endpoints:
- port: https
interval: 15s
scheme: https
tlsConfig:
caFile: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
serverName: kubernetes
bearerTokenFile: /var/run/secrets/kubernetes.io/serviceaccount/token
---
apiVersion: monitoring.coreos.com/v1alpha1
kind: ServiceMonitor
metadata:
name: k8s-apps-https
labels:
k8s-apps: https
spec:
jobLabel: k8s-app
selector:
matchExpressions:
- {key: k8s-app, operator: Exists}
namespaceSelector:
matchNames:
- kube-system
endpoints:
- port: https-metrics
interval: 15s
scheme: https
tlsConfig:
caFile: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
insecureSkipVerify: true
bearerTokenFile: /var/run/secrets/kubernetes.io/serviceaccount/token
---
apiVersion: monitoring.coreos.com/v1alpha1
kind: ServiceMonitor
metadata:
name: k8s-apps-http
labels:
k8s-apps: http
spec:
jobLabel: k8s-app
selector:
matchExpressions:
- {key: k8s-app, operator: Exists}
namespaceSelector:
matchNames:
- kube-system
- monitoring
endpoints:
- port: http-metrics
interval: 15s
- port: http-metrics-dnsmasq
interval: 15s
- port: http-metrics-skydns
interval: 15s

24
manifests/prometheus/prometheus-k8s.yaml Normal file
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apiVersion: monitoring.coreos.com/v1alpha1
kind: Prometheus
metadata:
name: k8s
labels:
prometheus: k8s
spec:
replicas: 2
version: v1.5.2
serviceMonitorSelector:
matchExpression:
- {key: k8s-apps, operator: Exists}
resources:
requests:
# 2Gi is default, but won't schedule if you don't have a node with >2Gi
# memory. Modify based on your target and time-series count for
# production use. This value is mainly meant for demonstration/testing
# purposes.
memory: 400Mi
alerting:
alertmanagers:
- namespace: monitoring
name: alertmanager-main
port: web