Active-Monitor is a Kubernetes custom resource controller which enables deep cluster monitoring and self-healing using Argo workflows.
While it is not too difficult to know that all entities in a cluster are running individually, it is often quite challenging to know that they can all coordinate with each other as required for successful cluster operation (network connectivity, volume access, etc).
Active-Monitor will create a new health namespace when installed in the cluster. Users can then create and submit HealthCheck object to the Kubernetes server. A HealthCheck / Remedy is essentially an instrumented wrapper around an Argo workflow.
The HealthCheck workflow is run periodically, as defined by repeatAfterSec or a schedule: cron property in its spec, and watched by the Active-Monitor controller.
Active-Monitor sets the status of the HealthCheck CR to indicate whether the monitoring check succeeded or failed. If in case the monitoring check failed then the Remedy workflow will execute to fix the issue. Status of Remedy will be updated in the CR. External systems can query these CRs and take appropriate action if they failed.
RemedyRunsLimit parameter allows to configure how many times a remedy should be run. If Remedy action fails for any reason it will stop on further retries. It is an optional parameter. If it is not set Remedyworkflow is triggered whenever HealthCheck workflow fails.
RemedyResetInterval parameter allows resetting remedy after the reset interval time and RemedyWorkflow can be retried again in case monitor workflow fails. If remedy reaches a RemedyRunsLimit it will be reset when HealthCheck passes in any subsequent run before RemedyResetInterval.
Typical examples of such workflows include tests for basic Kubernetes object creation/deletion, tests for cluster-wide services such as policy engines checks, authentication and authorization checks, etc.
The sort of HealthChecks one could run with Active-Monitor are:
- verify namespace and deployment creation
- verify AWS resources are using < 80% of their instance limits
- verify kube-dns by running DNS lookups on the network
- verify kube-dns by running DNS lookups on localhost
- verify KIAM agent by running aws sts get-caller-identity on all available nodes
- verify if pod max threads has reached
- verify if storage volume for a pod (e.g: prometheus) has reached its capacity.
- verify if critical pods e.g: calico, kube-dns/core-dns pods are in a failed or crashloopbackoff state
With the Cluster/Namespace level, healthchecks can be run in any namespace provided namespace is already created.
The level in the HealthCheck spec defines at which level it runs; it can be either Namespace or Cluster.
When level is set to Namespace, Active-Monitor will create a ServiceAccount in the namespace as defined in the workflow spec, it will also create the Role and RoleBinding with namespace level permissions so that the HealthChecks in a namespace can be performed.
When the level is set to be Cluster the Active-Monitor will create a ServiceAccount in the namespace as defined in the workflow spec, it will also create the ClusterRole and ClusterRoleBinding with cluster level permissions so that the HealthChecks in a cluster scope can be performed.
- Go Language tools
- Kubernetes command line tool (kubectl)
- Access to Kubernetes Cluster as specified in
~/.kube/config- Easiest option is to install minikube and ensure that
kubectl versionreturns client and server info
- Easiest option is to install minikube and ensure that
- Argo Workflows Controller
# step 0: ensure that all dependencies listed above are installed or present
# step 1: install argo workflow controller
kubectl apply -f https://raw.githubusercontent.com/keikoproj/active-monitor/master/deploy/deploy-argo.yaml
# step 2: install active-monitor CRD and start controller
kubectl apply -f https://raw.githubusercontent.com/keikoproj/active-monitor/master/config/crd/bases/activemonitor.keikoproj.io_healthchecks.yaml
kubectl apply -f https://raw.githubusercontent.com/keikoproj/active-monitor/master/deploy/deploy-active-monitor.yaml
# step 0: ensure that all dependencies listed above are installed or present
# step 1: install argo workflow-controller
kubectl apply -f deploy/deploy-argo.yaml
# step 2: install active-monitor controller
make install
kubectl apply -f deploy/deploy-active-monitor.yaml
# step 3: run the controller via Makefile target
make run
Create a new healthcheck:
Create a new healthcheck with cluster level bindings to specified serviceaccount and in health namespace:
kubectl create -f https://raw.githubusercontent.com/keikoproj/active-monitor/master/examples/inlineHello.yaml
OR with local source code:
kubectl create -f examples/inlineHello.yaml
Then, list all healthchecks:
kubectl get healthcheck -n health OR kubectl get hc -n health
NAME LATEST STATUS SUCCESS CNT FAIL CNT AGE
inline-hello-7nmzk Succeeded 7 0 7m53s
View additional details/status of a healthcheck:
kubectl describe healthcheck inline-hello-zz5vm -n health
...
Status:
Failed Count: 0
Finished At: 2019-08-09T22:50:57Z
Last Successful Workflow: inline-hello-4mwxf
Status: Succeeded
Success Count: 13
Events: <none>
Create a new healthcheck with namespace level bindings to specified serviceaccount and in a specified namespace:
kubectl create ns test
kubectl create -f https://raw.githubusercontent.com/keikoproj/active-monitor/master/examples/inlineHello_ns.yaml
OR with local source code:
kubectl create -f examples/inlineHello_ns.yaml
Then, list all healthchecks:
kubectl get healthcheck -n test OR kubectl get hc -n test
NAME LATEST STATUS SUCCESS CNT FAIL CNT AGE
inline-hello-zz5vm Succeeded 7 0 7m53s
View additional details/status of a healthcheck:
kubectl describe healthcheck inline-hello-zz5vm -n test
...
Status:
Failed Count: 0
Finished At: 2019-08-09T22:50:57Z
Last Successful Workflow: inline-hello-4mwxf
Status: Succeeded
Success Count: 13
Events: <none>
argo list -n test
NAME STATUS AGE DURATION PRIORITY
inline-hello-88rh2 Succeeded 29s 7s 0
inline-hello-xpsf5 Succeeded 1m 8s 0
inline-hello-z8llk Succeeded 2m 7s 0
activemonitor.keikoproj.io/v1alpha1/HealthCheckargoproj.io/v1alpha1/Workflow
apiVersion: activemonitor.keikoproj.io/v1alpha1
kind: HealthCheck
metadata:
generateName: dns-healthcheck-
namespace: health
spec:
repeatAfterSec: 60
description: "Monitor pod dns connections"
workflow:
generateName: dns-workflow-
resource:
namespace: health
serviceAccount: activemonitor-controller-sa
source:
inline: |
apiVersion: argoproj.io/v1alpha1
kind: Workflow
spec:
ttlSecondsAfterFinished: 60
entrypoint: start
templates:
- name: start
retryStrategy:
limit: 3
container:
image: tutum/dnsutils
command: [sh, -c]
args: ["nslookup www.google.com"]apiVersion: activemonitor.keikoproj.io/v1alpha1
kind: HealthCheck
metadata:
generateName: fail-healthcheck-
namespace: health
spec:
repeatAfterSec: 60 # duration in seconds
level: cluster
workflow:
generateName: fail-workflow-
resource:
namespace: health # workflow will be submitted in this ns
serviceAccount: activemonitor-healthcheck-sa # workflow will be submitted using this
source:
inline: |
apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
labels:
workflows.argoproj.io/controller-instanceid: activemonitor-workflows
spec:
ttlSecondsAfterFinished: 60
entrypoint: start
templates:
- name: start
retryStrategy:
limit: 1
container:
image: ravihari/ctrmemory:v2
command: ["python"]
args: ["promanalysis.py", "http://prometheus.system.svc.cluster.local:9090", "health", "memory-demo", "memory-demo-ctr", "95"]
remedyworkflow:
generateName: remedy-test-
resource:
namespace: health # workflow will be submitted in this ns
serviceAccount: activemonitor-remedy-sa # workflow will be submitted using this acct
source:
inline: |
apiVersion: argoproj.io/v1alpha1
kind: Workflow
spec:
ttlSecondsAfterFinished: 60
entrypoint: kubectl
templates:
-
container:
args: ["kubectl delete po/memory-demo"]
command: ["/bin/bash", "-c"]
image: "ravihari/kubectl:v1"
name: kubectl
kubectl -n health port-forward deployment/argo-ui 8001:8001
Then visit: http://127.0.0.1:8001
Active-Monitor controller also exports metrics in Prometheus format which can be further used for notifications and alerting.
Prometheus metrics are available on :8080/metrics
kubectl -n health port-forward deployment/activemonitor-controller 8080:8080
Then visit: http://localhost:8080/metrics
Active-Monitor, by default, exports following Promethus metrics:
healthcheck_success_count- The total number of successful healthcheck resourceshealthcheck_error_count- The total number of erred healthcheck resourceshealthcheck_runtime_seconds- Time taken for the healthcheck's workflow to complete
Active-Monitor also supports custom metrics. For this to work, your workflow should export a global parameter. The parameter will be programmatically available in the completed workflow object under: workflow.status.outputs.parameters.
The global output parameters should look like below:
"{\"metrics\":
[
{\"name\": \"custom_total\", \"value\": 123, \"metrictype\": \"gauge\", \"help\": \"custom total\"},
{\"name\": \"custom_metric\", \"value\": 12.3, \"metrictype\": \"gauge\", \"help\": \"custom metric\"}
]
}"
Please see CONTRIBUTING.md.
To add a new example of a healthcheck and/or workflow:
- Healthcheck: place it in
./examples - Workflow: place it in
./examples/workflows
Please see RELEASE.
The Apache 2 license is used in this project. Details can be found in the LICENSE file.
Instance Manager - Kube Forensics - Addon Manager - Upgrade Manager - Minion Manager - Governor