Comments (6)
The microservice_available_and_healthy
action is probably something to be mindful of. It's our first action and it tried to be clever by assuming a microservice was a clearly defined thing. Today, the approach tend to be to consider your pods/deployments as their own thing and consider what you can learn at that level.
You can learn from anywhere, in your case, because your services aren't directly visible to the internet, maybe they still have an impact in the overall workflow your user is following? Maybe at a higher level?
For instance, assume I'm killing a cache server, I'm not going to learn if the cache is up or not? But I am interested in understand the increased latency for my users when they connect to the application.
Try to locate the level at which you are interested in learning something new and look there, even if you impact something deeper and lower level.
does this make sense?
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I guess so. But as these services are used as internal endpoints to be consumed by a service in the same cluster, it might be a good idea to know about the status of the endpoints even if the pods are down.
from chaostoolkit-kubernetes.
You could run the experiment from the cluster itself (run chaostoolkit as a pod/job?)
from chaostoolkit-kubernetes.
Yes, I will try the alternative. Thanks!
from chaostoolkit-kubernetes.
No pb. Another solution, use a probe to query your monitoring solution for deleted pods?
from chaostoolkit-kubernetes.
yes, that seems easy :)
from chaostoolkit-kubernetes.
Related Issues (20)
- Failed to discover chaostoolkit-kubernetes HOT 1
- `service_is_initialized` should use field_selector when name is provided
- delete_deployment uses an incorrect label_selector due to variable and arg being the same name
- Bug in chaosk8s.statefulset.probes.statefulset_fully_available: V1StatefulSetStatus' object has no attribute 'unavailable_replicas' HOT 2
- Using two different source of truth to filter pods HOT 4
- deny_all_ingress not working HOT 1
- SSL Error - CERTIFICATE_VERIFY_FAILED HOT 3
- Merge terminate_pods and delete_pods to avoid confusion and unnecessary code bloat HOT 1
- Kubernetes delete_pod action is not working HOT 1
- exec_in_pods cannot use space in the command itself HOT 3
- Receiving msg: ConnectionRefusedError: [Errno 111] Connection refused HOT 2
- exec_in_pods fails to parse stderr as json HOT 1
- There is a cmd splitting issue, therefore the shell commands will not parse correctly
- [error] deny-all-ingress is not working
- terminate_pod is not working for OpenShift HOT 4
- exec_in_pods function can not handle pipe operator
- How to get the value for tolerance for all_pods_healthy Steady State Hypothesis probe ? HOT 2
- Link to the documentation in the README is broken HOT 2
- Using Kubernetes extension for Chaos Toolkit as a Kubernetes Operator
- chaostoolkit-kubernetes: Stress memory calls a stress cpu HOT 3
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