kube-monkey
kube-state-metrics
kube-monkey | kube-state-metrics | |
---|---|---|
9 | 33 | |
2,920 | 5,102 | |
- | 1.2% | |
3.4 | 9.1 | |
13 days ago | 7 days ago | |
Go | Go | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kube-monkey
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Does your company have a Change Advisory Board (CAB)?
Not in the typical sense, but we have plenty of standard practices and cross-team checkpoints to limit risk. By the time we're deploying changes to production, the work has had a card created, assigned points (which necessarily involves discussing scope and risk), architected (as a group), code peer reviewed, hit unit tests (automated), integration tests (automated), functional tests (automated), smoke tested (automated) end-to-end tests (a few automated, but mostly manual by QA), acceptance tested (by QA and business), resilience tests (chaos engineering with kube-monkey), been deployed to at least 3 environments (with the same exact same artifacts, just with config changes), and monitored for failures (pod restarts, log anomalies, etc -- all automated). Deploy to production is well communicated, and ANY team can request a halt to the deploy if they have concerns.
- Kube-monkey: an implementation of Netflix's Chaos Monkey for Kubernetes clusters
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What happens when a service fails in your infra, or in other words, do you practice chaos engineering?
Part of being a cloud native company means designing services for failure. What happens, for example, if the payment service/pod goes down? Do the rest of your services continue operating normally? One thing tools like kube-monkey does is automatically kill pods for you on a certain date at a certain time in order to plan for failure events. Just wondering if anyone has dove into the deep end with this type of tooling and really just gone all out, besides Netflix?
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Chaos Mesh for chaos engineering in Kubernetes
Chaos Mesh is a popular solution (about 5k GitHub stars), but — obviously — not the only one. E.g., Litmus is a powerful platform to test many things, and kube-monkey might be a good option for more basic stuff.
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How many of you actually test your infrastructure code? For those that do, what benefits did you discover that testing brings to your code base?
Exactly the kind of thing I love to see! Sounds like a great use case for a tool like kube-monkey as well.
- GitHub - asobti/kube-monkey: An implementation of Netflix's Chaos Monkey for Kubernetes clusters
- kube-monkey: An implementation of Netflix's Chaos Monkey for Kubernetes clusters
- 27 open-source tools that can make your Kubernetes workflow easier 🚀🥳
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Awesome Kubernetes Resources
Kube Monkey
kube-state-metrics
- Do we have any Prometheus metric to get the kubernetes cluster-level CPU/Memory requests/limits?
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10 Kubernetes Visualization Tool that You Can't Afford to Miss
git clone https://github.com/kubernetes/kube-state-metrics.git
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Why is the Prometheus metric 'kube_pod_completion_time' returning empty query results?
https://github.com/kubernetes/kube-state-metrics/blob/main/docs/pod-metrics.md According to this github repo completion is responsible of termination date if I correctly understood .
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Google Kubernetes Engine's metrics vs Self-managed
kube-state-metrics
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Prometheus node exporter and cadvisor to send metrics to central prometheus cluster
Those are entirely different types of data. You can get that from something like kube-state-metrics
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Scaling kube-state-metrics in large cluster
I've never had a cluster of that size, so take it with a grain of salt - but maybe you could try purpose-based sharding? KSM has allowlist and denylist config flags, for configuring which metrics it exposes https://github.com/kubernetes/kube-state-metrics/blob/main/docs/cli-arguments.md
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Questions about Kubernetes
Kubernetes itself will not notify you, the way I've seen people do this, is to use something like kube-state-metrics or node_exporter, export that to Prometheus (or preferrably VictoriaMetrics because Prometheus is terrible IMO), and then setup alarms on that with alertmanager or equivalent, or just look at dashboards regularly with Grafana. Realistically I recommend only setting alerts on disk usage and application/database latency. CPU and memory utilization isn't a great metric to alert on a lot of the time.
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EKS scalability best practices
Another tip that you could consider spelling out a little more, is to monitor the number of resources created by Kind. This is somewhat mentioned for jobs and services, but any Kind of which thousands of resources are created will put stress on the control-plane. The total number of resources per namespace/cluster can be monitored with kube-state-metrics. KSM does not emit metrics of resources created from CRDs. These metrics can be implemented with KSM's custom resource state metrics: https://github.com/kubernetes/kube-state-metrics/blob/main/docs/customresourcestate-metrics.md
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Observability-Landscape-as-Code in Practice
We then have various other Metrics called Kubernetes Workload Metrics. These are the dashboards with names that start with “Kubernetes / Compute Resources / Workload”. These dashboards are specific to the services you are running. They take into account the Kubernetes Workloads in your various namespaces, using kube-state-metrics. For a closer look, check out otel_demo_app_k8s_dashboard.tf.
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Kubernetes Costs: Effective Cost Optimization Strategies To Reduce Your k8s Bill
The first step to optimizing costs is gaining visibility into your costs using tools. Kubernetes provides a Metrics Server and kube-state-metrics that can give you the overall picture of resource utilization by your cluster. There are more tools that provide more granular breakdowns and provide dashboards with business metrics, infra cost, and alerting functionalities. Here are some strategies to optimize your resource utilization and cloud bills on k8s.
What are some alternatives?
chaoskube - chaoskube periodically kills random pods in your Kubernetes cluster.
cadvisor - Analyzes resource usage and performance characteristics of running containers.
istio - Connect, secure, control, and observe services.
metrics-server - Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
kube-bench - Checks whether Kubernetes is deployed according to security best practices as defined in the CIS Kubernetes Benchmark
php-fpm_exporter - A prometheus exporter for PHP-FPM.
skaffold - Easy and Repeatable Kubernetes Development
k3s - Lightweight Kubernetes
kube-burner - Kubernetes performance and scale test orchestration framework written in golang
kubespray - Deploy a Production Ready Kubernetes Cluster
quay - Build, Store, and Distribute your Applications and Containers
kube-metrics-adapter - General purpose metrics adapter for Kubernetes HPA metrics