Metrics-server Alternatives

metrics-server reviews and mentions

• 26 Top Kubernetes Tools
  18 projects | dev.to | 12 Jun 2024

  Metrics Server is a Kubernetes addon that collects CPU and memory resource utilization information at the Node and Pod level. It's a lightweight, single-cluster, Kubernetes-only alternative to more complex monitoring solutions like Prometheus.

• Lowest Price for your own kubernetes using Hetzner Cloud(incl. Storage Provisioner)
  4 projects | dev.to | 12 May 2024

  (kubespray-venv) kube-master1:~# curl -LO https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml nano components.yaml

• Upgrading Hundreds of Kubernetes Clusters
  17 projects | dev.to | 3 Apr 2024

  The last one is mostly an observability stack with Prometheus, Metric server, and Prometheus adapter to have excellent insights into what is happening on the cluster. You can reuse the same stack for autoscaling by repurposing all the data collected for monitoring.

• Deploy Secure Spring Boot Microservices on Amazon EKS Using Terraform and Kubernetes
  13 projects | dev.to | 23 Nov 2023

  and the Metrics Server.

• ☸️ Managed Kubernetes : Our dev is on AWS, our prod is on OVH
  6 projects | dev.to | 1 Jul 2023

  Metrics-server is installed by default on OVH, and has to be installed manually on AWS/EKS cluster.

• Kubernetes HPA on AKS is failing with error 'missing request for cpu'
  1 project | /r/codehunter | 8 Jun 2023

  I have also installed metrics-server (though not sure whether that was required or not) using the following statement:kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.6/components.yaml

• Factors affecting performance of job running in a pod
  1 project | /r/kubernetes | 5 Jun 2023

  For #2: There are MANY solutions but the simplest and easiest is https://github.com/kubernetes-sigs/metrics-server and then you can use kubectl top to view pods resource usage. If you want fancy graphs, long retention, alerting, analysis, etc. of resource metrics.. then you need to use something like new relic, data dog, or something open source but much more complex like prometheus/thanos/grafana.. or a managed SaaS version of those open source tools... also some k8s platforms like AWS, Spot.io, GKE, OpenShift, may have this stuff built in or turnkey

• Autoscaling Ingress controllers in Kubernetes
  4 projects | dev.to | 17 Apr 2023

  It's an autoscaler with a metrics server (so I don't need to install 2 different tools).

• Checking the Capability of ChatGPT for DevOps Automation Solution Design
  1 project | dev.to | 9 Apr 2023

  Sure, here's an example of how to configure the Kubernetes Metrics Server along with the Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) configurations we provided earlier. The Metrics Server is a Kubernetes add-on that provides resource utilization metrics for pods and nodes, which are used by the HPA and VPA to determine when and how to scale an application. First, you'll need to install the Metrics Server into your Kubernetes cluster. You can do this by running the following command: kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml Once the Metrics Server is installed, you can configure your HPA and VPA to use it for metrics by adding the following annotation to your deployment: apiVersion: apps/v1 kind: Deployment metadata: name: my-app annotations: autoscaling.alpha.kubernetes.io/metrics-provider: "metrics-server" With this annotation in place, the HPA and VPA will use the Metrics Server to obtain CPU and memory utilization metrics for your pods and nodes. Here's an updated example of the HPA configuration we provided earlier, with the addition of the Metrics Server configuration: apiVersion: autoscaling/v2beta2 kind: HorizontalPodAutoscaler metadata: name: my-app-hpa spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: my-app minReplicas: 1 maxReplicas: 10 metrics: - type: Resource resource: name: cpu targetAverageUtilization: 50 - type: Resource resource: name: memory targetAverageUtilization: 80 In this example, we've added a second metric to the HPA configuration that targets memory utilization at 80%. Here's an updated example of the VPA configuration we provided earlier, with the addition of the Metrics Server configuration: apiVersion: autoscaling.k8s.io/v1 kind: VerticalPodAutoscaler metadata: name: my-app-vpa spec: targetRef: apiVersion: apps/v1 kind: Deployment name: my-app updatePolicy: updateMode: "Off" resourcePolicy: containerPolicies: - containerName: "*" minAllowed: cpu: 50m memory: 256Mi maxAllowed: cpu: 500m memory: 1Gi metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 50 - type: Resource resource: name: memory target: type: Utilization averageUtilization: 80 In this example, we've added two metrics to the VPA configuration that target CPU and memory utilization, with target average utilization of 50% and 80% respectively. I hope this helps you configure the Metrics Server, HPA, and VPA for your application in Kubernetes!

• plz help
  1 project | /r/kubernetes | 26 Feb 2023

  Id go for k3s then install metrics-server, then you can deploy some hpa’s

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