We put together a collection of educational pages on how to run Kubernetes on AWS , focusing on best practices for configuration, installation options and management. Topics covered include: what Amazon services are required, the CNI interface and how pod networking is accomplished, defining ingress, how to use datastores with Kubernetes and how to meet the AWS IAM requirements.
This step by step tutorial shows how to set up Kubeflow, a tool that simplifies set up of a portable Machine Learning stack and Weave Cloud on the Google Cloud Platform. Kubeflow users will then be able to use Weave Cloud to observe and monitor the stack, including metrics for resource management.
Are your Kubernetes ReplicaSets slowing you down? With a quick little clean up, our CPU load went down by 10%! Here's a quick overview of how you can check how many you have running, set a revision limit and even request a rollback.
What a week we've had in Austin with fellow Kubernauts (4,000 to be exact!) for the annual KubeCon event. Thank you for stopping by our booth and chatting containers, microservices and Kubernetes with us. And don't miss our exciting announcement in collaboration with Google!
What a week we had last week with our partners and peers (43,000 to be exact!) in Vegas for the annual AWS re:invent. Thank you for stopping by our booth and chatting containers, microservices and Kubernetes with us! Of course one of the most exciting moments was the EKS announcement, a managed Kubernetes offering on AWS.
We've partnered with the Google team to create a simple set-up process that makes it easy to experience the power of Kubernetes (GKE) with Weave Cloud’s management capabilities. If you're exploring Kubernetes and want a completely integrated CI/CD pipeline with observability and monitoring then this gives you everything you need.
Sealed Secrets is a Kubernetes Custom Resource Definition Controller which allows you to store even sensitive information (aka secrets) in Git, which previously has not been an option. In addition, you can use Weave Cloud’s Deploy feature in conjunction with Sealed Secrets to create a continuous deployment pipeline where all operations are git based and where the desired state of your apps is declared in your git repos including your secrets.
Weaveworks, is proud to see Kubeadm become part of the Certified Kubernetes tools. Members of our Developer Experience team Ilya Dmitrichenko and Lucas Käldström are both core contributors of SIG-cluster-lifecycle. This particular SIG works on kubeadm, a tool for bootstrapping a best-practice Kubernetes cluster easily.
In this tutorial you will learn how to set-up OpenFaaS on Kubernetes with monitoring and alerting using Weave Cloud. Using OpenFaaS for serverless avoids being locked-in to one of the cloud vendors. It's easy to run in Kubernetes, letting you mix different services depending on your applications needs.
Weaveworks utilizes Kubernetes on AWS to achieve greater development velocity for a cloud native application to gain control and operational efficiencies. Read up on some of our best practices.
Hear from Weaveworks contractor Lucas Käldström on how far kubeadm has come, where it’s going, and how you can get involved.
Observability can be seen as part of the Continuous Delivery cycle for Kubernetes. Observed state must be compared with the desired state in Git. The role of a GitOps dashboard is to enable observation and speed up understanding and validation of the system, and suggest mitigating actions. Monitoring alone does not answer all questions: metrics are symptoms but not the disease.
Weave Cloud works alongside machine learning platforms such as Seldon’s. In this tutorial you will deploy a predictive service that recognizes drawn numbers from 0 to 9.
Step by step instructions on how you can achieve automated continuous delivery to a Kubernetes cluster using Weave Cloud Deploy. We will cover configuring automated builds, immutable container images, deploying new container images and automating deployments.
GitOps relies on your whole system to be expressed declaratively. The GitOps pipeline model places Git at the design centre - everything upstream of deployment is anchored by Git. As a result a developer can update some code in GitHub and release into production as a pull request.