Sylvain Hellegouarch (ChaosIQ) demonstrates how to implement an accelerated learning and system-improvement loop. With ChaosIQ , built on top of the open source Chaos Toolkit, controlled and careful Chaos Engineering experiments were executed against a system running in Kubernetes and then observed, diagnosed and rolled out with Weave Cloud to make improvements based on the surfaced weaknesses.
Part 4 of the GitOps blog series explains how you can make your continuous delivery pipeline more secure using 3 best practices which enables auditing and compliance. This is aimed at Kubernetes users who have adopted Continuous Integration (CI) and who want to add Continuous Deployment (CD) to their pipeline.
While Helm helps with getting applications running, you need other tooling to keep them up to date when something changes. Check out our alpha release of our Helm integration in Weave Flux. It makes sure your Helm chart releases are kept up to date with what’s in Git. You can try it out using the published repository in Github.
Weave Cloud Deploy is a Continuous Deployment/Delivery operator for Kubernetes which makes it super easy to automate releases to a cluster - but what about multiple clusters? Weave Cloud Deploy can filter tags - by tagging each image with an environment specific prefix, it’s possible for the same image build to be automatically released to each environment in turn.
See how Qordoba doubled their productivity by using Weave Cloud for Continuous Delivery to deploy machine learning models to Kubernetes.
Discover how to achieve an automated continuous delivery with Kubernetes, Google Cloud Platform and Weave Cloud multiple time a day. Discover the role, observability and metric monitoring play for determining whether you’re progressing once you’ve increased your speed of deployment.
This blog post explains techniques for development teams who strive for high velocity continuous delivery using Kubernetes and Docker. When we say “high velocity” we mean that every product team can safely ship updates many times a day — deploy instantly, observe the results in real time, and use this feedback to roll forward or back. The goal is for product teams to use continuous experimentation to improve the customer experience as fast as possible.
A “you build it, you own it” development process requires tools that developers know and understand. “GitOps” is our name for how we describe modern best practices for high velocity application development with cloud native tools. Read this summary post about the GitOps pipeline model, why its beneficial to adopt this methodology and how to get started.
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.
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.
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.
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.
Alexis Richardson is defining “GitOps” as a methodology for developer tooling to drive operations. This post discussed the use of declarative tools and best practices of configurations being code and therefore should be versions controlled.
Continuous delivery vs. continuous integration vs. continuous deployment. Do you know what the differences are? Our blog clears it up for you.