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.
See how Qordoba doubled their productivity by using Weave Cloud for Continuous Delivery to deploy machine learning models to Kubernetes.
Watch this short architecture overview video to learn how Weaveworks monitors clusters at scale using a highly available, multi-tenant system built on AWS services.
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.
This post shows step by step how to set up a multi-cloud environment for big data processing using Apache Flink, Docker Swarm and the new Weave Net Docker plugin.
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.
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.
This practical guide will help you getting started with monitoring your microservices with Prometheus. We walk through selecting key metrics, instrumentation, setting up alerts and Grafana dashboards.
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.
In this post we will be discussing how to set up application and infrastructure monitoring for Docker Swarm with the help of Prometheus. Swarmprom is a starter kit for Docker Swarm monitoring with Prometheus, Grafana, cAdvisor, Node Exporter, Alert Manager, and Unsee.
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.