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 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.
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 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.
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.
Canonical's conjure-up makes it easy to deploy and operate Kubernetes in production, using a neat, easy-to-use CLI installer. Weave Cloud fills in the gaps missing with a Kubernetes install and provides the tools necessary for a full development lifecycle.
This tutorial shows you how to deploy and manage Kubernetes with Rancher. You will then use Weave Cloud to complete the development lifecycle, and Deploy, Explore and Monitor your app as it runs in Kubernetes.
The Weave Online User Group talk given by Carter Morgan defines of what a "production-ready" cloud application looks like.
The world has been patiently waiting for the launch of Stringly™, a platform for distributing highly optimized strings that is sure to disrupt the global string market. The VC checks have cleared and its time to give the people what they...
Tom Wilkie shares Weaveworks monitoring philosophy and the three most important metrics to use in your microservices architecture.
Prometheus comes with its own query language called PromQL. It’s very powerful and easily allows you to filter with the multi-dimensional time-series labels that make Prometheus so great. But it can be daunting when you are faced with an...