Blog Posts
Livepeer Pipelines: Livestream AI
At Livepeer, we developed Livepeer Pipelines. Livepeer Pipelines does for livestreams what OpenArt Workflows has done for image generation. It takes ComfyUI Workflow and applies it in real-time to your...
Summary: Build Your Kubernetes Operator With the Right Tool
You have a lot of tools to choose from when you want to build a Kubernetes Operator for your software. Which is the right one for your use case? Operator...
Hazelcast Discovery Auto Detection
Hazelcast was always well integrated with all cloud environments thanks to discovery plugins like Hazelcast AWS Plugin or Hazelcast Kubernetes Plugin. With the IMDG 4.1 release, however, we went one...
Build Your Kubernetes Operator with the Right Tool
You want to build a Kubernetes Operator for your software. Which tool to choose from? Operator SDK with Helm, Ansible, or Go? Or maybe start from scratch with Python, Java,...
Caching with Spring Boot and Hazelcast
Spring Boot is very well integrated with Hazelcast. It’s enough to provide Hazelcast configuration on the classpath and it will be automatically used. In this blog post I’ll explain step-by-step...
Securing Hazelcast with Cert-Manager
Cert-Manager became a standard way for issuing and rotating certificates in Kubernetes and OpenShift environments. Simple to install. Simple to use. Well integrated with Vault and other secret managers. No...
How to Set Up Your Own On-Premises Hazelcast on Kubernetes
Hazelcast loves Kubernetes. Thanks to the dedicated Hazelcast Kubernetes plugin, you can use dynamic auto-discovery. Hazelcast on Kubernetes can also run in multiple topologies: embedded, client-server, or as a sidecar....
Helm 3: Top Five Improvements
Helm is a package manager for Kubernetes. One month ago the third major version was released and quite a few interesting changes took place. In this blog post, let me...
Hazelcast Resilient to Kubernetes Zone Failures
Data is valuable. Or I should write, some data is valuable. You may think that if the data is important to you, then you must store it in the persistent...
Where Is My Cache? Architectural Patterns for Caching Microservices
I’m sure you use caching somewhere in your system. This can be either to improve performance, reduce backend load, or to decrease downtime. Everybody uses caching. Caching is everywhere. However,...
Rolling Upgrade Hazelcast IMDG on Kubernetes
Hazelcast IMDG is tightly integrated into the Kubernetes ecosystem thanks to the Hazelcast Kubernetes plugin. In previous blog posts, we shared how to use auto-discovery for the embedded Hazelcast and...
Hazelcast Sidecar Container Pattern
The sidecar pattern is a technique of attaching an additional container to the main parent container so that both would share the same lifecycle and the same resources. You may...
How to Use Hazelcast Auto-Discovery with Eureka
Hazelcast IMDG supports auto-discovery for many different environments. Since we introduced the generic discovery SPI, a lot of plugins were developed so you can use Hazelcast seamlessly on Kubernetes, AWS,...
How to Use Embedded Hazelcast on Kubernetes
Hazelcast IMDG is a perfect fit for your (micro)services running on Kubernetes since it can be used in the embedded mode and therefore scale in and out together with your...
How to Set Up Hazelcast IMDG on AWS ECS
Amazon ECS (Elastic Container Service) is a container orchestration service that supports Docker containers. It allows to create scalable clusters backed up by EC2 Instances. Hazelcast IMDG is distributed in...
How to Scale Hazelcast IMDG on Kubernetes
Hazelcast IMDG is well integrated with the Kubernetes environment. Using Hazelcast Kubernetes Plugin, Hazelcast members can discover themselves automatically and be grouped by services to form separate clusters in one...
Hazelcast Helm Chart
Hazelcast was recently published in a form of Helm Chart. It means that now deploying a fully-functional Hazelcast cluster on Kubernetes is easier than ever.
AWS Auto Scaling with Hazelcast
In this blog post, I explain how to set up a Hazelcast cluster using AWS Auto Scaling mechanism. I also give a step-by-step example and justify why other, more trivial...
