How to install Red Hat OpenShift Service Mesh alongside microservices in a Red Hat OpenShift on IBM Cloud cluster.
This blog post is an excerpt from a recently published solution tutorial. Following the instructions in the tutorial, you will learn how to install the Red Hat OpenShift Service Mesh operator (along with other additional operators), configure an Istio ingress-gateway to expose a service outside of the service mesh, perform traffic management to set up important tasks like A/B testing and canary deployments, secure your microservice communication, and use metrics, logging, and tracing to observe services.
A service mesh is the network of microservices that make up applications in a distributed microservice architecture and the interactions between those microservices. When a service mesh grows in size and complexity, it can become harder to understand and manage.
Red Hat OpenShift Service Mesh provides a platform for behavioral insight and operational control over your networked microservices in a service mesh. With Red Hat OpenShift, you can connect, secure, and monitor microservices in your Red Hat OpenShift on IBM Cloud cluster.
Based on the open source Istio project, Red Hat OpenShift Service Mesh adds a transparent layer on existing distributed applications without requiring any changes to the service code. You add Red Hat OpenShift Service Mesh support to services by deploying a special sidecar proxy to relevant services in the mesh that intercepts all network communication between microservices. You configure and manage the Service Mesh using the control plane features.
Istio is an open platform to connect, secure, control and observe microservices-also known as a service mesh-on cloud platforms such as Kubernetes in OpenShift.
- Install Red Hat OpenShift Service Mesh in your cluster
- Deploy the BookInfo sample app
- Use metrics, logging, and tracing to observe services
- Set up the Istio Ingress Gateway
- Perform simple traffic management, such as A/B tests and canary deployments
- Secure your mesh using mTLS
Originally published at https://www.ibm.com on June 2, 2020.