chaos-mesh VS istio

Ive been messing around with chaos mesh recently (https://chaos-mesh.org/) and im wondering: is there any way i can define custom behaviour in one of my experiments? Specifically, I want to deploy a Pod with a certain image using an experiment.

Litmus, Gremlin, Chaos Mesh, and Chaos Monkey are all popular open-source tools used for chaos engineering. As we will be using AWS cloud infrastructure, we will also explore AWS Fault Injection Simulator (FIS). While they share the same goals of testing and improving the resilience of a system, there are some differences between them. Here are some comparisons:

https://chaos-mesh.org/ (open source)

Implement Chaos Mesh and Litmus chaos engineering framework to understand the behavior and stability of application in real-world use cases.

Here is our recent experience with Chaos Mesh for performing basic chaos engineering experiments on an application in Kubernetes.

In March 2018, an article titled Service Mesh is the broad trend, what about Database Mesh?, was pubslished on InfoQ China and went viral in the technical community. In this article, Zhang Liang, the founder of Apache ShardingSphere, described Database Mesh concept along with the idea of Service Mesh. Four years later, the Database Mesh concept has been integrated by several companies together with their own tools and ecosystems. Today, in addition to Service Mesh, a variety of “X Mesh” concepts such as ChaosMesh, EventMesh, IOMesh have emerged. Following four years of development, Database Mesh has also started a new chapter: Database Mesh 2.0.

🐒 Chaos Mesh will turn 2 on 2021.12.31! We're grateful for every contribution that helped this project grow, and we’d like to hear your Chaos Mesh story!

So i came across this recently, haven't used it myself but it seems to fit your requirements: https://github.com/chaos-mesh/chaos-mesh

Istio is a popular open-source service mesh framework that provides a comprehensive solution for managing, securing, and observing microservices-based applications running on Kubernetes.

Leverage a service mesh like Istio or Linkerd to manage communication between microservices within the Kubernetes cluster. These service meshes can be configured to intercept JMX traffic and enforce access control policies. Benefits:

Open Source and Cloud Computing: A Match Made in Heaven The cloud is accelerating OSS adoption. Cloud-native technologies like Kubernetes [https://kubernetes.io/] and Istio [https://istio.io/], both open-source projects, are revolutionizing how applications are built and deployed across cloud platforms.

Consider the case of Bookinfo, a sample application provided by Istio, rewritten using CloudWeGo's Kitex for superior performance and extensibility.

It is a dedicated infrastructure layer that manages service-to-service communication, providing features like load balancing, encryption, authentication, and monitoring. Istio deploys sidecar proxies alongside each microservice instance. These proxies handle communication, providing features like load balancing, service discovery, encryption, monitoring and authentication.

5Y old post that sounds like they've done similar here: Caddy Issue Istio Issue but doesn't cover much of the implementation

In a production environment there will be a load balancer setup with an Ingress Controller, Service Mesh or some type of Custom Router. This allows all traffic to be sent to the single load balancer IP address and then route the traffic to a service based on the Domain name or subpath. We are using a NGINX ingress controller but service meshes like Istio have been becoming the most popular solution to use as they offer more segmentation, security and granular control.

Flagger is a progressive delivery tool that enables a Kubernetes operator to automate the promotion or rollback of deployments based on metrics analysis. It supports a variety of metrics including Prometheus, Datadog, and New Relic to name a few. It also works well with Istio service mesh, and can implement progressive traffic splitting between primary and canary releases.

End-to-end data encryption with a service mesh: Using an end-to-end data encryption mechanism with a service mesh like Istio, TLS can secure communication between different microservices within a Kubernetes cluster. This is a popular approach for modern, distributed microservice architectures.