istio VS keda

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.

It seems you want something like KEDA (https://keda.sh)

Most just utilize out of the box macro resources available in HPA.

For more advanced use cases there is keda - https://keda.sh/

Thankfully KEDA operator was already part of the cluster, and all Robin had to do was create a ScaledObject manifest targeting the Dispatch ScaleUp event, based on the rabbitmq_global_messages_received_total metric from Prometheus.

Keda

KEDA introduces event-driven scaling to Kubernetes workloads. It integrates with Kubernetes Horizontal Pod Autoscalers and can scale pods based on external metrics from services like databases and message queues (Kafka, RabbitMQ, MongoDB).

# update version 2.8.2 if required kubectl apply -f https://github.com/kedacore/keda/releases/download/v2.8.2/keda-2.8.2.yaml

This is traditionally a AWS Lambda usecase - or an OpenFaas kind of usecase. But very recently i discovered https://keda.sh/ and it seems it is specifically meant for this in a kubernetes environment.

If you deploy the application to Amazon EKS, you can also consider using KEDA to auto-scale your consumer application based on the number of messages in the MSK topic.