istio VS thanos

AWS EKS provides a managed Kubernetes service, simplifying cluster management and deployment. Istio, an open-source service mesh, enables traffic management, security, and observability across microservices.

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.

Monitoring = netdata on each RPi https://www.netdata.cloud/ binded to the vpn interface being scraped into a prometeus thaons https://thanos.io/ setup with grafana to give management the Green all is good screens (very important).

Sounds like you want something like Thanos

Yes, but also no. The Prometheus ecosystem already has two FOSS time-series databases that are complementary to Prometheus itself. Thanos and Mimir. Not to mention M3db, developed at Uber, and Cortex, then ancestor of Mimir. There's a bunch of others I won't mention as it would take too long.

Long term storage all depends on your needs and sophistication. I use Thanos for our system since it has an extremely flexible scaling system. But there is also Grafana Mimir. They're both similar in that they use Prometheus TSDB format as part of the underlying storage. One nice Thanos advantage is that it does do downsampling in addition to being able to store raw metric data for a long time. It will auto-select downsampled data to make requests faster.

You can aggregate all your clusters Prometheus metrics together with a wonderful tool called Thanos. This will allow you to use just a single Grafana instance against Thanos and using a label select which cluster you wish to see metrics from. The downside of this, is that none of the Grafana dashboards from the internet will work as-is. You'll need to customize all of them for Thanos support. The other downside is, you have a single point of failure, and (see next item) you can't customize who can access what in regards to your dev vs production data/metrics/access.

Depending on how you want to set things up, you can use Thanos or Mimir to create the single-pane-of-glass view of your data.

You could look at something like Thanos and store your data in S3: https://thanos.io/