smi-spec VS helm

The Service Mesh Interface (SMI) specification was created to solve this portability issue.

> I suspect if a Service Mesh is ultimately shown to have broad value, one will make it's way into the K8S core

I'm not so sure. I suspect it'll follow the same roadmap as Gateway API, which it already kind of is with the Service Mesh Interface (https://smi-spec.io/)

It is very common that a service mesh deploys a control plane and a data plane. The control plane does what you might expect; it controls the service mesh and gives you the ability to interact with it. Many service meshes implement the Service Mesh Interface (SMI) which is an API specification to standardize the way cluster operators interact with and implement features.

Before we start, let's review the SMI Access Control Specification. There are two forms of traffic policies in osm-edge: Permissive Mode and Traffic Policy Mode. The former allows services in the mesh to access each other, while the latter requires the provision of the appropriate traffic policy to be accessible.

osm-edge is a simple, complete, and standalone service mesh and ships out-of-the-box with all the necessary components to deploy a complete service mesh. As a lightweight and SMI-compatible Service Mesh, osm-edge is designed to be intuitive and scalable.

I started on Monday, attending ServiceMeshCon2019. My guesstimate is that about 1000 people attended it. I believe Service Mesh is playing such a crucial role in scaling cloud native technologies that large scale cloud-native deployments may not be possible without service mesh. Just like you cannot really succeed in deploying a microservices based application without a microservices orchestration engine, like Kubernetes, you cannot scale the size and capacity of a microservices-based application without service mesh. That’s what makes it so compelling to see all the service mesh creators — Istio, Linkerd, Consul, Kuma — and listen to them. There was also a lot of discussion of SMI (Service Mesh Interface) — a common interface among all services mesh. The panel at the end of the day included all the major service mesh players, and some very thought provoking questions were asked and answered by the panel.

Do you need a Service Mesh?

In the episode with Annie, she gave a great overview of the CNCF and a handful of projects that she's excited about. Those include Helm, Linkerd, Kudo, Keda and Artifact Hub. I gave a bonus example of the Service Mesh Interface project.

SMI official website: https://smi-spec.io

Applying Kubernetes manifests individually is problematic because files can get overlooked. Packaging your applications as Helm charts lets you version your manifests and easily repeat deployments into different environments. Helm tracks the state of each deployment as a "release" in your cluster.

helm

Explanation here: https://github.com/helm/helm/issues/12681#issuecomment-19593...

Looks like it's a bug in Helm, but actually isn't Helm's fault, the issue was introduced by Fedora Linux.

Helm (Get from here https://helm.sh/)

It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.

Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!

Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.

We can search for charts https://helm.sh/ . Charts can be pulled(downloaded) and optionally unpacked(untar).

Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.

Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.