Ensuring a Smooth Kubernetes Dockershim Deprecation With Chaos Engineering

Learn what the deprecation of Docker as a container runtime means for you and how to ensure a pain-free transition.

Kubernetes 1.20 was released last week. This version contains a number of amazing enhancements including graceful node shutdown, more visibility into resource requests, and snapshotting volumes.

But the change generating the most buzz is the deprecation of Docker as a container runtime.

Much of the discussion revolves around a misunderstanding of what the Docker deprecation entails and how it affects both Kubernetes administrators and application developers.

Let’s dive into what this deprecation means for you and how you can use chaos engineering to ensure a smooth transition off of the Docker runtime.

Docker Isn’t Just a Container Runtime

They say that naming things is one of the hardest things in technology, and this is certainly true with Docker. Often when discussing Docker, there’s some confusion around whether this refers to the container images or the application that runs those containers. The Kubernetes deprecation is for the application that runs your containers.

But don’t worry, this doesn’t mean your Kubernetes cluster will stop running your Docker containers!

Docker, like most applications, is actually a collection of smaller applications. There are sub-applications for the UI, an API, and many other things, including the container runtime. In 2016, Docker spun off its container runtime into a new, more modular runtime project called containerd. Containerd is fully supported by Kubernetes, so your Docker containers are also fully supported by Kubernetes.

The piece that’s being deprecated is the support for all of the other sub-applications that come along with Docker. Supporting all of those pieces required an integration layer called dockershim that required additional work to maintain — work that is largely unnecessary because most Kubernetes users only needed containerd and not the extra Docker features. Deprecating this feature will actually reduce the workload on the Kubernetes maintainers and make Kubernetes less complex.

#docker #kubernetes #chaos engineering #docker and kubernetes

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Ensuring a Smooth Kubernetes Dockershim Deprecation With Chaos Engineering
Christa  Stehr

Christa Stehr

1602964260

50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

Ensuring a Smooth Kubernetes Dockershim Deprecation With Chaos Engineering

Learn what the deprecation of Docker as a container runtime means for you and how to ensure a pain-free transition.

Kubernetes 1.20 was released last week. This version contains a number of amazing enhancements including graceful node shutdown, more visibility into resource requests, and snapshotting volumes.

But the change generating the most buzz is the deprecation of Docker as a container runtime.

Much of the discussion revolves around a misunderstanding of what the Docker deprecation entails and how it affects both Kubernetes administrators and application developers.

Let’s dive into what this deprecation means for you and how you can use chaos engineering to ensure a smooth transition off of the Docker runtime.

Docker Isn’t Just a Container Runtime

They say that naming things is one of the hardest things in technology, and this is certainly true with Docker. Often when discussing Docker, there’s some confusion around whether this refers to the container images or the application that runs those containers. The Kubernetes deprecation is for the application that runs your containers.

But don’t worry, this doesn’t mean your Kubernetes cluster will stop running your Docker containers!

Docker, like most applications, is actually a collection of smaller applications. There are sub-applications for the UI, an API, and many other things, including the container runtime. In 2016, Docker spun off its container runtime into a new, more modular runtime project called containerd. Containerd is fully supported by Kubernetes, so your Docker containers are also fully supported by Kubernetes.

The piece that’s being deprecated is the support for all of the other sub-applications that come along with Docker. Supporting all of those pieces required an integration layer called dockershim that required additional work to maintain — work that is largely unnecessary because most Kubernetes users only needed containerd and not the extra Docker features. Deprecating this feature will actually reduce the workload on the Kubernetes maintainers and make Kubernetes less complex.

#docker #kubernetes #chaos engineering #docker and kubernetes

The Principles of Chaos Engineering

Resilience is something those who use Kubernetes to run apps and microservices in containers aim for. When a system is resilient, it can handle losing a portion of its microservices and components without the entire system becoming inaccessible.

Resilience is achieved by integrating loosely coupled microservices. When a system is resilient, microservices can be updated or taken down without having to bring the entire system down. Scaling becomes easier too, since you don’t have to scale the whole cloud environment at once.

That said, resilience is not without its challenges. Building microservices that are independent yet work well together is not easy.

What Is Chaos Engineering?

Chaos Engineering has been around for almost a decade now but it is still a relevent and useful concept to incorporate into improving your whole systems architecture. In essence, Chaos Engineering is the process of triggering and injecting faults into a system deliberately. Instead of waiting for errors to occur, engineers can take deliberate steps to cause (or simulate) errors in a controlled environment.

Chaos Engineering allows for better, more advanced resilience testing. Developers can now experiment in cloud-native distributed systems. Experiments involve testing both the physical infrastructure and the cloud ecosystem.

Chaos Engineering is not a new approach. In fact, companies like Netflix have been using resilience testing through Chaos Monkey, an in-house Chaos Engineering framework designed to improve the strength of cloud infrastructure for years now.

When dealing with a large-scale distributed system, Chaos Engineering provides an empirical way of building confidence by anticipating faults instead of reacting to them. The chaotic condition is triggered intentionally for this purpose.

There are a lot of analogies depicting how Chaos Engineering works, but the traffic light analogy represents the concept best. Conventional testing is similar to testing traffic lights individually to make sure that they work.

Chaos Engineering, on the other hand, means closing out a busy array of intersections to see how traffic reacts to the chaos of losing traffic lights. Since the test is run deliberately, more insights can be collected from the process.

#devops #chaos engineering #chaos monkey #chaos #chaos testing

Madelyn  Frami

Madelyn Frami

1603866300

Getting Started with Chaos Mesh and Kubernetes

What is Chaos Engineering?

Chaos engineering is the discipline of experimenting on a software system in production in order to build confidence in the system’s capability to withstand turbulent and unexpected conditions. For more details refer to Chaos Engineering.

Chaos experiments are executed in production environments, this leaves room for customer-facing outages. While there has to be some allowance for the short-term negative impact the blast radius or fallout from the experiment must be minimized and contained.

What is Chaos Mesh?

Chaos Mesh® is a Cloud Native Computing Foundation (CNCF) hosted project.

Chaos Mesh is a cloud-native Chaos Engineering platform that orchestrates chaos on Kubernetes environments.

Chaos Mesh is a versatile chaos engineering solution that features all-around fault injection methods for complex systems on Kubernetes, covering faults in Pod, network, file system, and even the kernel.

Now Let’s see what are the components of Chaos Mesh:

  • Chaos Operator: the core component for chaos orchestration. Fully open-sourced.
  • Chaos Dashboard: a Web UI for managing, designing, monitoring Chaos Experiments; under development.

#chaos-mesh #kubernetes-operator #kubernetes #business-continuity #chaos-engineering

Maud  Rosenbaum

Maud Rosenbaum

1601051854

Kubernetes in the Cloud: Strategies for Effective Multi Cloud Implementations

Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.

This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.

Kubernetes: Your Multi Cloud Strategy

Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.

In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.

Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.

In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.

The Compelling Attributes of Multi Cloud Kubernetes

Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.

Stability

In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.

#kubernetes #multicloud-strategy #kubernetes-cluster #kubernetes-top-story #kubernetes-cluster-install #kubernetes-explained #kubernetes-infrastructure #cloud