Articles

Istio 1.6 Improves Operability and Enhances Simplicity

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Significant changes were made to the Istio service mesh in its version 1.5 release earlier this year, including notable modifications to the control plane architecture and the creation of a single model for extending Istio and its Envoy proxies using WebAssembly. Istio’s latest quarterly release, version 1.6, at first glance may seem to carry less weight in comparison, however, this update includes several important enhancements that continue to improve its operability.

Installation and Configuration Management

Reducing Upgrade Risks

Istio 1.6 introduces canary support for upgrading versions of the Istio control plane, enabling users to deploy numerous releases of Istiod within the same cluster and migrate pods to a newer version. This will significantly reduce any risks that arise when carrying out upgrades in a production cluster. When installing new control plane versions, the istioctl the command-line tool now supports assigning names to versions that can be utilized when assigning workloads to each specific Istiod version running in the service mesh.

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Cloud-Native Benchmarking With Kubestone

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Intro

Organizations are increasingly looking to containers and distributed applications to provide the agility and scalability needed to satisfy their clients. While doing so, modern enterprises also need the ability to benchmark their application and be aware of certain metrics in relation to their infrastructure.

In this post, I am introducing you to a cloud-native bench-marking tool known as Kubestone. This tool is meant to assist your development teams with getting performance metrics from your Kubernetes clusters.

How Does Kubestone Work?

At it’s core, Kubestone is implemented as a Kubernetes Operator in Go language with the help of Kubebuilder. You can find more info on the Operator Framework via this blog post.
Kubestone leverages Open Source benchmarks to measure Core Kubernetes and Application performance. As benchmarks are executed in Kubernetes, they must be containerized to work on the cluster. A certified set of benchmark containers is provided via xridge’s DockerHub space. Here is a list of currently supported benchmarks:

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Introducing Aquayman

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At Loodse, we’re using Quay.io to host our various Docker repositories. Over the last few years, cruft accumulated and we noticed that keeping team memberships up-to-date as employees and customers change became a hassle.

For Github we already make use of Peribolos, a wonderful tool to manage your Github organization declaratively. For quay we unfortunately did not find an equivalent solution, so we made our own.

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Camel K in a Nutshell

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Camel K, a project under the famous Apache Camel project, is a project that totally changes the way developers work with Kubernetes/OpenShift cloud platforms by automating the nasty configuration and loads of prep work from developers. If you are an old-time developer like me, you did your best to slowly try to adapt to the latest and greatest cloud native “ecology.” It’s not difficult, but with small things and traps here and there. I’ll tell you it’s not a smooth ride. It’s understandable for emerging technologies. But with the large adoption of cloud, I see it’s reaching a level of maturity, where now we are thinking of how to make things go faster, as well as making it more accessible to the larger audience. 

Check out some reasons why you might love Camel K.

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Get Your First Container Up On K8s Using PMKFT

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Kubernetes in the leading container orchestration platform that allows you to apply fast and streamlined infrastructure workloads using a declarative API.

In this tutorial, we are going to follow a step-by-step guide for signing in with Platform9 Managed Kubernetes Free-Tier Platform, creating a new cluster and deploying an example application. Then we will see how to scale-up/down our application instances and how to roll out a new updated instance of our app.

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Deploying machine learning workflows on LKE with Kubeflow

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Introduction

Teams that work with Machine Learning (ML) workloads in production know that added complexity can bring projects for a grinding halt. While deploying simple ML workloads might seem like an easy task, the process becomes a lot more involved when you begin to scale and distribute these loads and implement tools like Kubernetes. Although Kubernetes allows teams to rapidly scale their organization’s infrastructure, it also adds a layer of complexity that can become a major burden without the right tools. 

Today I’m going to introduce you to an OSS project known as Kubeflow that seeks to assist engineering teams with deploying ML workloads into production in Kubernetes. The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable.

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DevOps Tutorial | DevOps With Docker, Kubernetes and Azure DevOps

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In this article, we focus our attention on the DevOps.

What is DevOps? How is it different from Agile? What are the popular DevOps Tools? What is the role of Docker, Kubernetes and Azure DevOps in DevOps. Let’s get started with a simple use case.

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How Does Low-Code Fit Into the Cloud-Native World?

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Unlike analysts at the large firms, who have to specialize in narrow market segments to avoid stepping on each other’s toes, we at Intellyx have the luxury of covering cross-cutting topics that align with business needs.

One of our tools in trade: looking closely at how two different markets interrelate and thus provide business value. In today’s Cortex, I’ll consider the relationship between low-code and cloud-native computing.

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Health Checks with ASP.NET Core and Kubernetes

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Health checks are a fundamental part of our APIs. I guess they fall in that category of "non-functional-but-heavily-required" things. More or less like a good part of the infrastructure code.

They don’t add business value per se but have an enormous impact for those in IT, like DDD and design patterns. You can normally see them in conjunction with container orchestration or monitoring tools to ensure that the system is alive and kicking.

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Kubernetes and Beyond: An Interview With Kelsey Hightower [Podcast]

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This Oracle Groundbreakers Podcast episode features a very special conversation about the current state and future of Kubernetes with Kelsey Hightower.

Kelsey is a developer advocate, an open source aficionado, and a widely recognized expert on Kubernetes. He is the creator of the open source tutorial Kubernetes The Hard Way, available on Github, and he is a co-author of Kubernetes: Up and Running: Dive Into the Future of Infrastructure, the second edition of which is now available from O’Reilly Media.

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