containers

Accessing Apache Kafka in Strimzi: Part 5 – Ingress

Accessing Apache Kafka in Strimzi: Part 5 – Ingress

In the fifth and final part of this series, we will look at exposing Apache Kafka in Strimzi using Kubernetes Ingress. This article will explain how to use Ingress controllers on Kubernetes, how Ingress compares with Red Hat OpenShift routes, and how it can be used with Strimzi and Kafka. Off-cluster access using Kubernetes Ingress is available only from Strimzi 0.12.0. (Links to previous articles in the series can be found at the end.)

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Application lifecycle management for container-native development

Application lifecycle management for container-native development

Container-native development is primarily about consistency, flexibility, and scalability. Legacy Application Lifecycle Management (ALM) tooling often is not, leading to situations where it:

  • Places artificial barriers on development speed, and therefore time to value,
  • Creates single points of failure in the infrastructure, and
  • Stifles innovation through inflexibility.

Ultimately, developers are expensive, but they are the domain experts in what they build. With development teams often being treated as product teams (who own the entire lifecycle and support of their applications), it becomes imperative that they control the end-to-end process on which they rely to deliver their applications into production. This means decentralizing both the ALM process and the tooling that supports that process. In this article, we’ll explore this approach and look at a couple of implementation scenarios.

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Accessing Apache Kafka in Strimzi: Part 4 – Load balancers

Accessing Apache Kafka in Strimzi: Part 4 – Load balancers

In this fourth article of our series about accessing Apache Kafka clusters in Strimzi, we will look at exposing Kafka brokers using load balancers. (See links to previous articles at end.) This article will explain how to use load balancers in public cloud environments and how they can be used with Apache Kafka.

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Accessing Apache Kafka in Strimzi: Part 3 – Red Hat OpenShift routes

Accessing Apache Kafka in Strimzi: Part 3 – Red Hat OpenShift routes

In the third part of this article series (see links to previous articles below), we will look at how Strimzi exposes Apache Kafka using Red Hat OpenShift routes. This article will explain how routes work and how they can be used with Apache Kafka. Routes are available only on OpenShift, but if you are a Kubernetes user, don’t be sad; a forthcoming article in this series will discuss using Kubernetes Ingress, which is similar to OpenShift routes.

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Accessing Apache Kafka in Strimzi: Part 2 – Node ports

Accessing Apache Kafka in Strimzi: Part 2 – Node ports

This article series explains how Apache Kafka and its clients work and how Strimzi makes it accessible for clients running outside of Kubernetes. In the first article, we provided an introduction to the topic, and here we will look at exposing an Apache Kafka cluster managed by Strimzi using node ports.

Specifically, in this article, we’ll look at how node ports work and how they can be used with Kafka. We also will cover the different configuration options available to users and the pros and cons of using node ports.

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Accessing Apache Kafka in Strimzi: Part 1 – Introduction

Accessing Apache Kafka in Strimzi: Part 1 – Introduction

Strimzi is an open source project that provides container images and operators for running Apache Kafka on Kubernetes and Red Hat OpenShift. Scalability is one of the flagship features of Apache Kafka. It is achieved by partitioning the data and distributing them across multiple brokers. Such data sharding has also a big impact on how Kafka clients connect to the brokers. This is especially visible when Kafka is running within a platform like Kubernetes but is accessed from outside of that platform.

This article series will explain how Kafka and its clients work and how Strimzi makes it accessible for clients running outside of Kubernetes.

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Container-related content you might have missed at Red Hat Summit

Container-related content you might have missed at Red Hat Summit

If you weren’t lucky enough to attend the recent Red Hat Summit or you went but couldn’t make it to all the container-related sessions, worry not. We teamed up with Scott McCarty, Principal Technology Product Manager–Containers at Red Hat, to bring you an overview of what you missed.

Choosing the right container base image for your applications

The Red Hat Universal Base Image (UBI) gives you three options for building containers with the full power of Red Hat Enterprise Linux (RHEL) underneath. The goal is to create the smallest possible image that fully supports your application. You select a base image depending on the application you’re packaging in a container. For example, if you have a Golang or .NET application, all of that application’s dependencies are built in. That means you can use the minimal image (ubi-minimal), which contains microdnf, a package manager that only supports install, update, and remove functions. It also includes, well, a minimal set of tools.

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Working with Red Hat Enterprise Linux Universal Base Images (UBI)

Working with Red Hat Enterprise Linux Universal Base Images (UBI)

If you’re like me—a developer who works with customers who rely on the tried-and-true Red Hat Enterprise Linux (RHEL), works with containerized applications, and also prefers to work with Fedora Linux as their desktop operating system—you’re excited by the announcement of the Universal Base Images (UBI). This article shows how UBI actually works, by building the container image for a simple PHP application.

With UBI, you can build and redistribute container images based on Red Hat Enterprise Linux without requiring a Red Hat subscription. Users of UBI-based container images do not need Red Hat subscriptions. No more extra work creating CentOS-based container images for your community projects or for your customers that prefer self-support.

I tested all these steps on my personal Fedora 29 system, and they should work on any Linux distribution. I am also a big fan of the new container tools such as Podman, which should be available to your favorite Linux distribution. If you are working on a Windows or MacOS system, you can replace the Podman commands with Docker.

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Command-line tools for Kubernetes: kubectl, stern, kubectx, kubens

Command-line tools for Kubernetes: kubectl, stern, kubectx, kubens

If you’ve ever worked with your hands, you know that you can’t do the job right without the right tools. That adage carries over quite well to software development as well. The right tools can make the difference between success or failure, regardless of the underlying technology. In the Kubernetes ecosystem, more and more tools are being introduced as folks find ways to solve a common problem. This article looks are four of those tools.

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2 tips to make your C++ projects compile 3 times faster

2 tips to make your C++ projects compile 3 times faster

In this article, I will demonstrate how to speed up your compilation times by distributing compilation load using a distcc server container.  Specifically, I’ll show how to set up and use containers running a distcc server to distribute the compilation load over a heterogeneous cluster of nodes (development laptop, old desktop PC, and a Mac). To improve the speed of recompilation, I will use ccache.

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