Welcome to our monthly recap of the articles we published in March 2022! This month, Red Hat Developer readers flocked to articles to help them write code on the platforms they trust. You can learn more about modular Perl in Red Hat Enterprise 8, get into the details of testing and code coverage in the Node.js reference architecture, or dive deeper into Quarkus in the latest installment of our Quarkus from the ground up series.
And there's much more as well! Read on for the March highlights.
Note: See the end of this article for the full lineup published in March 2022.
Podman and container development
Are you a .NET user interested in rolling out containerized applications with Podman? Another one of our most popular articles of the month explains how to control Podman from .NET. .NET users can also get tips on how to debug .NET applications running in local containers with VS Code; and if you're working with Red Hat CodeReady Workspaces, you can find out more about simplifying container development with that service.
OpenShift: What's new and what's fast
Version 4.10 of the Red Hat OpenShift Container Platform is here, and that's big news for the many developers who are deploying their container-based workloads on that platform. If you need a deep dive into what's for developers in the OpenShift 4.10 console, Red Hat Developer has you covered.
Want to learn more about how to get started with Red Hat OpenShift quickly? Check out our articles on packaging and running a Java Maven application on OpenShift in seconds and creating an Azure Red Hat OpenShift cluster in less than five minutes.
Do more with Kafka
Developers love Kafka for its ability to move truly massive amounts of data. Clustering is one of the keys to Kafka's power, but how many Kafka clusters does your infrastructure require? Red Hat Developer's most popular article in March tries to answer the question of whether you need a single Kafka cluster—or many clusters—to rule them all.
Meanwhile, for those interested in event-driven and serverless architectures, we've offered a guide to processing Apache Kafka records with Knative's serverless architecture.
Understand Java's nitty-gritty details
Java developers looking to learn more about how their code works under the hood got some treats this month. We did a deep dive into range checks, a technique the HotSpot JVM uses to improve performance. For those looking to use Cryostat to instrument and monitor their own code, we offered advice on injecting custom JDK Flight Recorder events in containerized applications.
Choose the best Camel for your integration ride
Apache Camel is the most popular open source integration framework today, and has evolved to support new environments such as containers on Kubernetes while continuously improving the developer experience. Want to find out more about all the ways you can use Camel and why each came into being? Read the first, second, and third parts of our series on the topic.
March 2022 on Red Hat Developer
Here's the full lineup of articles published on Red Hat Developer so far this month:
- Which is better: A single Kafka cluster to rule them all, or many?
- Modular Perl in Red Hat Enterprise Linux 8
- Introduction to the Node.js reference architecture, Part 7: Code coverage
- Package and run your Java Maven application on OpenShift in seconds
- REST API error modeling with Quarkus 2.0
- An easier way to generate PDFs from HTML templates
- Create an Azure Red Hat OpenShift cluster in less than 5 minutes
- Hello Podman using .NET
- Choose the best Camel for your integration ride, Part 1
- Process Apache Kafka records with Knative's serverless architecture
- Kafka Monthly Digest: February 2022
- Manage Python security with Thoth's cloud-based dependency resolver
- Choose the best camel for your integration ride, Part 2
- Range check elimination in loops in OpenJDK's HotSpot JVM
- Test GitHub projects with GitHub Actions and Testing Farm
- Node.js community update
- Choose the best camel for your integration ride, Part 3
- Preview: Clustering support for JBoss EAP on Azure App Service
- Inject custom JDK Flight Recorder events in containerized applications
- Data conversion in Pandas dataframes: 3 approaches to try
- Debug .NET applications running in local containers with VS Code
- Simplify container development with Red Hat CodeReady Workspaces
- Inspecting containerized Python applications in a cluster
- Enforce code consistency with clang-format
- SQL cache stores and more in Data Grid 8.3