Add standardized support information to your Node.js modules

Add standardized support information to your Node.js modules

The Nodeshift team recently improved the consistency of the projects we use to maintain our Node.js modules. We made sure that the same linter and tests—ESLint and Tape, for those interested—were used on all projects. We also added support information for the modules we publish to the npm registry. We looked to the Node.js Package Maintenance Working Group for the standardized support information to add.

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Spring Boot on Quarkus: Magic or madness?

Spring Boot on Quarkus: Magic or madness?

Quarkus is a Java stack tailored for OpenJDK HotSpot (or OpenJ9 on zSeries) and GraalVM, crafted from optimized Java libraries and standards. It is a good choice for building highly-scalable applications while using lower amounts of CPU and memory resources than other Java frameworks. These applications can be traditional web applications, serverless applications, or even functions as a service.

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Deploying Kubernetes Operators with Operator Lifecycle Manager bundles

Deploying Kubernetes Operators with Operator Lifecycle Manager bundles

This article shows an example of using the Operator Lifecycle Manager (OLM) bundle deployment architecture to deploy a Red Hat OpenShift or other Kubernetes Operator. You will learn how to use OLM and the Operator SDK (both components of the Kubernetes Operator Framework) together to deploy an Operator.

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Deliver your applications to edge and IoT devices in rootless containers

Deliver your applications to edge and IoT devices in rootless containers

Applications are often developed, tested, and delivered in containers, and Red Hat OpenShift is a great platform for that purpose. Sometimes, however, the target machine is much smaller than a Kubernetes cluster. It might be an embedded server, industry PC hardware, or a single server.
Image: Systemd + Podman + Ansible.

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How Red Hat ported OpenJDK to 64-bit Arm: A community history

How Red Hat ported OpenJDK to 64-bit Arm: A community history

It has been quite a year for Arm Ltd., the firm that designs reduced instruction set computing (RISC) architectures for computer processors. The news that Arm-based computers will be important for the foreseeable future has even reached the mainstream media. At the end of 2019, Amazon Web Services announced Arm-based Graviton2 servers. In June 2020, Apple announced its plans to move Macintosh computers over to Apple silicon—which means Arm.

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Write a Quarkus function in two steps on Red Hat OpenShift Serverless

Write a Quarkus function in two steps on Red Hat OpenShift Serverless

Serverless functions are driving the fast adoption of DevApps development and deployment practices today. To successfully adopt serverless functions, developers must understand how serverless capabilities are specified using a combination of cloud computing, data infrastructure, and function-oriented programming. We also need to consider resource optimization (memory and CPU) and high-performance boot and first-response times in both development and production environments. What if we didn’t have to worry about all of that?

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Static analysis updates in GCC 11

Static analysis updates in GCC 11

The GNU logo.
I work at Red Hat on the GNU Compiler Collection (GCC). In GCC 10, I added the new -fanalyzer option, a static analysis pass for identifying various problems at compile-time, rather than at runtime. The initial implementation was aimed at early adopters, who found a few bugs, including a security vulnerability: CVE-2020-1967. Bernd Edlinger, who discovered the issue, had to wade through many false positives accompanying the real issue. Other users also managed to get the analyzer to crash on their code.

I’ve been rewriting the analyzer to address these issues in the next major release, GCC 11. In this article, I describe the steps I’m taking to reduce the number of false positives and make this static analysis tool more robust.

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