10 GitHub Repositories to Master Self-Hosting
Learn how modern infrastructure works through self-hosting: containers, reverse proxies, monitoring, backups, networking, and systems operations.
InfoWorld AI·
If you’re using Kubernetes, especially a managed version like Azure Kubernetes Service (AKS), you don’t need to think about the underlying hardware. All you need to do is build your application and it should run, its containers managed by the service’s orchestrator. At least that’s the theory. However, implementing a platform that abstracts your code from the servers and network that support it brings its own problems, and a whole new discipline. Platform engineers fill the gap between software and hardware, supporting security and networking, as well as managing storage and other key services. Kubernetes is part of an ecosystem of cloud-native services that provide the supporting framework for running and managing scalable distributed systems, including the tools needed to package and deploy applications, as well as components that extend the functionality of Kubernetes’ own nodes and pods. Key components of this growing ecosystem are the various service meshes. These offer a way to m
Read full articleLearn how modern infrastructure works through self-hosting: containers, reverse proxies, monitoring, backups, networking, and systems operations.
Simplify Kubernetes operations by managing storage, data protection, and disaster recovery for AI workloads, containers and VMs directly within the Red Hat OpenShift console. SANTA CLARA, Calif., May 12, 2026 […] The post Everpure’s Portworx Makes Data Management Native to Red Hat OpenShift appeared first on AIwire.
A supply chain attack on SAP-related npm packages has put fresh scrutiny on the developer tools and build workflows that enterprises rely on to produce software. The campaign, referred to as “mini Shai-Hulud,” affected packages used in SAP’s JavaScript and cloud application development ecosystem. The malicious versions added installation-time code that could steal developer credentials, GitHub and npm tokens, GitHub Actions secrets, and cloud credentials from AWS, Azure, GCP, and Kubernetes environments. Researchers at SafeDep, Aikido Security, Wiz, and several other security firms said the affected packages included mbt@1.2.48, @cap-js/db-service@2.10.1, @cap-js/postgres@2.2.2, and @cap-js/sqlite@2.2.2. The suspicious versions were published on April 29 and were later replaced by safe releases. The malware encrypted stolen data and sent it to public GitHub repositories created from victims’ own accounts, according to the researchers. It also used stolen GitHub and npm tokens to add ma
For years, Kubernetes held an almost mythic place in enterprise IT. It was positioned as the control plane for the future, the standard abstraction for cloud-native systems, and the platform that would finally free enterprises from infrastructure lock-in. To be fair, some of that was true. Kubernetes brought discipline to container orchestration, enabled portable deployment models, and provided architects with a powerful framework for managing distributed applications at scale. However, the market is changing, and so are enterprise expectations. The question is no longer whether Kubernetes is technically impressive. It clearly is. The question is whether it still represents the best fit for a growing number of mainstream enterprise use cases. In many cases, the answer is increasingly no. What we are seeing is not the death of Kubernetes but the end of its unquestioned dominance as the default strategic choice. Here’s why. Too operationally expensive As Kubernetes adoption grew, many o
Running databases on Kubernetes is popular. For cloud-native organizations, Kubernetes is the de facto standard approach to running databases. According to Datadog, databases are the most popular workload to deploy in containers, with 45 percent of container-using organizations using this approach. The Data on Kubernetes Community found that production deployments were now common, with the most advanced teams running more than 75 percent of their data workloads in containers. Kubernetes was not built for stateful workloads originally—the project had to develop multiple new functions like StatefulSets in Kubernetes 1.9 and Operator support for integration with databases later. With that work done over the first 10 years of Kubernetes, you might think that all the hard problems around databases on Kubernetes have been solved. However, that is not the case. Embracing database as a service with Kubernetes Today we can run databases in Kubernetes successfully, and match those database workl