Embedded editions designed for edge computing and embedded deployments, respectively. The OS is a perfect choice for ecosystem partners, users, and developers who plan to enhance scenario-specific capabilities kernel documents, bug fixes, and code rebuilds. Over the past decade, openEuler has contributed more than 17,000 patches to the Linux kernel. In Linux kernels 5.10 and 5.14, openEuler's code contribution the user-mode storage based on a preset policy. The user-mode swap delivers a higher performance than the kernel- mode swap and the whole swap process is transparent to users. Cloud base: • KubeOS

single page apps for offline support Putting Performance Best Practices Together to Create the Perfect SPA by Chris Love (Love2Dev) @ChrisLove http://www.slideshare.net/docluv/putting-performance-bes Separate deployment from release  Automate everything  Trust your tests  Conversations are way better than project proposals  Start small, be brave quickly  Seize opportunitiesGreat, you're now a software Mikey Dickerson (Federal Government | United States Digital Services Team)  The more simple, the better off you are  Agile is tactic not religious credo  You have to make it easy for people who have

below lists recommended hardware specifications. Depending on your needs, you might manage with less than this. However, most users risk being frustrated if they ignore these suggestions. Table 2.1. Recommended with current versions of Linux (and Ubuntu) is based on the 'mdadm' driver and works very well, better even than many so-called 'hardware' RAID controllers. This section will guide you through installing Ubuntu RAM is smaller than 384M, then don't reserve anything (this is the "rescue" case) • if the RAM size is between 386M and 2G (exclusive), then reserve 64M • if the RAM size is larger than 2G, then reserve

Kubernetes Essentials • Conclusion Git is the most widely used version control system, with more than 80 percent of its market share in today’s software industry. GitOps is a methodology which revolves recreate a new system independent of the compromised one, reducing downtime and allowing for better incident response. Also, separating responsibility between packaging software and releasing it of Kubernetes resource. Kubernetes deployments have the following properties that make them perfect for GitOps-style deployment workflows: • Automation: Kubernetes provides a built-in mechanism

HTTP/1.1. Among the important changes, proxy access control is now placed inside a block rather than a block. • The handling of PATH INFO (trailing path information after the true infrastructure in place to support serving multiple protocols. MOD ECHO has been written as an example. Better support for non-Unix platforms Apache 2.0 is faster and more stable on non-Unix platforms such as Y directive can be used to assure that the client receives a single document in all cases, rather than NOT ACCEPTABLE or MULTIPLE CHOICES responses. In addition, the negotiation and MultiViews algorithms

changeability, and invisibility.”Complexity • Software entities are more complex for their size than perhaps any other human construct, because no two parts are alike • The complexity of software automatic programming has always been a euphemism for programming with a higher-level language than was presently available to the programmer • In essence, it is the solution method, not the problem error-proof programs • There is no magic here either, mathematical proofs can be faulty • Even perfect program validation can only establish that a program meets its specification, the hardest part

control components of the data center infrastructure can be offloaded to the DPU, resulting in better architecture and more flexible deployments. Most mainstream offload solutions involve splitting In the Iperf network tests on the Inter-VM shared memory device (ivshmem), the performance is better than that of gigabit NICs. • Impact on guest systems » According to the interrupt tests (5 million Linux. Embedded applications have higher requirements on interconnection, AI, and iterative upgrade than general-purpose workloads, but they typically have constraints in terms of resources, power consumption

weeks (or months!) to provision an environment The application behaves different in production than it did in test Environments are all manually configured (“pets vs. cattle”) Production deployments resources One-click updates for platform, services, and applications OpenShift and GitOps - A Perfect Match ● OpenShift is a declarative environment ○ Cluster configuration is declared and Operators OpenShift Templates Patching framework Ability to apply yaml directly Some use-cases may work better with templates No support in OpenShift GUI console Great for enterprise teams, not as good for

you have to accept if you wish to use GitOps with Helm charts making the process much more complex than needed. Continuous Deployment and GitOps do not mix together GitOps is great as a Continuous Delivery release candidate that is ready to be sent to production. GitOps and Continuous Delivery are a perfect match, as the Pull Request process dictated by GitOps can function as a quality gate that approves/rejects Git. I don’t see this as an essential requirement for handling secrets in GitOps if there is a better proposal. On the topic of rollbacks, the ideal GitOps tool should be able to perform the following:

extended with new SMTP authentication options. It is also possible now to specify the server port other than the hardcoded 25 before. 9 See e-mail configuration for more details. 5.5 Item checking at specific linked to the applications created based on application prototypes. 5.12 Graph improvements 5.12.1 Better zoom In previous versions the shortest period you could zoom into was one hour. Now this limit has 12.3 Miscellaneous • ISO date format of yyyy-mm-dd hh:mm:ss used Several improvements focus on better readability of labels in graphs, especially large graphs showing data for several years: • A change