# YAML YAML is a human-friendly data serialization language for all programming languages. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How to build a Language Server Protocol (LSP) plugin for Claude Code DevFeed: [How to build a Language Server Protocol (LSP) plugin for Claude Code]() Original publisher: [Read original article]() Author: Roger Winter Published: 2026-09-17T07:00:00Z Content type: tutorial Language: en Sources: [The CircleCI Blog Feed | CircleCI]() Topics: [Claude Code](), [CircleCI](), [Protocol (disambiguation)](), [YAML](), [CI/CD](), [Code]() Tags: [ai-development](), [ci-cd](), [circleci](), [claude-code](), [code](), [how-to](), [protocol](), [yaml]() ### AI overview This tutorial explains how to wrap CircleCI's open-source YAML language server as a Claude Code plugin. The plugin provides real-time diagnostics, hover guidance, and best-practice feedback while Claude edits CircleCI configuration files. The article also discusses the implementation, reuse with other language servers, and a benchmark against editing without that feedback, while noting that the example plugin is unofficial and unsupported. ### Source excerpt Build custom Claude Code plugins to wrap the CircleCI language server. Improve your CI/CD configs with real-time diagnostics and best-practice guidance. ## Mintlify rebuilds automations around pre-built templates for common use cases DevFeed: [Mintlify rebuilds automations around pre-built templates for common use cases]() Original publisher: [Read original article]() Author: Patrick Foster Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Mintlify Blog]() Topics: [Automation](), [Documentation](), [changelog](), [Pull Request](), [Markdown](), [YAML]() Tags: [announcements](), [automation](), [changelog](), [docs](), [documentation](), [execution](), [markdown](), [prompt](), [quality](), [rest]() ### AI overview Mintlify rebuilt its automations around pre-built templates for common use cases, including syncing content with code changes, generating changelogs, and improving documentation from user feedback and support signals. Custom prompts remain available for specialized tasks. ### Source excerpt We redesigned automations for quicker setup with pre-built automations optimized for common use cases. Choose the right automations for your project and you're set. No context engineering required. ## Policy as Code in 2026: OPA, Kyverno, Cedar and What's Next DevFeed: [Policy as Code in 2026: OPA, Kyverno, Cedar and What's Next]() Original publisher: [Read original article]() Author: Abhijit Pujare Eric Minick Published: 2026-09-11T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [policy-as-code](), [Open Policy Agent](), [rego](), [Kyverno](), [Software Engineering](), [Kubernetes](), [JSON](), [YAML](), [AI Agent]() Tags: [ai-agent](), [compliance](), [json](), [kyverno](), [opa](), [open-policy-agent](), [policies](), [policy-as-code](), [rego](), [security](), [software-engineering](), [yaml]() ### AI overview This article surveys the 2026 Policy as Code ecosystem, comparing general-purpose Open Policy Agent and Rego with specialized approaches such as Kyverno, Cedar, and agent-oriented governance. It discusses the shift toward automated, machine-readable governance, the separation of policy from business logic, and the challenges of authoring and maintaining Rego as schemas evolve. ### Source excerpt | Blog ## Configuring Guix services by translating Scheme fields to YAML DevFeed: [Configuring Guix services by translating Scheme fields to YAML]() Original publisher: [Read original article]() Author: Sergio Pastor Pérez Published: 2026-09-07T08:30:00Z Content type: tutorial Language: en Sources: [GNU Guix -- Blog]() Topics: [configuration](), [YAML](), [OpenSSH]() Tags: [configuration](), [development](), [functional-package-management](), [how-to](), [openssh](), [programming-interfaces](), [scheme-api](), [yaml]() ### AI overview This tutorial explains how Guix services represent configuration through Scheme bindings and how to define a complex Goimapnotify service configuration by translating Guile Scheme fields into YAML. ### Source excerpt Guix system and Guix home introduce the concept of services. These provide users with a way to control background processes, commonly refereed as daemons , as well as ways of controlling the setup of files. For example, openssh-service-type is a service which controls a SSH daemon. In contrast, etc-service-type is a service that populates the contents of the /etc directory. One peculiarity of Guix services is that it's customary to provide Scheme bindings for the different fields. By that I mean that the different fields of the configuration of most services will be a... ## Red Hat Developer Hub software template authoring with rhdh-templates DevFeed: [Red Hat Developer Hub software template authoring with rhdh-templates]() Original publisher: [Read original article]() Author: Kashish Mittal Published: 2026-09-07T07:01:32Z Content type: tutorial Language: en Sources: [Red Hat Developer]() Topics: [Backstage](), [internal developer portal](), [Nunjucks](), [AI-assisted coding](), [YAML]() Tags: [ai-coding-agents](), [artificial-intelligence](), [backstage](), [developer-portal](), [developer-productivity](), [developer-tools](), [platform-engineering](), [quick-start](), [red-hat](), [software-templates](), [terminal](), [validation]() ### AI overview This tutorial introduces the rhdh-templates skill for building Red Hat Developer Hub and Backstage software templates with an AI coding assistant. It covers Nunjucks conventions, YAML schema checking, reference templates, local offline validation, repository templatization, and optional testing against a Red Hat Developer Hub instance. ### Source excerpt If you are a platform engineer or developer building Red Hat Developer Hub software templates, you know the friction of wrestling with Nunjucks syntax, guessing location.yaml placements, and discovering errors only after rendering in your developer portal. While AI coding agents handle generic YAML, they lack Red Hat Developer Hub and Backstage-specific conventions. The post Red Hat Developer Hub software template authoring with rhdh-templates appeared first on Red Hat Developer. ## How Developers Can Test Their Feature Branch Against Various Playwright Configurations Before Creating a Merge Request in GitLab CI/CD DevFeed: [How Developers Can Test Their Feature Branch Against Various Playwright Configurations Before Creating a Merge Request in GitLab CI/CD]() Original publisher: [Read original article]() Author: T.J. Maher (noreply@blogger.com) Published: 2026-08-28T20:18:08Z Content type: tutorial Language: en Sources: [T.J. Maher]() Topics: [GitLab](), [CI/CD](), [Playwright](), [YAML](), [Development]() Tags: [bun-create-playwright](), [chromium](), [ci-cd](), [firefox](), [gitlab](), [gitlab-ci](), [playwright](), [tests](), [yaml]() ### AI overview This tutorial shows how to configure a GitLab CI/CD pipeline so developers can test a feature branch before creating a merge request. It uses spec inputs in a YAML configuration to let users choose the branch, Playwright test suite, and browser, including Chromium, Firefox, WebKit, or all browsers. ### Source excerpt Developers need the option to test out their feature branch before merging it into main. In the last section, we set up a GitLab CI/CD Pipeline in our bun-create-playwright project to check every GitLab Merge Request. Now, we will be giving developers option to create a new pipeline where they can choose: Which feature branch to test against. Which test suite to execute (LoginPage tests? Secure Area? Or all of them?) Which Playwright browser to use: Chromium, Firefox, WebKit, or all. All these features can be set up using our .gitlab-ci.yaml file! Go to to bun-create-playwright, view the Pipelines section, and select the New Pipeline button. Run a New Bun-Create-Playwright Pipeline If you go to the Run new pipeline page at https://gitlab.com/tjmaher/bun-create-playwright/-/pipelines/new you can see the following default values I've set: https://gitlab.com/tjmaher/bun-create-playwright/-/pipelines/new By default: Branch name is "main", TEST_SUITE is "all", BROWSER is "all". ... But all these values can be set, with the developer choosing the options laid out in the .gitlab-ci.yaml file. Collect User Data With Spec Inputs We are going to be adding to the GitLab Pipeline we built in our last post Setting up a CI/ CD pipeline with GitLab: Quality, Test and Report. First, we are going to add a "spec" section to the header of the YAML file to define the behavior of a pipeline, and within that spec header, we will ask the person who triggered a new pipeline to set user defined inputs for the pipeline. spec: inputs: browser: description: "Browser project to run against." default: "all" options: ["all", "chromium", "firefox", "webkit"] suite: description: "Select full regression suite, or a single spec" default: "all" options: ["all", "login.spec.ts", "secure-area.spec.ts"] This is where we declare the "browser" and "suite" variables that appear when a user creates a new pipeline. We've given them a choice to run their feature branch code against: Browser: All, Chromium, Fir ## The Real Python Podcast - Episode #309: Exploring Complex Systems & Maintainable Data Science Pipelines DevFeed: [The Real Python Podcast - Episode #309: Exploring Complex Systems & Maintainable Data Science Pipelines]() Original publisher: [Read original article]() Author: Real Python Published: 2026-08-28T12:00:00Z Content type: article Language: en Sources: [Real Python]() Topics: [Complex Systems](), [Data Science](), [Python](), [systems](), [configuration](), [ci](), [YAML](), [releases](), [Django](), [VS Code Extension]() Tags: [code](), [complex-systems](), [configuration](), [data-science](), [django](), [podcast](), [python](), [release](), [systems](), [vs-code](), [workflow]() ### AI overview This Real Python podcast episode explores complex versus complicated coding problems and practical patterns for designing maintainable systems. It also covers repeatable data science pipelines, DataFrame validation with Pointblank, configuration-driven modular workflows, Python releases, PEPs, Django's release cycle, and several Python community projects. ### Source excerpt What are the key characteristics of complex systems, and what are practical patterns for tackling complex coding problems? Christopher Trudeau is back on the show this week with another batch of PyCoder's Weekly articles and projects. ## Pulumi Kubernetes v4.34.0: CRDs as provider extensions DevFeed: [Pulumi Kubernetes v4.34.0: CRDs as provider extensions]() Original publisher: [Read original article]() Author: Guinevere Saenger Published: 2026-08-28T00:00:00Z Content type: release Language: en Sources: [Pulumi]() Topics: [Kubernetes](), [Extension](), [SDKs](), [YAML](), [ingress-nginx]() Tags: [extensions](), [install](), [kubernetes](), [migration](), [product](), [providers](), [release](), [releases](), [sdk](), [sdks](), [yaml]() ### AI overview Pulumi Kubernetes provider v4.34.0 adds support for extending the provider with Kubernetes Custom Resource Definitions through a manifest and the new --extension flag. The release generates SDKs, supports all supported Pulumi languages including YAML, uses a single provider instance, and provides a migration path from crd2pulumi. ### Source excerpt We're really excited to bring you v4.34.0, the newest version of the Pulumi Kubernetes provider, which includes improved support for Kubernetes Custom Resource Definitions (CRDs). As with any release, we've also shipped standard dependency updates and bug fixes. This provider release includes the newest resources for Kubernetes v1.37.0, which was recently cut. So that in itself is very exciting! But the feature we're proudest of is that you can now extend the Kubernetes provider with any Kubernetes Custom Resource Definition of your choice by passing its manifest file to Pulumi, using the new --extension flag. We believe first-class CRD support in Pulumi is becoming more important than ever. For example, since the retirement of the ingress-nginx controller earlier this year, the recommended path for cluster ingress is Gateway API, which is maintained and shipped as CRDs. Generating a Pulumi SDK for CRDs In your Pulumi project root, run: pulumi package add kubernetes --extension "name=gateway-networking crd-manifest=gateway-api-crds.yaml" You will see the custom SDK appear in a new sdks/ folder, as well as a new parameterization reference in Pulumi.yaml. Single provider instance Your new CRD schema exists as an extension to your existing provider and will be managed under the same provider instance, allowing you to use a single provider configuration and kubeconfig. SDKs as dependencies Additionally, your code no longer needs to ship SDK files as part of the project. The provider extension is referenced in your project file and its SDK, like all dependencies, can be regenerated via pulumi install. You can choose to version the extension SDK, or continue to check the files into version control if you so desire. Full language support, including for YAML Kubernetes CRDs can now be provisioned with Pulumi in all supported languages. Unified CLI experience pulumi package add --extension extends your CRD schema into the Pulumi Kubernetes provider, using the same CLI as any ## GitLab 19.3 released DevFeed: [GitLab 19.3 released]() Original publisher: [Read original article]() Author: GitLab Published: 2026-08-20T00:00:00Z Content type: release Language: en Sources: [GitLab]() Topics: [GitLab](), [Release notes](), [Artificial Intelligence](), [CI/CD](), [YAML](), [audit trail](), [Authorization](), [Command-line interface]() Tags: [agent](), [ai](), [audit-trail](), [ci-cd](), [command-line](), [release](), [release-notes](), [secrets]() ### AI overview GitLab 19.3 release notes describe the Flow Creator foundational agent, which generates runnable flow YAML through plain-language conversation and can help debug flows and explain framework concepts. The release also introduces GitLab Secrets Manager in Limited Availability on GitLab.com, with scoped credentials, existing permission integration, and audit-trail logging. ### Source excerpt GitLab 19.3 released with Flow Creator foundational agent ## Coding Challenge #131 - Automated Code Review Agent DevFeed: [Coding Challenge #131 - Automated Code Review Agent]() Original publisher: [Read original article]() Author: John Crickett Published: 2026-08-15T08:01:51Z Content type: tutorial Language: en Sources: [Coding Challenges]() Topics: [Code Challenge](), [GitHub Copilot code review](), [pull-requests](), [Pull Request](), [Orchestration](), [GitHub](), [Artificial Intelligence](), [YAML](), [engineering-culture]() Tags: [agent](), [ai](), [automated](), [code-review](), [coding](), [collaboration](), [github](), [orchestration](), [pull-request](), [run](), [tools](), [triggers](), [workflow](), [yaml]() ### AI overview Coding Challenge #131 asks readers to build an automated code review agent that reviews pull requests against team coding guidelines and posts findings as comments. The challenge covers retries, event triggers, concurrency control, large pull requests, static analysis tools, and lookup capabilities. ### Source excerpt This challenge is to build your own code review agent. ## Compress netlab Lab Topologies with Dot Notation DevFeed: [Compress netlab Lab Topologies with Dot Notation]() Original publisher: [Read original article]() Published: 2026-08-12T05:55:00Z Content type: article Language: en Sources: [ipSpace.net blog]() Topics: [Python](), [YAML](), [BGP]() Tags: [bgp](), [blog](), [blog-post](), [netlab](), [post](), [python]() ### AI overview An article about using Python Box dotted notation to make netlab lab topology definitions easier to read and more concise, including examples in YAML for BGP routers and IPv4 links. ### Source excerpt netlab is using the Python Box library to make the code easier to read1. When I started the project, I hated the way you fetch values from Python dictionaries with stuff like node['ospf']['area']; Python Box lets you write node.ospf.area. Even better2, you can tell Python Box to create intermediate dictionaries as needed. node.ospf.area = 1 will automatically create the node.ospf dictionary. But wait, there's more (yes, we're getting to the topic of today's blog post): Box lets you use the same dotted notation in YAML files. Read more ... ## Generating AI Descriptions of Automated Pull Requests DevFeed: [Generating AI Descriptions of Automated Pull Requests]() Original publisher: [Read original article]() Author: Daniel Doubrovkine (dblock@dblock.org) Published: 2026-08-11T00:00:00Z Content type: tutorial Language: en Sources: [Daniel Doubrovkine]() Topics: [GitHub Copilot CLI](), [GitHub Actions](), [GitHub Copilot](), [Large Language Model](), [Ruby](), [Slack](), [changelog](), [Pull Request](), [Open Source](), [JSON](), [YAML]() Tags: [ai](), [automated](), [changelog](), [ci](), [cli](), [copilot](), [github](), [github-actions](), [github-copilot](), [github-copilot-cli](), [json](), [llm](), [open-source](), [pull-request](), [pull-requests](), [ruby](), [yaml]() ### AI overview A tutorial explains how the maintainer of the slack-ruby-client library uses a scheduled GitHub Actions workflow and GitHub Copilot CLI to generate meaningful commit messages, pull request bodies, and CHANGELOG entries from diffs of regenerated Slack API code. It also covers YAML indentation, prompt files, response logging, and extracting a JSON result from Copilot CLI output. ### Source excerpt The slack-ruby-client library, an open source Ruby gem I maintain, runs a scheduled GitHub Actions workflow that regenerates code from Slack's API definitions and opens a pull request with the diff. The commit message and CHANGELOG entry used to be a generic "Update API (2026-08-11)", which told a reviewer nothing about what actually changed. Here's how we taught the workflow to describe its own diffs, using GitHub Copilot CLI, which open source maintainers can get for free. The Idea The workflow already computes a diff before opening the pull request. Instead of a boilerplate commit message, we pipe that diff through an LLM and ask it to summarize what changed, then use the response as the commit message and PR body. - name: Check for changes id: changes run: | if git diff --quiet; then echo "changed=false" >> "$GITHUB_OUTPUT" else echo "changed=true" >> "$GITHUB_OUTPUT" fi - name: Prepare diff for AI summary if: steps.changes.outputs.changed == 'true' run: | git diff --stat | sed 's/^/ /' > /tmp/diff_stat.txt git diff | head -c 20000 | sed 's/^/ /' > /tmp/diff.txt The sed 's/^/ /' indent isn't decorative. actions/ai-inference substitutes template variables as raw text into a prompt YAML file before parsing it, so a multi-line diff starting at column 0 breaks the indentation of the enclosing content: |- block scalar. Pre-indenting the file to match keeps the YAML valid no matter what the diff looks like. The Prompt File actions/ai-inference supports .prompt.yml files, a small convention for keeping the system/user prompt out of the workflow YAML. messages: - role: system content: |- You write CHANGELOG entries describing an automated API update to slack-ruby-client, a Ruby gem whose Web API endpoint methods, argument validations, specs, and bin commands are code-generated from vendored Slack API method definitions (via a git submodule and rake task). Given a diffstat and a diff of the regenerated files, respond with ONLY a single JSON object (no markdown code fence ## YAML for DevOps Beginners, Syntax, Rules and Common Mistakes DevFeed: [YAML for DevOps Beginners, Syntax, Rules and Common Mistakes]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-08-06T17:16:19Z Content type: tutorial Language: en Sources: [Kubernetes - KodeKloud Blog | DevOps, Cloud, Kubernetes, AI Tutorials & More]() Topics: [YAML](), [configuration](), [DevOps](), [Ansible](), [ci](), [Kubernetes]() Tags: [ansible](), [block-scalars](), [ci-cd](), [cloud](), [configuration](), [devops](), [errors](), [guide](), [how-to](), [json](), [kubernetes](), [kubernetes-yaml-manifests](), [linter](), [mistakes](), [multi-document-yaml](), [structure](), [syntax](), [validation](), [yaml](), [yaml-anchors-and-aliases](), [yaml-common-mistakes](), [yaml-for-devops](), [yaml-indentation-rules](), [yaml-norway-problem](), [yaml-syntax-rules](), [yaml-vs-json](), [yamllint-validation]() ### AI overview A tutorial explaining YAML syntax, implicit typing, indentation rules, block scalars, anchors, aliases, and merge keys. It emphasizes that YAML can silently reinterpret unquoted values and recommends linting and schema validation in CI pipelines. ### Source excerpt YAML tries to guess what you meant, and that is the entire problem. Once you know which values it silently reinterprets and why, the manifests that mysteriously break stop being mysterious. ## 2026.8: Approachable by design DevFeed: [2026.8: Approachable by design]() Original publisher: [Read original article]() Author: Ashley Abbott Published: 2026-08-05T00:00:00Z Content type: release Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [releases](), [Operating system](), [YAML](), [Cloud](), [Template]() Tags: [2026](), [core](), [esphome](), [live-stream](), [os](), [release-notes](), [releases](), [smart-home](), [youtube]() ### AI overview Home Assistant 2026.8 is a release focused on making the platform more approachable for users without technical expertise. It introduces improvements to installation, configuration, device handling, cloud exploration, entity IDs, templates, triggers, conditions, media search, and integrations. ### Source excerpt Tip Don't forget to join our release party live stream on YouTube on August 5, 2026, at 20:00 GMT / 12:00 PT / 21:00 CET! Tip There's more to look forward to next week: the ESPHome Starter Kit is launching, and you're invited to the official launch party! 🚀 Join the ESPHome team and their partners at Apollo Automation on the ESPHome YouTube channel on August 12 at 21:00 CEST. Familiar faces are dropping by to celebrate lift-off, too: Reed from Smart Home Solver, Simon from Simon Says Home Assistant, and Gavin from HomeTech.fm. Home Assistant 2026.8! 🎉 Hi, I'm Ashley, the Technical Program Manager at the Open Home Foundation. With Frenck taking a well-deserved break, Bram and I are teaming up to handle things this time around. We have been working on a lot over the past few weeks, and I'm excited to share some of what we have done for this release! If there's one thread tying this release together, it's a direction we care about: making Home Assistant something you don't need to be technical to use. This release is another step along that path. Enjoy the release! - Ashley Making Home Assistant more approachable The same Home Assistant, minus the magic number Your current setup keeps working Want to change the port? We've got you covered What this means for YAML Less "advanced", more approachable Describing the feature, not the user Just Tools, no developer required Home Assistant Cloud, now easier to explore Your entity IDs, your choice A cleaner way to handle your devices We can't stop adding triggers and conditions Integrations New integrations Noteworthy improvements to existing integrations Integration quality scale achievements Now available to set up from the UI Farewell to the following Other noteworthy changes Tell us how setup went A roomier template editor Taps that land where you mean them A combined battery level you can trust Search your media Find your favorite cards faster Z-Wave lock credentials, properly managed And a few more Patch releases 2026.8.1 ## Mastering PostgreSQL Configuration Management with CloudNativePG (CNPG) DevFeed: [Mastering PostgreSQL Configuration Management with CloudNativePG (CNPG)]() Original publisher: [Read original article]() Author: Wellingtone Luvonga Published: 2026-08-04T05:00:38Z Content type: tutorial Language: en Sources: [CYBERTEC PostgreSQL | Services & Support]() Topics: [configuration](), [PostgreSQL](), [postgresql clusters](), [Kubernetes](), [GitOps](), [YAML](), [kubectl]() Tags: [administration](), [cloudnativepg](), [configuration](), [configuration-management](), [gitops](), [how-to](), [kubectl](), [kubernetes](), [postgresql](), [replication](), [yaml]() ### AI overview This tutorial explains how CloudNativePG manages PostgreSQL configuration in Kubernetes. It contrasts imperative editing of configuration files with declarative management through Kubernetes YAML and shows how to define database parameters and pg_hba.conf rules in a CNPG cluster resource. ### Source excerpt This blog talks about Configuration Management in PostgreSQL with CNPG, with some great examples in a comprehensive way. The post Mastering PostgreSQL Configuration Management with CloudNativePG (CNPG) appeared first on CYBERTEC PostgreSQL | Services & Support. ## What is Ansible? DevFeed: [What is Ansible?]() Original publisher: [Read original article]() Author: Roger Perkin Published: 2026-07-23T18:25:09Z Content type: tutorial Language: en Sources: [Roger Perkin Network Automation Consultant]() Topics: [Ansible](), [Automation](), [configuration](), [Network](), [Open Source](), [ssh](), [YAML](), [Server]() Tags: [ansible](), [applications](), [automation](), [configuration](), [faq](), [network](), [open-source](), [servers](), [ssh](), [tasks](), [yaml]() ### AI overview Ansible is an open-source, agentless IT automation tool for configuring systems, deploying applications, and managing network devices. It uses human-readable YAML playbooks and connects through SSH to automate repetitive changes across routers, switches, and servers. ### Source excerpt Ansible is an open-source IT automation tool that configures systems, deploys applications, and manages network devices using simple, human-readable YAML files called playbooks. It's agentless, connecting via SSH, and widely used by network engineers to automate repetitive tasks like configuration changes across routers, switches, and servers at scale. ## How to scale GitOps in the enterprise: From single cluster to fleet management DevFeed: [How to scale GitOps in the enterprise: From single cluster to fleet management]() Original publisher: [Read original article]() Author: Artem Lajko Published: 2026-07-23T05:40:01Z Content type: tutorial Language: en Sources: [Platform Engineering Blog]() Topics: [GitOps](), [Tooling](), [Git](), [YAML](), [flux]() Tags: [complexity](), [config](), [deployment](), [developers](), [git](), [guide](), [helm](), [how-to](), [kubectl](), [learn](), [operational](), [platform](), [reconciliation](), [scale](), [secrets](), [secrets-management](), [workflow](), [workflows]() ### AI overview This guide explains how to scale GitOps from a single cluster to enterprise fleet management across 50 or more clusters. It focuses on architectural patterns, state store strategies, multi-cluster topology, secrets and policy management, configuration sprawl, repository performance, reconciliation delays, and the organizational discipline required for reliable operations. ### Source excerpt Learn how to scale GitOps from 1 to 50+ clusters using advanced state store patterns (OCI, ConfigHub), multi-cluster topology, and enterprise secrets/policy management ## Scaling Kubernetes governance: A platform engineer's guide to Kyverno and CEL DevFeed: [Scaling Kubernetes governance: A platform engineer's guide to Kyverno and CEL]() Original publisher: [Read original article]() Author: Koray Oksay Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Kubernetes](), [Platform Engineering](), [Security](), [developer velocity](), [Containers](), [supply-chain-security](), [YAML](), [opa](), [rego]() Tags: [common-expression-language](), [compliance](), [container-images](), [containers](), [cosign](), [deployment](), [developer-velocity](), [governance](), [hipaa](), [integration](), [kubernetes](), [kyverno](), [pci-dss](), [platform](), [policy](), [security](), [security-policies](), [sigstore](), [soc-2](), [supply-chain-security]() ### AI overview A guide to using Kyverno and its Common Expression Language support for Kubernetes governance. It explains how platform engineering teams can enforce policies, automate resource changes, generate resources, verify image signatures, and maintain security and compliance while preserving developer velocity. ### Source excerpt Kyverno with CEL support provides Policy-as-Code for Kubernetes governance. Enforce security, automate guardrails, and boost developer velocity for platform engineering teams. ## kPointer Replaces cw-json with Support for JSON, YAML, HTML, and XML DevFeed: [kPointer Replaces cw-json with Support for JSON, YAML, HTML, and XML]() Original publisher: [Read original article]() Author: CommonsWare Published: 2026-07-22T12:27:15Z Content type: release Language: en Sources: [The CommonsBlog]() Topics: [data](), [JSON](), [YAML](), [HTML](), [XML](), [Command-line interface](), [test]() Tags: [blog](), [cli](), [data](), [html](), [json](), [sdk](), [test](), [testing](), [xml](), [yaml]() ### AI overview kPointer replaces cw-json as a library for extracting values from structured data. It supports JSON, YAML, HTML, and XML through adapter-style abstractions, adds JavaScript access path notation, and includes conformance testing and a CLI. ### Source excerpt The cw-json project has been replaced by kPointer -- learn what kPointer offers! ## How to Troubleshoot and Debug Ansible Playbooks DevFeed: [How to Troubleshoot and Debug Ansible Playbooks]() Original publisher: [Read original article]() Author: Mrinalini Sugosh Published: 2026-07-15T00:00:00Z Content type: tutorial Language: en Sources: [Harness Blog]() Topics: [Ansible](), [debugging](), [Infrastructure as code](), [YAML]() Tags: [ansible](), [debugging](), [how-to](), [iac](), [infrastructure-as-code](), [troubleshooting](), [yaml]() ### AI overview This tutorial explains how to troubleshoot and debug Ansible playbooks. It covers structured and conditional debugging, verbosity controls, targeted variable inspection, reusable debugging roles, failure taxonomies, and CI/CD-friendly logging. It also describes common problems such as syntax errors, variable conflicts, connection errors, and inconsistent execution across hosts. ### Source excerpt Master how to debug Ansible with expert tips for troubleshooting playbooks. Learn structured debugging, reduce errors, and streamline Infrastructure Deployments | Blog ## OpenTelemetry Spring Boot Starter Adds Declarative YAML Configuration in Version 2.26.0 DevFeed: [OpenTelemetry Spring Boot Starter Adds Declarative YAML Configuration in Version 2.26.0]() Original publisher: [Read original article]() Author: OpenTelemetry Authors; Docs CC BY Published: 2026-07-14T07:47:36Z Content type: article Language: en Sources: [Blog on OpenTelemetry]() Topics: [OpenTelemetry](), [Spring Boot](), [YAML](), [configuration](), [Environment Variables](), [telemetry](), [tracing]() Tags: [configuration](), [environment](), [java](), [opentelemetry](), [schema](), [setup](), [spring-boot](), [telemetry](), [traces](), [yaml]() ### AI overview The article explains how declarative configuration in the OpenTelemetry Spring Boot starter, available from version 2.26.0, embeds the SDK's YAML schema in application.yaml. It contrasts this approach with environment-variable configuration and describes how the YAML schema can represent telemetry pipelines and options beyond the fixed environment-variable catalog. ### Source excerpt The OpenTelemetry Spring Boot starter gained declarative-configuration support starting in version 2.26.0 -- the same YAML schema the Java agent introduced in late 2025, now embedded inside application.yaml. This post traces what one env var, OTEL_SERVICE_NAME=petclinic, does in that new world, and where the seams are. In a hurry? Jump straight to the Spring Boot starter declarative-config docs, paste your application.properties into the interactive converter, or pick your SDK setup in the Ecosystem Explorer with the Spring Boot starter target selected. Come back for the story when you have a coffee. ## Kubernetes Dashboard to Headlamp: A Step-by-Step Guide DevFeed: [Kubernetes Dashboard to Headlamp: A Step-by-Step Guide]() Original publisher: [Read original article]() Author: Vincent T Published: 2026-07-13T18:00:00Z Content type: tutorial Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [dashboards](), [migration](), [Web app](), [client](), [API](), [YAML](), [Authorization]() Tags: [api](), [app](), [debug](), [dev](), [features](), [forms](), [guide](), [kubernetes](), [logs](), [migration](), [resources](), [scale](), [tokens](), [ui](), [web]() ### AI overview A step-by-step guide to moving from Kubernetes Dashboard to Headlamp. It compares their deployment models, authentication, permissions, resource-management workflows, and multi-cluster capabilities, then introduces a pre-migration checklist. ### Source excerpt 1. Before you start: know what is changing Kubernetes Dashboard and Headlamp both show what is running in a cluster, but they work differently. When Headlamp runs on the desktop, it uses your existing kubeconfig to connect to one or more clusters and can be extended with plugins. When Headlamp runs inside a cluster, it uses a Kubernetes ServiceAccount to access the API and follow RBAC rules. Kubernetes Dashboard, in contrast, only runs in-cluster and always relies on service account tokens. Understanding these models early helps you choose the right setup and permissions. 1.1 How Kubernetes Dashboard works Dashboard is a web app that runs inside your cluster. You install it in the cluster, often with Helm. You usually run one Dashboard per cluster. You often reach it with kubectl port-forward or an ingress. You log in with a Bearer token. That token is often from a service account. It includes forms that help you create resources. It leans on tables and lists for navigation. It feels like this: a UI that lives with the cluster. 1.2 How Headlamp works Headlamp acts more like a Kubernetes client with a UI. It can run on your desktop or in a cluster. It reads your kubeconfig, like kubectl does. It can show more than one cluster in one place. It favors YAML when you create or change resources. It includes list views and a visual map. You can add features with plugins. Headlamp is a UI that follows your identity, not your cluster. 1.3 What stays the same Many workflows will feel familiar: Browse workloads and resources Filter by namespace Inspect YAML, events, and status View logs Take actions your RBAC allows 1.4 What changes A few things will feel different: Login shifts from pasted tokens to kubeconfig (and sometimes SSO). Creation shifts from forms to "apply YAML." Multi-cluster becomes normal, not a special case. The map view helps you see how resources connect. 2. Pre-migration checklist This checklist helps you avoid surprises during the switch. It makes sure Head ## Rebuilding the CircleCI CLI from scratch DevFeed: [Rebuilding the CircleCI CLI from scratch]() Original publisher: [Read original article]() Author: Pete Steyert-Woods Published: 2026-07-07T16:00:00Z Content type: article Language: en Sources: [The CircleCI Blog Feed | CircleCI]() Topics: [Command-line interface](), [Go Language](), [MCP Server](), [OAuth](), [Text-based user interface](), [debugging](), [telemetry](), [configuration](), [YAML](), [AI-assisted coding]() Tags: [ai-development](), [ci](), [circleci-cli](), [cli](), [coding-agents](), [configuration](), [debugging](), [developer-tools](), [go](), [mcp](), [mcp-server](), [oauth](), [terminal](), [yaml]() ### AI overview CircleCI rebuilt its CLI from scratch in Go, focusing on human-first terminal output, predictable JSON, stable exit codes, browser OAuth login, debugging features, and an MCP server for coding agents. ### Source excerpt We rebuilt the CircleCI CLI from the ground up in Go: human-first output, -json everywhere, browser OAuth login, a built-in debugging TUI, and an MCP server for your coding agent. ## Stream Oracle changes to ClickHouse in real time DevFeed: [Stream Oracle changes to ClickHouse in real time]() Original publisher: [Read original article]() Author: Prakhar Garg Published: 2026-07-07T00:00:00Z Content type: tutorial Language: en Sources: [Redpanda]() Topics: [clickhouse](), [Redpanda-Connect](), [Oracle Database](), [Kafka](), [real-time](), [data](), [Database](), [YAML]() Tags: [clickhouse](), [connectors](), [data](), [database](), [event](), [integration](), [kafka](), [oracle](), [pipeline](), [real-time](), [redpanda-connect](), [schema](), [yaml]() ### AI overview A hands-on walkthrough shows how to stream Oracle change data capture events through Redpanda Connect into ClickHouse in real time. It uses Oracle LogMiner and YAML-configured pipelines, with a Redpanda topic serving as an intermediate store before data is delivered to ClickHouse or other destinations. ### Source excerpt A hands-on walkthrough of the new Oracle input in Redpanda Connect. No Debezium, no Kafka Connect runtime, no JVM. [Next page]()