# YAML Published articles for YAML. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Dependabot version updates support Agent Package Manager DevFeed: [Dependabot version updates support Agent Package Manager]() Original publisher: [Read original article]() Author: Allison Published: 2026-11-03T20:24:07Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [Dependabot]() Tags: [agent](), [agent-skills](), [ai](), [apm](), [dependabot](), [dependencies](), [enterprise](), [github](), [github-enterprise-server](), [improvement](), [pull-requests](), [schedule](), [security](), [security-updates](), [supply-chain-security](), [version](), [yaml]() ### AI overview Dependabot can now update supported Git dependencies declared in an APM `apm.yml`: it opens pull requests and regenerates `apm.lock.yaml` when present. This covers version updates only, not security updates. To enable it, add an `apm` entry to `.github/dependabot.yml`, set the directory containing `apm.yml`, and choose a schedule. APM support is generally available on github.com across all GitHub plans and is planned for GitHub Enterprise Server 3.24. ### Source excerpt You can now keep your AI agent skills, prompts, and instructions up to date with Dependabot version updates for Agent Package Manager (APM). Dependabot opens pull requests to update supported... The post Dependabot version updates support Agent Package Manager appeared first on The GitHub Blog. ## Governance for your automation platform, in a git repo DevFeed: [Governance for your automation platform, in a git repo]() Original publisher: [Read original article]() Author: Ruben Fiszel Published: 2026-11-02T13:14:22.552503Z Content type: article Language: en Sources: [Windmill Blog]() Topics: [internal developer platform automation](), [CI/CD](), [Automation]() Tags: [account](), [admin](), [ai](), [app](), [apps](), [audit](), [automation](), [ci](), [enterprise](), [git](), [governance](), [governance-enterprise-infrastructure](), [identity](), [infrastructure](), [mapping](), [platform](), [protection](), [repo](), [roles](), [rules](), [run](), [windmill](), [yaml]() ### AI overview Windmill makes much of automation governance reviewable as YAML in git: instance files define identity integration, roles, worker configuration and package registries, while workspace files map groups to roles, set folder run-as defaults and control deployments. CI or instance tooling applies changes; dry runs, pull requests and audit logs support review. Jobs can run as configured service identities instead of the deploying user, and protection rules can require changes to reach production through reviewed paths. The post notes limits: some administration remains outside user files, and custom roles, SAML/SCIM, protection rulesets, the Kubernetes operator and full audit logs require Enterprise Edition; several workspace and runtime settings work on every edition. ### Source excerpt How do you keep who can do what, and what runs as whom, on an automation platform reviewable? In Windmill, roles, identity mapping, run-as rules and protection rulesets are YAML in git, applied by CI. ## PLGM Has Grown Up: A New UI and Many More Features DevFeed: [PLGM Has Grown Up: A New UI and Many More Features]() Original publisher: [Read original article]() Author: Daniel Almeida Published: 2026-10-29T14:57:09Z Content type: release Language: en Sources: [Percona]() Topics: [Tool](), [Test automation](), [Percona]() Tags: [analysis](), [benchmark](), [benchmarking](), [benchmarks](), [browser](), [charts](), [command-line](), [database-trends](), [featured](), [features](), [has](), [insight-for-dbas](), [insight-for-developers](), [load](), [mongodb](), [monitoring](), [open-source](), [percona](), [performance](), [queries](), [schema](), [test](), [tips](), [tool](), [ui](), [yaml]() ### AI overview PLGM lets teams benchmark MongoDB using their own schemas and queries, and its new web UI adds workload modeling, query analysis, run trends, and replay across multiple servers. After a run, it samples executed queries with explain--including fast queries--and reports scan efficiency, latency, workload impact, execution overhead, and available $lookup work. It can suggest indexes based on existing indexes, while labeling its efficiency score as a rule of thumb and treating recommendations as suggestions to test. Trends compare retained runs and flag insufficient data as not comparable. For fair server comparisons, PLGM can replay recorded operations or generate deterministic traffic; it can also convert MongoDB JSON logs or system.profile exports into recordings. Across two to eight servers, it checks document counts and indexes before running and compares live charts and per-operation outcomes. Writes are analyzed without rerunning the actual write, and $out/$merge pipelines are only planned. Recordings and outcome files contain real query values, and should be handled like production data. ### Source excerpt Back in December I introduced Percona Load Generator for MongoDB Clusters (PLGM), a benchmark tool built around one idea: test your database with your own schema and your own queries, not some random data. At the time, PLGM was a command-line tool. You edited a YAML file, ran the binary, and read the numbers in ... Continued The post PLGM Has Grown Up: A New UI and Many More Features appeared first on Percona. ## dbt Charts: a new open-source language for dashboards that live inside your dbt repo DevFeed: [dbt Charts: a new open-source language for dashboards that live inside your dbt repo]() Original publisher: [Read original article]() Author: Daniel Poppy Published: 2026-10-27T17:54:00Z Content type: news Language: en Sources: [dbt Labs]() Topics: [Data visualization](), [Open Source]() Tags: [ai](), [ai-agent](), [ai-tools](), [analytics](), [analytics-engineering](), [apache-2-0](), [branch](), [built-in](), [charts](), [conversational-ai](), [css](), [dashboards](), [dbt](), [deploy](), [language](), [learn](), [models](), [open-source](), [repo](), [version](), [yaml]() ### AI overview dbt Charts is an open-source YAML language for defining dashboards alongside dbt models. Its structure uses variables, queries, charts, and layout rows; a charts folder sits next to the models folder so changes can be versioned and deployed in the same Git branch and pass through the same tests. The language is Apache 2.0 licensed and can run locally with the dct CLI. A hosted service adds permissioning, sharing, a visual editor, version history, and conversational AI for building and editing dashboards. Its defaults include direct labels instead of legends, decimal-aligned support tables, and axis labels positioned to keep attention on recent data. The excerpt contrasts this code-centered approach with AI-generated dashboards that can vary in their technology and be difficult to trace to queries, and UI-first BI tools whose AI is described as limited in what it can change. ### Source excerpt dbt Charts is a plain YAML language for building dashboards that version and deploy alongside your dbt models. ## OneCodeReviewBench: Typed Decisions for Code Review and Search DevFeed: [OneCodeReviewBench: Typed Decisions for Code Review and Search]() Original publisher: [Read original article]() Author: Mohamad Mohebifar, Alex Bit Published: 2026-10-27T04:00:00Z Content type: article Language: en Sources: [arXiv: Software Engineering]() Topics: [Code review](), [ai code review](), [code search](), [Memory Safety](), [software security audit]() Tags: [bugs](), [code](), [code-review](), [cs-se](), [errors](), [languages](), [memory](), [memory-safety](), [model](), [openai](), [python](), [search](), [yaml]() ### AI overview OneCodeReviewBench evaluates bounded code-review decisions across 1,968 synthetic cases in 12 programming languages and YAML, using explicit contracts for runtime assumptions, source scope, and answer criteria. Among ten model-adapter systems, OpenAI Decisions scores 81.3% Boolean balanced accuracy; Kev-27B scores 76.8% Choice accuracy and 0.367 Score mean absolute error. A bounded Python import resolver matches all 40 references tested within its supported profile. The benchmark also includes raw symbol-search comparisons, engineer-reviewed cases, and a versioned artifact. Remaining reviewer disagreements and repaired inputs need resolution; transfer to repositories and matched latency and cost evaluation remain future work. ### Source excerpt arXiv:2610.33389v1 Announce Type: new Abstract: Code review requires finding functional bugs, memory-safety errors, security weaknesses, and performance problems across languages and software stacks. Tools can express bounded parts of this work as decisions about supplied code. We present OneCodeReviewBench, 1,968 synthetic cases across 12 programming languages and YAML, with Boolean, categorical, and ordered answers. Explicit contracts specify runtime assumptions, source scope, and answer criteria; separate evidence records support reference review. One author reviewed 150 cases; two additional engineers reviewed 100 of those cases. We compare ten model--adapter systems on the same cases and contracts: OpenAI Decisions reaches 81.3% Boolean balanced accuracy; Kev-27B reaches 76.8% Choice accuracy and Score mean absolute error of 0.367. Excluding two families with incomplete contracts preserves these leaders. Additional comparisons cover 586 cases with raw symbol search and 40 with a bounded Python import resolver; the resolver matches all 40 references within its supported profile. A versioned artifact reproduces these analyses and retains the 85 cases with matching engineer answers; the reported review subset excludes two incomplete-contract cases. Remaining reviewer disagreements and repaired inputs require resolution; repository-scale transfer and matched latency/cost evaluation remain future work. ## pnpm 12.16.0 DevFeed: [pnpm 12.16.0]() Original publisher: [Read original article]() Author: Zoltan Kochan Published: 2026-10-27T00:00:00Z Content type: release Language: en Sources: [pnpm]() Topics: [pnpm](), [.env](), [patches]() Tags: [flag](), [pnpm](), [security](), [setup](), [signing](), [updates](), [yaml](), [zstd]() ### AI overview pnpm 12.16.0 adds repeatable global `--env-file` loading: later files override earlier ones, existing environment variables stay intact, and loaded values are available to `.npmrc` interpolation and lifecycle scripts. `pnpm setup --no-modify-path` installs without changing shell, registry, or GitHub Actions path settings and prints lines users can add themselves. Symlinked lockfiles can be updated when their target is in configured directories. Security fixes address zstd decompression memory and allocation handling and timing leakage in signing. The release also makes installs respect changed store, linker, and related settings; improves registry resolution and package handling; and includes performance and reliability fixes. This overview reflects the supplied release notes, which list many additional changes. ### Source excerpt This release adds a global --env-file flag, updates to a symlinked pnpm-lock.yaml, and pnpm setup --no-modify-path. It also fixes two security issues, in zstd decompression and in signing. ## Actions Runner v2.338.2: Node 24 internal operations and broker connectivity probes DevFeed: [Actions Runner v2.338.2: Node 24 internal operations and broker connectivity probes]() Original publisher: [Read original article]() Author: github-actions\[bot\] Published: 2026-10-26T14:45:48Z Content type: release Language: en Sources: [GitHub Action Runners]() Topics: [self-hosted runner](), [GitHub](), [Dependabot](), [CI/CD]() Tags: [2026](), [actions](), [buildx](), [codeql](), [cryptography](), [dependabot](), [docker](), [dotnet](), [encoding](), [eslint](), [github](), [github-actions](), [node](), [node-js](), [repository](), [sdk](), [update](), [v2](), [version](), [yaml]() ### AI overview Actions Runner v2.338.2 updates dependencies and build tooling, adds broker-session and WebSocket probe changes, and moves internal operations to Node 24. The listed functional changes include accepting `$/` self-repository references in action manifests, including the owned session ID when deleting broker sessions, and implementing broker-listener WebSocket connectivity probes. The release also updates Docker, Buildx, the .NET SDK, and several JavaScript and .NET packages. Installation instructions provide packages for Windows x64 and arm64, macOS x64 and arm64, and Linux x64, arm64, and arm; Windows guidance recommends placing the runner folder at the drive root to help avoid permission and long-path issues. The notes state that releases roll out progressively, so availability may vary by enterprise, organization, or repository. ### Source excerpt What's Changed Bump @typescript-eslint/eslint-plugin from 8.67.0 to 8.68.0 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4661 chore: update Node versions by @github-actions[bot] in #4665 Bump browserslist from 4.28.5 to 4.28.9 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4677 Update Docker to v29.8.0 and Buildx to v0.37.0 by @github-actions[bot] in #4676 Update Node.js 20 removal date to September 23rd, 2026 by @salmanmkc in #4685 Bump @typescript-eslint/parser from 8.68.0 to 8.69.0 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4673 Bump Microsoft.DevTunnels.Connections from 1.3.51 to 1.3.56 by @dependabot[bot] in #4667 Bump github/codeql-action from 4.37.8 to 4.37.9 by @dependabot[bot] in #4664 Bump lint-staged from 17.3.0 to 17.5.0 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4663 Bump System.Formats.Asn1 and System.Security.Cryptography.Pkcs by @dependabot[bot] in #4688 Bump @typescript-eslint/parser from 8.69.0 to 8.70.0 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4705 Bump js-yaml from 4.3.1 to 4.3.2 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4696 Bump lint-staged from 17.5.0 to 17.5.1 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4715 chore: update Node versions by @github-actions[bot] in #4716 Bump github/codeql-action from 4.37.9 to 4.38.0 by @dependabot[bot] in #4713 Bump @typescript-eslint/eslint-plugin from 8.68.0 to 8.70.0 in /src/Misc/expressionFunc/hashFiles by @dependabot[bot] in #4714 Update Buildx to v0.37.1 by @github-actions[bot] in #4712 Bump System.Text.Encoding.CodePages from 10.0.11 to 10.0.12 by @dependabot[bot] in #4701 Update dotnet sdk to latest version @8.0.425 by @github-actions[bot] in #4717 Bump github/codeql-action from 4.38.0 to 4.38.1 by @dependabot[bot] in #4731 Update Docker to v29.8.1 by @github-actions[bot] in #4730 Accept $/ self-repository references in action manifests by @nodeselector in #4669 Bump Microsoft ## Building an AI Agent That Writes and Validates Kubernetes Manifests DevFeed: [Building an AI Agent That Writes and Validates Kubernetes Manifests]() Original publisher: [Read original article]() Author: Pramodh Kumar M Published: 2026-10-25T16:20:00Z Content type: tutorial Language: en Sources: [KodeKloud]() Topics: [AI Agent](), [Learning](), [rule-engine](), [Claude](), [CI/CD]() Tags: [agent](), [ai](), [ai-agent](), [ai-agents](), [build](), [building](), [cluster](), [devops](), [go](), [golang](), [kodekey](), [kubernetes](), [kubernetes-manifests](), [llm](), [models](), [platform-engineering](), [rules](), [yaml]() ### AI overview The tutorial builds a roughly 350-line Go agent that drafts Kubernetes manifests through KodeKey, checks them with `kubectl apply --dry-run=server`, and feeds validation or policy errors back to the model for up to three total attempts. Server-side dry runs validate against the live API server and return defaults without saving objects; unlike client-side checks, they require cluster access and permission to create the objects. Additional Go rules check namespace, replica count, image tags, resource requests and limits, readiness probes, and non-root settings, though they cover Deployments only and skip init containers. Once checks pass, the agent prints the manifest and waits for a person to type `y` before applying it, then watches workload rollout. These checks do not run the application or ensure the chosen image actually runs as non-root, so review remains necessary. The tutorial requires Go 1.26+, `kubectl`, a reachable test cluster, and a KodeKey API key; it recommends limiting credentials and considering Git review for team use. ### Source excerpt Models write YAML that looks right and is often wrong. Build a small Go agent in four rounds that checks its own manifests against the cluster and your rules, fixes them and waits for your yes. ## ZDI-26-787: NVIDIA Megatron Bridge YAML File Parsing Code Injection Remote Code Execution Vulnerability DevFeed: [ZDI-26-787: NVIDIA Megatron Bridge YAML File Parsing Code Injection Remote Code Execution Vulnerability]() Original publisher: [Read original article]() Published: 2026-10-22T05:00:00Z Content type: news Language: en Sources: [Zero Day Initiative]() Topics: [Exploit](), [file]() Tags: [2026](), [bridge](), [code](), [code-execution](), [code-injection](), [execution](), [exploit](), [file](), [interaction](), [malicious](), [megatron](), [nvidia](), [open](), [parsing](), [remote](), [remote-code-execution](), [remote-code-execution-vulnerability](), [required](), [vulnerability](), [yaml]() ### AI overview ZDI-26-787 (CVE-2026-24250) concerns NVIDIA Megatron Bridge's handling of model configuration files: a user-supplied string is used to execute Python code without proper validation, enabling arbitrary code execution as the current user. Exploitation requires user interaction, such as visiting a malicious page or opening a malicious file. ZDI assigned CVSS 7.8; NVIDIA has issued an update to address the vulnerability. ### Source excerpt This vulnerability allows remote attackers to execute arbitrary code on affected installations of NVIDIA Megatron Bridge. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The ZDI has assigned a CVSS rating of 7.8. The following CVEs are assigned: CVE-2026-24250. ## pnpm 12.15.0 DevFeed: [pnpm 12.15.0]() Original publisher: [Read original article]() Author: Zoltan Kochan Published: 2026-10-21T00:00:00Z Content type: release Language: en Sources: [pnpm]() Topics: [pnpm]() Tags: [aliases](), [archive](), [audit](), [bitbucket](), [branch](), [build](), [catalog](), [config](), [dependencies](), [deploy](), [files](), [include](), [install](), [pnpm](), [registry](), [release](), [responses](), [settings](), [yaml](), [zstd]() ### AI overview pnpm 12.15.0 adds delegated workspace configuration through `pnpm-workspace.yaml`'s `include` field, tar-based lockfile integrity, and support for registries serving uncompressed tar archives with gzip or zstd content coding. Tar registries use `serverType: pnpr`; zstd responses with windows larger than 8 MiB are rejected, and unpacked package files are capped at 4 GiB by default. `SOURCE_DATE_EPOCH` now bounds timestamps written by `pnpm deploy` and `pnpm install`, enabling repeatable output under the stated conditions. Security fixes reject registry metadata naming a different package (`ERR_PNPM_REGISTRY_NAME_MISMATCH`) and incomplete revision metadata. The release also improves dependency and peer resolution, frozen-lockfile checks, deploy behavior, and workspace installation performance. On a 12-core Mac, a warm-store install of 1,352 packages took 1.3 seconds versus 2.2 previously; `PNPM_MACOS_LINK_THREADS` changes the default of four linking threads, with `0` using the install's regular thread count. ### Source excerpt This release lets pnpm-workspace.yaml delegate settings to other files and config dependencies with include, adds lockfile.integrityTarget: tar and tar-registry support, accepts zstd-compressed registry responses, and honors SOURCE_DATE_EPOCH in pnpm deploy and pnpm install. It also rejects... ## CVE-2026-109413: Unbounded Recursion in the YAML Inline Lexer Lets a Single Document Crash the Process DevFeed: [CVE-2026-109413: Unbounded Recursion in the YAML Inline Lexer Lets a Single Document Crash the Process]() Original publisher: [Read original article]() Author: Fabien Potencier Published: 2026-10-15T08:00:00Z Content type: news Language: en Sources: [Symfony]() Topics: [cve remediation]() Tags: [cve](), [php](), [security](), [symfony](), [yaml]() ### AI overview A flaw in Symfony YAML's inline lexer allowed deeply nested collections to exhaust the stack and crash a process or trigger a fatal error. The issue affects specified Symfony YAML versions and code parsing untrusted YAML, including certain MapRequestPayload endpoints. Fixed versions bound inline collection nesting and raise a ParseException when the limit is exceeded. ### Source excerpt Affected versions Symfony YAML versions <5.4.54, >=6, <6.4.45, >=7, <7.4.18, >=8, <8.1.6 are affected by this security issue. The issue has been fixed in Symfony YAML 5.4.54, 6.4.45, 7.4.18, 8.1.6. Description Yaml\Parser::lexInlineStructure()... ## New in Symfony 8.2: Attribute-Based Workflows DevFeed: [New in Symfony 8.2: Attribute-Based Workflows]() Original publisher: [Read original article]() Author: Javier Eguiluz Published: 2026-10-14T07:16:00Z Content type: tutorial Language: en Sources: [Symfony]() Topics: [Symfony]() Tags: [audit-trail](), [class](), [enum](), [enums](), [php](), [symfony](), [workflow](), [yaml]() ### AI overview Symfony 8.2 adds PHP attributes for defining workflows, transitions, event listeners, and place metadata. The article demonstrates modeling a task state machine, using string-backed enums for places, and configuring guards and other workflow options. ### Source excerpt Contributed by Grรฉgoire Pineau in #61935... ## Perseid 0.1.0 is now available DevFeed: [Perseid 0.1.0 is now available]() Original publisher: [Read original article]() Published: 2026-10-14T00:00:00Z Content type: release Language: en Sources: [PostgreSQL news]() Topics: [Database Migration](), [versioning](), [constraintlayout]() Tags: [postgresql](), [schema](), [yaml]() ### AI overview Perseid 0.1.0, a successor to Pyrseas, is a set of utilities for versioning PostgreSQL database schemas. It provides tools to export schemas as YAML and generate or apply SQL to match a target database to a YAML specification. This release supports schemas, tables, columns, and constraints and requires PostgreSQL 17 or higher. ### Source excerpt I am very pleased to announce that, after a long hiatus, Perseid 0.1.0, a set of utilities for versioning PostgreSQL database schemas, has been released. Perseid 0.1.0 is available from: Codeberg Git repository: https://codeberg.org/perseas/perseid Documentation is available at: https://perseas.codeberg.page/perseid/ Perseid is the successor to Pyrseas. It provides dbtoyaml and yamltodb to extract a PostgreSQL database schema as YAML and to generate or apply SQL to bring a target database into agreement with a YAML specification. This initial release supports SQL SCHEMAs, TABLEs, COLUMNs and CONSTRAINTs. PostgreSQL 17 or higher is required. Many thanks to those who contributed code, ideas, and discussions to make this first release possible. Best wishes, Joe Abbate ## 2026.10: You are here ๐Ÿ“ DevFeed: [2026.10: You are here ๐Ÿ“]() Original publisher: [Read original article]() Author: Franck Nijhof Published: 2026-10-07T00:00:00Z Content type: release Language: en Sources: [Home Assistant]() Topics: [Home Assistant](), [YAML](), [MSP MCP](), [User interface design](), [Grafana]() Tags: [automation](), [core](), [home-assistant](), [release-notes](), [triggers](), [yaml]() ### AI overview Home Assistant 2026.10 adds a redesigned automation editor with easier trigger ID selection, updates its maps to use locally rendered OpenStreetMap vector tiles, and adds integrations and features across dashboards, Modbus, and AI connections. The release also documents backward-incompatible changes, including changes to authentication and several integrations. ### Source excerpt Home Assistant 2026.10! ๐ŸŽ‰ Last week, Nabu Casa dropped: Big Tech ruined the cloud, so we're renaming ours. Home Assistant Cloud is on its way to becoming Home Assistant Link. Same service, new name. I love that title, by the way. If you haven't read the story behind it yet, go have a look, and tell us what you think. The change is planned for the December release, so there is still time. ๐ŸŽ Now, I'll let you in on a secret: I'm an automation person. Dashboards are lovely and I admire everyone who builds a pretty one, but for me, automationsAutomations in Home Assistant allow you to automatically respond to things that happen in and around your home. [Learn more] are what make a smart home actually smart. So you can imagine how happy I am with what's in this release. One of the most powerful features you never thought you'd need has been sitting in Home Assistant for years: trigger IDs. Give your triggersA trigger is the part of an automation that makes the automation start when something specific happens, for example, when the sun sets, a door opens, or a button is pressed. [Learn more] an ID, and one automation can do the job of two, three, or five. It was also tucked away in a menu, you had to invent the IDs yourself, and then remember which was which. Plenty of you never found it, and that's on us. Not anymore. Trigger IDs finally get a proper UI: you check the triggers you want in the condition, and Home Assistant takes care of the IDs behind the scenes. And if you like writing your own IDs in YAMLYAML is a human-readable data serialization language. It is used to store and transmit data in a structured format. In Home Assistant, YAML is used for configuration, for example in the configuration.yaml or automations.yaml files. [Learn more], nothing changes. Those keep working exactly as before. That makes it my favorite of this release. ๐Ÿง  Don't get me wrong, the map is absolutely a cool feature too. Last release, every map in Home Assistant broke overnight when ou ## 7 Advanced Docker Compose Tricks to Clean Up Multi-Container Stacks in Linux DevFeed: [7 Advanced Docker Compose Tricks to Clean Up Multi-Container Stacks in Linux]() Original publisher: [Read original article]() Author: Ravi Saive Published: 2026-10-06T06:20:58Z Content type: tutorial Language: en Sources: [Tecmint: Linux Howtos, Tutorials & Guides]() Topics: [Docker Compose](), [Docker](), [CI/CD]() Tags: [compose](), [container](), [docker](), [docker-compose](), [docker-compose-profiles](), [docker-compose-tricks](), [docker-compose-watch](), [linux](), [yaml]() ### AI overview A tutorial explains seven built-in Docker Compose features for reducing duplicated configuration, managing service startup and optional services, splitting Compose files, syncing code during development, controlling overrides, and embedding configuration. It also covers validation and protecting secrets in environment files and configuration output. ### Source excerpt The post 7 Advanced Docker Compose Tricks to Clean Up Multi-Container Stacks in Linux first appeared on Tecmint: Linux Howtos, Tutorials & Guides . Most compose.yaml files slowly turn into long, copy-pasted blocks with fragile startup dependencies. Docker Compose includes several built-in features that The post 7 Advanced Docker Compose Tricks to Clean Up Multi-Container Stacks in Linux first appeared on Tecmint: Linux Howtos, Tutorials & Guides. ## From Upstream Changes to Downstream Confidence: Inside Torch Spyre's Integration with PyTorch CRCR DevFeed: [From Upstream Changes to Downstream Confidence: Inside Torch Spyre's Integration with PyTorch CRCR]() Original publisher: [Read original article]() Author: Mehant Kammakomati (IBM), Jewel K M (Red Hat), Anubhav Jana (IBM), Padmanabha Venkatagiri Seshadri (IBM) Published: 2026-09-30T13:40:56Z Content type: article Language: en Sources: [PyTorch]() Topics: [CI/CD](), [Continuous integration](), [PyTorch]() Tags: [blog](), [build](), [changes](), [ci](), [code](), [cuda](), [declarative](), [engineering](), [integration](), [pytorch](), [test](), [tests](), [upstream](), [workflow](), [yaml]() ### AI overview PyTorch's Cross-Repository CI Relay lets out-of-tree accelerator projects run downstream CI in response to upstream changes and report results to PyTorch reviewers. The article describes how Torch Spyre reached L2 integration using an agentic test-selection pipeline, a declarative YAML framework for adapting upstream tests without patching them, and workflows designed for reliability and reproducibility. The approaches are presented as reusable for other privateuse1 devices. ### Source excerpt TL;DR PyTorch's Cross-Repository CI Relay (CRCR) gives out-of-tree accelerators a clean, scalable way to plug into upstream CI - and it leaves each backend free to decide which of PyTorch's... ## NVIDIA launches an open platform for agent safety using OpenShell and Sentry DevFeed: [NVIDIA launches an open platform for agent safety using OpenShell and Sentry]() Original publisher: [Read original article]() Author: Asif Razzaq Published: 2026-09-28T19:21:25Z Content type: news Language: en Sources: [MarkTechPost]() Topics: [OpenShell](), [Docker Sandboxes](), [BlueField DPU](), [DOCA](), [NVIDIA Vera](), [Arm]() Tags: [agent-safety](), [agent-security](), [agentic-ai](), [ai-agents](), [ai-ethics](), [ai-governance](), [ai-shorts](), [applications](), [artificial-intelligence](), [docker](), [editors-pick](), [enterprise-ai](), [first](), [for-devs](), [hardware](), [harness](), [identity](), [implementation](), [infrastructure](), [new-releases](), [sandboxes](), [software-engineering](), [staff](), [tech-news](), [technology](), [yaml]() ### AI overview NVIDIA has launched an open reference design for securing AI agents outside the agents themselves. OpenShell runs agents in isolated sandboxes and applies policies to network access, credentials, filesystems, and processes. Sentry uses BlueField-4 DPUs to inspect requests and responses, verify identity, and enforce access controls. OpenShell is available under Apache 2.0 and is labeled alpha; Sentry's described deployment depends on BlueField-4 hardware. ### Source excerpt NVIDIA has launched the Open Agent Safety Platform, an open reference design that enforces AI agent safety outside the agent itself. OpenShell, an Apache 2.0 runtime, sandboxes agents under YAML policies. Sentry, an out-of-band watchdog on BlueField-4 DPUs, can quarantine an agent that escapes its boundary in milliseconds. NVIDIA says over 100 organizations are working with the platform. The post NVIDIA Launches Open Agent Safety Platform: OpenShell Sandboxes Agents on Vera CPUs While Sentry on BlueField-4 Quarantines Them in Milliseconds appeared first on MarkTechPost. ## Connection Refused, No Error, and How Kagent Finds It DevFeed: [Connection Refused, No Error, and How Kagent Finds It]() Original publisher: [Read original article]() Author: Nimesha Jinarajadasa Published: 2026-09-28T10:26:52Z Content type: tutorial Language: en Sources: [KodeKloud]() Topics: [K8Guard](), [OpenClaw](), [engineering-culture]() Tags: [ai-agent](), [debugging](), [devops](), [kagent](), [kubectl](), [kubernetes](), [logs](), [networking](), [open-source](), [pod](), [yaml]() ### AI overview The article explains how an open-source AI agent in a Kubernetes cluster can diagnose connection failures caused by a mismatch between a service's expected pod label and the labels actually assigned to the pods. Kagent runs Kubernetes commands to identify the mismatch and proposes a fix for the user to approve. ### Source excerpt Kagent is an open-source AI agent in your Kubernetes cluster. See how it finds a silent label mismatch that returns connection refused - with no error logged. ## Prefix Sets: Simplifying netlab ACLs and Prefix Filters DevFeed: [Prefix Sets: Simplifying netlab ACLs and Prefix Filters]() Original publisher: [Read original article]() Published: 2026-09-28T06:16:00Z Content type: tutorial Language: en Sources: [ipSpace]() Topics: [CIDR and subnets](), [Scapy]() Tags: [cisco](), [eos](), [ideas](), [ipv4](), [ipv6](), [netlab](), [prefix-lists](), [vlan](), [yaml]() ### AI overview The article describes a redesign of netlab's prefix filters and ACLs into generic prefix sets. The change allows lists of IPv4 and IPv6 addresses, prefixes, and object descriptors, reducing repetitive YAML and generating device configurations such as Arista EOS ACLs, Cisco IOS XR prefix sets, and prefix lists. ### Source excerpt When I implemented prefix filters in netlab (release 1.9.0), I wanted them to match the final device configurations as closely as possible, including the one prefix per entry rule to match the device configuration sequence numbers. That worked well, but resulted in YAML bloat, since each matching prefix requires several lines of YAML. We tried to use the same approach with ACLs but quickly gave up when we realized the port not in range operation requires multiple ACL entries on most platforms. With the matching sequence numbers paradigm gone with the wind, it made no sense to limit ourselves to one prefix per ACL entry - the initial ACL entry implementation already accepted lists of prefixes and expanded them into ACL entries. Read more ... ## How a Kubernetes YAML File Could Enable Google Cloud Organization-Wide Privilege Escalation DevFeed: [How a Kubernetes YAML File Could Enable Google Cloud Organization-Wide Privilege Escalation]() Original publisher: [Read original article]() Author: Sponsored by Varonis Published: 2026-09-23T14:01:11Z Content type: news Language: en Sources: [BleepingComputer]() Topics: [Security](), [Kubernetes](), [YAML](), [GitOps](), [Authorization](), [Google Cloud Platform (GCP)](), [Gke](), [Cloud](), [Google]() Tags: [computer-help](), [computer-security](), [computers](), [cybersecurity](), [gcp](), [gitops](), [google-cloud](), [google-kubernetes-engine](), [ibac](), [infosec](), [kubernetes](), [linux](), [mac](), [malware](), [malware-removal](), [permissions](), [privilege-escalation](), [security](), [spyware](), [support](), [tech-support](), [technical-support](), [varonis](), [virus](), [virus-removal](), [windows](), [yaml]() ### AI overview The document explains how Google Kubernetes Config Connector uses a controller and Workload Identity to manage Google Cloud resources without giving developers direct cloud credentials. Because the controller may hold broad organization-level permissions, a Kubernetes YAML resource could potentially enable organization-wide privilege escalation through a confused deputy flaw. ### Source excerpt A Kubernetes user with limited permissions can potentially gain control of an entire Google Cloud organization by exploiting the authority granted to Google Kubernetes Config Connector. Varonis explains how this confused deputy problem can turn a single Kubernetes YAML file into a path to organization-wide privilege escalation. [...] ## New in Symfony 8.2: JSON Schema for Configuration DevFeed: [New in Symfony 8.2: JSON Schema for Configuration]() Original publisher: [Read original article]() Author: Javier Eguiluz Published: 2026-09-23T07:07:00Z Content type: release Language: en Sources: [Symfony]() Topics: [Symfony](), [JSON Schema](), [YAML](), [configuration](), [ide]() Tags: [configuration](), [editor](), [ides](), [json-schema](), [symfony](), [validation](), [yaml]() ### AI overview Symfony 8.2 dynamically generates a JSON Schema for an application's YAML configuration by merging the configuration trees of its registered bundles. Editors can use the schema for autocomplete and validation, and Symfony's command can validate configuration in CI. ### Source excerpt Symfony 7.4 added JSON schemas for YAML files like services.yaml and routes.yaml, so IDEs can autocomplete and validate them. The files in config/packages/ weren't included and that's where you write or maintain most of your YAML config. Each bundle defines... ## AI-Assisted Vulnerability Discovery Should Become Part of Secure Software Development DevFeed: [AI-Assisted Vulnerability Discovery Should Become Part of Secure Software Development]() Original publisher: [Read original article]() Author: Sai Teja Erukude Published: 2026-09-22T17:07:45Z Content type: article Language: en Sources: [SD Times]() Topics: [ai security](), [Application Security](), [Vulnerabilities](), [Artificial Intelligence](), [AI-assisted coding](), [Exploit](), [Software Engineering](), [Language models]() Tags: [ai](), [analysis](), [code-review](), [language-models](), [remote-code-execution](), [remote-code-execution-vulnerability](), [secure-software](), [security-vulnerabilities](), [static-analysis](), [vulnerability](), [yaml]() ### AI overview The article argues that AI-assisted vulnerability discovery should complement static analysis, human review, and penetration testing in secure software development. It describes four remote code execution vulnerabilities found through an AI-assisted workflow and explains how language models helped connect code signals to testable exploit paths. ### Source excerpt When this AI security researcher confirmed an unauthenticated remote code execution vulnerability in OpenMed, the finding was not just another security bug. It showed how AI can help vulnerability researchers move from scattered code signals to a real, reproducible attack path. Software teams already use AI to write code, generate tests and summarize pull requests.... ... continue reading The post AI-Assisted Vulnerability Discovery Should Become Part of Secure Software Development appeared first on SD Times. ## A faster, more reliable GitHub Actions alternative: Run Actions on CircleCI DevFeed: [A faster, more reliable GitHub Actions alternative: Run Actions on CircleCI]() Original publisher: [Read original article]() Author: Jacob Schmitt Published: 2026-09-22T15:00:00Z Content type: release Language: en Sources: [CircleCI]() Topics: [GitHub Actions](), [CircleCI](), [CI/CD](), [Taskfile](), [Availability]() Tags: [ci-cd](), [circleci](), [circleci-news](), [github](), [github-actions](), [github-actions-alternative](), [github-actions-compatibility](), [github-actions-on-circleci](), [github-actions-outages](), [incident](), [integrations](), [queue](), [reliability](), [yaml]() ### AI overview CircleCI announces an open preview that runs existing GitHub Actions YAML directly on CircleCI. The company says the feature offers faster builds, shorter queue times, and an alternative to GitHub-hosted orchestration for standard Linux environments. ### Source excerpt GitHub Actions outages and queue times are pushing teams to look elsewhere. CircleCI now runs your existing GitHub Actions YAML directly, with 40% faster builds. ## How GitLab reduced code-per-agentic-flow ratio by 45% DevFeed: [How GitLab reduced code-per-agentic-flow ratio by 45%]() Original publisher: [Read original article]() Author: Mikolaj Wawrzyniak Published: 2026-09-22T00:00:00Z Content type: article Language: en Sources: [GitLab]() Topics: [GitLab](), [Artificial Intelligence](), [Langgraph](), [Orchestration](), [YAML](), [abstraction](), [Scalability](), [state-management](), [Code](), [implementation]() Tags: [abstraction](), [ai](), [ai-frameworks](), [bugs](), [complex](), [devsecops](), [engineering](), [features](), [gitlab](), [langgraph](), [orchestration](), [state-management](), [yaml]() ### AI overview GitLab describes Flow Registry, a component-based framework that compiles declarative YAML configurations into LangGraph flows for the GitLab Duo Agent Platform. Reusable components replace repetitive Python implementations and reduce GitLab's code-per-agentic-flow by 45%, while improving iteration speed, reliability, maintenance, and backward compatibility. ### Source excerpt GitLab Duo Agent Platform orchestrates and automates complex tasks through agentic flows. A key part of the platform is the Flow Registry, a declarative configuration framework, built from reusable components, that compiles YAML into fully functional LangGraph flows. By using Flow Registry, agent builders -- both our GitLab engineers and our customers can use declarative YAML configurations instead of repetitive, ad-hoc Python implementations. Flow Registry turns bespoke state management and agent wiring duplicated across agents into a set of reusable components and primitives available to agent builders. Using Flow Registry has reduced our own code-per-agentic-flow by 45%. What is this translating to? Faster iteration speed due to a declaration framework with reusable components and primitives. Increased reliability because one-off implementation mistakes and boilerplate bugs are handled on a component level. Lower maintenance cost because platform improvements are made once, but benefit all agents. Backward compatibility for our functionalities, for both our GitLab-authored foundational flows and also customers' custom flows, because of the abstraction layer. All of these benefits are available to customers orchestrating and building agents on GitLab Duo Agent Platform. In this article, we share the architectural principles and lessons from this effort and how to apply them in your environment. LangGraph as the foundation for GitLab Duo Agent Platform After releasing GitLab Duo Code Suggestions and Duo Chat, we dug into a then-novel technology, autonomous agents. We researched available AI frameworks and selected LangGraph, an agent runtime and low-level orchestration framework from LangChain, as the foundation for GitLab Duo Agent Platform. LangGraph's rich feature set, which includes a broad range of model adapters, durable execution, and traceability, combined with an excellent level of engineering autonomy, brought all the necessary building blocks we looked fo [Next page]()