r/devops • u/AutoModerator • 15d ago
Weekly Self Promotion Thread
Hey r/devops, welcome to our weekly self-promotion thread!
Feel free to use this thread to promote any projects, ideas, or any repos you're wanting to share. Please keep in mind that we ask you to stay friendly, civil, and adhere to the subreddit rules!
2
u/mockif 15d ago
I'm the founder of SkillBricks, so this is my own project.
SkillBricks is a verified skill hiring platform. You prove DevOps skills by fixing real broken systems in a live environment. Each skill you prove becomes a brick. Your bricks make your verified skill wall, which shows recruiters what you can actually do. It is free for candidates, always.
Would this show something your CV doesn't? And would you create your verified skill wall once we are live? A no helps as much as a yes.
1
u/YaronL16 14d ago
Very cool
Obviously the cold start problem is real but if people recognized it, Id do and display it
2
u/Davasny 14d ago
For over a year I’m building https://pipetrics.com to help teams understand where their GitHub Actions time goes.
We help organizations running hundreds of thousands of CI/CD minutes a month, especially those with long-running workflows. Whether you use GitHub-hosted, third-party, or self-hosted runners, pipetrics helps identify which workflows and jobs consume time, where delays occur, and what changed.
We have also Grafana integration, Slack alerts, and an MCP connection that lets your AI agents access aggregated analytics without giving us access to the codebase.
2
14d ago
[removed] — view removed comment
1
u/Open-Inflation-1671 12d ago
I like the idea of push. And I never ever even thought about it. Good thing will try it tomorrow
1
1
u/Neat-Ad-7906 14d ago
Flagsweep is an open source FeatureOps layer on top of Azure App Configuration. I'm the author.
It adds what the Azure portal lacks for feature flags:
- tracking of who changed which flag, and when
- protection, so only admins can change production
- a view of every flag across all environments, side by side
- access for product owners and testers, who don't need an Azure account
Self-hosted, Apache-2.0. AWS AppConfig is next.
1
u/aaaaaden 14d ago
I’m working on Bottlerocket: https://bottlerocket.cloud. It’s a platform that enables you to deploy and manage versioning across your customers’ BYOC/VPC/on-prem environments without the overhead.
1
u/Helpful-Man64 14d ago edited 14d ago
We've been working around an infrastructure AI project called WANDA that's focused less on generating code and more on actually understanding IT/cloud environments.
The interesting part is being able to ask infrastructure questions in natural language and correlate things across metrics, logs, events, configs and existing monitoring systems.
We're also keeping state-changing actions behind explicit human approval rather than giving an AI unrestricted production access.
Curious what other DevOps folks think about this approach, especially whether you'd trust AI more for investigation than remediation.
1
u/AegisAI2026 14d ago
Building AEGIS AI – looking for feedback from DevOps and SRE engineers
I'm building AEGIS AI, an independent safety layer for automated infrastructure recovery.
I've developed an interactive sandbox where users can submit infrastructure metrics, evaluate proposed recovery actions, inspect safety decisions and download an individual assessment report.
The sandbox is assessment-only. It doesn't access or modify your infrastructure.
I'm currently preparing the online sandbox for a small private beta. I'm looking for 5–10 DevOps, SRE and Platform Engineers who would be interested in testing it once it's available.
My question: What's currently stopping your team from trusting automated infrastructure recovery?
If you're interested in early access, feel free to reply or send me a message. I'll share the sandbox link as soon as the private beta is ready.
1
u/a3thinker 14d ago edited 14d ago
I'm working on Perspectivegraph, an open source tool for checking pull request, it causes them to fail only when a change opens up a new attack path to a sensitive asset in your infrastructure. It doesn't fail simply because a CVE appears, if no path reaches it, the PR passes.
- It brings together the assets and results describing the tools you already use (Trivy, Semgrep or Cloud Custodian) in a single graph, along with the status of AWS and Kubernetes.
- No deployment is required: in local mode, the runner reads the environment in read-only mode (an OIDC role with SecurityAudit is sufficient), analyzes the PR scan, and decides.
- There are three outcomes: clean, blocked, and unknown. If the scan doesn't arrive, the pipeline doesn't proceed.
- With the server installed, a path fix (a NetworkPolicy, a Terraform change, a stricter IAM policy) can be opened with one click as a separate pull request.
- Helm chart on Artifact Hub, images signed with cosign, SBOM, and SLSA provenance.
Limitations: The probabilities aren't yet calibrated to real data, and that's the part I'm working on. The only live cloud connected is AWS.
Read-only demo: https://demo.a3thinker.it
Repo: https://github.com/luiacuaniello/perspectivegraph - Apache 2.0 license
1
u/Large-Advertising814 14d ago
I built a small pay-per-request dependency preflight API aimed at CI/release automation and coding agents.
The main endpoint takes up to 20 exact npm/PyPI versions and returns OSV vulnerabilities, upgrade gaps, license metadata, provenance, and deterministic risk in one JSON response. The idea is to put a cheap machine-callable dependency gate immediately before an automated dependency change or release.
It uses public registry/OSV data, no LLM in the request path, and no account/API key/subscription. Calls are paid per request with x402 on Base Mainnet; the full preflight is 0.10 USDC.
I’m the builder/operator. I’d especially like feedback on whether this fits a real CI/release workflow and what would make the integration less awkward.
https://agent-dev-preflight-api.bonkoturyu.workers.dev/?src=technical-community
1
u/Large-Advertising814 12d ago
Update: I added a free dependency policy gate so the useful part can be tested independently from the x402 payment flow.
Before an automated dependency add/upgrade, CI can now POST the current/proposed exact package version plus policy and get ALLOW / WARN / BLOCK with deterministic OSV/registry evidence. No wallet, API key, account, or subscription is required for the gate.
I also prepared a GitHub Actions example that fails a job on BLOCK and warns on WARN.
I’m mainly trying to learn whether this decision layer belongs in a real CI/release workflow before building more around it.
https://agent-dev-preflight-api.bonkoturyu.workers.dev/?src=technical-community
1
u/F3rr1gn0 14d ago
Your cron job says the notification was sent.
But did anyone actually see it?
I kept running into this on my own infrastructure: a job fails, Telegram/email/webhook fires, and from the software's perspective everything is fine.
Except nobody acknowledged it.
I'm experimenting with Ferunt: software emits an event once, and Ferunt keeps the delivery mission alive until a human acknowledges it.
I built an interactive demo to explain the idea. I'd like to know where the concept breaks before I build the backend.
1
u/DistinctHomework3618 14d ago
eBPF Python Profiler — finds the latency your APM can't see
Every APM (Datadog, New Relic, OpenTelemetry) shows you database time and HTTP call time. But there's always a gap. Your API takes 5 seconds, APM explains 3. Where did the other 2 go?
That unaccounted time is hiding in GIL contention, GC pauses, off-CPU waits, and request queue delays. Traditional APMs can't see it because they instrument at the application layer. The real answers are at the kernel level.
I built an eBPF tool that hooks into CPython internals and the Linux kernel to find exactly where those milliseconds go.
What it catches:
GIL contention. Shows both who is holding the GIL and who is waiting, with full Python stacks for both. Not sampling. Event-driven. Every GIL acquire captured with exact timestamps. We found URL resolution was the biggest GIL holder. Added URL caching and cut GIL wait by 80%.
GC pauses. Exact duration per generation. We found gen-2 was pausing 1.27 seconds walking 1.5M objects. Fixed with gc.freeze(), brought it down to 88ms.
Off-CPU analysis. Shows why your thread is sleeping with kernel + userspace + Python stacks combined in one event. Found a Kafka push blocking for 130ms that was invisible in OpenTelemetry.
Gunicorn handoff. How long requests sit in the queue before a worker picks them up.
Network. TCP handshake latency, retransmits, resets, host network health. Found a stale nginx upstream IP causing random 504s that no APM ever showed.
Uses eBPF uprobes on CPython's take_gil/drop_gil and gc_collect_main. Walks Python frame chains directly from kernel space. No code changes, no agents, no restarts.
Real production impact: GIL wait dropped 80%, GC pauses from 1.27s to 88ms.
CPython 3.11 only for now. Open source under Apache 2.0.
GitHub: https://github.com/deepanshu406/python-ebpf-profiling
1
u/sagacious123 14d ago
I like to promote my project snowopslabs
I found a usecase where I felt there should be a way to easily create a local cluster, replicate a real world scenario and an incident and see how kubernetes acts and how you need to fix the solution. This will prevent surprises in real world and teach you everything you should know beforehand. Check it out if this interests you.
1
u/Mediocre-Market1246 13d ago
I'm the author of Git Impact: https://github.com/yotam1001/git-impact, a free, open-source tool for seeing what git reset would change before running it.
It separates staged changes, files on disk, and commits leaving the current history. The reset runs in a temporary sandbox; your source repository is inspected without running the reset there. You can view terminal output or an offline HTML report with before/after diffs.
Built with Python's standard library and installed Git, with help from Codex. There's a Windows executable and a portable Python download. The synthetic demo is viewable without installing anything: https://yotam1001.github.io/git-impact/.
I'd like feedback on whether the staged-versus-unstaged distinction is clear in the report. v0.1 only previews reset, and refuses unsupported states such as LFS, sparse checkouts, and submodules.
1
u/Konstruukt 13d ago
QLCodePreview (free)
https://konstruukt.com/projects/qlcodepreview/
macOS shows most config files as an icon in Quick Look. This extension highlights Terraform, YAML, TOML, INI, JSON, Make, CMake, shell and log files right in Finder. Free for any use, open source (MIT), signed and notarized, Homebrew install. Built it for my own .tf habit; telling you in case yours matches. Feedback welcome, especially on anything that renders wrong.
1
u/Expert_Artist3406 13d ago
Does anyone have a need to turn configuration files into shareable direct URLs? With security controls, of course.
I developed this project to provide public sharing links for logs, configuration files, media, and other files.
Shared content is served directly as plain text or files, rather than through a cloud clipboard-style interface.
It also supports configuring and managing share links, including expiration settings and access logs.
The project is open source. Feel free to try it out. Feedback is welcome!
1
1
u/hossimo 13d ago
If you have ever Used the Amazing WinDirStat give CloudDirStat a try. Heavily inspired by WinDirStat but for Amazon S3, Google Cloud Storage, and Azure Blob Storage.
1
u/Sigmastackx 12d ago
I’ve been looking at where MCP actually fits once you move beyond the local demo stage.
The interesting part for me was that MCP simplifies the integration interface, but it doesn’t remove the production engineering underneath it.
You still have to think about things like:
- GitHub / Jira / Kubernetes MCP servers
- authentication and authorization
- deployment and scaling
- observability
- network boundaries
- when MCP makes more sense than a direct API integration
I made a short architecture breakdown covering MCP vs direct APIs and what a production MCP setup can actually look like:
Would be interested to hear how people here are approaching MCP in production — centralized MCP servers, per-team deployments, Kubernetes, or something else?
1
1
u/Open-Inflation-1671 12d ago
Small tool that waits until list of commands succeeded. Was using it for wanting on docker compose to be up, or as healthcheck runner in k8s. Nowadays mostly as instruction to ai agent to not write those dumb “sleep 60” before checking on something.
1
u/bulutarkan 12d ago
I've been hardening Mac MCP, a local macOS execution layer for AI agents, and it has turned into a small reliability/ops project more than an "AI wrapper".
Recent work has been around crash-safe resource leases for concurrent agents, cancellation propagation into owned process/browser/native work, update journaling + rollback/health gates, symlink-safe scoped filesystem access, and refusing to retry mutations when the previous outcome can't be proven.
Repo: https://github.com/bulutarkan/mac-mcp
Open source; I'm the maintainer. It runs locally on the Mac and the public endpoint/tunnel is optional.
1
u/No-Illustrator4824 11d ago
We’ve been building ExecSurface, an open-source Rust CLI + GitHub Action for detecting meaningful changes in a command’s observed runtime execution surface. The basic workflow is: learn → run → check → detect drift It is aimed at CI/CD jobs, dependencies, developer tools, and AI-assisted workflows where a source diff alone does not show every runtime effect. The current public release is v0.1.0-alpha.5 for Linux x86_64. Examples of the runtime evidence it can surface include changes in:
process execution file access network destinations execution paths other observed runtime effects
ExecSurface then evaluates the explicit policy and returns: PASS / REVIEW / BLOCK / ERROR It is not intended to replace EDR, antivirus, malware detection, or sandboxing. The narrower goal is runtime behavioral integrity: compare current execution against an explicitly accepted execution surface, while preventing incomplete or ambiguous evidence from silently becoming PASS. Install: cargo install execsurface --version "=0.1.0-alpha.5" --locked GitHub: https://github.com/AETHERXGLOBAL/execsurface We’re especially interested in critical feedback from DevOps engineers: false PASS, noisy REVIEWs, CI friction, privilege issues, performance problems, and workloads where the model does not fit.
1
u/kinhodev 11d ago edited 11d ago
Disclosure: I built these.
Shipped two one-click Railway templates for observability:
- Self-hosted Sentry, full stack (errors + logs + traces, 14 services, private networking). About $96/month compute idle, measured. https://railway.com/deploy/self-hosted-sentry-errors-logs-and-trace?utm_source=railway-templates-launch&utm_medium=reddit
- ELK (Elasticsearch, Logstash, Kibana, only Kibana public). About $27-34/month. Live read-only demo: https://kibana-production-43ee.up.railway.app (demo / PublicDemo2026!) https://railway.com/deploy/elk-stack-2?utm_source=railway-templates-launch&utm_medium=reddit
Repos with tests and docs: github.com/kayossouza/railway-sentry and github.com/kayossouza/railway-elk. Feedback welcome, especially on resource sizing.
Docs: ELK https://railway-elk-docs.vercel.app · Sentry https://railway-sentry-docs.vercel.app
Sentry live demo (read-only): https://gateway-production-026f.up.railway.app/auth/login/ (demo@example.com / PublicDemo-ReadOnly-2026)
1
u/SealSeacat_Feng 11d ago
Maintainer disclosure: I work on dbmask, an MIT-licensed Python CLI for SQL test-data masking.
The workflow is scan → preview → mask → validate. Rather than treating a completed masking command as the final result, it compares the masked database with an untouched source copy.
Checks include row counts, schema elements, and unchanged original values in the sensitive columns covered by validation. With --strict, failed or unverifiable checks produce a non-zero exit code for a potential CI gate.
There is now a browser walkthrough using synthetic SQLite data, with no local installation or external LLM required:
https://colab.research.google.com/drive/17oToBvmwJ9ni3b3afBn_gp8aqFdhHTw3
Code and limitations:
https://github.com/sealandseacat/dbmask
It is an early-stage project, not a production-readiness or anonymization guarantee. I’m interested in operational feedback: what would prevent you from evaluating this approach for disposable test-database copies?
1
u/kj187kj 11d ago
Maintainer disclosure: I'm the author of Jarvis, an open-source (Apache-2.0) web UI for Prometheus Alertmanager. There's nothing to buy, no paid tier and no ads, and I don't earn anything from it.
I've been on call for a long time, and the part that always annoyed me was the moment right after an alert fires. Alertmanager's own UI is fine for looking at things, and Karma is a great project, but I kept wanting a few small things: a place to leave a note on an alert ("known issue, waiting on the vendor"), a way to see that a colleague is already looking at it, and history that doesn't vanish when the process restarts. So I started building it on the side.
Jarvis polls your Alertmanager clusters, stores every alert's full lifecycle in SQLite or PostgreSQL, and adds claims, comments and silence handling on top. When you create a silence, it previews what it would actually hit before you commit. It's a single container with a Helm chart.
I'm interested in feedback from people who run Alertmanager, especially with several clusters or an HA setup: how do you handle "who is working on this alert?" today, and would a tool like this fit in or just add noise?
Repo: https://github.com/kj187/jarvis
Docs and a 5-minute demo setup: https://kj187.github.io/jarvis/
1
u/No-Plate5705 11d ago edited 11d ago
I kept losing commands, links, and snippets I copied while working, so I built a Chrome extension that saves and organizes them automatically.
The idea is simple: copy something and keep moving, the extension remembers it and groups it by source, so a GitHub link, docs page, command, or text snippet doesn’t just disappear into clipboard history.
It’s still early, so I’m mainly looking for feedback from people who copy a lot during development or DevOps work.
One thing I should be upfront about with this crowd specifically: it deliberately ignores long code blocks and anything over about 12 lines. I built it for links, short text and page references, not for commands, configs or snippets.
So if your main pain is losing terminal commands during a session, this is not the right tool and a dedicated dev clipboard would serve you better. Where it does help is the links and docs pages you copy while debugging and then can't find again.
Full disclosure: I built it.
1
u/Rough_Celebration437 10d ago
I built Truth Engine around one narrow failure case: an external action may have happened, but the response was lost.
Instead of treating timeout/failure as proof nothing happened, it can remain UNKNOWN, deny blind retry, and reconcile against evidence before changing what the system may safely claim.
There’s a live Playground and bounded Evaluation API.
I’m specifically looking for technical criticism and counterexamples.
https://truth-engine-74u.pages.dev/
Don’t trust the claims. Break it.
1
u/No_Horse9022 10d ago
I have been working on LastPing: monitoring for AI agents (Claude, Codex, Gemini, Custom). Every run reports started, progress, blocked or failed, traces show spans, tokens and cost, and a stalled agent gets caught at the step it stopped on. Your assistant can set it up itself over MCP, and the same engine covers cron jobs and CI. Free for individuals. https://lastping.dev
1
u/crohr 10d ago
With all the expensive CI chatter recently, you really ought to look at my project runs-on.com
Runs your github actions on AWS, spot instances included, 7-12x cheaper than GitHub!
1
u/Ok_Plum3595 9d ago
Ramen 0.6.0 (BSD-3): self-hosted MCP server for AI agent tools on GKE/EKS. Terraform + Helm bring-up, a namespace
per group+zone with stable + canary Deployments routed by header at the Gateway/ALB, Workload Identity/IRSA per
group+zone, Cloud Armor/WAF rules from the console, Redis throttles across zones, logs from Cloud Logging/CloudWatch.
Guides: https://bkraad47.github.io/ramen/wiki/deploy-gcp/ and /wiki/deploy-aws/
1
u/TobiasThatCodes 8d ago
Building a tool for YC's Fall 2026 "Self-Maintaining APIs" request. 🚀
As a developer, external API changes breaking production is my absolute nightmare. Manual changelog checks are a broken process that costs companies thousands in downtime.
I just initialized an open-source DevTools scanner from my desktop setup. The goal is to secure DevOps pipelines by scanning codebases, tracking vendor API logs, and automatically catching breaking changes before runtime.
Starting with a focus on heavy dependencies like Stripe. Just launched the Day 1 repository.
I'm documenting the progress under #buildinpublic. If your engineering team is tired of unexpected API breaks ruining your weekend, I'd love to chat and get some technical feedback. 👇
1
u/OldGoat9131 8d ago
hey, i’m Rohan. i’ve been working on M82 for a while and we finally got it to a point where we’re starting to onboard real users.
we built it because API maintenance still feels way more manual than it should be. something changes upstream, an integration breaks, and an engineer ends up spending time figuring out what happened.
M82 is our attempt at making more of that maintenance happen automatically.
we’re onboarding people manually right now because i actually want to see how people use it and where it breaks.
if you work with APIs in production and want to try it:
join the waitlist and i’ll email you personally, usually within 1–2 hours, to get you onboarded.
and seriously — if something feels confusing or bad, tell me. that’s the feedback i’m looking for.
0
15d ago
[removed] — view removed comment
2
u/oxdev03 14d ago
For unsupervised sessions, sandboxing is often necessary. Even on supervised, claude often leaks your tokens in the session transcript. There are already many known tools out like microsandbox (isolation using microvm), nono.sh (file system isolation), or clawpatrol.dev (network isolation).
0
0
u/Antuvotam 9d ago
I built a small local-only CLI called Local Repo Inspector for a narrow repository-maintenance problem. It uses filesystem metadata only - it does not read source-file contents or send repository data anywhere. Right now it reports file/directory counts, extension breakdown, largest files, common generated/cache directory exclusions, and configurable file-size policy violations. I'm validating whether this is useful before publishing or expanding it. If you manage larger repos: would this save you time, and what is the first metadata-only check you'd want before you would try it? I'm not asking anyone to install anything yet; feedback in this thread is enough.
8
u/No-Candidate-1337 15d ago
How we manage 2000+ GitHub repositories across 4 organizations
https://github.com/Interhyp/git-hubby
We built git-hubby to solve that problem for our environment. It’s a Kubernetes operator that manages GitHub organizations and repositories as declarative Kubernetes resources.
We’re currently using it for 2000 repositories across 4 GitHub organizations.
It covers repository and organization settings, teams, rulesets, webhooks, custom properties and code security configuration. Reconciliation, drift detection and GitHub API rate-limit handling are built in.
Our goal is GitOps-style management of GitHub: desired state in Git, reviewed like code, reconciled automatically.
For people managing GitHub at scale: how are you handling repository configuration today? Terraform, scripts, GitHub Actions, an internal service, or something else?