How good is devops as a career?

So, currently I am working as a QA on a certain company. I am currently doing bachelors and will graduate this coming september of 2026. I am planning to choose devops as my career and will try to go abroad for further studies. How good is devops as a career and how hard it is to reach a certain good level? What is the market requirements for a DevOps intern? Can anyone help me with this?


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Cloudflare is down again

All I see is "500 Internal Server Error"... almost everywhere...

Is it just me?

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CycloneDX or SPDX

Hi everyone! We (BellSoft) are trying to determine which SBOM format to use for our hardened images. There are obvious considerations: SPDX is more about licenses, while CycloneDX is more about security.

But what we don't know - what actual people want/need/prefer to use.

So, here's the question: what do you need/use/want? And another one: which tools you are using support which format?

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How do you guys get into Cloud with no previous experience

Some things about me first.

I started out as a junior software engineer building websites. I found a lot of people were not paying so i decided to chase my other love, security and hacking. I tried the freelance thing for \~2 years.

Started a new job in a security operation center. The job was fun at the start, but as i kept learning more and getting more responsibilities i found out that it has nothing to do with what i had in mind, at least on in most companies in Greece. In the end of the day it was just us overselling other peoples products. But i build up a lot of experience in managing linux servers, elk stack, networking etc. I stayed on that job 2 years.

Then i got an offer from a friend to work as a sysadmin. There i got to work with backups, deploying new software, ansible, jenkins, hetzner(mostly managing dedicated servers), managed and installed dbs(mariadb), proxies, caches, self hosted emails, dns and a loooot in general. I also coded a lot in go and python which i loved. Stayed there 4+ years. Job was fine but the employer crossed a lot of lines that made people quit and the environment stopped being what it was.

Then due to all the knowledge i got from all these jobs i decided that i actually love what people called devops. And i chased that position next!

Now i have been working as a devops engineer for the past 5 years, working with kubernetes(all kinds of flavors), deploying with bamboo, automating a ton of stuff everyday, managing vms, dockerizing apps, deploying in all kinds of envornments, managing kafka clusters(mainly cdc via strimzi, sync via mm2) and lately been into using azure(foundry + ai search) to create agents that serve our documentation to users to improve on-boarding and generally assist people across all managerial positions that raise the same questions again and again or developers that needs specific environment info, how to's etc.

So whats all this intro about? Cloud is nowhere to be seen. Terraform is nowhere to be seen. ArgoCD is nowhere to be seen. And these are the big 3 right now in terms of wanted skills. I even made my own projects, used these tools, got certifications(AZ-900, AZ-104, terraform associate) but i never got to use them since i got them, so now i cant say that i even know anything. Its been 3 years since i got these. And i cant go around paying myself all the time to learn something that i wont get to use anytime soon.

My main problem is, how on earth do you get into these positions in any way other than taking a huge pay cut and start again from a lower position? Companies, at least where i live, do not seem to care for the fact that all that these are, are tools, and with the experience one carries will catch up fast, given some time.

You either got what they want, or you dont. And with devops evolving every other year(with AI/MLOps being the new shiny thing) how can you get into these areas if your company is not setup to use these tools and technologies? I wish i had enough money to throw around into new projects. But i dont. How do you guys manage to follow through the tech evolving and not stay behind? What has your experience been so far with getting into positions where you lack some of the knowledge the listing needs?

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Building a complete Terraform CI/CD pipeline with automated validation and security scanning

We recently moved our infrastructure team off laptop-based Terraform workflow. The solution was layered validation in CI/CD. Terraform fmt and validate run in pre-commit hooks. tflint catches quality issues and deprecated patterns during PR checks. tfsec blocks security misconfigurations like unencrypted buckets or overly permissive IAM policies. Then Conftest with OPA enforces organizational policies that used to live in wikis.

One key decision was using OIDC authentication instead of long-lived access keys. GitHub Actions authenticates directly to AWS without storing credentials. Every infrastructure change requires PR review, shows the plan output as a comment, and needs manual approval before apply runs.

Drift detection runs on a schedule and creates issues when it finds manual changes. Infracost posts cost estimates in PRs so expensive mistakes get caught during review. The entire pipeline uses open-source tools and works without Terraform Cloud.

Starting advice: don't enable every security rule at once. You'll get 100+ warnings and your team will ignore it. Start with HIGH severity findings, fix those, then tighten gradually.

I documented the complete setup with working GitHub Actions workflows and policy examples: Production Ready Terraform with Testing, Validation and CI/CD

What's your approach to Terraform governance and automated validation?

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How did you reduce testing overhead at your startup without sacrificing quality?

Our engineering team is 8 people and we're drowning in testing overhead. Between unit tests, integration tests, and e2e tests we're spending almost 30% of sprint time on testing related work (writing, maintaining, fixing flaky tests).

Don't get me wrong, i know testing is important and we've caught a lot of bugs before production. But the overhead is getting ridiculous, we're moving slower than our competitors because we're spending so much time on test maintenance.

Curious how other startups have tackled this, especially teams that scaled testing without adding dedicated qa headcount. Did you find better tools? Change your testing strategy? Just accept the overhead as cost of quality?

We're using playwright right now which is better than selenium but still requires constant maintenance. Every UI change breaks tests even with data-testid attributes. CI times are also getting long which slows down deployment velocity.

Looking for practical advice from people who've actually solved this not theoretical best practices. What worked for you?

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finally cut our CI/CD test time from 45min to 12min, here's how

We had 800 tests running in pipeline taking forever and failing randomly. Devs were ignoring test failures and just merging because nobody trusted the tests anymore

We tried a bunch of things that didn't work, parallelized more but hit resource limit, split tests into tiers but then we missed bugs, rewrote flaky tests but new ones kept appearing

What actually worked was rethinking our whole testing approach. Moved away from traditional selector-based testing for most functional tests because those were breaking constantly on ui changes and kept some integration tests for specific scenarios but changed the approach for the bulk of our test suite

We also implemented better test selection so we're not running everything on every pr. Risk based approach where we analyze what code changed and run relevant tests and full suite still runs on main branch and nightly

Pipeline now runs in about 12 min average and test failures actually mean something again. Devs trust them enough to investigate instead of just rerunning and it literally feel like we finally have a sustainable qa process in ci/cd

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Yea.. its DataDog again, how you cope with that?

So we got new bill, again over target. Ive seen this story over and over on this sub and each time it was:

- check what you dont need

- apply filters

- change retentions etc


—


Maybe, maybe this time someone will have some new ideas on how to tackle the issue on the broader range ?

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Hosting 20M+ Requests Daily

I’ve been reading the HN comments on the battle between Kubernetes and tools like Uncloud. It reminded me of a real story from my own experience, how I hosted 20m+ daily requests and thousands of WebSocket connections.

Once, some friends reached out and asked me to build a crypto mining pool very quickly ("yesterday"). The idea was that if it took off, we would earn enough to buy a Porsche within a month or two. (We almost made it, but that’s a story for another time.)

I threw together a working prototype in a week and asked them to bring in about 5 miners for testing. About 30 minutes later, 5 miners arrived. An hour later, there were 50. Two hours later, 200. By the next day, we had over 2000, ...

The absolute numbers might not look stunning, but you have to understand the behavior: every client polled our server every few seconds to check if their current block had been solved or if there was new work. On top of that, a single client could represent dozens of GPUs (and there were no batching or anything). All of this generated significant load.

By the time we hit 200 users, I was urgently writing a cache and simultaneously spinning up socket servers to broadcast tasks. I had absolutely no time for Kubernetes or similar beauty. From the moment of launch, everything ran on tmux ;-)

At the peak, I had 7 servers running. Each hosted a tmux session with about 8-10 panes.

Tmux acted not just as a multiplexer, but as a dashboard where I could instantly see the logs for every app. In case a server crashed, I wrote a custom noscript to automatically restore the session exactly as it was.

This configuration survived perfectly until the project eventually died.

Are there any lessons or conclusions here? Nope ;-) The whole thing came together by chance, didn't last as long as we’d hoped.

But ever since then, whenever I see a discussion about these kinds of tools, an old grandpa deep inside me wakes up, smiles, and says: "If I may..."



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Transition from backend to devops/infrastructure/platform

How did you transit from a backend to a platform/infra position?

I find myself really bored with developing backend business stuff. However I find myself really interested in the infrastructure side of things. K8s, containers, monitoring and observability. And each time I discover new tools, I feel really excited to try them out.

Also, it feels like the infra side of things have a lot of interesting problems and I gravitate towards these. How would I slowly transit towards these roles? I’m also thinking of studying and getting the CKA cert next year.

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Made a nifty helper noscript for acme.sh

I recently had trouble with user permissions while configuring slapd on alpine. So I made this little noscript called apit to "config"fy the installation of certs. It is just 100 lines of pure UNIX sh, and should work everywhere.

Sharing it here in the hopes it might be useful for someone.

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The Missing Foundation of Non-Human Identity

I’ve been working on an identity/authorization system for machines and kept getting stuck on a basic question: what is machine identity, independent of any one stack (Kubernetes, cloud, OAuth, etc.)?

This post proposes a simple model based on where identity originates (self-proven / attested / asserted), what privileges it has at birth, and how it lives over time (disposable vs durable). I’ve also mapped common systems like SSH, SPIFFE/SPIRE, API keys, IoT, and AI agents into it.

I’d be very interested in counterexamples, ways this breaks down in real systems, or prior art I’ve missed.

Here's the post: https://www.hessra.net/blog/the-missing-foundation-of-non-human-identity

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In AI/infra/devtools companies with usage-based pricing, who actually owns “adoption”?

In a lot of AI / infra / devtools products that charge by usage (requests, tokens, build minutes, cluster hours, etc.), there’s this blurry line after the deal is closed:

On paper, it looks like “someone on the post-sales side” owns adoption,
But in reality, I keep hearing about Solution Architects, Technical Account Managers, “technical success” folks, field engineers, SREs, and even core engineers getting dragged in when a key account’s usage isn’t where it’s supposed to be.

Sometimes usage is way below what was expected, sometimes it spikes in weird ways, sometimes it’s flat, but everyone feels something is off. And then suddenly there’s a Slack war room and a bunch of people with very different goals looking at the same graphs.

In your org (AI/infra/devtools, usage-based or pay-as-you-go):

When usage is clearly off for an important customer, who actually takes the lead on figuring out what’s going on and what to do about it, and what does that usually look like from your side?

Curious how this plays out in real life vs. how the org chart says it should.

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Job Switch

Currently working as a devops engineer and I like it a lot, been doing this for about 7-8 years. I want to switch into more backend/distributed systems but not sure what programming languages are best for this. I see it being split between Python & Go.

For anyone who has transitioned from Devops to BE/DSE or the other way around. What language would you say is best to learn ?

I’m trying to lock in for the next 12 months alongside grad school.

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Looking for developers

Hello Developers,

I’m a co-founder of Dayplay, an upcoming mobile app designed to help people quickly discover things to do—activities, local spots, events, hidden gems, and more. Our goal is to make finding something to do fast, easy, and fun.
We’re looking for a US-based full-stack developer with strong mobile app development skills to join our small founding team. We currently have two in-house devs, but one is going on leave due to personal reasons. Our MVP is 95% complete, and we’ll be launching on TestFlight for beta testers very soon. This role will have a big impact on the final stages of development and our early product growth.

About Dayplay
Dayplay is a mobile app built for quick decision-making. Users can instantly discover new places, activities, and experiences nearby through a clean, fast, and intuitive interface.

Who We’re Looking For
A well-rounded developer who can contribute across the stack and help push the mobile app to launch. Ideally someone with:
Full-stack experience (frontend + backend)
Strong mobile app development skills (React Native/Expo preferred)
Solid understanding of databases, APIs, and modern app architecture
Ability to move quickly, collaborate with a small team, and own tasks end-to-end
(If you want the full breakdown of the tech stack and responsibilities, feel free to DM me.)

Compensation
Compensation will be discussed directly and will be based on experience and expertise.



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I am so tired of debugging headless Chrome in Docker

I feel like I spend more time fixing my container setup than actually writing automation code. Getting a headless browser to run remotely without crashing from memory leaks is a huge pain. I just want to run my agent and have it work without spending a week on config files.

Has anyone found a way to just sandbox the whole thing? I am looking for something where I can just add a decorator or a simple command to handle the deployment side so I don't have to deal with the infrastructure mess.

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Introducing localplane: an all-in-one local workspace on Kubernetes with ArgoCD, Ingress and local domain support

Hello everyone,

I was working on some helm charts and I needed to test them with an ArgoCD, ingress, locally and with a domain name.

So, I made localplane:

https://github.com/brandonguigo/localplane

Basically, with one command, it’ll :
- create a kind cluster
- launch the cloud-provider-kind command
- Configure dnsmasq so every ingress are reachable under *.localplane
- Deploy ArgoCD locally with a local git repo to work in (and that can be synced with a remote git repository to be shared)
- delivers you a ready to use workspace that you can destroy / recreate at will

This tool, ultimately, can be used for a lot of things :
- testing a helm chart
- testing load response of a kubernetes hpa config
- provide a universal local dev environment for your team
- many more cool stuff…

If you want to play locally with Kubernetes in a GitOps manner, give it a try ;)

Let me know what you think about it.

PS: it’s a very very wip project, done quickly, so there might be bugs. Any contributions are welcome!


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API Schema Pollution: When Malformed Requests Break Your Entire Backend 🧩

https://instatunnel.my/blog/api-schema-pollution-when-malformed-requests-break-your-entire-backend

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How do you manage multiple chats and focus on your work

Initially I was allocated to a single project and was working in that project. For that project also there were like 5 chats. Dev Chat, DevOps chat, Support chat ( with support team ), Product chat ( with customers ) which is fine. But the problem is they were expecting a reply within few minutes, and If I don't due to some reason, they gonna raise a complain, which is actually toxic.

Now the problem is, recently I'm responsible for reply to chats with few other projects as well. So there are like 20 teams chats, and messages are popping up like in every few mins. We have 4 team members. But everyone is expected to do the same.

I'm a person who don't like frequent context switching and like to focus on one task at a time.

But this new approach is driving me crazy. What should I do. This frequent messages are adding more stress.

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Zerv – Dynamic versioning CLI that generates semantic versions from ANY git commit

TL;DR: Zerv automatically generates semantic version numbers from any git commit, handling pre-releases, dirty states, and multiple formats - perfect for CI/CD pipelines. Built in Rust, available on crates.io: `cargo install zerv`

Hey r/rust! I've been working on Zerv, a CLI tool written in Rust that automatically generates semantic versions from any git commit. It's designed to make version management in CI/CD pipelines effortless.



🚀 The Problem

Ever struggled with version numbers in your CI/CD pipeline? Zerv solves this by generating meaningful versions from **any git state** - clean releases, feature branches, dirty working directories, anything!



✨ Key Features

\- `zerv flow`: Opinionated, automated pre-release management based on Git branches

\- `zerv version`: General-purpose version generation with complete manual control

\- Smart Schema System: Auto-detects clean releases, pre-releases, and build context

\- Multiple Formats: SemVer, PEP440 (Python), CalVer, with 20+ predefined schemas and custom schemas using Tera templates

\- Full Control: Override any component when needed

\- Built with Rust: Fast and reliable



🎯 Quick Examples

# Install
cargo install zerv


# Automated versioning based on branch context
zerv flow


# Examples of what you get:
# → 1.0.0 # On main branch with tag
# → 1.0.1-rc.1.post.3 # On release branch
# → 1.0.1-beta.1.post.5+develop.3.gf297dd0 # On develop branch
# → 1.0.1-alpha.59394.post.1+feature.new.auth.1.g4e9af24 # Feature branch
# → 1.0.1-alpha.17015.dev.1764382150+feature.dirty.work.1.g54c499a # Dirty working tree



🏗️ What makes Zerv different?

The most similar tool to Zerv is semantic-release, but Zerv isn't designed to replace it - it's designed to **complement** it. While semantic-release excels at managing base versions (major.minor.patch) on main branches, Zerv focuses on:

1. Pre-release versioning: Automatically generates meaningful pre-release versions (alpha, beta, rc) for feature and release branches - every commit or even in-between commit (dirty state) gets a version
2. Multi-format output: Works seamlessly with Python packages (PEP440), Docker images, SemVer, and any custom format
3. Works alongside semantic release: Use semantic release for main branch releases, Zerv for pre-releases



📊 Real-world Workflow Example

https://raw.githubusercontent.com/wislertt/zerv/main/assets/images/git-diagram-gitflow-development-flow.png

The image from the link demonstrates Zerv's `zerv flow` command generating versions at different Git states:

\- Main branch (v1.0.0): Clean release with just the base version

\- Feature branch: Automatically generates pre-release versions with alpha pre-release label, unique hash ID, and post count

\- After merge: Returns to clean semantic version on main branch

Notice how Zerv automatically:

\- Adds `alpha` pre-release label for feature branches

\- Includes unique hash IDs for branch identification

\- Tracks commit distance with `post.N` suffix (commit distance for normal branches, tag distance for release/* branches)

\- Provides full traceability back to exact Git states



🔗 Links

\- **GitHub**: https://github.com/wislertt/zerv

\- **Crates.io**: https://crates.io/crates/zerv

\- **Documentation**: https://github.com/wislertt/zerv/blob/main/README.md



🚧 Roadmap

This is still in active development. I'll be building a demo repository integrating Zerv with semantic-release using GitHub Actions as a PoC to validate and ensure production readiness.



🙏 Feedback welcome!

I'd love to hear

your feedback, feature requests, or contributions. Check it out and let me know what you think!

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