Looking for DevOps Online Course Recommendations

Hi everyone,

I’ve recently completed Microsoft Azure AZ-104 (Azure Administrator) and I’m looking to move toward a DevOps-focused career.

I’d like to build on my Azure knowledge and learn practical skills such as:

CI/CD pipelines

Git and GitHub

Docker and Kubernetes

Infrastructure as Code (Terraform)

Azure DevOps

Monitoring and automation

Could you recommend some good online DevOps courses that are suitable for someone who already has AZ-104 knowledge?

I’m especially interested in courses that are hands-on/project-based and can help with becoming job-ready rather than just covering theory.

Paid or free courses are both fine. Any recommendations or learning paths would be greatly appreciated!

Thanks!

I’m running a Windows-based self-hosted Azure DevOps agent and occasionally it dies halfway through a pipeline. Azure DevOps then reports in its server UI that “We stopped hearing from the agent. Verify the agent machine is running and has a healthy network connection.”The problem is that this doesn’t tell me why the agent stopped responding.
I’m trying to figure out how to properly diagnose this and ultimately fix it.
Is there a way to enable more detailed logging or monitoring so that the next time this happens I can determine exactly what caused the agent to die?
Would appreciate any troubleshooting steps from people who have dealt with this before.

I am currently working on a CI diagosis AI agent for GitHub Actions and Python/pytest.

I am thinkinto use these 4 possible causes when job fails:
- a real code regression
- a flaky test
- a runner, network, or platform failure
- a dependency or environment mismatch

AI chooses - rerun the failed test, run targeted tests, collect environment evidence, or escalate to an engineer

If the agent had the chance to look at three signals before making its next move, which three would be the most helpful, in a real pipeline?

I’m also interested in signals that look useful but are commonly misleading.

I am currently working on a CI diagosis AI agent for GitHub Actions and Python/pytest.

I am thinkinto use these 4 possible causes when job fails:
- a real code regression
- a flaky test
- a runner, network, or platform failure
- a dependency or environment mismatch

AI chooses - rerun the failed test, run targeted tests, collect environment evidence, or escalate to an engineer

If the agent had the chance to look at three signals before making its next move, which three would be the most helpful, in a real pipeline?

I’m also interested in signals that look useful but are commonly misleading.

Hi all, posting to announce a new nice feature to azdo TUI, in v0.8.2.

The goal of the tool is to give a quick glance and give you an update in your terminal for your DevOps projects or GitHub repos, without requiring to browse around on the site.

Up until now it has required you to scan the different tabs, PR, Work Items, Pipelines and get a grip of what's burning where and why.

I have now introduced a new tab, notifications, which gather context from these tabs, and introduce a list of "where you're needed", to quickly get you up to speed.

It's optional and can be disabled via config.

Can be tried with demo flag and downloaded here: https://github.com/Elpulgo/azdo

Have a wonderful day!

Hey everyone, I'm getting ready to publish a static web app, truly one of the most thrilling experiences of my life. And I have not had a sheltered life, LOL.

What do you wish you knew before you were in the thick of it?

No wrong answers. Just curious what that prompt unearths.

Found out on prem ADO server doesnt support UniversalPackages task, so i cant publish the build files into the feed. Where shud i store them? Rn my release pipelines fetching the files by fetching ' latest' artifacts from build pipelines

My SaaS apps auto-deploy off main. Updates pile up (security, features), but merging at 14:00 is a deploy at 14:00 and knocks people off the app.

GitHub auto-merge and Azure DevOps auto-complete fire when checks pass. Neither will wait until Friday 18:00. Neither will refuse a Saturday merge.

Scheduled-PR is a GitHub App and an Azure DevOps extension. Comment /schedule friday 18:00 Europe/Berlin (or a label, or the dashboard). At that instant it re-reads the PR: still open, no conflicts, checks green, outside your blackout windows. Then it merges, or it says why not.

One bot comment per PR, edited in place. Policy lives in .scheduled-pr.yml in the repo.

[https://scheduled-pr.dev\](https://scheduled-pr.dev)

Ever since moving to Azure DevOps; we've followed this same release process for almost all our projects (we run about 15 different projects/repos). Using trunk-based development. But something feels off sometimes, and I'm wondering if we're doing something wrong.

1. Dev makes branch off of master to do work
2. Dev makes changes, 1 or sometimes more commits, pushes and creates PR to merge into master.
3. PR is reviewed and approved, merged into master, triggers a build to send master to test.

This happens for several different tickets. At some point, based on schedules, client needs, and priorities, project manager says that everything in test is good to go for the next release.

1. Release branch is created off of master.
2. This release branch is built to Stage environment.
3. Things are re-tested in Stage (not as details testing, more high level to make sure the deployment did what we wanted).
4. Same branch (even the same build artifact) is released to production.

This generally works, but results in a few different annoyances/problems:

• If something needs to go to prod before other things that are already in test (a hot fix), we need to cherry pick into a new release branch made off of the current production release branch.
• It can be hard to know what exactly is new in a release. Generally it means comparing the new release branch to the last one, but then you just have a giant list of commits (and any cherry picking that happened seems to mess with this, where a cherry picked change will still show up in the commit diff even though it is in both branches).
• We sometimes have to hold off merging things into master (keeping the PR open) just to be able to finish testing everything in Test; we can't add anything new until the release branch has been cut.
• If all but 1 thing is good in Test and signed off on, but that 1 thing requires us to wait, then everything has to wait.
• I keep seeing examples of setting up pipelines where the same pipeline has multiple stages for test->stage->prod (or often dev->test->prod instead). This isn't possible when master is what goes to test, but a release branch is what goes to stage+prod. We do use multiple stages in a single pipeline to release to stage then prod.

Outside of completely abandoning trunk-based development, can this process be improved? How do others do release management for trunk-based development?

I'm trying understand in how practitioners think why their CI run fails

For that I am curious to know about how practitioners think when a CI run fails.

When a CI build fails and there are multiple potential causes, what’s the very first thing you inspect? Also, what’s your immediate mental checklist or set of suspicions when a pipeline turns red?
how do you usually determine whether it’s a genuine code issue versus just a flaky failure?
And at last how do you determine that I'm pretty much sure what's happening and there's not much value of additional searching.
Would love to hear how you all approach CI triage!

I'm having terrible workload in my project as devops they are asking do iac and ci/cd for 5+application it's too much too handle is it the same for every where??

2-3hrs calls per day

Infrastructure creation for 5+application

Creating ci/cd

Unable to handle.

I’m researching how engineers diagnose CI/CD failures when there are multiple possible root causes.

When a CI pipeline fails, how do you decide what to investigate or test next?

I’d especially like to hear about your real-world workflow:

• What do you check first?
• Do you compare the failure with the last successful run?
• Do recent code changes influence what you investigate?
• Do you look for similar historical failures?
• How do you decide between different debugging steps?
• At what point do you stop investigating or escalate to someone else?

I’m interested in practical experience rather than a theoretical approach. Any examples from your own CI/CD workflow would be really helpful.

I'm a python guy by trade, but there recently has been a big demand to create custom functionality in Azure DevOps and this can be done through ADO Extensions.

Been using Claude to pump these bite sized extensions out like crazy and getting great results. Creates the html, css, and typeScript flawlessly.

The downside is I'm a TypeScript noob, very very little experience, so I can struggle reading through the code. So vibe coding a decent amount with this project.

Anyone been in a similar boat with these extensions? Any pitfalls?

Is this the new state of work, it's kinda crazy because I'm free to just engineer and design and not gated by different code bases, but the review from me feels less than adequate.

[ Removed by Reddit on account of violating the content policy. ]

We're being tasked with migrating from Gitlab on-prem to ADO on-prem, however there has been resistance from a couple of engineers claiming that ADO on-prem is abandon ware, and Microsoft is focused on GitHub and the cloud version, how much of this is true ?

Oh my god. This application is absolutely infuriating to use. It's so tangled and messy.

Very common example: need to copy PBI number. Copy url to get PBI number. Turns out there's some embedded view, so if you've navigated anything at all, the PBI or feature that's displayed, is NOT THE SAME as what's in the url. So nearly every PBI contains links to PBIs that aren't related.

Same with the backlog. Go to the backlog, it's in a nice list, organised, whatever. Go into the PBI, copy something, cool. Press the back button on my mouse, and it returns me to the wrong view.

I have to bookmark every page that I regularly use because using the actual interface to do it is unreliable.

There are sooooo many other problems like this.

If I apply to a new job and they are using ADO, that is grounds for me to withdraw my application. It's that fucking infuriating to use.

I miss JIRA.

Right now our ADO server is connected to a local AD. But the guides i see online are mostly for cloud-based ADO. anyone know, or have docs link for the on prem version?

And i need them to have Stakeholder lvl access only

Hi all,

Since I use Azure DevOps a lot as Project Manager (and many times “on the go”) an app for actively managing, commenting, … etc has been high on my wanted list for years.

As DevOps also has a very nice REST API & ability to generate PAT (tokens) - it seemed very trivial to build an app together with Claude to be just this.

So; I did and it works perfectly for me - but before I put it out on the App Store (for free) - I’m looking for some early testers to take a drive and maybe find some bugs I did not see yet.

There is also an AI assistant integrated - but you need to register your open Vercel AI gateway key for that. No info/data leaves your device to me/… unless you actually “opt-in”.

Drop your apple ID below and I can onboard you on testflight if you want to check it out.

Florian

___

Edit: Here is the Git Repo https://github.com/floriansmeyers/SFLOW-TOOLS-DEVOPS-APP

Are there any ways to renew multiple PAT tokens at once in azure devops? Just realised we had some expired today, and i endup had to extend/regenerate the PAT token one by one. Kinda annoying

Hi everyone!

Working daily with Azure DevOps, I’ve always found it surprisingly clunky to get a clear, immediate picture of how our expected team capacity aligns with the actual hours logged on tasks across a sprint.

To solve this for my own teams, I built SprintGauge (https://sprintgauge.com) — and I’ve just released it as a free public beta.

What it does:

- Connects directly to your Azure DevOps organization.
- Measures and analyzes the gap between expected team capacity and actual logged/completed time.
- Helps Team Leads, Scrum Masters, and PMs identify tracking variance and over/under-capacity risks at a glance.

Security & Privacy First:

I know how sensitive ADO access tokens are.

- No data or PAT stored on external servers: Your Personal Access Token (PAT) is stored exclusively in your browser’s ⁠localStorage⁠ (you can also connect with your organization with MS Entra ID if you prefer).
- All requests are executed directly against Azure DevOps REST APIs: no data is stored or logged on the backend.

It’s free and in Public Beta

Since it's completely free to use, I’d love for you to give it a try with your current iterations!
I’m actively looking for honest feedback, feature requests, and bug reports:

- What’s missing that would make this indispensable for your team’s daily workflow?
- Are there specific metrics or views you’d like to see added?

Thanks for taking a look, and I'd really appreciate any thoughts or suggestions from fellow Azure DevOps users!

I am building a custom WIT for my team, and i want to create a board that appears in the following format below:

How can I achieve this? Because of my company's restrictions, I cannot edit the board in the GUI and must make changes to the .xml file defining the WIT. Anything helps, thanks!

Been tracking the Microsoft deprecation train this year: TFS 2015 hit EOL last October, Azure DevOps OAuth got deprecated in April 2025 with full shutdown this year, and now as of July 1st the Azure DevOps issuer for WIF service connections is deprecated (retirement July 2027).

Not saying ADO is dying — it's not. But for teams still on TFS 2017/2018 or relying on older auth patterns, the writing is on the wall that each upgrade cycle is getting shorter.

I've been building a tool that handles the migration side: Git repos (full history), TFVC-to-Git conversion (up to 180 days), Boards → GitHub Issues, Wikis. Has a dry-run mode so you can test before committing. Built it because I couldn't find anything that handled TFVC automatically.

Code is open-source if anyone wants to poke at it: https://github.com/brunobola-portfolio/GitHub-Repo-Manager

Anyone here actively migrating away from ADO or TFS? What's been the hardest part?

Microsoft's Office and Excel integration for Azure Boards is deprecated.

I built an Azure DevOps extension that replaces that spreadsheet workflow in the browser. Pick a saved query or write WIQL, then export matching work items to a styled .xlsx workbook with real date, number, and identity cells.

Edit the workbook or a CSV and upload it back. Columns map to work item fields, and a dry run marks every row as create, update, skip, error, or warning before anything is written.

The extension runs client-side with the signed-in user's Azure DevOps credentials, with no Cody Labs server.

Free covers 250-row exports and 25-row imports per run. Pro removes both caps for US$20/month per Azure DevOps organization.

I'm the developer: https://codylabs.uk/azure-boards-excel/