I may be over relying on AI and I’m not sure how to stop

I understand that similar questions might have been asked before but most of the answers assume the person is thinking of ditching AI entirely and people say it’s only a tool and should be used.

My problem is I’m still basically at the first levels of devops and I can’t for the life of me learn with a deadline. I understand the concepts and what almost everything does, but writing those noscripts? Almost every time I have a project , even if personal, with a deadline I use AI and as the noscripts and stuff are generally easy and simply, it does it in a single message.

I then assume I’ll finish everything and submit and then take the time to understand, and while I do actually understand, I wouldn’t be able to replicate or do some of those noscripts completely on my own.

What did everyone do at the start? How did you start studying and understand without relying much on AI? And when do you mix AI with your work? I know that maybe in the future we won’t be writing noscripts but I’d like to at least know how to write them and then I can throw it on the AI.

https://redd.it/1nir0ap
@r_devops

Basic tool for small tasks during the day using pomodoro technique for focus

I have difficulty jumping from tool to tool, projects, languages and you can't really track time with project management tools. I started writing a tool after some courses and books in go. It works for Linux/wsl/mac not windows cause I still have some issues.

You just start a task in your terminal like:
Pomo-cli start --task "write post in reddit" --time 15 --background

Then a pid process starts and a local db is updated in your homedir\.pomo-cli. After it finishes you receive a message in the terminal and it's added to the db. You can also view the statistics and pause the task. It helps me focusing and take short breaks between changing repos or tools.

If anyone wants to use it:
https://github.com/arushdesp/pomo-cli

https://redd.it/1niqnir
@r_devops

I built a fully automated CI/CD pipeline for a Node.js app using Docker, Terraform & GitHub Actions

Hey everyone,



I just completed a hands-on project to practice modern DevOps workflows:



Built a Node.js service with a public route / and a protected route /secret using Basic Auth.



Dockerized the application to make it portable.



Provisioned a GCP VM with Terraform and configured firewall rules.



Set up a CI/CD pipeline with GitHub Actions to build the Docker image, push it to GitHub Container Registry, and deploy it automatically to the VM.



Managed secrets securely with GitHub Secrets and environment variables.



This project helped me learn how to connect coding, containerization, infrastructure as code, and automated deployments.



Check out the repo if you want to see the full implementation:

https://github.com/yanou16/dockerized-service

Would love feedback from anyone with experience deploying Dockerized apps in production!

https://redd.it/1nit4lz
@r_devops

Shift left security practices developers like

I’ve been playing around with different ways to bring security earlier in the dev workflow without making everyone miserable. Most shift left advice I’ve seen either slows pipelines to a crawl or drowns you in false positives.

A couple of things that actually worked for us:

tiny pre-commit/PR checks (linters, IaC, image scans) → fast feedback, nobody complains
heavier stuff (SAST, fuzzing) → push it to nightly, don’t block commits
policy as code → way easier than docs that nobody reads
if a tool is noisy or slow, devs ignore it… might as well not exist

I wrote a longer post with examples and configs if you’re curious: Shift Left Security Practices Developers Like

Curious what others here run in their pipelines without slowing everything down.

https://redd.it/1niuyxw
@r_devops

Has anyone done local deployment on Proxmox and kubernetes before?

How is this done normally and is this a normal way to go about it? Looking to deploy local web applications that’s only accessible on our local on-site server

https://redd.it/1niwx9u
@r_devops

Airbyte OSS is driving me insane

I’m trying to build an ELT pipeline to sync data from Postgres RDS to BigQuery. I didn’t know it Airbyte would be this resource intensive especially for the job I’m trying to setup (sync tables with thousands of rows etc.). I had Airbyte working on our RKE2 Cluster, but it kept failing due to not enough resources. I finally spun up an SNC with K3S with 16GB Ram / 8CPUs. Now Airbyte won’t even deploy on this new cluster. Temporal deployment keeps failing, bootloader keeps telling me about a missing environment variable in a secrets file I never specified in extraEnv. I’ve tried v1 and v2 charts, they’re both not working. V2 chart is the worst, the helm template throws an error of an ingressClass config missing at the root of the values file, but the official helm chart doesn’t show an ingressClass config file there. It’s driving me nuts.

Any recommendations out there for simpler OSS ELT pipeline tools I can use? To sync data between Postgres and Google BigQuery?

Thank you!

https://redd.it/1nixzmx
@r_devops

Engineering leaders; how do you respond when leaders ask you “ROI of a tool or of developers?”

Title. Curious how one could measure these consistently and reliably.

https://redd.it/1nj12px
@r_devops

Script/Automation "Orchestration". Does this exist? Is Github Actions the best option? Maybe use "ETL" orchestration tools that are originally meant for data pipelines?

Many times if an org is doing IAC or already using GHA (Github Actions), Azure DevOps, or similar CI/CD platform, they'll inevitably leverage it for running Scripts/Automations as well, often times for "manual" workflows. Things like "Deploy a lab in AWS" Or "Rotate these secrets". Is there a better alternative?

I know there are ways to run automations, like Azure Automation accounts, AWS lambdas, azure functions..etc. However these are more programmatic and event-based. Not really designed for putting it Infront of L1-L2 technicians/users that are terrified of github/code and shouldn't have access anyway. I am aware you could use slack/teams w/ webhooks, build your own frontend of some sort to use webhooks...etc. I've done this using custom Slack bots + Lambdas and Azure Automation. However it's not ideal, and there's zero reporting really.


I bring this up because I've joined an environment where GHA is used for what I'd call "automation orchestration". Theres dozens of automation noscripts built to go out and deploy things to AWS/Microsoft/Cloud SaaS Solutions, which require user technicians to input 10-20 parameters per environment and run the workflow manually for new clients or dev environments. Some of these actions are running dozens of PowerShell noscripts and bash commands as steps, sequentially setting up cloud environments. Terraform does not cover all the options, so there's inevitably REST APIs that have to get hit or PoSh/Bash CLI commands for the various SaaS offerings that have to be used. Maybe in future the TF Providers will cover everything we need, but I digress.


Then there's automations that run against our managed environments, of which there are hundreds, each with their own unique parameters and such, to do things like secret management, cloud resource deployments, reporting, IAC tasks, building images...etc.


These workflows have to run on self-hosted runners for security and compliance reasons. It's all powershell, python, bash...etc. Which means it's just running noscripts on a container/VM to interact with public REST APIs at the end of the day, if we're being frank.


GHA can do a lot of this, and we've done a lot of creative engineering to make it work, but I think it's not exactly "built" for this sort of job. The actions web UI isn't terribly featureful nor built for sort of "reporting" besides what you can put in job summaries and error logs. It is fantastic for dev work, build tasks..etc, and I really enjoy it for those tasks don't get me wrong. It has worked well for our use, but perhaps we should be using something else?



Are there better solutions to, for lack of a better word, "automation orchestration"? A platform that simply runs noscripts on schedule, manually, triggered, etc? Similar to ETL orchestration solutions? Prefect, Airflow, various DAGs do something like this but they're more built for python and don't support j. A platform that has reporting, logs, UIs for showing failures and results, all in one place? Additionally it would have to be self-hosted.

I could be mistaken, and something like Airflow can do this quite easily, I'm not intimately familiar with the offerings and solutions, just that they preform a similar sort of orchestration functionality.

Is anyone utilizing GHA for similar use cases beyond simple IAC deployments? Would you have any recommendations? Thanks!

https://redd.it/1nj0q9r
@r_devops

Fix deploy bugs before they land: a semantic firewall for devops + grandma clinic (beginner friendly, mit)

last week i shared a deep dive on failure modes in ai stacks and got great feedback here. a few folks asked for a simpler, beginner friendly version for devops. this is that post. same math idea, plain language. the trick is simple. instead of patching after a bad deploy, you install a tiny semantic firewall before anything runs. if the state is unstable, it loops, narrows, or refuses. only a stable state is allowed to execute.

why you should care

after style: output happens then you scramble with rollbacks and quick fixes. the same class of failure returns with a new shape.
before style: a pre-output gate inspects state signals first. if boot order is wrong, a lock is pending, or the first call will burn, it stops early. fixes become structural and repeatable.

what this looks like in devops terms

No.14 bootstrap ordering. hot pan before eggs. readiness probes pass, caches warmed, migrations staged.
No.15 deployment deadlock. decide who passes the narrow door. total order, timeouts and backoff, fallback path.
No.16 pre-deploy collapse. wash the first pot. versions pinned, secrets present, tiny canary first.
No.8 debugging black box. recipe card next to the stove. every run logs which inputs and checks created the output.

quick demo. add a pre-output gate to ci
paste this into a repo as preflight.sh and call it from your pipeline. it fails fast with a clear reason.

#!/usr/bin/env bash
set -euo pipefail

say() { printf "[preflight] %s\n" "$*"; }
fail() { printf "[preflight][fail] %s\n" "$*" >&2; exit 1; }

# 1) bootstrap order
say "checking service readiness"
kubectl wait --for=condition=available --timeout=90s deploy/app || fail "app not ready"
kubectl wait --for=condition=available --timeout=90s deploy/db  || fail "db not ready"

say "warming cache and index"
curl -fsS "$WARMUP_URL/cache"  || fail "cache warmup failed"
curl -fsS "$WARMUP_URL/index"  || fail "index warmup failed"

# 2) secrets and env
say "checking secrets"
[[ -n "${API_KEY:-}" ]]      || fail "missing API_KEY"
[[ -n "${DB_URL:-}"  ]]      || fail "missing DB_URL"

# 3) migrations have a lane
say "ensuring migration lane is clear"
flock -n /tmp/migrate.lock -c "echo locked" || fail "migration lock held"
./migrate --plan  || fail "migration plan invalid"
./migrate --dry   || fail "migration dry run failed"

# 4) deadlock guards
say "testing write path with timeout"
curl -m 5 -fsS "$HEALTH_URL/write-probe" || fail "write probe timeout likely deadlock"

# 5) first call canary
say "shipping tiny canary"
resp="$(curl -fsS "$API_URL/ping?traffic=0.1")" || fail "canary failed"
grep -q '"ok":true' <<<"$resp" || fail "canary not ok"

say "preflight passed"

github actions wiring. run preflight before real work.

name: release
on: [push]
jobs:
  ship:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: setup
        run: echo "WARMUP_URL=$WARMUP_URL" >> $GITHUB_ENV
      - name: pre-output gate
        run: bash ./preflight.sh
      - name: deploy
        if: ${{ success() }}
        run: bash ./deploy.sh

kubernetes job with a gate. refuse if gate fails.

apiVersion: batch/v1
kind: Job
metadata:
  name: job-with-gate
spec:
  template:
    spec:
      restartPolicy: Never
      containers:
      - name: runner
        image: your-image:tag
        command: ["/bin/bash","-lc"]
        args:
          - |
            ./preflight.sh || { echo "blocked by semantic gate"; exit 1; }
            ./run-task.sh

minimal “citation first” for runbooks
the same idea works for human steps. put the card on the table before you act.

runbook step 2 – change feature flag
require: ticket id + monitoring link
refuse: if ticket or dashboard missing, do not flip flag
accept: when both are pasted and the dashboard shows baseline stable for 2 minutes

what changes after you add the gate

you stop guessing. every failure maps to a number and a fix you can name.
fewer rollbacks.

first call failures are caught on the canary.
fewer flaky deploys. boot order and locks are tested up front.
black box debugging ends. each release has a small trace that explains why it was allowed to run.

how to try this in 60 seconds

1. copy preflight.sh into any pipeline or cron job.
2. set three env vars and one canary endpoint.
3. run. if it blocks, read the message, not the logs.

if you want the plain language guide
there is a beginner friendly “grandma clinic” that explains each failure as a short story plus the minimal fix. the labels above map to these numbers. start with No.14, No.15, No.16, No.8. if you need the doctor style prompt that points you to the exact page, ask and i can share it.

faq

q. do i need to install a platform or sdk
a. no. this is shell and yaml. it is a reasoning guard before output. you can keep your stack.

q. will this slow down release
a. it adds seconds. it removes hours of rollback and root cause churn.

q. can i adapt this for airflow, argo, jenkins
a. yes. drop the same gate into a pre step. the checks are plain commands.

q. how do i know it actually worked
a. acceptance targets. you decide them. at minimum require readiness passed, secrets present, no lock held, canary ok. if these hold three runs in a row, the class is fixed.

q. we also run ai agents to modify infra. does the same idea work
a. yes. add “evidence first” to the agent. tool calls only after a citation or a runbook page is present.

q: where is the plain language guide
a: “Grandma Clinic” explains the 16 common failure modes with tiny fixes. beginner friendly.

link:

https://github.com/onestardao/WFGY/blob/main/ProblemMap/GrandmaClinic/README.md

closing
this feels different because it is not a patch zoo after the fact. it is a small refusal engine before the fact. once a class is mapped and guarded, it stays fixed. Thanks for reading my work

https://redd.it/1nj1okk
@r_devops

Are these types of DevOps interview questions normal for fresher/junior roles, or was this just overkill?

Hey everyone,

I recently gave a DevOps interview through Alignerr (AI-based assessment), and I honestly came out feeling like I got cooked. 🥲

The questions were way harder than I expected for a fresher/junior role. Some examples:

Identifying port 22.

How to separate broad staging and dev environments from a large Terraform configuration file.

Handling configs for multiple environments with variables.

Dealing with things bound to 0.0.0.0 and what policies you’d set around that.

General stuff about modules and structuring one big configuration.

Integrating Sentinal with CICD pipeline


I was expecting more “Terraform init/plan/apply” level or maybe some AWS basics, but these felt like senior-level production questions.

https://redd.it/1nj73nc
@r_devops

Help me give my career some direction

I am a 2021 graduate from B.Tech IT graduate from a private college in Manipal, India.

My career has been a mess ever since. Soon after graduation I went to US for pursuing master's in 2021, but I didn't complete my degree and returned to India in about 6 months. Then I went back to US 6 months later and returned again in about 3 months. So overall I spent about 2 years gaining nothing and doing back and forth between India and US. I also accumulated some debt in the process. The reason for this flipflop were some untreated mental health issues.

After returning to India for second time in 2023, after extensive search, I finally found a DevOps Engineer job at a firm in Bengaluru. The salary was good until the job lasted (15 LPA or $17k/year), but layoffs hit soon in 2024. I was lucky to find another job in Bengaluru which paid the same, but the thing is I never learned core DevOps skills: Cloud Management, Kubernetes, CI/CD pipelines etc. For 2 years I have been working only on Python & Bash based programs and noscripts.

Now I am willing to undergo some certifications to aim for higher packages. Certified Kubernetes adminstrator and AWS DevOps Engineer Professional are the ones I am targeting. But, I am unsure if they will lead to higher packages at all. Most DevOps jobs in India are in WITCH like consulting companies. I am unsure how to aim for product based companies, especially in the current environment, when there are no jobs anywhere.
Should I try to switch to development, which seems so risky in the age of AI?

Tldr; I am a lost engineer, currently employed but looking for ways to increase my compensation. Please help me give my career some direction. I have wasted a lot of time but I am still only 26, and have many years ahead of me.

https://redd.it/1nj7jd4
@r_devops

How are you keeping CI/CD security from slowing down deploys?

Our pipeline runs Terraform + Kubernetes deploys daily. We’ve got some IaC linting and container scans in place, but it feels like every added check drags the cycle out. Security wants more coverage, but devs complain every time scans add minutes.

How are you balancing speed and security here? Anyone feel like they’ve nailed CI/CD security without breaking velocity?



https://redd.it/1nj8ysz
@r_devops

How to get real-time experience with Rest Assured?

Hey everyone,

I’ve learned Rest Assured and Postman from YouTube and other online resources, but I don’t have any real-time industry experience using them.

From what I understand, Postman is mostly about validating status codes, response bodies, and response data. But I’m curious — how do companies actually use Rest Assured in real projects?

Also, if I want to practice and improve my skills, what kind of test cases should I automate beyond the basics? Any ideas on good sample APIs or projects to work on would be super helpful.

Thanks!


https://redd.it/1nja5q0
@r_devops

My app is getting rejected
https://www.reddit.com/gallery/1njbpe9

https://redd.it/1njbqzt
@r_devops

Cut our hiring process from 6 weeks to 2 here’s what changed

We were losing great candidates because our process dragged: six rounds, take-homes, endless scheduling. By the time we made an offer, they were gone.

The breakthrough was ditching fragmented evaluations. Now, we run one in-depth technical session where candidates work on a real problem we’re facing. The team is in the room, asking questions, giving context. Candidates love it when they get a peek into our environment, and we see how they think under realistic conditions.

Services like paraform help keep the pipeline moving, but the real change was shifting from “testing everything” to evaluating real performance.

https://redd.it/1njbyc2
@r_devops

Want to switch from Testing (3 YOE) to DevOps – Need guidance, roadmap, and resources

Hey everyone,

I’ve been working as a tester for almost 3 years, and I’m considering switching to DevOps. I know some basics of Jenkins and a bit about CI/CD pipelines, but I’m not very confident yet.

Recently, I’ve seen a lot of LinkedIn posts and articles saying that DevOps is booming and offers great opportunities. Is this really true right now?

If yes, could you please guide me on:
1. Where to start – which DevOps tools/concepts to learn first.
2. A roadmap to move from testing to DevOps step-by-step.
3. Study material/resources (courses, books, or projects) to learn and practice.

My goal is to become skilled enough to transition into a DevOps role. Any advice from people who have made this switch or are working in DevOps would be super helpful!

Thanks in advance 🙏


https://redd.it/1njavo8
@r_devops

tips for preparing for a devops course

hello everyone,

in a month im going to start a pretty intense course in devops, a course for people with a little bit of background in code and IT, meaning we wont start completely from scratch.

looking for tips on how to prepare.

I used to work in IT, and studied a python course in uni (mostly basic concepts and medium-hard leetcode).

I have a good base for networks, operating systems (windows from IT, and linux from studying online and using it daily).

most people I asked told me that networking, python and linux are the base of everything devops, though I feel like these are my strong sides, problem is, how do I know? I do leetcode in python, but how would one truly know he knows enough about linux and networking? how do I practice?

I just completed courses on udemy on ansible, jenkins, and docker, but how does one practice to make sure he actually knows around them? I dont like the concept of studying and just listening to the guy talk with no real confidence that I actually understood anything he said.

the udemy course had practice labs on kodekloud which were nice but i've done them all, and I feel like they mostly checked my understanding on syntax and commands, its not checking my understanding of what these tools do and why im doing what im doing.

any tips for how to practice? and any other tips are welcome!



https://redd.it/1njcwc0
@r_devops

What was the 'killer feature' for your IDP?

I'm making a shopping list for IDP features and a loose roadmap. I'm curious to hear from those who have build/bought a "Platform" - what feature added the most value for your developers/infra teams? Was it something that people were asking for or something you didn't expect? Our objective is to build velocity, so less dev time mucking about trying to find which infra team should be helping them, and faster time to new app creation.
WHAT COULD GO WRONG?!?

https://redd.it/1njgpmt
@r_devops

The Ultimate SRE Reliability Checklist

A practical, progressive SRE checklist you can actually implement. Plain explanations. Focus on user impact. Start small, mature deliberately.


https://oneuptime.com/blog/post/2025-09-10-sre-checklist/view

https://redd.it/1njbgeh
@r_devops

From AWS Intern to Remote-Ready Cloud Engineer: Looking for Guidance

Hey everyone — I recently completed a cloud support engineering internship at AWS where I was exposed on how to handle global support cases involving EC2, IAM, and VPC but also got greater exposure to Linux, and high available web application developed a strong understanding of security, governance, and compliance principles.

I'm AWS SAA-C03, AIF-C01, and CCNA certified, and have solid hands-on skills in cloud diagnostics, CLI tooling, and automation.

I'm now looking to pivot into remote work — ideally with startups or dev shops where I can contribute to infrastructure support, observability, or AI ops. I’m based in Kenya, with strong internet and power, and comfortable working US/EU hours.

Would love to hear from anyone who’s hired globally or transitioned from a support background into DevOps or infra roles. 

Any advice, referrals, or critique of my approach would be hugely appreciated!

Happy to DM my CV or portfolio if helpful 🙏

https://redd.it/1njotqk
@r_devops