Simple way to Analyse .ddl file

Hey,

we Need a task in a Pipeline with a Script Which Extrakt the properties from the ddl file and if the file has a signature, do you have any Examples with powershell or something Else?

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

Simple, self-hosted GitHub Actions runners

I needed more RAM for my GitHub Actions runners and I couldn't really find an offering that I could link to a private repository (they all need organization accounts?).

Anyways, I have a pretty powerful desktop for dev work already so I figured why not put the runner on my local desktop. It turns out the GHA runner is not containerized by default and, more importantly, it is stateful so you have to rewrite the way your actions work to get them to play nicely with the default self-hosted configuration.

To make it easier, I made a Docker image that deploys a self-hosted runner very similar to the GitHub one, check it out! https://github.com/kevmo314/docker-gha-runner

https://redd.it/1kkj6p7
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Perplexity for DevOps

Hey !

We’ve been building Anyshift, the Perplexity for DevOps. It answers questions like:

* “Are we deployed across multiple regions or AZs?”
* “What changed in my DynamoDB prod between April 8–11?”
* “Which accounts have stale or unused access keys?”

and make detailed answered with verified sources (AWS URL, git commits etc...)

Behind the scenes, it queries a live graph of your code and cloud with no hallucinations, just real answers backed by real data from:

* GitHub (Terraform & IaC)
* Live AWS resources
* Datadog

Why we built it:
Terraform plans are often opaque. One small change (like a CIDR block or SG rule) can trigger unexpected consequences. We wanted visibility into those dependencies — including unmanaged or clickops resources

Under the hood :

* We use Neo4j graph updated via event-driven pipelines
* We provide factual answers with links to source data
* It can be used as a Slackbot or web UI

The setup takes \~5 mins (GitHub app or AWS read-only on a dev account to test it quickly).
And its free for teams up to 3 users :) [https://app.anyshift.io](https://app.anyshift.io)

Would love your feedback — especially around Terraform drift, shadow IT, or blast radius use cases.

Thanks a lot :)))
Roxane

https://redd.it/1kknbpf
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IaCConf: the first community-driven virtual conference focused entirely on infrastructure as code

If you're working with Terraform, OpenTofu, Crossplane, or others, check out IaCConf.

IaCConf is 100% online and free, and it starts at 11:00 am EDT, May 15, 2025.

The conference is for every skill level, and here are some of the topics that will be covered:

Getting started with IaC
Managing IaC at scale
IaC + Platform Engineering
AI in IaC

Full agenda and free registration on the site.

https://redd.it/1kkndmb
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Kubernetes Scaling: Replication Controller vs ReplicaSet vs Deployment - What’s the Difference?

Hey folks! Before diving into my latest post on Horizontal vs Vertical Pod Autoscaling (HPA vs VPA), I’d actually recommend brushing up on the foundations of scaling in Kubernetes.

I published a beginner-friendly guide that breaks down the evolution of Kubernetes controllers, from ReplicationControllers to ReplicaSets and finally Deployments, all with YAML examples and practical context.

Thought of sharing a TL;DR version here:

ReplicationController (RC):
1. Ensures a fixed number of pods are running.
2. Legacy component - simple, but limited.

ReplicaSet (RS):
1. Replaces RC with better label selectors.
2. Rarely used standalone; mostly managed by Deployments.

Deployment:
1. Manages ReplicaSets for you.
2. Supports rolling updates, rollbacks, and autoscaling.
3. The go-to method for real-world app management in K8s.

Each step brings more power and flexibility, a must-know before you explore HPA and VPA.

Would love to hear your thoughts, what part confused you the most when you were learning this, or what finally made it click? Drop a comment, and let’s chat!

Check out the full article with YAML snippets and key commands here:

First, Why You Should Skip RC and Start with Deployments in Kubernetes

Next, Want to Optimize Kubernetes Performance? Here’s How HPA & VPA Help

If you found it helpful, don’t forget to follow me on Medium and enable email notifications to stay in the loop. We wrapped up a solid 30Blogs in the #60Days60Blogs ReadList series of Docker and K8S and there's so much more coming your way.

And hey, if you enjoyed the read, leave a Clap (or 50) in Medium to show some love!

https://redd.it/1kkp3h8
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📌 Case Study Changing GitHub Repository in AWS Amplify — Step-by-Step Guide

Hey folks,

I recently ran into a situation at work where I needed to change the GitHub repository connected to an existing AWS Amplify app. Unfortunately, there's no native UI support for this, and documentation is scattered. So I documented the exact steps I followed, including CLI commands and permission flow.

💡 Key Highlights:

Temporary app creation to trigger GitHub auth
GitHub App permission scoping
Using AWS CLI to update repository link
Final reconnection through Amplify Console

🧠 If you're hitting a wall trying to rewire Amplify to a different repo without breaking your pipeline, this might save you time.

🔗 Full walkthrough with screenshots (Notion):
https://www.notion.so/Case-Study-Changing-GitHub-Repository-in-AWS-Amplify-A-Step-by-Step-Guide-1f18ee8a4d46803884f7cb50b8e8c35d

Would love feedback or to hear how others have approached this!

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

Need suggestions

I am 5+ years experience IT professional. First worked as a windows admin then as a cloud (azure) admin. want to shift my career towards DevOps. How can i get handon experience with yaml based pipelines or IAC. My project in company does not use this. Even Containerization is not there.

Also i have been stuck in the same company for 5 years want to change. Please help

https://redd.it/1kkn0co
@r_devops

What is usually done in Kubernetes when deploying a Python app (FastAPI)?

Hi everyone,

I'm coming from the Spring Boot world. There, we typically deploy to Kubernetes using a UBI-based Docker image. The Spring Boot app is a self-contained .jar file that runs inside the container, and deployment to a Kubernetes pod is straightforward.

Now I'm working with a FastAPI-based Python server, and I’d like to deploy it as a self-contained app in a Docker image.

What’s the standard approach in the Python world?
Is it considered good practice to make the FastAPI app self-contained in the image?
What should I do or configure for that?

https://redd.it/1kkswy6
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Learning and Practice: iximiuz Labs vs Sad Servers?

I am keen to learn and practice technologies, particularly Linux troubleshooting, Docker, Kubernetes, Terraform, etc. I came across two websites with a good collection: iximiuz Labs vs Sad Servers.

But I need to choose one of these to get a paid subscription. Which one should I go with?

https://redd.it/1kktlz8
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Is 2025 CKA harder than it was before? (Rant)

I waited to post this for a few months.

For context, I started my Kubernetes journey fresh in September 2024, having minimal experience (only with docker and docker-compose, but no orchestration, but I have sys admin/devops experience). I went through whole KodeKloud course, I did all 70+ killercoda scenarios and scored 80% on my killer.sh attempt. I probably spent 120+ hours studying and practicing for this exam.

I took the exam the updated exam on 1st of March 2025, so I knew about the updates and I went over the additional stuff as well. I took multiple kodekloud mock exams, with mixed results. But I read a lot about how killer.sh is much harder than real CKA exam, so when I scored 80% on my practice attempt so I was pretty confident going into the exam (maybe I was just lucky that the killer.sh questions suited me).

When I started the exam, oh boy: flaged 1st, flaged 2nd, flagged 3rd... I think the first question I started solving was 7 or 8th. I could've written down with what exactly I struggled, but I felt it was much harder than killer.sh. I think I can navigate the K8s docs pretty well, but I know I had some Gateway API questions, but I feel the docs were non existent for my questions, then also why use helm, and not allow helm docs? I remember I had to install and configure CNI, but why would you allow the docs/github for it? Does every Certified Kubernetes Admin know this from top of their head? Even when there is an update? I know there was somethings such as resource limits on the nodes I could've had and studied better for.

So after 2hours, I scored 45% (probably better than 60-65% as I would be more angry at myself but also more confident for the retake).

So I wanted to ask some who did the exam before and retook is after the February update: Was the exam harder? Or am I just stupid?

By end of this month I want to start revising again and do the retake in July/August. Do you guy have any other resources than KodeKloud, killercoda and killer.sh? I'm buying a hertner vps and going to host something in K8s to get more real-life experience.

End of my rant.

Edit: I'm not time traveller, fixed


https://redd.it/1kkv3ua
@r_devops

MacBook or Mac Mini for DevOps?

Basically the title says. Currently working as a DevOps Engineer and looking for laptop / desktop something stable and smooth for personal use. Want to know that going for MacBook Air or Mac Mini is worth and long-lasting. And appreciate if anyone have suggestions other than these with specs :)

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

The first time I ran terraform destroy in the wrong workspace… was also the last 😅

Early Terraform days were rough. I didn’t really understand workspaces, so everything lived in default. One day, I switched projects and, thinking I was being “clean,” I ran terraform destroy .

Turns out I was still in the shared dev workspace. Goodbye, networking. Goodbye, EC2. Goodbye, 2 hours of my life restoring what I’d nuked.

Now I’m strict about:

Naming workspaces clearly
Adding safeguards in CLI scripts
Using terraform plan like it’s gospel
And never trusting myself at 5 PM on a Friday

Funny how one command can teach you the entire philosophy of infrastructure discipline.

Anyone else learned Terraform the hard way?

https://redd.it/1kkzo2h
@r_devops

Discussion: Model level scaling for triton inference server

Hey folks, hope you’re all doing great!

I ran into an interesting scaling challenge today and wanted to get some thoughts. We’re currently running an ASG (g5.xlarge) setup hosting Triton Inference Server, using S3 as the model repository.

The issue is that when we want to scale up a specific model (due to increased load), we end up scaling the entire ASG, even though the demand is only for that one model. Obviously, that’s not very efficient.

So I’m exploring whether it’s feasible to move this setup to Kubernetes and use KEDA (Kubernetes Event-driven Autoscaling) to autoscale based on Triton server metrics — ideally in a way that allows scaling at a model level instead of scaling the whole deployment.

Has anyone here tried something similar with KEDA + Triton? Is there a way to tap into per-model metrics exposed by Triton (maybe via Prometheus) and use that as a KEDA trigger?

Appreciate any input or guidance!


https://redd.it/1kl1ctu
@r_devops

Hellp/suggestions needed USA - Devops Engineer Interview

Hello All ,

I recently applied to a company
the below was its job description , I am familiar with many concepts , but some how I am worried about the interview. I got a screening call and awaiting response

Can anyone please help with suggestions on where to focus more , expected questions and any other tips please

thanks in Advance

**Required Skills:**

* **3+ years work experience in a DevOps or similar role**
* **Fluency in one or more scripting languages such as Python or Ruby**
* **In-depth, hands-on experience with Linux, networking, server, and cloud architectures**
* **Experience in configuration management technologies such as Chef, Puppet or Ansible**
* **Experience with AWS or another cloud PaaS provider**
* **Understanding of fundamental network technologies like DNS, Load Balancing, SSL, TCP/IP, SQL, HTTP**
* **Solid understanding of configuration, deployment, management and maintenance of large cloud-hosted systems; including auto-scaling, monitoring, performance tuning, troubleshooting, and disaster recovery**
* **Proficiency with source control, continuous integration, and testing pipelines**
* **Championing a culture and work environment that promotes diversity and inclusion**
* **Participate in the team’s on-call rotation to address complex problems in real-time and keep services operational and highly available**



**Preferred Skills:**

* **Experience with Containers and orchestration services like Kubernetes, Docker etc.**
* **Familiarity with Go**
* **Understand cloud security and best practices**

https://redd.it/1kl3lgg
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Is current state of querying on observability data broken?

Hey folks! I’m a maintainer at [SigNoz\](https://signoz.io), an open-source observability platform

Looking to get some feedback on my observations on querying for o11y and if this resonates with more folks here

I feel that current observability tooling significantly lags behind user expectations by failing to support a critical capability: querying across different telemetry signals.

This limitation turns what should be powerful correlation capabilities into mere “correlation theater”, a superficial simulation of insights rather than true analytical power.

Here’s the current gaps I see

1/ Suppose I want to retrieve logs from the host which have the highest CPU in the last 13 minutes. It’s not possible to query this seamlessly today unless you query the metrics first and paste the results into logs query builder and retrieve your results. Seamless correlation across signal querying is nearly impossible today.

2/ COUNT distinct on multiple columns is not possible today. Most platforms let you perform a count distinct on one col, say count unique of source OR count unique of host OR count unique of service etc. Adding multiple dimensions and drilling down deeper into this is also a serious pain-point.

and some points on how we at SigNoz are thinking these gaps can be addressed,

1/ Sub-query support: The ability to use the results of one query as input to another, mainly for getting filtered output

2/ Cross-signal joins: Support for joining data across different telemetry signals, for seeing signals side-by-side along with a couple of more stuff.

Early thoughts in [this blog\](https://signoz.io/blog/observability-requires-querying-across-signals/), what do you think? does it resonate or seems like a use case not many ppl have?

https://redd.it/1kl6rhd
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Is KodeCloud worth it?

I’ve been lurking here for awhile after getting handed a bunch of dev ops tasks at work and wanted to see if kode kloud is a good recourse for getting up to speed with docker, ansible, terraform and concepts like networking, ssl, etc.? Really enjoying this stuff but am finding out how much I don’t know by the day.

https://redd.it/1kl9qop
@r_devops

What should I do ?

Hello Everyone,

Long time lurker but now I’m asking questions. So I’ve been in DevOps coming up on 5 years and I’m trying to figure out is it time for a new AWS cert (architect professional ) or should I finally use my cybersecurity degree and get AWS Certified Security - Specialty or a high level security cert ? My thing is that I want to increase my $120k salary to be closer to $160k - $180k. I don’t want to go down in salary? What should I do ?

https://redd.it/1kl9ldv
@r_devops

How to handle buildkit pods efficiently?

So we have like 20-25 services that we build. They are multi-arch builds. And we use gitlab. Some of the services involve AI libraries, so they end up with stupid large images like 8-14GB. Most of the rest are far more reasonable. For these large ones, cache is the key to a fast build. The cache being local is pretty impactful as well. That lead us to using long running pods and letting the kubernetes driver for buildx distribute the builds.



So I was thinking. Instead of say 10 buildkit pods with a 15GB mem limit and a max-parallelism of 3, maybe bigger pods (like 60GB or so), less total pods and more max-parallelism. That way there is more local cache sharing.



But I am worried about OOMKills. And I realized I don't really know how buildkit manages the memory. It can't know how much memory a task will need before it starts. And the memory use of different tasks (even for the same service) can be drastically different. So how is it not just regularly getting OOMKilled because it happened to run more than one large mem task at the same time on a pod? And would going to bigger pods increase or decrease the chance of an unlucky combo of tasks running at the same time and using all the Mem.

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

Check out our blog post about AI SRE

https://www.icosic.com/blog/what-is-an-ai-sre

In this post we define the AI SRE and we outline its advantages and compare it to human SREs.

Thanks in advance for reading!

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

Every K8s Beginner’s Safety Net: --dry-run Explained in 5 Mins

Hey there, So far in our 60-Day ReadList series, we’ve explored Docker deeply and kick started our Kubernetes journey from Why K8s to Pods and Deployments.

Now, before you accidentally crash your cluster with a broken YAML… Meet your new best friend: --dry-run

This powerful little flag helps you:
\- Preview your YAML
\- Validate your syntax
\- Generate resource templates
… all without touching your live cluster.

Whether you’re just starting out or refining your workflow, --dry-run is your safety net. Don’t apply it until you dry-run it!

Read here: Why Every K8s Dev Should Use --dry-run Before Applying Anything

Catch the whole 60-Day Docker + K8s series here. From dry-runs to RBAC, taints to TLS, Check out the whole journey.

https://redd.it/1kleghk
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Is Linux foundation overcharging their certifications?

I remember CKA cost 150 dollars. Now it is 600+. Fcking atrocious Linux

https://redd.it/1klf2ab
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