AI and Context Switching

Found this article discussing AI and context switching -- https://medium.com/@vibhatha/context-switching-in-the-age-of-ai-b7c53433164c

Does AI really help minimizing context switching? If you have to learn new skills in managing multiple AI agents, it may add more workloads. But if you are comfortable with the setup in the environment, why should you use AI to "rock the boat"?

Just a thought.

https://redd.it/1v36rpb
@r_devops

Multi platform build

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I am planning to have my docker images to be multi architecture and for it my plan is to have two codebuilds for arm and amd when they both succeeds event bridge will invoke a lambda and lambda will merge the images into one

But I am unable to think a way to set up event my current plan is something like when codebuilds are triggered if anyone succeeds let's say arm build then event bridge will match the source version and and if the other build also success then it will invoke lambda

Apparently there is no ability to compare source version in eventbridge and I would have to invoke lambda and lambda has to compare the source version

Is there any way I can implement this

https://redd.it/1v39ap7
@r_devops

Currently on Falco for runtime security — anyone moved to Tetragon/KubeArmor/Tracee and regretted (or loved) it?

Running Falco in our EKS clusters right now for runtime detection, paired with Kyverno for admission control and Cosign/Vault for supply chain signing/secrets. Been solid so far, but I keep seeing Tetragon and KubeArmor come up as alternatives, especially for teams who want enforcement (block, not just alert) rather than detect-and-notify.

Curious what people are actually running in production and why:

If you moved off Falco, what pushed you? Overhead, rule fatigue, lack of enforcement?
Anyone running Tetragon specifically for the eBPF enforcement piece? Is it worth the Cilium tie-in if you're not already on Cilium for CNI?
KubeArmor folks: how's LSM behavior in practice across different node kernel configs (AppArmor vs BPF-LSM)? Heard that's where it gets messy.
Tracee: anyone using this seriously in prod or is it mostly a DFIR/forensics tool for you?

Not looking to rip out Falco, just trying to figure out if there's a compelling reason to add enforcement on top, or if pairing Falco with Falco Talon covers that gap well enough.

https://redd.it/1v3aave
@r_devops

Who owns the "why we did it this way" knowledge on your team?

Small team here and I keep running into the same thing. The reasoning behind half our setup lives in two people's heads.

Not in the runbooks, not in Confluence, not in the repo. Someone new joins and rediscovers everything the hard way and when one of those two is out we just stall.

It got noticeably worse once we started leaning on Claude Code and Cursor for real work. The agents read whatever context files we give them and treat it as truth, so now stale knowledge doesn't just slow a person down, it gets confidently baked into code by something that has no idea the decision changed months ago.

So I wonder how this actually works at bigger shops. Is there anyone whose job includes keeping that stuff current or does it just live with whoever happens to remember? And has anyone here had a documentation process survive past the first busy quarter or does it always quietly die?

Not looking for tool recommendations just trying to work out whether we're unusually bad at this or whether it's the normal state of things.

https://redd.it/1v3bzt2
@r_devops

Where is AI actually adding value in your DevOps workflow and where isn't it?

Senior DevOps here. AI is being pushed into every part of the pipeline right now, and I want to cut past the hype and hear real production experience.

Two questions:

Where have you put AI into production in your DevOps process and it genuinely adds value? (e.g. CI/CD, code review, IaC generation, monitoring/alerting, incident response, log analysis, documentation)

Where did it not prove worthwhile? Think cost, alert noise, false positives, or maintenance overhead that outweighed the benefit.

Thanks.

https://redd.it/1v3a3u7
@r_devops

How do you handle production patching for EC2 instances?

how do you handle production patching for EC2 instances in your environment?

I'm interested in learning about real-world production practices.

Some questions:

* Do you use AWS Systems Manager Patch Manager, Patch Policies, or another approach?
* Do you patch EC2 instances in place, or do you replace them with new AMIs (immutable infrastructure)?
* How do you schedule maintenance windows and minimize downtime?
* How do you handle Auto Scaling Groups during patching?
* What's your rollback strategy if a patch causes issues?
* Do you test patches in dev/staging before production?
* How much of the process is automated versus manually approved?

I'd really appreciate hearing how your organization handles production patching at scale, along with any best practices or lessons learned.

https://redd.it/1v3fu2f
@r_devops

Best way to learn K8 now?

Hi all, I’m learning Kubernetes right now for work (I use Colima + kubectl) - what is the best way to do so with AI?

I’ve used docker before in previous projects and studied concepts of containers in school - im no expert but I should know enough to learn Kubernetes.

I started the Udemy + kodekloud course: Kubernetes for the absolute beginners - Hands on. I’m not sure if it’s relevant for 2026 - so far it’s asking me to manually write yaml files, which I’m sure is important, but do I really need to be able to write yaml files with vscode extensions and AI that writes it for me?

So basically, what’s the best way to learn Kubernetes in 2026? I would appreciate any courses I should complete after my current one or a roadmap.

I have around a month or so to be good enough to collaborate with our platform and aws teams.

https://redd.it/1v3gykw
@r_devops

I am a Sr System Administrator and want to switch to DevSecOps

To begin with this is my first post or i don't know what it is called on reddit,

Apologies for the mistakes in my English please ignore it,

But I really want to switch from system admin job to DevSecOps

About myself

I have 12 years of experience starting from desktop support Engineer to laptop repairing to Data center to Monitoring to Asset management to system administration, I have knowledge of both windows and Linux operating system and currently managing Windows and Linux server (QA) no prod since my senior have never let me work on prod server even though I have worked with him since 7 years, handled a US based client for 3 years working with his team and currently handling two clients one with just some basic needs regarding systems and O365 and second with Linux servers, kind of devops but not fully the second client have a deployment using jenkins ( fetch the code from got repo, call the specific server through ssh and run the deployment and build script)

Worked with a friend's company as a contractor on his client for 6 months which ended last December and since then no work on core devops, started learning k8s and currently learning it but not able to give 100% to it also leaning python scripting and bash scripting by the help or AI can read the code and understand what it does but can not write with full confidence

I know the tools below tools

Terraform

Github

Github pipeline

Jenkins ( basic free style pipeline)

Got the idea of Sonarqube while working as a contractor but it was short lived

Understanding New relic as now the client wants to setup it

AWS basic

Azure basic and ADO basic

GCP not so much

Done a course in cybersecurity as well from local institute but not able to perform handson

I honestly want to work in Devsecops

I am already 38 and according to me not earning enough (peer pressure)

Any suggestions any help or direction is appreciated

I am even ready to do an unpaid internship ( beside the job since i have responsibilities)

Call it desperation, determination or pressure but I really want to work in Devsecops domain

Please help

https://redd.it/1v3jdnh
@r_devops

At what point do you stop treating timeouts as normal?

Hey guys! we've got a couple of internal services that will occasionally throw timeout errors under load. They retry, recover, and users never seem to notice.

The annoying part is that it's been happening long enough that nobody really reacts to it anymore. Every incident review ends up with the same general response that it's just something we've always seen.

Now I'm wondering if thats just the reality of distributed systems, or if we've gotten too comfortable ignoring something that probly deserved a closer look a while ago.

How do you decide when intermittent timeouts have crossed the line from something you live with to something worth digging into?

https://redd.it/1v3gelr
@r_devops

Looking for Terraform + AWS hands-on project ideas after completing Terraform Associate and AWS SAA

Hi everyone,

I recently completed:

HashiCorp Certified: Terraform Associate (003)
AWS Certified Solutions Architect – Associate (SAA-C03)

Now I want to move beyond certifications and gain more hands-on practical experience with Terraform on AWS.

I understand the Terraform concepts and AWS services at a theoretical level, but I want to build real-world projects that would help me improve my skills and also create some strong portfolio projects for my resume.

I am looking for recommendations on projects that simulate what a Cloud Engineer / DevOps Engineer would actually work on in an organization.


My goal is not just to deploy resources but to understand how Terraform is structured and used in real enterprise environments.

Would appreciate suggestions on:

Which projects are most valuable for learning Terraform + AWS together?
Any GitHub repositories, courses, or labs you recommend?
What kind of Terraform projects stand out on a Cloud/DevOps resume?

Thanks in advance!

https://redd.it/1v454t7
@r_devops

Which DevOps tool looked amazing during the PoC but became painful after six months?

I am Little confused ?

https://redd.it/1v445k8
@r_devops

Moving a high-memory Python application from Kubernetes to a dedicated Linux server — what would be the best setup?

Hello,

At the company where I work, we have a Python application running on a Kubernetes cluster. The application is fully integrated into a CI/CD workflow. Whenever code is merged, Jenkins pulls the source code from GitLab, builds the application, and pushes the image to Harbor. Argo CD then deploys it to the Kubernetes cluster.

However, the application consumes a large amount of RAM, and I have had to increase its memory allocation several times. We have now decided to move the application to a separate Linux server.

The application runs with Uvicorn, and I plan to make it accessible through a domain name, just as it currently is in the Kubernetes environment. However, I am not sure what the best-practice architecture would be for this setup, so I would appreciate your recommendations.

I still want Jenkins to automatically pull the application from GitLab, build it, and deploy it. After deployment, the application should automatically start and run as a web service.

My main concerns are how to restore the application as quickly as possible if a problem occurs, how to handle backups, and what kind of deployment and recovery strategy would be best.

In short, could you please advise me on the best way to design and implement this setup?

https://redd.it/1v475m2
@r_devops

How are developers and operations meant to work in this situation?

Here’s our situation - a mature operations team with pipelines building container images for a third party product going into kube

Company acquired a company with a development team who had no ops but are proficient at producing dockerfiles for their products

Ops is in azure devops, developers in bitbucket

We want to leverage the developer teams skills to get the apps into ops docker images

Some suggest that ops could build base images and developers could build their apps with that as the base - but what if the base images need patching? That means ops depends on developers for that?

Another thought I had was developers keep Dockerfiles in devops, the containers build from sources (aka git clone bitbucket) and build the project all in the ops pipeline

Would love to hear how others do this…

https://redd.it/1v480u5
@r_devops

Terraform/Github deployment overwriting another deployment

I'm on a team that shares a Github repository. Whenever we open a PR from a feature branch to the dev branch, a deployment to the AWS development account is automatically triggered.

The issue we're facing is that one developer may deploy to dev, and then another developer deploys afterward. Even though they're working on different files, the second deployment ends up overwriting the first developer's change in AWS.

How can we prevent this?

We're following a Gitflow workforce (feature -> dev -> release -> main), and our biggest challenge right now is that the second developer's code is often "outdated" when it's deployed, causing it to overwrite changes that were already deployed by someone else.

We tried merging everything to dev, but when it's time to deploy to prd, the dev branch ends up filled with a lot of unnecessary changes.

We using Github Actions + Terraform.

https://redd.it/1v4np15
@r_devops

AWS says its DevOps Agent delivers 75% lower MTTR and 94% root cause accuracy

Straight from the GA blog: customers report "up to 75% lower MTTR, 80% faster investigations, and 94% root cause accuracy, enabling 3-5x faster incident resolution."

https://aws.amazon.com/blogs/mt/announcing-general-availability-of-aws-devops-agent/



GA since March. I haven't seen anyone outside AWS's own blog actually use it. Did you try?

https://redd.it/1v4nqwx
@r_devops

Are these the 10 best practices for DevOps as a Solo developer?

Hi r/devops!

The ten:

1. Secure base images by default (cgr, rapidfort, etc) — `cgr.dev/chainguard/*`, \~0 CVEs
2. Multi-stage builds, non-root user — build tools never ship
3. Pin everything — lockfiles, image digests, actions by commit SHA
4. Least-privilege CI tokens — explicit permissions: contents: read
5. No secrets in code, images, or logs — OIDC over long-lived keys
6. Health checks + rollback-ready deploys — /healthz, one-step revert
7. Plan before apply — read the diff; never hand-edit live infra
8. Structured logs with levels — JSON events, not print("here 2")
9. Fail fast, cache hard in CI — lint before build before test
10. Small, frequent, reversible releases — boring deploys are the goal

DevOps is hard. It used to frustrate me, but the tools are making it easier.

Cheers!

https://redd.it/1v4vkg0
@r_devops

Why do coding agents behave differently in scheduled runs than interactive runs?

One thing that feels under-discussed with coding agents is the gap between interactive success and scheduled reliability.

In an interactive run, a lot of assumptions are quietly true: the user is present, credentials are warm, the working directory is right, logs are visible, and a bad step can be stopped.

I have had small automations work perfectly when I ran them by hand, then fail in the scheduled version because the path, auth, or environment was slightly different.

For a coding agent, that failure mode feels worse because it may keep reasoning, retrying, or making changes while the real problem is just the runner state.

Would you treat scheduled coding-agent runs more like CI jobs, with strict preflight and timeouts? Or is that too heavy for personal/dev workflows?

https://redd.it/1v4xotv
@r_devops

How do I learn how to architect a system?

Yes I know the question is extremely broad and complex. I'm simply looking for a starting point (or middle point).

I've been working on designing an SPA using AWS services for an NPO for the past few months. I've realized that the system works but I'm not happy with it. I know it can be better (more organized, a more sophisticated and automated system). I often find myself asking questions like: should these be a microservices architecture? Should it be a event-driven? some sort of layered architecture? How should the tests be? Is this the best programming language to use?

I know quite a few of those questions and doubts are best to be left to "whatever ur comfortable with". But I like to get into the nitty gritty. Are there certain books/youtube videos/etc that I can look into to learn about the basics of system design and architecture up to an intermediate or expert level? The only one I know of is Hello Interview.

https://redd.it/1v53dyz
@r_devops

How to tackle 90days NP.

I have been working at TCS for the past 4.7 years as an AWS DevOps Engineer. I have been trying to switch jobs for the last four months.

I receive calls through Naukri only when I update my notice period to 15 days or less. Most of the calls are not from MNCs. Even when I do receive calls from MNCs that generally accept a 90-day notice period, they still prefer immediate joiners.

I don't have the confidence to resign before securing another offer because I have a lot of financial and personal responsibilities.

I requested my manager to release me from the current project, but the request was declined. Ironically, there is very little work for me. Most days, I simply swipe in, swipe out, and spend the day with almost nothing to do.

Given this situation, I'm confused about my next step. I would really appreciate your suggestions.

https://redd.it/1v54wgy
@r_devops

How do you catch the stuff you never thought to put an alarm on?

so everyone talks about tuning alarms and reducing false positives but honestly the scarier problem for us has been the opposite. stuff breaking that we just never set up monitoring for in the first place.

had this happen a few weeks ago. a queue consumer quietly stopped processing overnight, nobody had an alarm on messages piling up in that specific queue because it's like a secondary internal thing, not customer facing directly. found out the next morning when downstream stuff started failing and someone finally went looking. by then there was hours of backlog to clear

and it's not like we were being lazy, we've got a decent number of alarms set up. it's just impossible to think of every metric on every resource ahead of time, especially as stuff gets added and nobody goes back and audits what's covered

so how are people actually dealing with the "unknown unknowns" side of this. do you just accept some stuff will slip through until it's bad enough someone notices manually. anyone actually using baseline/anomaly based detection that catches things without you having to pre-configure a threshold for every single metric, and does it actually work or is it just a different kind of false positive machine

genuinely asking, not trying to set up alarms on literally everything because that just becomes its own nightmare to maintain

https://redd.it/1v569m7
@r_devops

🚨 Never use Hostinger, worst experience ever 👎

We purchased the KVM 8 plan with a one year subscription, which includes 8 vCPUs, 32 GB RAM, and 400 GB of storage. On paper, it offers strong specifications at a competitive price. However, after several months of use, we began encountering an issue that significantly affected day to day operations.

We experienced recurring Connection Timed Out errors when accessing hosted websites or connecting via SSH. In many cases, the issue was resolved immediately by using a VPN or by obtaining a different public IP address after restarting the router.

Because residential internet providers routinely assign dynamic IP addresses, customers generally have no control over the reputation or previous history associated with the IP they receive. As a result, connectivity problems based on IP reputation can unexpectedly affect legitimate users.

Over the following months, we contacted Hostinger support on multiple occasions to request that our IP address be unblocked. Each request was resolved manually and access was restored. However, we were never provided with logs or a technical explanation describing why the IP had been blocked in the first place.

The absence of diagnostic information made it difficult to identify the underlying cause or prevent the issue from recurring. By comparison, providers such as Cloudflare offer detailed security logs that show blocked requests, security challenges, and rule matches, enabling customers to troubleshoot issues more effectively. While every provider implements security differently, a similar level of visibility would have been helpful in this situation.

Hostinger's billing model also meant that the service could not be easily discontinued once the initial refund period had passed. As a result, although the subscription remains active, I have limited its use to testing and non critical workloads rather than production services.

https://redd.it/1v56g1h
@r_devops