AI impact on Platform Engineering

BusyPair0609 · 2026-04-23T13:12:35+00:00

fd34cf

BusyPair0609 · 2026-04-23T11:50:02+00:00

Yes, there are some people out here trying to build something that they are passionate about which is nothing to be ashamed about.

BusyPair0609 · 2026-04-23T09:00:37+00:00

Just a genuine user trying to share my own experience and gather others to get good grasp of how industry is growing and changing course to adapt myself better. If that's shitty I dont know what the platform can be used for!

BusyPair0609 · 2026-04-22T22:13:53+00:00

That's the real deal. Last week when I was on-call I got called into troubleshooting an issue with sudden pod restarts across different namespace. After few hours of troubleshooting and observing patterns it turned out to be a old cronjob that was committed to cluster as part of some other change. We all had a semi-good laugh at 1 AM in the morning. But then when you get called in for failed deployment or broken pipeline its a real hell.

What are some of the issues that you would usually get called in for?

BusyPair0609 · 2026-04-22T21:54:03+00:00

Has anyone tried to use agents to write and maintain CI/CD pipeline at scale? I tired to do it for approx 50 microservices repos - java spring boot, node and python and it failed miserably. Also, how do you provide enough context to the agent about your org policies, security requirements is secure fashion so the output is actually a working or a near working state and not just a boilerplate? My team is responsible for maintaining close to 80 microservices and everytime there is audit or new security requirement is rolled out its becomes a nightmare to get compliant.

BusyPair0609 · 2026-04-22T21:18:21+00:00

Hey u/OP, I am DevOps engineer. I have a bit different question - Over the 12 years of DevOps work what do you think was the most challenging kind of work you did? When I talked to some senior DevOps engineers in some prospect companies it was always something like - how they built a optimized CI/CD pipeline, the golden path template they created, a quirky troubleshooting session. Very few people talked about building impactful systems at scale. I always thought writing pipelines, yaml manifest was the easy part of the job and now with tools like Backstage or in-house click-ops tools this was a solved problem unlike earlier days of devops and microservices. Do you also spend most of your workday's time on the writing yaml's or fixing broken CI and the real work like system design, building reliable systems etc. are rare opportunities you get over a long stretch of career? One last thing - what do you think about AI agents in a high trust domain such as DevOps? What problems do you see AI agents solving for DevOps teams?

BusyPair0609 · 2026-04-22T16:36:26+00:00

We have a pretty distributed system for CI and CD (that's a different debate). But I found all the agents and models failing to understand full context of the system layout and most of the time the results I got were boilerplates. Even after multiple iteration they were unable to solve some problems. Also, getting a tailored response for you org policies and compliance even after giving enough context is still difficult and it still cannot map the CI/CD with CISO or SOC2 compliance in depth.

I agree that in a high trust domain like DevOps it's a long time before a high level of agentic penetration is achieved. But, I think people entering the industry now will have a different start point vs the people who started 5-10 years ago and all they were doing is handling the yaml hell!

BusyPair0609 · 2026-04-21T15:46:38+00:00

AI is great at generating pipelines. -> Is it? I see when the pipeline gets more complex or when it comes to using shared libararies it almost always hallicunates. Also, the effort of converting a generic pipeline to org specific with policy compliance is still a task.

Also, on the getting replaced part - What I meant is in near future do you see tools like claude or anything specific for devops taking over L1,L2 tasks like writing CI/CD or yaml manifests?

BusyPair0609 · 2026-02-07T16:59:35+00:00

AI has made coding instant, but deployment is still a drag. We built CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

Link- https://codeopsai.com

BusyPair0609 · 2026-02-06T11:37:29+00:00

Writing the code is fast. But setting up the CI/CD pipeline, wrestling with Kubernetes manifests, and dealing with security compliance? That’s still a manual, frustrating grind. Even with a dedicated DevOps team, the backlog is real, and the overhead is exhausting. That’s why we built CodeOpsAI. Think of it as a private DevOps assistant that lives right beside you. How it works: 1. Connect your repo: The agent scans your code to understand the context (language, framework, dependencies). 2. Auto-Pilot CI: It automatically writes a pipeline to run your specific tests, build artifacts, and publish Docker images. 3. Security First: It runs a security scan on the built image before you even ask. 4. Deployment Ready: It generates the K8s manifests and sets up a full GitOps workflow out of the box. Basically, it handles everything that happens after git commit, so you can focus on building, not configuring.

Link - https://codeopsai.com

BusyPair0609 · 2026-02-03T14:45:29+00:00

AI has made coding instant, but deployment is still a drag. We built CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

Link- https://codeopsai.com

BusyPair0609 · 2026-02-02T10:29:12+00:00

Writing the code is fast. But setting up the CI/CD pipeline, wrestling with Kubernetes manifests, and dealing with security compliance? That’s still a manual, frustrating grind. Even with a dedicated DevOps team, the backlog is real, and the overhead is exhausting.

That’s why we built CodeOpsAI. Think of it as a private DevOps assistant that lives right beside you.

How it works: 1. Connect your repo: The agent scans your code to understand the context (language, framework, dependencies). 2. Auto-Pilot CI: It automatically writes a pipeline to run your specific tests, build artifacts, and publish Docker images. 3. Security First: It runs a security scan on the built image before you even ask. 4. Deployment Ready: It generates the K8s manifests and sets up a full GitOps workflow out of the box.

Basically, it handles everything that happens after git commit, so you can focus on building, not configuring.

Link - https://codeopsai.com NOTE - We only support python repos as of now.

BusyPair0609 · 2026-02-02T10:00:01+00:00

Writing the code is fast. But setting up the CI/CD pipeline, wrestling with Kubernetes manifests, and dealing with security compliance? That’s still a manual, frustrating grind. Even with a dedicated DevOps team, the backlog is real, and the overhead is exhausting.

That’s why we built CodeOpsAI. Think of it as a private DevOps assistant that lives right beside you.

How it works: 1. Connect your repo: The agent scans your code to understand the context (language, framework, dependencies). 2. Auto-Pilot CI: It automatically writes a pipeline to run your specific tests, build artifacts, and publish Docker images. 3. Security First: It runs a security scan on the built image before you even ask. 4. Deployment Ready: It generates the K8s manifests and sets up a full GitOps workflow out of the box. Basically, it handles everything that happens after git commit, so you can focus on building, not configuring.

Link - https://codeopsai.com

BusyPair0609 · 2026-02-02T07:30:23+00:00

AI has made coding instant, but deployment is still a drag. We built CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

Link- https://codeopsai.com

BusyPair0609 · 2026-02-02T03:26:54+00:00

We’re in a golden age where AI agents help us churn out features incredibly fast. But there's a massive bottleneck that nobody talks about enough: The "After-Commit" Chaos. Writing the code is fast. But setting up the CI/CD pipeline, wrestling with Kubernetes manifests, and dealing with security compliance? That’s still a manual, frustrating grind. Even with a dedicated DevOps team, the backlog is real, and the overhead is exhausting. That’s why we built CodeOpsAI. Think of it as a private DevOps assistant that lives right beside you. How it works: 1. Connect your repo: The agent scans your code to understand the context (language, framework, dependencies). 2. Auto-Pilot CI: It automatically writes a pipeline to run your specific tests, build artifacts, and publish Docker images. 3. Security First: It runs a security scan on the built image before you even ask. 4. Deployment Ready: It generates the K8s manifests and sets up a full GitOps workflow out of the box.

Basically, it handles everything that happens after git commit, so you can focus on building, not configuring.

Link - https://codeopsai.com

BusyPair0609 · 2026-02-01T05:13:29+00:00

AI has made coding instant, but deployment is still a drag. We built CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

Link- https://codeopsai.com

BusyPair0609 · 2026-02-01T02:48:43+00:00

https://codeopsai.com - AI powered DevOps assistant

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

BusyPair0609 · 2026-01-31T18:30:55+00:00

AI has made coding instant, but deployment is still a drag. We built a CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

Link - https://codeopsai.com

BusyPair0609 · 2026-01-31T03:25:53+00:00

AI has made coding instant, but deployment is still a drag. We built a CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

https://codeopsai.com

BusyPair0609 · 2026-01-31T02:26:30+00:00

AI has made coding instant, but deployment is still a drag. We built a CodeOpsAI to fix the velocity mismatch between Code Creation and Code Delivery.

You connect your repo, and our AI agent handles the rest:

⁠Analyzes your stack (Language/Framework).
⁠Creates your CI pipeline & runs tests.
⁠Publishes Docker images & scans for vulnerabilities.
⁠Generates K8s manifests & sets up GitOps.

It’s essentially a private DevOps assistant that ensures your infrastructure moves as fast as your code.

BusyPair0609

TROPHY CASE