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@catops

DevOps and other issues by Yurii Rochniak (@grem1in) - SRE @ Preply && Maksym Vlasov (@MaxymVlasov) - Engineer @ Star. Opinions on our own.

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Recent Posts 20 shown
Post #2983 899
Shopify wrote an article on them moving from React Native to the native code for their mobile apps. They were already ridiculed for this on Reddit for the lack of in-house knowledge of the native languages. However, I think this is a great precedent for AI. Apparently, if you know the end goal and you have enough of guardrails, you can do that. The argument that AI won't be able to debug something in the future is as applicable to humans as to AI.

At the same time, Shopify's CEO calls out that people are throwing "slop grenades" at each other. Yet, two things can be true at the same time. You can successfully use AI for major refactorings and throw "slop grenades" in the form of useless documents.

#ai #programming
Shopify Native is now the future of mobile at Shopify (2026) - Shopify Coding agents changed what it costs to build mobile apps twice. Here’s why Shopify is moving from React Native back to Swift and Kotlin.
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Post #2981 1.05K
​​A good friend of the channel raises funds for his new unit (a small air defense unit). They are raising funds for tools and materials for their positions.

You can donate to this Monobank jar:

https://send.monobank.ua/jar/4SB2PtGPzV

#donations #Ukraine
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Post #2980 1.26K
There will be no digest today because I haven't posted much this week.

So, instead here is an article from Anthropic on how to deal with the strain that AI development and reviews put on CI. This is a real problem in the AI-driven SDLC, or so-called "software factories", but unlike code reviews and harnesses, it's not been talked about so much, unfortunately.

#cicd #ai
Claude Agentic coding is straining CI. Here’s how we scaled test impact analysis at Anthropic | Claude by Anthropic Our CI job volume increased 25x over 6 months. We patched our test selection service three times before finding a sustainable solution.
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Post #2977 1.27K
I recall, back in the day, there was a popular interview question: "What would you not automate in your job?" I haven't heard it for a while, but with AI now, maybe it's still relevant. Perhaps it's even more relevant than back then.

What SREs Should Automate — and Never Automate — with AI is an article about that. I would argue that the point about security incidents contradicts a bit to what was said earlier: if AI can collect the data for a normal incident, why cannot it do the same for the security one? A human would still stay in charge of the remediation and the final decision.

#sre #ai
Hackernoon What SREs Should Automate — and Never Automate — with AI | HackerNoon Automate based on impact and recoverability, not on whether the AI is technically capable of doing the task.
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Post #2976 1.17K
An interesting article on how to configure AI reviews for Terraform plans with GitHub Actions and AWS Bedrock.

I don’t necessarily like the style of this article, but the content is cool. Now, I need to check how to do something similar with Atlantis. I presume, I could just trigger a GHA on a comment.

P.S. This article was brought to you by weekly.tf. If you actively work with Terraform, you may find this newsletter helpful. So, make sure to subscribe!

#terraform #ai
Medium I Built an AI Terraform Plan Reviewer and Hit Five Access Gates Getting There Every Terraform PR I review goes the same way. I open the plan output, scroll past forty lines of ~tags and ~id noise, and try to spot the…
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Post #2975 1.22K
​​Today, I’d like to remind you about the fundraiser a friend of mine is doing. The goal is to raise 70k UAH for a pickup truck for Zaporizhzhia direction.

You can donate on this Monobank jar:

https://send.monobank.ua/jar/8Mjotj4Uei

#donations #Ukraine
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Post #2973 1.4K
A nice visualization of Go dependencies.

It's interesting how you can instantly see packages that support hundreds, if not thousands, of others. I would have guessed that testify is popular, but I wouldn't have guessed that it's the most popular.

Also, I did not expect to see Viper and Cobra being so influential, even though I think they are cool.

#go #programming
Luís Sousa The Shape of Go — Luís Sousa Every public Go module and every declared dependency in a single graph: 2,638,112 modules and 9,443,537 edges.
Post #2971 1.22K
I already shared postmortems from both OpenAI and Hugging Face on the recent security incident when a frontier model broke out of its sandbox to search for a solution for its task.

Here is a more detailed writeup by OpenAI on this incident. Given that OpenAI has an intrinsic motivation to advertise their models, I would still take this with a pinch of salt, but it should be interesting.

I haven't read this article fully yet, but the start is promising.

#ai #security
OpenAI The Hugging Face incident and the road ahead OpenAI shares findings from the Hugging Face security incident and the steps we’re taking to strengthen AI model security, monitoring, and alignment.
Post #2970 1.15K
​​For today's Donations Monday, I'd like to remind you about a fundraiser by a friend of mine. Its goal is to get 70k UAH for a pick up truck. So far, about 20k has been raised. Let's make it happen!

https://send.monobank.ua/jar/8Mjotj4Uei

#donations #Ukraine
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Post #2968 1.44K
Cloudflare shares a story of how they automated GitHub issues triage with AI for their Astro project.

It neatly shows the evolution from a collection of skills to a semi(?) autonomous state machine that has taken the project to zero open issues.

They also share the workflows they use publicly, but in my opinion the more valuable lesson here is the step-by-step model of how they got there.

#ai #open_source
Cloudflare Blog How we built a software factory to drive Astro’s GitHub issue count to zero By replacing manual issue verification with isolated AI subagents running in GitHub Actions, the Astro maintainers reduced open issue count by 85%. This post explores the architecture behind automated bug reproduction, patch verification, and preview releases.
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Post #2967 1.3K
A great article about Postgres' MVCC, or rather, issues with MVCC and the ways other engines tried to mitigate those.

It has a neat comparison of the tradeoffs, strong and weak parts of different implementations. It also provides insights into how different DB engines work.

A quote:

... if someone tells you a database has solved multi-versioning, ask them the four questions: where do old versions live, which way do chains point, what do indexes point at, and who cleans up. Then ask what happens when a transaction stays open over lunch.

#postgres #databases
boringSQL | Supercharge your SQL & PostgreSQL powers PostgreSQL's MVCC is bad. So is everyone else's. The critics are right: PostgreSQL's MVCC bloats tables and amplifies writes. Oracle, InnoDB, SQL Server, MongoDB, LSM stores, and etcd answer the same four design questions differently, and each pays for it somewhere else.
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