Hey SweetOps! Sharing this because it's directly relevant to what this community is building with every day.

If you're using Claude Code or thinking about it, Packt Publishing is running a hands on bootcamp on May 30 with Luca Berton — Anthropic certified Claude Code instructor, former Red Hat engineer, creator of the Ansible Pilot project, and speaker at KubeCon 2026 and Red Hat Summit 2026. This is someone who builds production grade AI systems for enterprises, not just talks about them.

What you actually get on the day:

10 real world projects built live — CLI tools, APIs, dashboards, git workflows, production readiness reports. You leave with a working portfolio not just notes.

A free downloadable Claude skills library — CLAUDE.md templates, code review prompts, test generation, security checklists, git workflows. Battle tested and ready to drop into your existing projects from day one.

Packt endorsed certification — pass the final assessment and it goes straight on your LinkedIn.

5 hours live, hands on throughout, 1 hour of open Q&A with Luca directly.

We've already got DevOps engineers, CTOs, engineering managers and SREs registered from the US and UK.

Full details here: https://claudecodebootcamp.eventbrite.co.uk/?aff=sps

https://rmoff.net/2026/05/06/ai-slop-is-killing-online-communities/

Is anybody here using Cloud Custodian? Curious what your experience has been and what use cases you use it for!

https://cloudcustodian.io

IAM misconfigurations sit in ticket queues for 14 days on average. the fix itself takes four minutes. wrote up this article on a closed-loop remediation system that handles it in 90 seconds instead, and explains which security findings you should never auto-remediate. I would love some feedback on this.

https://dev.to/riya_mittal_cdd264250ad45/closed-loop-iam-remediation-auto-fixing-security-misconfigurations-without-a-human-in-the-loop-dhc

🚀Bay Area Devs folk— quick one: a 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗚𝗶𝘁-𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿 𝗶𝗻 𝗦𝗮𝗻 𝗙𝗿𝗮𝗻𝗰𝗶𝘀𝗰𝗼 to talk about what’s actually working (and what’s breaking) in AI-First SDLC.


🗓️ 𝗠𝗮𝘆 𝟭𝟰 | 𝟱:𝟯𝟬–𝟴:𝟯𝟬 𝗣𝗠
📍 TestMu, San Francisco

If you’re in backend, QA, or DevOps — this will be worth your time.

Spots are limited (invite only).

👉️ Register: https://lnkd.in/dxaGF9iN


𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗴𝗲𝘁:
→ Real conversations with engineers building at scale
→ Live demo (not a sales pitch)
→ Practical ideas you can take back to your team
→ Swag + good coffee

🇺🇸 US based software engineers!
You can get refresh new jobs hourly basis here.
https://usdevjobs.com/

Hey guys 👋

I built a self-service developer platform and it's live on the public internet — you can try it from your phone right now.

👉️ https://backstage.gabrieleweka.dev (sign in with GitHub or Google)

The flow: click Create, type a name, pick prod or dev. In ~2 minutes you get:
• A new GitHub repo with a Flask API + frontend
• Full CI/CD pipeline (super-linter + Trivy scans, build, push, deploy)
• Auto-deployed to Kubernetes via ArgoCD with a valid HTTPS URL
• Its own Grafana dashboard (pods, CPU, memory, network, crash count)
• TechDocs page rendered in Backstage

Other stuff to poke at:
• https://argocd.gabrieleweka.dev — read-only login: viewer / viewer123
• http://grafana.gabrieleweka.dev — no login, opens on the Platform Overview
• http://prometheus.gabrieleweka.dev

Heads up: scaffolded apps auto-delete after 30 min (a CronJob reaps them), so don't get attached. Whole thing runs on my old laptop through a Cloudflare Tunnel — $0/month.

Would love feedback 🙌

A github issue complaining MiniMax model but in Chinese, https://github.com/MiniMax-AI/MiniMax-M2/issues/102, many found the post from google and confirmed the bad performance

GPT 5.5 is coming?

Hi everyone!

We built a knowledge graph as a service for production teams: real-time mapping of your infra, apps and codebase, with causal reasoning for incident resolution and prediction.

Would love feedback from people who deal with this daily, or a pointer to someone who'd be keen to try it. Free trial here: https://www.anyshift.io/

Used by Citrix, MotherDuck and Yelp. SOC 2 certified, self-hosted option available. Happy to chat or do a quick demo!

Not sure if there is a similar project for MFA token chaining, if not, I have just made one, https://github.com/snowsky/mfa-chain-orchestrator, which can be installed with pip install mfa-chain-orchestrator, and an example can be found at https://github.com/snowsky/mfa-chain-orchestrator/tree/main/examples.

The idea is simple, user can set up MFA with multiple authenticators in a chain. I tested in my application. When user logs in, he can use password first, and then will be prompted for Google Authenticator and Microsoft Authenticator in sequence or random.

Another week, another resource control policy! I guess this is what IAM geeks do. 😹

github.com/sqlxpert/aws-rcp-s3-require-encryption-kms
…is my new way to replace KMS encryption statements potentially repeated in hundreds of S3 bucket policies.

• Install it in your AWS Organizations management account, with CloudFormation or native Terraform.
• Tag an S3 bucket and enable attribute-based access control (ABAC) for the bucket.
security-s3-require-encryption-kms-key-arn = ARN of KMS key required in this bucket

(Two other identifiers are also supported. One is for the simplest setups, in which S3 bucket and KMS key are only ever used in one region and AWS account. The other fits KMS multi-region keys defined in a central AWS account.)

• Any attempt to create an object with the wrong encryption type or wrong KMS key yields AccessDenied .
• An optional service control policy locks the tag.
Between the resource control policy itself, the automated test stack (CloudFormation only, because it's temporary), and the documentation, there's lots of information about:
• New 2025–2026 S3 features (attribute-based access control, account-regional namespaces)
• IAM policy condition keys for tags, and condition operator semantics
• Secure, future-proof KMS key configurations
I really appreciate your feedback, and that's not an empty statement: I improve stuff based on user requests, and I of course acknowledge the source.

I hope this will be useful. If you give it a try, thank you!

I built CubbyDrop — encrypted file sharing where the server never sees your data.
How it works: your files are encrypted with AES-256-GCM in the browser before upload. The key stays in the link — the server literally can't access
your files.

Main features:
• End-to-end encrypted file transfers
• Password protection & download limits
• Delete-after-download for sensitive files
• Live peer-to-peer mode (no server, no size limits)
• Personal subdomains (you.cubbydrop.com)
• Team plans with admin dashboard & domain discovery
• QR code sharing for mobile
• Encrypted text/password paste
https://cubbydrop.com
Would love honest feedback — what's missing? What would make you switch from your current tool?

AI infrastructure is moving fast, and the cost of getting it wrong is rising.

Too many teams are still dealing with the same problems: surface-level conversations, fragmented market views, and uncertainty over whether the right people are even in the room.

AI Infra Summit is built to solve that.

It brings together the technical leaders, enterprises, hyperscalers, and infrastructure players driving the industry forward, so you can get practical insight, see the full ecosystem more clearly, and make connections that matter.

If you want a sharper perspective and better conversations, register your interest here: https://lnkd.in/e9HVGddr

Sam may be intentionally to stay behind Dario to avoid to be hated by engineers being laid off but maintain his business market. the hatred turning against to the 1st leader may happen in a snap, hope this wouldn’t happen

Hey 👋
DevOps / SRE here (~8y professional experience).

After constantly dealing with load testing setups, I built a tool to simplify the workflow (distributed tests, regression detection, reports, CI/CD, etc):
https://loadtester.org

Would love feedback from others engineers — happy to jump on a quick demo call if useful, otherwise feel free to register and use a free plan!

Not sure if this was shared already; @Matt Gowie shared with me https://www.youtube.com/watch?v=g1R71Wbxlkk

👋 Hi everyone!

My name is Chi, and I'm a VIP Experience Executive at Kisaco Research - a London-based B2B events company that produces high-level industry conferences and summits for some of the world's leading tech communities.

I'll be honest, I'm relatively new to the AI and infrastructure space 😄 but I'm learning fast and this community looks like exactly the right place to do that!

The reason I wanted to reach out is that we have our AI Infra Summit coming up at the Santa Clara Convention Center, 15–17 September, and it may be of interest to some of you. Here's a flavour of what's on:

🔹 6 content stages covering Compute, Data Movement, Data & Models, AI Data Centre, Physical AI, and a Main Stage
🔹 8,000+ attendees from across the AI infrastructure engineering world
🔹 Speakers include Jeff Dean (Chief Scientist, Google), Lip-Bu Tan (CEO, Intel), plus teams from Microsoft, Meta, Boeing, Lockheed Martin, eBay and 50 more announced just this week
🔹 Real-world architecture talks from teams running large-scale AI workloads in production

Complimentary tickets are available for qualifying enterprises, hyperscalers, and AI labs, which is exactly where my role comes in. I handle VIP guesting for enterprise and hyperscaler attendees, so if you're interested in attending or know a colleague who might be, feel free to drop me a message and I'll get you sorted 😁

We also have a free webinar coming up on 16 April - AI in Practice: From Innovation to Market Reality - if you'd like a taster before the main event. 👉️ https://lnkd.in/eDRCQEAY

Great to meet you all, and looking forward to getting to know this community! 🙌

Hey folks, just wanted to share a new tutorial on building a closed-loop workflow with Codex and Signadot. It covers using MCP to let agents spin up their own K8s sandboxes and self-correct based on test results. Hope it's helpful!
https://www.signadot.com/docs/tutorials/autonomous-closed-loop-codex

AI is so powerful now. I feel companies should look at flexible time sharing contractors instead of part-time or full-time ones, benefit for both sides

hi everyone
wanted to share a small project i’ve been working on.

KubeAgent watches your Kubernetes clusters 24/7, diagnoses issues automatically, and applies safe fixes or pings you on Slack, Discord, Teams, Telegram, or PagerDuty to approve risky ones.

would love feedback from you.
https://kubeagent.net/

I just completed the self-service microservice IDP project, built with Backstage, ArgoCD, GitHub Actions and Helm. dev fills out a form in Backstage and gets a full repo + CI/CD + k8s would really appreciate any feedback, repos: - backstage portal: https://github.com/Eweka01/backstage-app - software templates: https://github.com/Eweka01/backstage-software-templates writeup: https://medium.com/@oseweka1/i-built-a-self-service-microservice-platform-with-backstage-argocd-github-actions-2037f46a3b50 (edited)

Medium
I Built a Self-Service Microservice Platform with Backstage, ArgoCD & GitHub Actions
Tech Stack: Python · Docker · GitHub Actions · Kubernetes · Helm · ArgoCD· Backstage: From CI/CD Pipelines to an Internal Developer Portal

Next Stategraph Demo Day is April 22: https://stategraph.com/demo-day
I’ll be putting the demo gods to the test by refactoring a messy Terraform repo live using Claude Code and the Stategraph SKILL.md

['=]---

Ever stopped an RDS or Aurora database, only to be surprised by a big bill because it was re-started after 7 days?

I'm excited to share a new release of github.com/sqlxpert/step-stay-stopped-aws-rds-aurora !

It should now work beyond just the aws partition (please confirm, and I'll acknowledge you in the next ReadMe update). I've also added an optional service control policy and enabled immutable releases.

Key elements are security (IAM intricacies and optional KMS encryption — the real thing, with support for multi-region keys housed in a separate account), multi-region + multi-account deployment (CloudFormation StackSet + optional Terraform), and serverless simplicity (EventBridge→Step Function). This was inspired by a user request, so I welcome your feedback…

the hashicorp license change last year made me realize i had no idea what it would actually take to migrate off terraform if we ever needed to. turned out the answer was way more complicated than just rewriting some hcl files - we're locked into the provider sdk, the module registry, and most painfully the state file format which doesn't have any clean conversion path to other tools unless you manually import every single resource one by one.
i documented the four types of lock-in most teams don't realize they have until they try to leave, plus realistic migration timelines based on team size

https://dev.to/muskan_8abedcc7e12/terraform-lock-in-is-real-heres-how-to-get-out-4j8g

anyone going to gitex africa ?

came across this post about Trivy, https://raxe.ai/labs/advisories/RAXE-2026-045

Claude Code source codes may be leaked…

Additional fall out from the Trivy compromise: https://security.snyk.io/vuln/SNYK-JS-AXIOS-15850650

https://stategraph.com/first-principles

wdy? looks like the case for monolith terraform repos mostly

The Trivy incident is a good reminder that supply chain attacks are as much an incident response problem as a security one. You can harden your pipeline, but when something slips through, the question becomes: how fast can you reconstruct what actually happened and what was touched?

That's the problem we work on at Anyshift. I'm Valentine, ML/Data background, now Founding GTM there. We build causal reasoning over production and infra data so when things break (or get quietly compromised), you're not stitching together logs and timeline manually. https://www.anyshift.io/

Curious how people here handle post-compromise investigation, any tooling beyond the usual SIEM + log grep?

While working around non-prod environments, I kept running into one issue, lack of visibility into actual usage vs assumed usage.

We tend to keep dev/staging infra “ready,” but rarely question:
are these environments really being used at that level?

Tried building a Grafana dashboard combining workload utilization, environment-level signals and rough cost indicators.

Nothing fancy, just trying to make decisions a bit more data-backed.

Shared what I explored here:
https://dev.to/muskan_8abedcc7e12/grafana-dashboards-for-non-prod-environment-observability-cost-performance-in-one-view-40hc

Would love to know how you all handle non-prod optimization in your setups.

finally: https://opentofu.org/docs/language/meta-arguments/enabled/

it took just 12 years to land that

Interesting read on the gap between how fast AI agents can generate code and how slow enterprise teams can actually validate it. Gets into why CI pipelines are becoming the bottleneck and what infrastructure needs to change.
https://thenewstack.io/ai-agent-validation-bottleneck/

https://claude.com/contact-sales/claude-for-oss

This Trivy compromise is insane to me. I've been trying to spread the word that this is probably more widespread than people realize: https://rosesecurity.dev/2026/03/20/typosquatting-trivy.html

Hey everyone,
Just announced our upcoming Skills product and would love to hear the community’s thoughts on it.
Skills are composable, deterministic validation capabilities that platform teams govern, developers define, and agents can run autonomously against live infrastructure to close the loop and deliver validated changes in distributed systems.
Here’s the blog. Please share any feedback or ideas for which skills would be most useful to your team.
https://www.signadot.com/blog/introducing-skills-microservices-validation-superpowers-for-coding-agents/

Was digging into Kubernetes cost optimization and ended up testing Spot + Karpenter + Graviton together, it turned out more practical than I expected.
Would be interested to hear how others are handling stability and trade-offs with similar setups.
Here’s what I observed:
https://dev.to/muskan_8abedcc7e12/going-to-production-spot-instances-karpenter-and-the-graviton-advantage-4oi5

AI tools are powerful… but they keep forgetting your code.

What if context never reset?

This session on Context Engineering with Tetrix shows how AI can actually understand your codebase, retain memory across sessions, and work seamlessly across tools like Cursor & Claude.

If you’re building with AI or working on complex systems — this is a must-attend.

📅 March 24 | 7:30 PM IST

Register here: https://luma.com/gssl6616