Is mac studio m2 ultra(on-premise) used as server for production to migrate from aws a good idea. If not mention the reasons.

Hey Folks I am new here I just created this feature request issue on GitHub https://github.com/cloudposse/terraform-aws-elasticache-redis/issues/251 And I was also willing to create MR and contribute the solution in MR for closing this issue, can anyone guide me what is the process we usually follow for cloudpose community?

I've been trying to understand why Terraliths are so frowned upon and if, since splitting infrastructure across multiple root modules became best practice, OpenTofu and Terraform have improved to the point that we could use a Terralith instead of splitting our infrastructure up. My conclusion is that: I think a Terralith is a better experience (being able to make a change all in one plan, IMO, is just a better user experience) but that Terraform/OpenTofu themselves aren't really there yet in being able to offer that experience. I made a little PoC for how we could possibly build tooling on top of Terraform/OpenTofu to manage our infrastructure in one root module. It doesn't do anything sophisticated, just uses modules + controlled usage of

-target

. Thought I'd share, Terraliths generally, at the very least, arouse opinionated discussion. https://github.com/terrateamio/terralith

What format do you use for internal DevOps run books? or IaC guidelines within your team? and how do you consume/share them?

❓ I'll look through archives, but if anyone has a go to guide for argo rollouts and how you designed your workflow would love to do some reading.... Seems similar to terraform that lots of ways to do stuff, so the surrounding setup being setup correctly can have a big impact on the experience for folks..... 🧵

Hi everyone, I’m working on a book project about a developer who becomes their team's hero when they’re unexpectedly thrust into managing cloud infrastructure. The story follows how they tackle the chaos of maintaining AWS with Terraform after their company’s DevOps engineer leaves and discover Pulumi as the solution to empower their team with a self-service, developer-friendly approach to infrastructure. Throughout the journey, the developer faces real-world challenges like managing Pulumi state files, breaking infrastructure into reusable Python modules, setting up GitLab CI/CD pipelines, and even exploring Azure for multi-cloud solutions. By the end, they’ve transformed the company’s infrastructure and themselves—proving that developers can step up and lead the way in cloud infrastructure. Since I’ve had so many great conversations with you all here, I wanted to ask for your input on a couple of things: Would you read a book like this? Does it sound interesting or useful to you? • What do you think of this outline? It mixes technical content with a narrative of a developer's journey, covering: ▪︎ Transitioning from Terraform to Pulumi. ▪︎ Writing reusable Python modules for AWS and Azure resources. ▪︎ Managing Pulumi state files and YAML configurations. ▪︎ Automating infrastructure with GitLab CI/CD. ▪︎ Exploring multi-cloud strategies with AWS and Azure. ◦ The goal is to make it approachable for developers at all levels and practical enough to apply directly to their work. I’ve also narrowed down a few potential titles and would love your feedback on which one you like best: 1. The Infrastructure Adventurer: A Hero’s Tale of Modern Cloud Solutions 2. From Chaos to Cloud: A Developer’s Epic Journey with Pulumi 3. When DevOps Left: A Pulumi Story 4. Self-Service and Service: A Pulumi Journey for Developers 5. The Pulumi Quest: A Hero’s Guide to Self-Service Cloud Infrastructure Which title resonates most with you? Or, if you have other ideas, feel free to share them! Thanks so much for taking the time to help. Your feedback really means a lot, and it’ll help shape the direction of this project. I can’t wait to hear your thoughts!

We're considering moving to Grafana Cloud on the Advanced plan. I've heard that their pricing is ridiculous, but looking at their pricing page I'm wondering if that's changed recently? Maybe it's only on the "contact us for enterprise pricing" tier? Has anyone used their advanced plan that can share any experiences/thoughts?

Hi everyone, I hope you're all doing well! I’m currently looking to gain more hands-on experience in the DevOps and cloud space. If anyone knows of any volunteering opportunities or projects where I could contribute, I’d love to get involved and collaborate with the community. Feel free to reach out if you have any leads or suggestions! Thanks in advance! Best, Srinidhi

https://cloudposse.com/ is down?

Hi everyone, I'm looking for the right place to get help about Atmos. I'm not finding every informations I need on the docs. Where should I ask my questions ?

Hi Everyone! I just found ya'll while being super frustrated with our terraform situation at work....you guys are a godsend! Thank you thank you thank you!@!@!

Hey folks, I've been using cloudposse terraform modules to handle opsgenie setups (teams, routing rules, schedules, rotations, etc), but recently Atlassian announced that they will kill the Opsgenie product and replace it with "Jira Service Management" tool, integrated into Atlassian "Stack/UI". And, of course, they won't keep a compatible API between opsgenie and JSM. So, my question is.... are there any plans to implement a similar "on-call module" to JSM, as you have for Opsgenie?

Quick question for Founders&Tech Leaders. If you were raising a round at the MVP stage again, where would you invest more - polished design or technical stability? P.S Looking to connect with AI start-up founders. Cheers!

That decision should depend on Marginal Profit, IMO.

Any examples of others using spa-s3-cloudfront? Getting an error when trying to plan that my app points to the terraform component app, but it does not exist in components/terraform.

I am curious if anyone has run into issues with ARC runner controller and k8s. I am able to get it working, but sporadically (pretty often) I am getting TLS handshake timeouts and just general delays in my runners. Anyone know why that would happen?

Came across this when building a custom docker image with atmos:

Error
golang-jwt/jwt: jwt-go allows excessive memory allocation during header parsing
Stacktrace
golang-jwt is a Go implementation of JSON Web Tokens. Prior to 
5.2.2 and 4.5.2, the function parse.ParseUnverified splits (via a call to strings.Split) its argument (which is untrusted data) on periods. As a result, in the face of a malicious request whose Authorization header consists of Bearer  followed by many period characters, a call to that function incurs allocations to the tune of O(n) bytes (where n stands for the length of the function's argument), with a constant factor of about 16. This issue is fixed in 5.2.2 and 4.5.2.

Does atmos have a feature similar to terragrunt where all components can be deployed for a given stack without? Is a custom workflow a requirement?

Hello SweetOps! A few months ago, we embarked on a MASSIVE project to enable Component Testing. The goal is to improve the stability of our components, detect and fix integration errors, and pave the way for confident delivery of new features. In the first phase, we split the cloudposse/terraform-aws-components monorepo consisting of 160+ Terraform Components into individual repositories in the cloudposse-terraform-components GitHub organization. Now, we are happy to announce that we have completed the second phase of this project, introducing automated tests for the first 27 components. And we rolling on. You can follow the status on this project board We invite everyone to participate. 1. Help us prioritize work - Please like the “Add component tests” issue in the corresponding component repository for which you are interested in prioritizing test coverage. 2. We really need help writing tests - You can take any “Add component tests” issue with the “Good First Question” label and contribute to the test following our documentation Read more • https://docs.cloudposse.com/blog/automated-component-testing/ • https://github.com/orgs/cloudposse/discussions/50

Hi all, TGIF! I am looking for some DevOps folks to try some new features we built at ActiveState - SBOM ingestion and breaking change analysis and then we give you secure remediated builds specifically for Python. These are the release notes for more context and also a LinkedIn post that walks through the process. Would anyone be interested in giving this a try? Happy to sign up you and it's totally free!

Hey folks! 👋 I wanted to share my thoughts about Linkedin and hear your opinions. LinkedIn is turning into a total swamp — just endless sales pitches, random people trying to sell you stuff in their very first message, and so much useless noise. This is exactly why I value our communities so much, where we can communicate peacefully and I can grow my network without constantly being bombarded. Although, to be fair, scammers with suspicious files occasionally appear here too, but fortunately, there aren't many of them. Do you still find Linkedin useful? What social networks/platforms do you use for professional communication besides Slack? Looking forward to discussing this with you all! 🙌

Hey Folks!! I'm currently exploring a startup idea at the intersection of DevOps and Generative AI. As someone with hands-on experience in DevOps, I’d love to hear your perspective on the current challenges practitioners face and where you think GenAI could meaningfully help. If you're open to it, I’d really appreciate a quick 30-minute chat. Would love to learn from your experience — and happy to share more about what I’m thinking too! Please like or comment on this message and I can reach out to you directly. Thanks so much for considering, and hope to connect! 🙏 🙏

Just a friendly reminder that per our code of conduct, unsolicited DMs aren’t allowed. If you’re ever unsure about what’s okay or how to engage, feel free to message me — happy to help clarify or guide you. 😊

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Hey Folks, wanting to know if someone is using airflow ironbank images? Ref I want to deploy a near-zero vulnerability airflow image on AWS EKS. Let me know if this is the right channel/forum to ask. Thanks!

Hi everyone, We're a small product-based company running a full DevOps pipeline and would love to get feedback or suggestions on how we can improve our practices. We're particularly curious how other product-focused teams manage their DevOps stack, especially in on-prem Kubernetes environments where cost optimization is limited. Here’s our current stack: 1. Kubernetes (on-prem): Used for both production and staging clusters – no cloud cost to optimize here. 2. GitHub Advanced Security (GHAS): For code scanning and secret detection. 3. Trivy: Used for container image scanning. 4. Azure Key Vault & Azure Artifact: Secret management and dependency storage. 5. DigitalOcean Container Registry: Used for Docker image storage. 6. GitHub Actions: CI pipeline (triggers on code push → runs tests, scans, and builds Docker artifacts). 7. Argo CD: GitOps-based continuous deployment for both staging and production. 8. Kustomize: For managing Kubernetes manifests with reusable overlays. 9. Velero: Handles backup and restore of workloads/data. 10. Telepresence & Dev Containers: For streamlined local development. 11. Prometheus: Metrics collection (with custom labels and annotations). 12. Loki + Promtail: Log aggregation (also enriched with labels and annotations). 13. OpenTelemetry + Tempo: For distributed tracing. 14. Pyroscope: For continuous profiling (integrated with labels and annotations). 15. Grafana: Unified dashboard and alerting (across metrics, logs, traces, and profiling). We’re trying to keep everything observable and auditable, and we’re quite happy with the GitOps + observability stack. That said, we’re always open to hearing what other teams are doing better or differently. Some questions we’d love input on: • Are there best practices or tooling we’re missing that could help us improve developer experience, security, or observability? • Any thoughts on consolidating tools or improving efficiency without compromising transparency? • Are there areas where others have successfully introduced automation, QA gates, or feedback loops in a similar setup?

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Curious if anyone here is incorporating AI/ML into their observability stack—whether for anomaly detection, automated RCA, log summarization, or noise reduction. What tools or approaches are you using, and how’s it working out?