DevBrainOps
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The group whose goal is to find the best approaches and solve problems of #DevOps practice.
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OpenAI's free course on GPT-o1 prompting. Taught by OpenAI's head of AI solutions, Colin Jarvis. Complete in just over an hour

#ai #courses

https://www.deeplearning.ai/short-courses/reasoning-with-o1/
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Resourcefulness above all else

#humor #dev #ops
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🎮 Welcome to the immersive multiplayer demo ! In this session, we’ll explore how to design and deploy a cloud-first implementation of a global-scale, real-time multiplayer game.

Key Features:
❄️Global Scale: Seamlessly connect players worldwide using robust cloud infrastructure.
❄️Realtime Multiplayer: Enable low-latency gameplay with dedicated game servers tailored for high performance.
❄️Cloud-First Implementation: Built on Google Cloud products, leveraging their reliability, scalability, and efficiency.
❄️Open Source Gaming Solutions: Enhance flexibility and innovation by incorporating open-source technologies like Agones for dedicated server orchestration.

What You'll Learn:
❄️How to deploy and manage dedicated game servers with tools like Agones and Kubernetes.
❄️How to integrate Google Cloud products, such as Compute Engine, Cloud Functions, and Pub/Sub, to build a reliable backend.
❄️Best practices for scaling and optimizing real-time multiplayer experiences globally.

https://github.com/googleforgames/global-multiplayer-demo/raw/main/images/architecture.png

🍯By the end of this workshop, you’ll understand how to architect and deploy a scalable, immersive, real-time multiplayer gaming experience that combines the best of cloud computing and open-source solutions.

Let’s get started and level up your game development skills!

#gamedev #devops #infrastructure

https://github.com/googleforgames/global-multiplayer-demo
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Well-covered monitoring 🩻 should cover such issues:

What went wrong 💡=> Metrics
Why it went wrong 💡=>Logs
Where it went wrong 💡=> Traces
How it went wrong 💡=> Profiles

#observability #DevBrainOps
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Kubernetes Best Practices.pdf
2.4 MB
Kubernetes best practices: this guide in the context of azure will help you learn good techniques for using kubernetes in the cloud

#infrastructure #learning #book #azure
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Things Every Developer Should Know: Concurrency is 𝐍𝐎𝐓 parallelism. 🧑‍💻

#development #SystemsDesign
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Unlock the power of Crossplane with these expertly written guides 🍇, perfect for budding platformer engineers who looking to streamline multi-cloud management.
Master infrastructure as code efficiently and elevate your skills with practical, real-world insights from industry pros 🤓

💡 Crossplane: A Comprehensive Introduction 🫨 🔬
An expertly crafted introduction to Crossplane, ideal for budding platformer engineers. It leverages Kubernetes effectively, offering a robust foundation for managing multi-cloud environments with precision.
🧲 https://www.codecentric.de/en/knowledge-hub/blog/crossplane

💡 Testing Crossplane Compositions with kuttl: Part 1 🔬
This article provides a detailed guide on testing Crossplane compositions using kuttl with a structured approach to ensure reliable infrastructure configurations.
🧲 https://www.codecentric.de/en/knowledge-hub/blog/testing-crossplane-compositions-kuttl

💡Testing Crossplane Compositions with kuttl: Part 2 🔬
This article dives into kuttl’s Given-When-Assert method for Crossplane testing, it enhances understanding of validation techniques with expert clarity.
🧲 https://www.codecentric.de/en/knowledge-hub/blog/testing-crossplane-compositions-kuttl-part-2-given-when-assert

💡Crossplane Configuration Packages with GitHub 🔬
This article provides expert guidance on packaging Crossplane configurations using GitHub, providing efficient version control and deployment practices.
🧲 https://www.codecentric.de/en/knowledge-hub/blog/crossplane-configuration-packages-github

#Crossplane #Kubernetes #CloudNative #PlatformEngineering #DevOps #MultiCloud #Infrastructure
#TechTutorials #SoftwareEngineering #GitHub #CloudComputing #TechLearning #SRE #TechCommunity
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“Typing good AI prompts” is not an engineering discipline 😏, and slapping "engineer" into your role doesn’t make it a real job.

Prompt engineering is just a collection of tricks and workarounds for getting LLMs to overcome their inherent limitations. ☺️

#humor #ai
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🎒Google, Harvard, Microsoft and more are offering FREE AI courses with no payment required.

Here are 8 free courses to learn AI in 2025:

1. Introduction to Generative AI | Google
This is an introductory level microlearning course aimed at explaining what Generative AI is.
https://lnkd.in/eW5k4DVz

2. Microsoft's AI for Beginners
Microsoft's AI course starts with the basics and goes deeper. Learn about neural networks and deep learning as you progress.
🔗 https://lnkd.in/eKJ9qmEQ

3. Introduction to AI with Python
Harvard offers a 7-week course to explore AI concepts and algorithms.
Learn the tech behind AI and gain insights into machine learning libraries.
🔗 https://lnkd.in/dvHKidDp

4. Prompt Engineering for ChatGPT
Vanderbilt University offers a 6-module course for beginners on crafting effective prompts. Start with basics and learn how to get ChatGPT to work exactly how you want.
🔗 https://lnkd.in/d-rCb-AM

5. ChatGPT Prompt Engineering for Devs
OpenAI and DeepLearning present this course taught by Isa Fulford and Andrew Ng. Learn best practices and get hands-on experience with prompting.
🔗 https://lnkd.in/gtGc5Znp

6. LLMOps
Google Cloud and DeepLearning offer this course led by Erwin Huizenga. Master the LLMOps pipeline, train, and deploy your custom LLM.
🦾 https://lnkd.in/gMXDr7MJ

7. Big Data, Artificial Intelligence, and Ethics
UC Davis introduces big data and IBM’s Watson in this 4-module course. Learn about big data opportunities and AI’s limitations.
🔗 https://lnkd.in/gVEf3Dvm

8. AI Applications and Prompt Engineering
edX offers an intro course that goes beyond basic prompt engineering. Learn the basics and create your own AI applications.
🔗 https://lnkd.in/eyEVG4jD

#learning #freecources #ai
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The Kubecon London talk about Crossplane and v2
https://www.youtube.com/watch?v=6MrXcbcxnN4
#infrastructure #DevOps #video
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How Kubernetes Works from Start to Finish ? 🛵

👣 1. You set up a Kubernetes cluster - it consists of a control plane and worker nodes.
2. You define your application using YAML files - typically with Deployment, Service, ConfigMap, etc.
3. You apply the YAML using kubectl apply -f, the request goes to the API Server, the central control point.
4. Kubernetes checks the request to decide what to do:
a). Create a new object like a Pod or Deployment?
b). Update or delete an existing object?
c). Trigger a controller to take action? etc.
5. The API server stores the object’s spec in etcd, the cluster’s database.
6. The appropriate controller sees the new spec - like a ReplicaSet controller watching for new Deployments.
7. The controller creates the necessary resources - for example, telling the scheduler to place new Pods.
8. The scheduler picks a suitable node for each Pod - based on resource availability and scheduling rules.
9. The Pod spec is sent to the node’s Kubelet - it requests the container runtime to start the container.
10. The container runtime pulls the image, creates the container, and runs it inside the Pod.
11. The CNI plugin assigns a network identity - the Pod gets an IP address and joins the cluster network.
12. kube-proxy sets up routing rules - allowing Services to forward traffic to healthy Pods.
13. The Kubelet reports Pod status back to the API server - used to track readiness and health.
14. If a Pod crashes or is deleted, the controller notices and recreates it - keeping the system in sync.
15. This entire loop keeps running - Kubernetes constantly watches and reconciles to match the desired state.

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#infrastructure #devops #kubernetes
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How tightly are your application code and CI/CD pipelines tied to a specific cloud or on-prem environment? While Kubernetes abstracts workload execution, other critical factors—such as infrastructure dependencies, service configurations, build processes, and deployment descriptors—can lock you into a single environment. This coupling limits flexibility, complicates migrations, and increases costs when adapting to new platforms, compliance requirements, or specialized technologies.

📺 In this video you can see the approach how standardize and decouple these elements, creating portable, reusable workflows that streamline CI/CD across diverse environments, enhance observability, and empower seamless transitions without vendor lock-in.

#DevOps #infrastructure #kubernetes #video
#Dapr #Crossplane #Dagger #ArgoCD

https://www.youtube.com/watch?v=PSenmCMU5mQ&t=48s
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