🚀 Modern CI/CD with Dagger, Argo CD, and Kubernetes!

This flexible architecture leverages Dagger for portable CI/CD pipelines, Argo CD for GitOps-driven deployments, and AWS EKS with Karpenter for dynamic scaling 🧨

* Run pipelines in containers for isolation and portability.
* Automate infrastructure with Git as the single source of truth.
* Scale efficiently with ephemeral Dagger Engines and Karpenter.
* Integrate seamlessly with GitHub via Actions Runner Controller.

Cost-effective and cloud-native, it optimizes resources and supports modern DevOps.

#CICD #GitOps #Kubernetes #DevOps

https://dagger.io/blog/argo-cd-kubernetes

Imagine CQRS as the over-caffeinated coder who insists on reading AND writing data at the speed of light, while Microservices are like that friend who splits the group project into a million tiny tasks—total chaos but somehow it works! Event-Driven? That’s the guy who reacts to every ping like it’s a party invite.

#DevOps #Architecture #application

💡 Using AWS EKS? Watch out - cross-AZ control plane traffic might hit your wallet 💸

Yes - even inside the same AWS region, some traffic can be billed and other clouds are in the same situation. These costs are often hard to detect, and it's tricky to know which traffic you're paying for or who's generating it.
Let’s take a closer look at when and why this happens - and how the EKS architecture plays into it 👉

https://docs.aws.amazon.com/images/eks/latest/best-practices/images/reliability/eks-data-plane-connectivity.jpeg

🧱 Understanding the EKS Control Plane
To get to the root of the issue, we first need to understand how Amazon EKS sets up its control plane. By default, the EKS control plane is distributed across two Availability Zones (e.g., AZ A and AZ B), even when there's no load yet on the cluster. Meanwhile, when you create your cluster, you likely spread your worker nodes (like managed node groups or Karpenter node pools) across three Availability Zones for high availability - something AWS strongly recommends for reliability.

🧮 When Traffic is Free - and When It’s Not
Here’s where cost comes in. According to AWS:
Traffic within the same Availability Zone is free
Traffic between different Availability Zones, even in the same region, is billed
So, what does this mean in practice?
💰 Pods in AZ A communicating with the control plane in AZ A = ✅ free
💰 Pods in AZ B communicating with the control plane in AZ B = ✅ free
But...
💳 Pods in AZ C trying to talk to the control plane (which only exists in AZ A and B) = 💸 paid inter-AZ traffic

This kind of traffic might happen frequently - especially for workloads that constantly interact with the Kubernetes API server (like CI/CD tools, controllers, or operators), and there may also be work on the Amazon side, for example, rolling out patches to the control plane, which will lead to a change in zones for the control plane servers.

🛠 How to Reduce Inter-AZ Costs
To avoid or minimize these charges:
☘️ Align your worker node placement with control plane AZs (e.g., only use AZ A and B if cost is a concern)
☘️ Pin high-frequency API consumers (e.g., system pods or controllers) to AZs where the control plane resides
☘️ Use VPC Flow Logs + Athena or CloudWatch, KubeCost, CloudWatch + Usage Reports with Athena, CostExplorer, AWS CUR (Cost and Usage Report) with Athena or QuickSight(Cudos dashboards), or custom metrics to monitor traffic patterns.

Of course, I don’t think that with the increase in loads you will encounter this problem, since the control plane is automatically scaled and you will be in all availability zones. But it's good to have knowledge in this area and understanding these details can help you make better architecture choices - and avoid surprise costs ☀️

If you have any cool ways to find network traffic prices by source that I didn't list above, please share them in the comments 🤑

#aws #eks #network #AmazonEKS #CloudNative
#CloudCosts #AWSBilling #FinOps #InterAZTraffic
#AWSNetworking #DevOps #SRE #Observability

🚨Running Aws EKS in production is not just about launching a cluster !

😶It’s about engineering for scale, reliability, and application-specific behavior and that only comes with real production experience.
Creating effective solutions based on AWS EkS requires deep production experience. It’s not enough to "spin up a cluster"- you must design, adapt, and operate for real workloads.

Good cloud services are just a set of tools, to create good architectural solutions for applications and then their excellent performance to work on a global scale, you need cool engineers who have experience with such tools🧑‍💻

Here is a good article confirming my words: https://engineering.probo.in/production-grade-pain-lessons-from-scaling-kubernetes-on-eks-03571838c7a3

#K8s #AmazonEKS #application #architecture #infrastructure
#Kubernetes #CloudComputing #DevOps #CloudArchitecture #SiteReliabilityEngineering #ProductionReady #InfrastructureAsCode #CloudNative #SRE #Observability #PlatformEngineering #Scalability

The article “LLM Serving with BentoML” is a free, in-depth textbook 📚 that guides you through deploying and serving Large Language Models (LLMs) using BentoML. For DevOps professionals, this resource is a game-changer: it covers real-world workflows for packaging, automating, and scaling LLMs in production with modern CI/CD, containerization, and cloud-native best practices. As LLMs become a core part of future infrastructure, learning BentoML is a future-proof skill that will help you efficiently manage and operate AI-powered services. 🚀

https://bentoml.com/llm/

#DevOps #AI #LLM #BentoML #OpenSource #FutureSkills #FreeLearning #CloudNative #MLOps #Automation 🤖

User Guide Amazon EKS

#eks #infrastructure #DevOps #books

Cluster API vs Crossplane ⚔️ Which Kubernetes Deployment Tool Should You Choose? 🤔

Just had an interesting deep-dive conversation about Kubernetes deployment strategies. Here's what I've learned about choosing the right tool for deploying K8s clusters across any platform 💼

Cluster API (CAPI) - Most universal, Kubernetes-native approach
Crossplane + CAPI - Choice for unified management
Terraform + K8s Provider - DevOps favorite
Rancher - User-friendly management platform
Kubeadm - DIY approach for full control

You CAN use just Cluster API alone if your goal is purely cluster lifecycle management. But here's when you should consider adding Crossplane.

Cluster API Only is Enough When:
✅ You just need to create/upgrade/scale clusters
✅ Your infrastructure scope is limited to what CAPI providers handle
✅ You're comfortable with CAPI CRDs and clusterctl
✅ Your team is primarily ops/platform-focused

One of CAPI's biggest strengths is its ability to deploy Kubernetes on bare metal hardware servers through specialized providers. This opens up powerful on-premises and edge computing possibilities.

Some of the cool capi's providers for hardware deployment:
Tinkerbell - Bare metal provisioning engine for physical servers
KubeVirt - Virtual machines on Kubernetes
Proxmox - Virtualization platform with KVM/LXC
vSphere - VMware virtualization platform
Metal3 - Bare metal host management

Add Crossplane When You Need:
🚀 Broader infrastructure management (VPCs, databases, storage, etc.)
🔐 Self-service APIs for application teams
🌍 Multi-cloud governance and policy enforcement
🔄 Unified GitOps workflows for both clusters and cloud services

For most enterprise environments, Crossplane + Cluster API gives you the best of both worlds: Crossplane manages the cloud infrastructure, CAPI manages the Kubernetes clusters on top of it.

If you're already using Crossplane (like I am), consider whether you want managed control planes (EKS/GKE/AKS via Crossplane) or self-managed clusters (via CAPI) based on your operational preferences.

✨ Cluster API Only = You're just managing cluster lifecycles (create/upgrade/scale) - basic stuff
🚀 Crossplane + CAPI = You're building a full infrastructure stack

💊 PS: From the latest trends it will also be a good choice for an independent approach and with controller minimization without crossplane deployment of such clusters with the help of these controllers and tools -
* Where can crossplane replace and improve these controllers - https://github.com/flux-iac/tofu-controller, https://github.com/pulumi/pulumi-kubernetes-operator, https://github.com/kro-run/kro
* Gardener can enhance the Сluster API and provide a cool user experience - https://gardener.cloud/blog/2025/08/08-04-cluster-api-provider-gardener/

What's your experience with these tools?

#Kubernetes #DevOps #CloudNative #Crossplane #ClusterAPI #GitOps #PlatformEngineering #MultiCloud #Infrastructure

🤖✨ Hey tech builders & AI explorers!

Just found a gem on GitHub: 500+ AI Agent Use Cases 👉 https://github.com/ashishpatel26/500-AI-Agents-Projects

This repo is packed with practical AI agents — from health diagnostics 🏥 and trading bots 💹 to smart farming 🌱 and logistics automation 🚚.

Frameworks spotlighted:
• CrewAI – workflow automation (emails, meetings, resumes, Instagram content)
• Autogen – code generation, LLM debugging, web-browsing agents
• Agno – helpers like support chat, market insights, study companions
• Langgraph – multi-agent orchestration, RAG workflows, chatbot eval, SQL agents

💡 Why it matters for your career:
Learning how to design and integrate AI agents isn’t just “cool tech” — it’s a future-proof skill. Whether you’re into DevOps, cloud, data, or app engineering, these agents show how automation + AI can free you from repetitive tasks, sharpen your problem-solving, and even open doors to new roles in AI-driven infrastructure and operations.

Dive in, experiment, and maybe even contribute your own use case. The more you play with agents today, the more valuable you’ll be tomorrow. ⭐

#AI #AIAgents #Automation #DevOps #MLOps #Cloud #Kubernetes #CICD #CareerGrowth #OpenSource

🍬Want to master the creation of complex system architectures and confidently ace system design interviews at top companies?

📘This book is your key:
System Design Interview – Vol. 1 (Alex Xu)

✅ It breaks down real-world system design challenges step by step.
✅ Gives you the mental models to reason about scalability, reliability, performance, and trade-offs.
✅ Prepares you for high-stakes interviews, where system design is often the hardest part.
✅ Helps you think like an architect, not just an implementer.

⚡ Many engineers call this book the “Bible of System Design” — a foundation every serious DevOps and Platform Engineer should know.

👉 Start reading today, and you’ll not only grow as an engineer but also unlock career-defining opportunities.
#architecture #book #CareerGrowth
#CloudArchitecture #books #DevOps #learning #systemdesign

🚀 Looking to sharpen your GitOps skills with Argo CD?

🎯 Learn what it takes to become an Argo CD Project Champion 👉 https://www.youtube.com/watch?v=LSejrYaYcBI

⚙️ And go deeper with advanced application configuration patterns for more efficient and reliable deployments 👉 https://www.youtube.com/watch?v=aRKrDmqYLCE

#GitOps #ArgoCD #DevOps 🖥✨