In this blog, I share my experience completing the AWSUG Madurai Builders Skill Sprint, where I built AI agents using the Strands Agents SDK, Amazon Bedrock, and MCP servers. Along the way, I explored tool calling, memory, streaming responses, cloud debugging, and ultimately created an AWS Architecture Roaster that combines official AWS documentation with humorous architecture reviews.

In this meetup we will (finally) talk about Amazon Connect and we are very fortunate to have Shubhangi Soni joining us from the Frankuft UG. She is going to talk about: *

Welcome to the AWS User Group AI/ML, Kuala Lumpur! This group is for professionals and enthusiasts interested in all things artificial intelligence and machine learning on the Amazon Web Services plat...

A group created for true Cloud advocates - based around the leading Cloud offerings from Amazon Web Services (AWS) and the latest technology trends. If you're keen, or simply curious - join us (non-te...

Last night, I spoke at the AWS Melbourne User Group, providing a deep dive into AWS Fargate. I began by recounting my first talk at the AWSUG in 2012 _Talking at the AWSUG Aug 2012_ ## Why Fargate? I highlighted the key challenges Fargate aims to solve: * With the rise of 12-factor apps, teams want to focus on deploying containers without managing underlying infrastructure * Keeping operating systems up-to-date is often difficult and easily neglected ## Fargate Architecture AWS Fargate (Linux version) is powered by Firecracker VM technology, providing security isolation for Linux-based Fargate containers and Lambda functions. The compute resource appears in your AWS account and is shared via a network interface (ENI). ## Pricing Considerations Fargate pricing depends on several factors: * Spot vs. on-demand instances * ARM vs. X86 architecture (note: Windows Fargate doesn't yet support ARM) * Windows vs. Linux (Windows incurs additional licensing costs) * CPU shares and memory allocation from a predefined menu (custom configurations not available) ## Container Scheduler Platforms AWS offers two main container scheduler platforms: * Elastic Kubernetes Service (EKS) * Elastic Container Service (ECS) Both platforms support: * Running containers on Fargate * Running containers on self-managed EC2 instances (or managed nodegroups in EKS) * Mixed deployment models ## ECS vs. EKS: Key Differences **ECS:** * Highly opinionated and simple * AWS-specific * Supports decentralized "you build it, you run it" operating models * Suited for multiple ECS clusters **EKS:** * Highly flexible with a rich plugin ecosystem * Requires specialized skills to operate effectively * Better suited for centralized operations * Typically uses fewer, larger clusters ## Choosing the Right Approach Consider your organization's operating model: * For traditional SRE centralized operations, EKS might be preferable * For decentralized operations that empower teams, ECS's simplicity may be advantageous _Note: Regardless of platform choice, developer-focused golden path tooling remains critical!_ ## Fargate Limitations at Scale When operating at scale, Fargate on EKS has some limitations: * Cannot run daemonsets (requires sidecar pattern instead) * Risk of overprovisioning if pod requirements don't align with Fargate launch options For a middle-ground approach, consider Bottlerocket as an AMI in EKS to reduce OS-level security risks. Additionally, running kube-scheduler on Fargate (including Karpenter) while using Karpenter to manage EC2-based nodes offers an excellent compromise. This is the video of my talk: here

A free, 8 hour virtual event bringing together cloud builders from across Aotearoa, Australia, and the wider Asia-Pacific region. Featuring sessions on the latest AWS services, real-world production…

Every journey has a “Day One.” For me, it began at AWS Community Day Philippines in 2023—just a curious student eager to learn. Two years later, that path led me to leading communities, delivering talks, graduating, and even boarding my first international flight to represent AWSUG Philippines at AWS Community Day Singapore. This is a story of growth, mentorship, and the power of community—proof that when you take a leap of faith, the opportunities are limitless.

Welcome to the AWS User Group AI/ML, Kuala Lumpur! This group is for professionals and enthusiasts interested in all things artificial intelligence and machine learning on the Amazon Web Services plat...

## **🚀 AWS User Group AI/ML Kuala Lumpur – Inaugural Meetup** 📅 **Date:** Thursday, 27 November 2025 🕖 **Time:** 7:00 PM – 9:00 PM 📍 **Venue:** AWS Malaysia Office, Ku

Last night, I spoke at the AWS Melbourne User Group, providing a deep dive into AWS Fargate. I began by recounting my first talk at the AWSUG in 2012 _Talking at the AWSUG Aug 2012_ ## Why Fargate? I highlighted the key challenges Fargate aims to solve: * With the rise of 12-factor apps, teams want to focus on deploying containers without managing underlying infrastructure * Keeping operating systems up-to-date is often difficult and easily neglected ## Fargate Architecture AWS Fargate (Linux version) is powered by Firecracker VM technology, providing security isolation for Linux-based Fargate containers and Lambda functions. The compute resource appears in your AWS account and is shared via a network interface (ENI). ## Pricing Considerations Fargate pricing depends on several factors: * Spot vs. on-demand instances * ARM vs. X86 architecture (note: Windows Fargate doesn't yet support ARM) * Windows vs. Linux (Windows incurs additional licensing costs) * CPU shares and memory allocation from a predefined menu (custom configurations not available) ## Container Scheduler Platforms AWS offers two main container scheduler platforms: * Elastic Kubernetes Service (EKS) * Elastic Container Service (ECS) Both platforms support: * Running containers on Fargate * Running containers on self-managed EC2 instances (or managed nodegroups in EKS) * Mixed deployment models ## ECS vs. EKS: Key Differences **ECS:** * Highly opinionated and simple * AWS-specific * Supports decentralized "you build it, you run it" operating models * Suited for multiple ECS clusters **EKS:** * Highly flexible with a rich plugin ecosystem * Requires specialized skills to operate effectively * Better suited for centralized operations * Typically uses fewer, larger clusters ## Choosing the Right Approach Consider your organization's operating model: * For traditional SRE centralized operations, EKS might be preferable * For decentralized operations that empower teams, ECS's simplicity may be advantageous _Note: Regardless of platform choice, developer-focused golden path tooling remains critical!_ ## Fargate Limitations at Scale When operating at scale, Fargate on EKS has some limitations: * Cannot run daemonsets (requires sidecar pattern instead) * Risk of overprovisioning if pod requirements don't align with Fargate launch options For a middle-ground approach, consider Bottlerocket as an AMI in EKS to reduce OS-level security risks. Additionally, running kube-scheduler on Fargate (including Karpenter) while using Karpenter to manage EC2-based nodes offers an excellent compromise. This is the video of my talk: here