Shubham Londhe
Happy Learning :)
Pune, India
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Hi, I am Shubham Londhe, a Senior Developer Advocate, passionate about developing and deploying production-ready applications while building and working with teams of Software Developers, DevOps Engineers and Solutions Architects.
After developing Applications in a product-based startup and a mid-size service-based firm, I gained experience in Python, Django, Flask, AngularJS, SQL, Neo4J, MongoDB, DevOps, Docker, AWS, Leadership Skills, and Soft skills.
Getting the responsibility of working with a team of enthusiastic software developers was one of the biggest achievements which improved my communication skills and I could share my knowledge and experience with college students from Symbiosis, MIT, and Pune as well as freshers and Associates.
I believe continuous learning and development to keep myself up-to-date and up-skilled is the solution to modern-day application development for customers and community.
Area of Expertise
Topics
Context Aware Clusters: Scaling Kubernetes Clusters with EKS MCP Server
Deploying and managing production-ready Kubernetes can be a complex and time-consuming task, especially as your footprint grows. Fortunately, Amazon EKS MCP Server is here to simplify your cloud-native journey.
In this session, we'll dive deep into the power of EKS MCP Server with EKS Auto Mode, and uncover how it can revolutionize the way you approach Kubernetes operations. Learn to leverage intelligent automation to:
- Provision highly available, secure, and scalable Kubernetes clusters with a single click
- Automatically manage your control plane and data plane with Karpenter
- Reduce the operational burden of Kubernetes lifecycle management
- Ensure your clusters are always running the latest version and security patches
- Unlock the full potential of your Kubernetes deployments and free up your team to focus on building innovative applications. Join us and discover how EKS Auto Mode can help you streamline your path to production-ready Kubernetes at scale.
Building Long Running Crash-proof AI Agents with MCP
Everyone's building AI agents with MCP right now, but almost nobody is testing what happens when things crash halfway through a tool call.
Spoiler Alert: Your agent loses everything and you have no idea where it stopped.
In this workshop, we'll build an AI agent from scratch that talks to tools via MCP. First we'll build it the naive way, break it on purpose, and see how bad it gets.
Then we'll rebuild it by wrapping MCP tools in durable workflows so your agent survives crashes, restarts, and network failures as if nothing happened.
No slides. Just code. You break things, you fix things, you leave with something real.
Tech Stack needed:
- Python 3,12+
- Temporal
- AWS Strands Agents or Langchain
- Docker
- mem0
Rest we can do live, even if you're a complete beginner,
Building Durable AI Agents with AWS Strands, MCP, and Temporal
AI agents are everywhere, but most demos fall apart the moment something goes wrong
— a tool call fails, an API times out, or a long-running workflow loses its state.
In this hands-on workshop, you'll learn how to build AI agents that actually work
in the real world.
We'll start from scratch using AWS Strands Agents SDK to build an AI agent, then
connect it to external tools and data sources using the Model Context Protocol
(MCP). Finally, we'll tackle the hardest part of production AI — reliability — by
integrating Temporal to make our agent workflows durable, resumable, and
fault-tolerant.
What you'll learn:
- How to build AI agents using the Strands Agents SDK
- Connecting agents to external tools with MCP servers
- Why AI agent workflows fail in production and how to fix it
- Using Temporal to add durability, retries, and state management to agent
workflows
Who should attend: Developers curious about AI agents, whether you're just getting
started or looking to move beyond basic chatbot demos. No prior experience with
Strands, MCP, or Temporal required — just bring your laptop and a sense of
curiosity.
Prerequisites: Basic Python knowledge and a laptop with Python 3.10+ installed.
Shubham Londhe
Happy Learning :)
Pune, India
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