Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-François Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Publication

Let’s Build an AI On-Call Buddy: An MVP Using AWS Bedrock to Supplement Incident Response
Latest   Machine Learning

Let’s Build an AI On-Call Buddy: An MVP Using AWS Bedrock to Supplement Incident Response

Author(s): Asif Foysal Meem

Originally published on Towards AI.

This member-only story is on us. Upgrade to access all of Medium.

Source: Image by Midjourney

Imagine a system where an on-call engineer can simply ask a chatbot — “What’s wrong with the checkout service?” and receive a concise, actionable response — complete with logs, metrics, and insights.

Hot take 🔥 — Being on-call is already a unique brand of excitement — a mix of firefighting and waiting for the next alarm to ruin your dinner plans — Why not add the fun of debugging log retrieval systems to the mix?

That’s the vision that drove this experiment: to integrate AWS Bedrock, AWS Lambda, and CloudWatch logs into a seamless support system. But like any ambitious project, it came with its share of challenges, particularly a pesky 25 KB payload limit.

AWS Bedrock, AWS Lambda, and CloudWatch logs are powerful tools in modern cloud architecture. However, combining these services to achieve seamless functionality can reveal some surprising limitations. This article recounts an experiment to integrate these AWS services for an on-call support chatbot and explores solutions to overcome the challenges encountered, specifically a 25 KB payload limit.

The project started with a clear objective: to build a functional MVP for a DevOps chatbot using AWS Bedrock…. Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓