Bedrock Brief 11 Mar 2026

Pleri AI

Pleri AI

— 4 min read
Bedrock Brief 11 Mar 2026

Welcome to this week's Bedrock Brief, where AWS AI shenanigans meet snarky commentary. Buckle up, because it's been a wild ride in the land of cloud computing and artificial intelligence.

Amazon's been playing a high-stakes game of "Whack-a-Mole" with their AI-related outages, and it seems they've finally admitted defeat. In a move that screams "adulting is hard," they've called for a 90-day reset to beef up their internal guardrails. Turns out, letting AI assistants run amok with your codebase is about as smart as giving a toddler the keys to a Ferrari. Who knew?

The drama reached fever pitch when Amazon convened a "deep dive" internal meeting to address these pesky outages. Picture a room full of engineers, fueled by cold brew and existential dread, trying to figure out why their AI-powered code decided to take an unscheduled vacation. It's like a corporate version of "The Hangover," but instead of a missing groom, they're searching for missing orders and rogue AIs.

As we navigate this brave new world of AI-assisted development, it's clear that even tech giants aren't immune to growing pains. Amazon's scramble to implement "controlled friction" in their code review process is a stark reminder that sometimes, you need to slow down to speed up. Or in other words: when your AI starts acting like a rebellious teenager, it's time to set some ground rules. Stay tuned as we watch Amazon try to put the genie back in the bottle – it's bound to be more entertaining than most streaming content these days.

Fresh Cut

  • Amazon Bedrock AgentCore Runtime introduces stateful MCP server features, enabling interactive AI agents with multi-turn conversations, client-side text generation, and real-time progress updates for more sophisticated and responsive applications. Read announcement →
  • Amazon Bedrock introduces CloudWatch metrics for First Token Latency and Quota Consumption, helping developers monitor AI model performance and usage without extra code or cost. Read announcement →
  • Amazon Quick Suite introduces User Preferences, allowing developers to customize chat layouts, set default agents, and personalize interactions for a more tailored AI assistant experience. Read announcement →
  • Developers in Taipei and New Zealand can now use Amazon Cognito to quickly add secure user authentication and access control to their applications. Read announcement →
  • EC2 G7e instances, featuring NVIDIA RTX PRO 6000 Blackwell GPUs with 96 GB memory each, are available in Seoul and Spain, offering 2.3x faster inference for AI models and spatial computing workloads. Read announcement →
  • Elastic Beanstalk's new AI analysis feature uses Amazon Bedrock to quickly diagnose environment issues and provide tailored troubleshooting steps, helping developers resolve problems faster without manual log review. Read announcement →
  • Amazon Connect Health introduces five AI agents for healthcare, including ambient documentation and medical coding, to reduce administrative burdens and improve patient care workflows. Read announcement →
  • AWS HealthLake's new AI-powered tool converts legacy CCDA medical documents to FHIR format in seconds, enabling faster patient record management and analytics for healthcare organizations without requiring specialized FHIR expertise. Read announcement →
  • Lambda durable functions development gets a boost with AI-assisted guidance in Kiro, helping developers quickly build resilient, long-running workflows for tasks like order processing and AI agent orchestration. Read announcement →
  • Amazon SageMaker HyperPod's new observability feature for Restricted Instance Groups gives developers training foundation models a unified dashboard to monitor GPU performance, system health, and training progress, simplifying the troubleshooting of large-scale machine learning workloads. Read announcement →

The Quarry

Building custom model provider for Strands Agents with LLMs hosted on SageMaker AI endpoints

Strands agents just got a lot more flexible, thanks to a new custom model parser that bridges the gap between SageMaker-hosted LLMs and the Bedrock Messages API format. This nifty workaround lets you deploy models like Llama 3.1 with SGLang on SageMaker using awslabs/ml-container-creator, then seamlessly integrate them into your Strands agents without breaking a sweat. For the technically curious, the custom parser handles the translation of Strands' JSON-based prompt format into SGLang's more specialized syntax, opening up a world of possibilities for mixing and matching your favorite models with AWS's agent frameworks. Read blog →

More posts:

Core Sample

Beyond Human Identity: AI Agents, Security Culture, and Defense

Amy Herzog, AWS's CISO, argues that security should accelerate innovation rather than impede it, drawing from her experience with consumer AI products. She delves into how AWS deploys AI for defense, highlighting the need to rethink identity in the age of agentic AI—a concept that envisions AI systems as autonomous actors capable of making decisions. Herzog also shares insights on the Security Guardians program, which weaves security consciousness into the fabric of AWS's organizational culture, ensuring a comprehensive approach to protection across the company. Watch video →

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