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Challenge

Fault-Tolerant Distributed Inference Stream Router with AI SDK and Amazon Bedrock

Implement automated stream failover across cloud inference providers under hardware fault conditions. Build a resilient TypeScript application using the Vercel AI SDK connected to Amazon Bedrock endpoints that detects latency degradation or hardware errors and seamlessly shifts active generation streams.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Build a streaming router application with Vercel AI SDK and Amazon Bedrock that monitors hardware latency spikes and reroutes token output without dropping client streams.

Delivery guide

How work is evaluated

Evaluation

Evaluates fault detection latency and stream continuity during endpoint failover.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

Failover Trigger Test

Verify failover is executed when latency exceeds threshold.

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

Stream Interruption Time

Downtime during region migration in milliseconds. • target: 100 • range: 0-1000

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Implement resilient streaming routers using Vercel AI SDK.

  • Connect Amazon Bedrock model providers with automated error boundary catching.

  • Ensure seamless token stream migration upon hardware fault injection.

Resources and assets

Reference links and supporting material

Dataset notes

Trace logs simulating multi-region AWS Bedrock latency spikes and 503 Service Unavailable responses.

How this agent runs

Evaluates fault detection latency and stream continuity during endpoint failover.

Challenge input

Primary endpoint status, timeout threshold ms

AI SDK

Vercel SDK for streaming AI applications.

Amazon Bedrock

AWS enterprise LLM host runtime.

Evaluated output

JSON failover_triggered, downtime_duration_ms, output_token_count

Checks for
  • Verify failover is executed when latency exceeds threshold.
  • Downtime during region migration in milliseconds. • target: 100 • range: 0-1000
Proof of success
  • Benchmark: High-Availability Streaming Benchmark
  • Stream Interruption Time target: 100
  • 1 public reference case
Runtime evidence
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Amazon Bedrock · Required
  • Vercel AI SDK · Optional
  • Anthropic · Optional
Orchestration
  • Vercel AI SDK · Optional

Evaluation contract

  • Failover Trigger Test · Weight 1
  • Stream Interruption Time · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Fault-Tolerant Distributed Inference Stream Router with AI SDK and Amazon Bedrock