Amazon AI & ML Services Monitoring
Amazon's Artificial Intelligence (AI) and Machine Learning (ML) services portfolio enables organizations to build, train, and deploy generative AI applications without managing complex underlying infrastructure. At the core of this portfolio, it provides services that enable you to access foundation models (FMs) from leading AI companies through a single API, as well as enables autonomous AI agents that orchestrate foundation models, APIs, and knowledge bases to execute multi-step tasks.
Monitoring these AI and ML services is essential to control generative AI costs, maintain low-latency inference, and ensure reliable execution of AI-driven workflows. Applications Manager provides comprehensive monitoring capabilities for Amazon AI & ML Services, enabling you to track invocation performance, token consumption, throttling events, agent orchestration health, and log delivery status across your AWS environment from a single console. Applications Manager supports monitoring of following Amazon AI & ML services:
Amazon Bedrock monitoring
Amazon Bedrock is a fully managed service that provides access to high-performing foundation models (FMs) from leading AI companies through a single API. It enables developers to build and scale generative AI applications using techniques such as fine-tuning, retrieval-augmented generation (RAG), and agent orchestration, without managing the underlying infrastructure.
Applications Manager monitors the regional Bedrock environment by providing visibility into foundation model invocations and performance of your Bedrock resources at the regional level. With Applications Manager, you can:
- Track Invocation Client Errors, Invocation Server Errors, and Throttled Invocations to quickly detect request failures and service quota breaches affecting your generative AI workloads.
- Monitor Estimated TPM Quota Usage across the Converse, ConverseStream, InvokeModel, and InvokeModelWithResponseStream API operations to proactively manage token-per-minute quota consumption and avoid throttling.
- Measure Invocation Latency and Time to First Token to evaluate model responsiveness for both standard and streaming inference requests.
- Track Input Tokens, Output Tokens, and Images Generated to understand usage patterns across foundation models and control generative AI costs.
- Monitor total Invocations to gain visibility into overall request traffic and identify unexpected usage spikes.
- Ensure reliable observability by tracking successful and failed log deliveries to CloudWatch Logs and Amazon S3, including large data logs, to maintain complete audit trails of model invocations.
Amazon Bedrock Agents monitoring
Amazon Bedrock Agents is a feature of Amazon Bedrock that enables developers to build autonomous AI agents capable of executing multi-step tasks by orchestrating foundation models, APIs, and knowledge bases. Agents interpret natural language instructions, break down complex requests into sequences of actions, invoke tools such as Lambda functions and knowledge bases, and return coherent responses, without requiring custom orchestration logic.
With Applications Manager, you can:
- Monitor agent configuration details such as Lifecycle State, Agent Version, Foundation Model, Orchestration Type, Memory Type, IAM Role, and Session Idle Time-to-Live to maintain visibility into agent setup and behavior.
- Track linked Guardrail and Knowledge Base associations, along with their build and grounding pipeline states, to ensure agent safety controls and retrieval sources remain healthy.
- Monitor alias deployment records, including Deployment Status, Associated Version, and Creation/Last Updation times, to confirm agents are deployed and routed correctly.
- Track Total Requests, Client Errors, Server Errors, and Throttled Requests per alias and operation to quickly detect failures in orchestration execution.
- Measure Time to First Token and Request Latency to evaluate end-to-end agent responsiveness during multi-turn conversations.
- Track Prompt Tokens and Response Tokens consumed per alias deployment to manage generative AI costs at a granular level.
- Monitor model-level invocation metrics, including Model Client Errors, Model Server Errors, Model Request Throttles, Model Request Latency, and Model Requests, to isolate issues at the foundation model layer.
Looking to monitor your Amazon AI & ML Services?
Applications Manager is an all-in-one monitoring tool that effectively monitors a wide range of Amazon services. Start monitoring your AWS AI and machine learning workloads in minutes with Applications Manager's comprehensive AWS monitoring solution and ensure reliable, cost-effective generative AI operations. Download a 30-day free trial today!
Do more with Applications Manager's AWS monitoring with:
- Amazon Analytics Services Monitoring
- Amazon Compute Services Monitoring
- Amazon Container Services Monitoring
- Amazon Database Services Monitoring
- Amazon Management Services Monitoring
- Amazon Migration & Transfer Services Monitoring
- Amazon Network Management and Content Delivery Monitoring
- Amazon Networking Infrastructure Monitoring
- Amazon Storage Services Monitoring
- Amazon Integration Services Monitoring
- Amazon Security Services Monitoring
