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AWS Cheat Sheets

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Amazon SageMaker Model Monitor Cheat Sheet

2026-01-12T09:02:21+00:00

Bookmarks Features How It Works Implementation Use Cases Integration Best Practices Pricing    A fully-managed, automated service within Amazon SageMaker that continuously monitors the quality of machine learning (ML) models in production. It automatically detects data drift and model performance decay, sending alerts so you can maintain model accuracy over time without building custom monitoring tools. Features Automated Data Capture & Collection Configures your SageMaker endpoints to capture a specified percentage of incoming inference requests and model predictions. This data, enriched with metadata (timestamp, endpoint name), is automatically stored in your [...]

Amazon SageMaker Model Monitor Cheat Sheet2026-01-12T09:02:21+00:00

Amazon Sagemaker Jumpstart Cheat Sheet

2026-01-12T07:23:56+00:00

Bookmarks Features How It Works Implementation Use Cases Integration Best Practices Pricing    A centralized machine learning hub within Amazon SageMaker AI designed to drastically reduce the time and expertise required to build, train, and deploy models. It provides instant access to a curated catalog of production-ready assets.   Features Foundation Models Hub Access a broad selection of state-of-the-art foundation models from providers like AI21 Labs, Cohere, Meta, Mistral AI, and Stability AI, alongside hundreds of open-source models from Hugging Face. You can evaluate, compare, and perform tasks like text summarization, [...]

Amazon Sagemaker Jumpstart Cheat Sheet2026-01-12T07:23:56+00:00

Amazon Bedrock Runtime

2026-01-07T13:42:57+00:00

Bookmarks Amazon Bedrock Runtime Actions Key Data Types Inference Concepts Security Pricing Amazon Bedrock Runtime Cheat Sheet Amazon Bedrock Runtime is a high-performance, serverless API that enables developers to make inference requests to Foundation Models (FMs) available in Amazon Bedrock. It serves as the primary runtime interface for building generative AI applications, supporting use cases including text generation, multi-turn conversations, real-time streaming, image generation, embeddings, and more. The API is optimized for low latency and high throughput and provides unified access across multiple model providers.   Amazon Bedrock [...]

Amazon Bedrock Runtime2026-01-07T13:42:57+00:00

Amazon Bedrock API Reference

2026-01-07T13:33:19+00:00

Bookmarks Amazon Bedrock API Reference Common Parameters Amazon Bedrock API Reference Common Errors API Endpoint Structure Best Practices Amazon Bedrock API Reference Sheet Amazon Bedrock API Reference is the master specification for the Amazon Bedrock service. It encompasses protocols, authentication methods, endpoints, common parameters, and error-handling standards used across the entire Bedrock ecosystem (both the Control Plane and the Data Plane).   Amazon Bedrock API Reference Common Parameters Action: (String) Specifies the particular API action to be performed. Version: (String) Indicates the API version used for the request, formatted as [...]

Amazon Bedrock API Reference2026-01-07T13:33:19+00:00

Amazon Sagemaker Ground Truth Cheat Sheet

2026-01-07T05:39:07+00:00

Bookmarks Features How It Works Implementation Use Cases Integration Best Practices Pricing    A fully managed data labeling service that uses a combination of human workers and machine learning to build high-quality datasets for training machine learning models. It provides built-in workflows, multiple workforce options, and automated labeling to reduce cost and time.   Features Automated Data Labeling (Active Learning) Uses a machine learning model to pre-label datasets and continuously learns from human feedback. It sends only low-confidence data to human reviewers, reducing labeling costs by up to 70% compared to [...]

Amazon Sagemaker Ground Truth Cheat Sheet2026-01-07T05:39:07+00:00

Amazon Bedrock Prompt Management

2025-12-30T14:14:17+00:00

Bookmarks Core Concepts Supported Regions and Models Prerequisites Creating a Prompt Viewing Prompt Information Modifying a Prompt Testing a Prompt Optimizing a Prompt Deployment using Versions Deleting a Prompt Security Best Practices Pricing Amazon Bedrock Prompt Management Cheat Sheet Amazon Bedrock Prompt Management is a centralized prompt management system for generative AI, enabling easy creation, testing, versioning, and deployment of structured prompts while separating prompt engineering from application code. It offers key [...]

Amazon Bedrock Prompt Management2025-12-30T14:14:17+00:00

Amazon Titan

2025-12-30T14:40:34+00:00

Bookmarks Features Use Cases Amazon Titan Text Models Amazon Titan Text Embeddings Models Amazon Titan Multimodal Embeddings G1 Model Amazon Titan Image Generator G1 Models Pricing Amazon Titan Cheat Sheet Amazon Titan models are a family of powerful, general-purpose models pre-trained by AWS on massive datasets. They are designed to be used out of the box or fine-tuned with your own data, allowing you to adapt them for specific tasks without the need to annotate large volumes of training data. The Titan family consists [...]

Amazon Titan2025-12-30T14:40:34+00:00

AWS Strands Agents

2025-12-30T14:06:23+00:00

Bookmarks Key Features Use Cases Implementation Approach for Strands Agents Real World Examples of Strands Agents Agents Tools Model Providers Streaming Multi-Agent Safety and Security Observability and evaluation Strands Agents vs. Strands Agents SOPs Pricing AWS Strands Agents Cheat Sheet AWS Strands Agents is an open-source SDK that enables developers to build, test, and deploy AI agents by simply defining a prompt and a list of tools in code. True to its [...]

AWS Strands Agents2025-12-30T14:06:23+00:00

AWS Agent Squad

2025-12-30T14:03:07+00:00

Bookmarks Key Features Use Cases How AWS Squad Agents Work Agents Supported (Built-in Agents) Core Concepts Pricing AWS Agent Squad Cheat Sheet An open-source framework for orchestrating and routing user queries across multiple specialized AI agents. It uses LLM-based intent classification to dynamically assign tasks to the best-suited agent, such as Amazon Bedrock models, Lex bots, or Lambda functions, while maintaining unified conversation context for seamless interactions.   Key Features Intelligent Intent Classification: Dynamically routes queries to the most suitable agent by analyzing context and content. [...]

AWS Agent Squad2025-12-30T14:03:07+00:00

Amazon Bedrock Data Automation Cheat Sheet

2025-12-30T06:07:02+00:00

Bookmarks Features Use Cases Implementation Security Best Practices Pricing    Amazon Bedrock Data Automation is a purpose-built service for transforming complex, unstructured content—such as invoices, contracts, forms, and research papers—into structured data. It handles the entire pipeline, from document parsing and classification to advanced information extraction using natural language and computer vision, enabling you to build scalable document workflows integrated directly with Knowledge Bases, databases, and analytics tools.   Amazon Bedrock Data Automation Features Multimodal Document Understanding Processes a wide range of document types and formats, including scanned PDFs, digital PDFs, JPEG/PNG images, [...]

Amazon Bedrock Data Automation Cheat Sheet2025-12-30T06:07:02+00:00

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