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aaws amazon cheat sheets

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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 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

Amazon Bedrock Flows Cheat Sheet

2025-12-30T05:34:25+00:00

Bookmarks Features Use Cases Implementation Security Best Practices Pricing    Amazon Bedrock Flows is a core feature for implementing production-ready, complex generative AI applications. It abstracts the heavy lifting of coding integrations, state management, and deployment pipelines into a drag-and-drop visual interface or API. This allows teams—from developers to subject-matter experts—to collaborate and rapidly iterate on AI workflows, moving from prototyping to scalable, versioned deployments in minutes.   Amazon Bedrock Flows Features Visual, Low-Code/No-Code Builder Design workflows using a drag-and-drop interface in Amazon Bedrock Studio. Link nodes representing Prompts, Foundation Models (FMs), Knowledge [...]

Amazon Bedrock Flows Cheat Sheet2025-12-30T05:34:25+00:00

Amazon Bedrock AgentCore Runtime Cheat Sheet

2025-12-20T06:21:59+00:00

Bookmarks Features Use Cases Implementation Security Best Practices Pricing Amazon Bedrock AgentCore Runtime is the execution engine within the Bedrock AgentCore platform, providing a low-latency, serverless environment to run AI agents. It handles the complex infrastructure of scaling, security, and session management, allowing you to focus on developing agent logic. The service supports everything from rapid prototyping to production-scale deployments. Amazon Bedrock AgentCore Runtime Features Framework Agnostic Runtime lets you transform any local agent code to cloud-native deployments with a few lines of code. It works seamlessly with popular frameworks like LangGraph, [...]

Amazon Bedrock AgentCore Runtime Cheat Sheet2025-12-20T06:21:59+00:00

Amazon Bedrock AgentCore Observability Cheat Sheet

2025-12-18T09:15:12+00:00

Bookmarks Features Use Cases Implementation Integration Security Best Practices Pricing Amazon Bedrock AgentCore Observability Cheat Sheet Amazon Bedrock AgentCore Observability delivers complete visibility into AI agent operations, enabling developers to monitor, analyze, and optimize agent performance, understand decision patterns, and troubleshoot issues across complex multi-agent workflows. It provides insights into agent reasoning, tool usage, and conversation flows. Amazon Bedrock AgentCore Observability Features Comprehensive Metrics and Monitoring Collect detailed performance metrics including response times, token usage, success rates, and error patterns. Monitor agent health and availability with configurable thresholds and alerts. [...]

Amazon Bedrock AgentCore Observability Cheat Sheet2025-12-18T09:15:12+00:00

Amazon Bedrock AgentCore Memory Cheat Sheet

2025-12-08T06:13:27+00:00

Bookmarks How Memory Works Memory Types  Implementation Integration Security Best Practices Pricing A managed service that enables AI agents to store, retrieve, and maintain context across conversations, allowing them to remember user information, preferences, and interaction history for more coherent and personalized responses. How Memory Works Memory Storage and Retrieval The Memory service automatically captures relevant information from agent-user conversations and stores it for future use. When an agent needs context, it queries the memory to retrieve past interactions, user details, or learned facts. The system uses semantic search to [...]

Amazon Bedrock AgentCore Memory Cheat Sheet2025-12-08T06:13:27+00:00

Amazon Bedrock AgentCore Gateway Cheat Sheet

2025-12-05T03:21:09+00:00

Bookmarks Overview Features Use Cases Implementation Security Best Practices Pricing A fully managed service that transforms how AI agents discover, access, and utilize tools by providing a centralized, secure gateway for tool management and execution across your organization. Overview The Amazon Bedrock AgentCore Gateway acts as a single point of entry for AI agents to discover and use approved tools and APIs. It streamlines tool management by centralizing authentication, monitoring, and access control for all agent interactions. This gateway enables consistent governance and security while maintaining development flexibility across teams [...]

Amazon Bedrock AgentCore Gateway Cheat Sheet2025-12-05T03:21:09+00:00

Amazon DocumentDB

2025-12-31T05:10:56+00:00

Bookmarks How it Works Use Cases Performance Scaling Reliability Backup and Restore Security Pricing Limitations Amazon DocumentDB Cheat Sheet Fully managed document database service designed to be fast, scalable, and highly available. Data is stored in JSON-like documents. Compatible with MongoDB. Flexible schema and indexing. Commonly used for content management, user profiles, and real-time big data. How it Works An Amazon DocumentDB cluster decouples storage and compute. A cluster consists of Cluster volume and Instances Cluster volume refers to the storage layer that spans multiple Availability Zones. Each [...]

Amazon DocumentDB2025-12-31T05:10:56+00:00

Working with AWS KMS key using the AWS KMS API

2024-07-11T09:28:47+00:00

What is AWS Key Management Service? AWS Key Management Service (or KMS for short) is the service you use to securely store your encryption keys in AWS. If you need data encryption on your AWS resources, such as EBS volumes or RDS databases, you can use AWS KMS to simplify the process for you. You start using the service by requesting the creation of a KMS key. By default, AWS KMS creates the key material for your KMS key. You also have the option of importing your own keys to AWS if you wish to. Note that during key rotation, [...]

Working with AWS KMS key using the AWS KMS API2024-07-11T09:28:47+00:00

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