9. Glossary

Action Group — A set of tools (Lambda functions) exposed to a Bedrock Agent via an OpenAPI schema. The agent decides when to call which action based on the schema descriptions. On AgentCore, the equivalent is tools exposed through AgentCore Gateway as MCP tools.

Approximate Nearest Neighbor (ANN) — A class of algorithms (HNSW, IVF, FAISS) that find approximately similar vectors efficiently at scale, trading some recall accuracy for dramatically faster search compared to exact k-NN.

Automated Reasoning Check — A Bedrock Guardrails feature that formally verifies FM outputs against a defined set of logical rules or policies, providing higher-confidence grounding than semantic similarity alone.

Bedrock Agents — A fully managed AWS service that orchestrates multi-step FM reasoning loops with tool use, session memory, and knowledge base retrieval without custom orchestration code. Now Bedrock Agents Classic: closed to new customers since July 30, 2026; AWS points new builds to Amazon Bedrock AgentCore.

Bedrock Data Automation — A managed service for extracting structured information from multimodal documents (PDFs, images, audio, video) at scale, replacing custom extraction pipelines.

Bedrock Guardrails — A managed content safety layer that evaluates FM inputs and outputs against defined policies: topic denial, content filters, word filters, PII redaction, and grounding checks.

Bedrock Knowledge Bases — A fully managed RAG service that handles document ingestion, chunking, embedding, indexing, and retrieval as a single managed pipeline.

Bedrock Model Evaluations — A managed service for running systematic quality evaluations of FM outputs against golden datasets using automated metrics and LLM-as-Judge scoring.

Bedrock Prompt Flows — A visual, low-code orchestration service for building multi-step FM workflows with branching, Lambda integration, and Knowledge Base retrieval steps.

Bedrock Prompt Management — A versioned prompt template management service with parameterized variables, immutable versions, and IAM-controlled access for governing production prompts.

BERTScore — An evaluation metric measuring semantic similarity between generated and reference text using BERT embeddings, more appropriate than BLEU for GenAI output evaluation.

Chain-of-Thought (CoT) — A prompting technique instructing the FM to explicitly reason step-by-step before producing a final answer, improving accuracy on multi-step reasoning tasks.

Chunking — The process of splitting documents into smaller segments for vector indexing. Strategies include fixed-size, sentence-based, hierarchical, and semantic chunking.

Context Window — The maximum number of tokens an FM can process in a single inference call, encompassing system prompt, conversation history, retrieved context, and user input combined.

Continued Pre-Training — A customization technique that trains an FM on a large domain corpus to deeply internalize domain knowledge, modifying the model's knowledge base rather than its behavior.

Cross-Region Inference — A Bedrock feature that automatically routes FM invocations to alternative regions when the primary region lacks capacity or the model is unavailable.

Defense-in-Depth — A security architecture principle requiring multiple independent protective layers such that bypassing one layer still leaves others active.

Embedding Model — A model that converts text (or other modalities) into dense numerical vectors in a high-dimensional semantic space, enabling similarity-based search.

EventBridge — An AWS serverless event bus that routes events from sources (S3, Salesforce, custom) to targets (Lambda, SQS, Step Functions), enabling event-driven GenAI architectures.

Fine-Tuning — A customization technique that modifies an FM's output probability distribution by training on labeled examples, changing how the model responds without changing what it knows.

Foundation Model (FM) — A large-scale pre-trained model trained on broad data that can be adapted to many downstream tasks. Examples: Claude 3, Titan Text, Llama 3.

GenAI Gateway — A centralized application layer providing authentication, rate limiting, cost attribution, model routing, and safety enforcement for all GenAI API calls across an organization.

Grounding — The property of an FM response being factually supported by retrieved context. Low grounding = hallucination risk.

Hallucination — The FM producing confident, fluent, semantically coherent text that is factually incorrect or unsupported by provided context.

HNSW (Hierarchical Navigable Small World) — An approximate nearest-neighbor graph algorithm used for efficient vector search, configured by ef_construction (build quality) and ef_search (query recall vs. speed).

Human-in-the-Loop — An architectural pattern where AI-generated decisions require human approval before execution, implemented via Step Functions waitForTaskToken.

HyDE (Hypothetical Document Embeddings) — A query transformation technique that generates a hypothetical answer using an FM and uses that answer's embedding as the search query, bridging query-document vocabulary gaps.

Indirect Prompt Injection — A prompt injection attack where malicious instructions are embedded in retrieved documents rather than user input, causing the FM to execute the embedded instructions.

k-NN (k-Nearest Neighbor) — A search algorithm retrieving the k most similar vectors to a query vector. Exact k-NN guarantees 100% recall but scales poorly; approximate (ANN) algorithms trade recall for speed.

Knowledge Base Sync — The process of ingesting new or updated documents into a Bedrock Knowledge Base. Not real-time — may take minutes to hours for large corpora.

LoRA (Low-Rank Adaptation) — A parameter-efficient fine-tuning technique that adds small trainable rank-decomposition matrices to a frozen base model, dramatically reducing fine-tuning compute cost.

LLM-as-Judge — An evaluation technique using a capable FM to score other FM outputs against defined criteria, scaling human-like quality assessment to large evaluation sets.

MCP (Model Context Protocol) — An open protocol developed by Anthropic that standardizes the interface between AI models and external tools/data sources, enabling interoperable tool integration across agent frameworks.

Model Card — Documentation for an FM deployment describing intended use, training data, evaluation results, known limitations, and responsible AI considerations.

Model Context Protocol — See MCP.

Model Invocation Logging — A Bedrock feature that records every FM request and response to CloudWatch Logs and/or S3, providing the primary forensic audit trail for production GenAI applications.

Multi-Agent Architecture — A system where multiple specialized AI agents collaborate, with a supervisor agent routing tasks to specialized sub-agents. Implemented with AWS Agent Squad.

Provisioned Throughput — A Bedrock pricing model where you purchase reserved model units providing dedicated capacity and consistent latency, cost-effective above ~60–70% utilization.

Prompt Caching — A Bedrock feature that caches the key-value representations of static prompt prefixes (system prompts, documents), eliminating re-processing cost for repeated identical content.

Prompt Injection — An attack where adversarial instructions embedded in user input or retrieved documents override the system prompt, causing the FM to execute unintended behavior.

RAG (Retrieval-Augmented Generation) — An architecture pattern that retrieves relevant documents from a knowledge base and injects them into the FM's context, grounding responses in factual retrieved content rather than model weights alone.

RAGAS — A framework providing four independent metrics for evaluating RAG pipelines: Faithfulness, Answer Relevancy, Context Precision, and Context Recall.

ReAct — A reasoning pattern interleaving Thought (explicit reasoning), Action (tool call), and Observation (tool result) in a loop until the FM has sufficient information to produce a final answer.

Reranker — A model that re-scores initially retrieved chunks based on their specific relevance to the query, improving retrieval precision after the initial approximate k-NN search.

Semantic Caching — An application-layer caching strategy that stores FM responses indexed by query embedding, returning cached responses for semantically similar future queries.

Semantic Chunking — A document splitting strategy that uses an FM to detect topic shifts and splits at semantic boundaries rather than fixed token counts.

Strands Agents — An open-source, Python-first AWS agent framework providing code-level control over agent reasoning, tool integration, and multi-agent orchestration.

Transfer Question — An exam question testing a concept in a novel scenario not covered in the study guide, evaluating whether knowledge generalizes beyond memorized examples.

VPC Endpoint (PrivateLink) — An AWS networking service that routes traffic to AWS services (including Bedrock) through the private AWS network, preventing data from traversing the public internet.

waitForTaskToken — A Step Functions integration pattern that pauses a state machine execution until an external process (human reviewer, approval workflow) sends a SendTaskSuccess or SendTaskFailure callback.