Boomi Architect study guide
Boomi Architect · Work through your exam, one topic at a time.
The Boomi Architect credential is an advanced, vendor-specific certification for integration professionals who design solutions on the Boomi Enterprise Platform. It suits experienced Boomi developers, integration leads, and solution consultants who already build processes and now want to prove they can own architecture decisions: environment strategy, reusable component design, error handling, security, and deployment governance. The Boomi Architect study guide has 5 sections and about 1,818 words.
01Integration & Automation: Processes, Shapes, and Runtime Behavior
Boomi's integration engine is a document-flow runtime. A process starts with a start shape, moves documents through shapes, and each shape transforms, routes, or acts on the document.
399 words, about 2 min02API Management: Gateways, Components, and Policies
API Management in Boomi centers on the API gateway and the components used to publish and secure APIs. Candidates must know the API component (defines the API, its resources, operations, and the backing process or service), the API Service component (exposes a process as a service), and the API gateway (runtime that enforces policies, authentication, and routing).
377 words, about 2 min03Data Management: Profiles, Maps, and Document Handling
Data Management covers how Boomi represents, transforms, and validates data. The core concepts are profiles (JSON, XML, flat file, database, EDI), maps (transformation between profiles), functions (built-in transformations like string, date, math, and lookup functions), and document handling (split, combine, batch, and document cache).
349 words, about 2 min04AI Infrastructure: Models, Connectors, and Runtime Foundations
AI Infrastructure in Boomi covers the components that let processes call AI services and models. Candidates must understand connectors to AI providers (for example, LLM service connectors), model configuration (model selection, parameters such as temperature and token limits), prompt construction (templates, variable injection), and response handling (parsing model output into a profile).
348 words, about 2 min05Agentic Capabilities: Tools, Orchestration, and Guardrails
Agentic capabilities extend integration beyond fixed flows to goal-directed agents that reason, select tools, and act. Candidates must understand the core concepts: an agent (an LLM-driven component with instructions and access to tools), tools (callable actions such as API calls, process invocations, or data lookups), orchestration (how the agent decides which tool to call and in what order), and memory/context (what the agent retains across steps).
345 words, about 2 min