Salesforce MuleSoft Developer study plan
Salesforce MuleSoft Developer · Give each week a clear focus.
8 weeks · About 6 hours per week
Transforming Data with DataWeave
Write DataWeave expressions that select, filter, and map fields from a JSON array using map, filter, and reduce
Convert between JSON, XML, CSV, and Java payloads using the output/input MIME directives
Use the dw::core::Strings and dw::core::Arrays modules to transform nested collections
Debug DataWeave errors by reading the stack trace line and column references in the Mule log
Your checkpoint
A single DataWeave transformation project with 6 passing scripts (JSON→JSON, JSON→XML, CSV→JSON, flat→nested, nested→flat, aggregation) committed and runnable in Studio
Transforming Data with DataWeave & Implementing RESTful API Logic with Mule Flows
Compose multi-step transformations by chaining named functions and local variable blocks
Apply flow control operators (choice, scatter-gather, for-each) and justify each choice in a written note
Implement a DataWeave script that consumes a function module imported from src/main/resources
Build a flow that accepts an HTTP request, transforms the payload with DataWeave, and returns the result
Your checkpoint
A working Mule app exposing one HTTP endpoint whose response is produced by a custom DataWeave module, demonstrated with 3 curl calls captured in a README
Implementing RESTful API Logic with Mule Flows
Design RESTful resources and HTTP methods that follow the MuleSoft API-led layering pattern (experience, process, system)
Configure HTTP Listener, Request, and Query params with validation in the flow
Connect flows to a database or SaaS system using the appropriate connector and externalize credentials into properties files
Implement idempotency and pagination behavior in a system API flow
Your checkpoint
A three-layer (experience/process/system) mini-application with request validation, externalized config, and one end-to-end tested use case
Implementing RESTful API Logic with Mule Flows & Controlling Event Flow and Handling Errors
Configure global error handlers and per-flow error handlers with on-error-continue and on-error-propagate
Map connector-specific errors to custom application error types using the error type hierarchy
Add retry and until-successful scopes around flaky outbound calls
Trace a failing request end-to-end in the Mule log and identify which handler caught it
Your checkpoint
An error-handling matrix document plus a working app where 5 distinct failure injections each produce a documented, correct HTTP status and error body
Controlling Event Flow and Handling Errors
Control message ordering and concurrency with VM queues, async scopes, and JMS where appropriate
Apply validation module rules and the raise-error component to reject bad input early
Implement circuit-breaker style behavior with a choice-based fallback flow
Explain when to use each scope (until-successful, scatter-gather, batch, async) in a decision table
Your checkpoint
A reference decision table for scope selection plus a demo app with batch processing and an async sub-flow, both verified by log evidence
Explaining and Creating API Specifications with Anypoint Platform
Author a RAML 1.0 spec with resource types, traits, data types, and reusable examples
Author an equivalent OpenAPI 3.0 spec and compare the two on reusability and tooling
Mock the API in Design Center and exercise it with the mocking service
Publish the spec to Exchange with a version, asset metadata, and a generated connector or snippet
Your checkpoint
One published Exchange asset (RAML) with a passing mock-service smoke test and a second, smaller OpenAPI 3.0 asset for comparison
Deploying and Managing API Implementations & Explaining and Creating API Specifications with Anypoint Platform
Bind an implementation to its spec using API Autodiscovery and API Manager
Apply a rate-limiting and a client-ID-enforcement policy and verify both with test calls
Deploy the app to CloudHub 2.0 (or runtime manager target) with properties and a correct runtime version
Configure alerts and read deployment logs to diagnose a failed start
Your checkpoint
A deployed application in a managed environment with two enforced policies, screenshots of the policy dashboard, and one documented deployment failure and its fix
Explaining and Creating API Specifications with Anypoint Platform & Deploying and Managing API Implementations & Implementing RESTful API Logic with Mule Flows & Transforming Data with DataWeave & Controlling Event Flow and Handling Errors
Re-run every prior week's deliverable and repair anything that no longer passes
Complete two full-length timed practice exams and tag every miss by domain
Re-study only the two weakest domains using targeted drills
Write a one-page cheat sheet of DataWeave functions, error scopes, and deployment commands
Your checkpoint
A scored practice-exam log showing per-domain accuracy with every item below 70% remediated and re-tested
Milestones
Week 2: Can write a nested JSON-to-JSON DataWeave transform from scratch in under 10 minutes without reference, and explain the difference between map and mapObject
Week 4: Can trace any failing request through a flow and correct error handler and state the resulting HTTP status without running the app
Week 5: Can choose the correct scope for 8 out of 10 scenario prompts on flow control and error strategy
Week 7: Has a live managed deployment bound to an Exchange asset with at least two enforced policies
Week 8: Scores 80%+ overall on two consecutive full practice exams with no single domain below 70%