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MuleSoft Developer

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MuleSoft Developer Study Checklist
  • Platform Administrator
  • Platform App Builder
  • Platform Foundations
  • Platform Developer
  • Platform Administrator II
  • Agentforce Sales Consultant
  • Agentforce Service Consultant
  • Platform Data Architect
  • Platform Development Lifecycle and Deployment Architect
  • Platform Identity and Access Management Architect
  • Platform Integration Architect
  • Platform Sharing and Visibility Architect
  • Heroku Architect
  • B2C Solution Architect
  • Experience Cloud Consultant
  • Agentforce Field Service and Operations Consultant
  • Agentforce Nonprofit Consultant
  • Data 360 Consultant
  • Omnistudio Consultant
  • CRM Analytics and Einstein Discovery Consultant
  • Platform User Experience Designer
  • Platform Strategy Designer
  • B2C Commerce Developer
  • JavaScript Developer
  • Omnistudio Developer
  • Platform Developer II
  • Marketing Cloud Engagement Administrator
  • Marketing Cloud Engagement Specialist
  • Marketing Cloud Engagement Consultant
  • Marketing Cloud Account Engagement Specialist
  • Marketing Cloud Next Consultant
  • Agentforce Sales Foundations
  • Business Analyst
  • Marketing Cloud Engagement Developer
  • Marketing Cloud Engagement Foundations
  • Agentforce Specialist
  • Agentforce Life Sciences Consultant
  • B2B Commerce Administrator AP
  • B2B Commerce Developer AP
  • Agentforce Communications AP
  • Agentforce Consumer Goods AP
  • Agentforce Financial Services AP
  • Agentforce Health AP
  • Agentforce Manufacturing AP
  • Public Sector Solutions AP
  • Revenue Cloud Consultant
  • MuleSoft Integration Foundations
  • MuleSoft Developer
  • MuleSoft Developer II
  • MuleSoft Platform Integration Architect
  • MuleSoft Platform Architect
  • Tableau Desktop Foundations
  • Tableau Data Analyst
  • Tableau Consultant
  • Tableau Server Administrator
  • Tableau Next Consultant
  • Tableau Architect
  • Slack Administrator
  • Slack Consultant
  • Slack Developer

Checklist progressProgress

0/232Learned

  • Application network definition and building blocks
  • Application network benefits and the IT challenges it addresses
  • API contracts, abstraction and benefits of using APIs
  • Characteristics of a modern API
  • RESTful versus SOAP web services as API styles
  • Anypoint Platform components for building an application network
  • Classifying APIs into System, Process and Experience layers
  • Key attributes of API-led connectivity
  • Change isolation and reuse across API-led layers
  • API-led connectivity versus point-to-point integration
  • IT delivery gap and the production-consumption operating model
  • Center for Enablement role, staffing and expected benefits
  • Center for Enablement versus traditional Center of Excellence
  • C4E activities for publishing foundational assets and driving consumption
  • Metrics that measure C4E success and asset reuse
  • Testing REST calls with a REST client or the API Console
  • HTTP Request configuration versus Request operation settings
  • RAML URI parameters and query parameters in an HTTP Request
  • Dynamic HTTP Request paths built with DataWeave expressions
  • Custom request headers for consuming secured REST APIs
  • Mule event contents after an HTTP Request operation returns
  • HTTP Request error types for unsuccessful response status codes
  • Consuming a RAML-described API from Anypoint Exchange in Studio
  • HTTP method semantics for create, read, update and delete operations
  • Methods on collection resources versus individual item resources
  • RAML syntax for declaring resources, nested resources and methods
  • Required versus optional parameters in RAML 1.0
  • RAML request header declarations on a method
  • HTTP status codes for REST API responses
  • RAML response declarations keyed by HTTP status code
  • Data types and examples in RAML request and response bodies
  • Mocking service responses generated from declared examples
  • Choosing URI parameters versus query parameters in REST API design
  • RAML syntax for declaring URI parameters on a resource
  • RAML syntax for declaring query parameters on a method
  • Request URLs that satisfy a RAML resource and parameter definition
  • Reading URI and query parameters from Mule event attributes
  • Mule event and Mule message composition
  • Set Payload value syntax and inline DataWeave expressions
  • Transform component set-payload structure and external scripts
  • Single-value, multi-value and descendants selectors on payloads
  • Index, range and selector modifiers on payload data
  • Payload changes as the event passes through processors
  • Attributes versus payload in the Mule message
  • HTTP Listener request attribute selectors
  • Selector syntax for header and attribute names with special characters
  • Attribute state after an outbound HTTP Request or File operation
  • Setting attributes with the Transform component
  • Set Variable component configuration and value syntax
  • Reading Mule variables with the vars keyword in DataWeave
  • Setting variables in a Transform Message component
  • Preserving the original payload or attributes in a variable
  • Creating, updating and removing Mule variables
  • Variable visibility across Flow Reference calls
  • Connector operation targets and the message passed downstream
  • Target Value expressions for connector targets
  • Mule project folder structure and file purposes
  • Encapsulating global elements in a separate configuration file
  • Imported versus side-by-side loading of multiple configuration files
  • Configuration Properties global element and properties file formats
  • Property placeholder syntax for YAML and .properties keys
  • Reading configuration properties inside DataWeave expressions
  • Environment-specific properties files selected through an env property
  • Property value precedence across files, global, system and deployment properties
  • Flows, private flows and subflows compared
  • Payload and variable changes returned from a referenced flow or subflow
  • Flow Reference target and targetValue configuration
  • Error behaviour when a referenced flow or subflow fails
  • VM connector versus Flow Reference for passing events between flows
  • Variable and attribute persistence across connector boundaries
  • Hand-built HTTP Listener flows for spec resources and methods
  • Importing an API specification to scaffold a new Mule project
  • Hand-built REST interfaces versus APIkit-scaffolded interfaces
  • APIkit for REST versus APIkit for SOAP scaffolding
  • Components APIkit scaffolds from a RAML specification
  • APIkit module XML: apikit:config, router and flow mappings
  • Naming convention of APIkit-generated backend flows
  • Request URLs and parameter values reaching APIkit backend flows
  • Responses from scaffolded flows before implementation
  • APIkit Router request validation against the RAML contract
  • Requests that trigger each APIkit Router error type
  • Generating and regenerating APIkit flows from an updated RAML
  • Replacing scaffolded mock flows with implementation logic
  • Returning the status codes and headers a RAML response declares
  • Scaffolded APIkit error handlers and the error responses they build
  • Database Config connection types and JDBC driver setup
  • Parameterized Database queries with input parameters
  • Select operation result structure and downstream access
  • Insert, Update and Delete operation outputs
  • Database operation error types
  • File, FTP and SFTP connectors and their shared operation set
  • File and FTP connector global configuration and working directory
  • Read operation syntax: path, MIME type, encoding and lock
  • Read operation result: payload, file attributes and source file
  • Write operation modes and dynamic file path syntax
  • Mule event after a File or FTP Write operation
  • List operation output and iterating listed files
  • Copy, Move, Rename and Delete operation outcomes
  • On New or Updated File source polling and post-processing options
  • Connector operations versus event sources for mid-flow retrieval
  • Mule event state after a mid-flow connector operation
  • Combining stored lookup results with the current payload
  • SOAP web service calls mid-flow with Web Service Consumer
  • For Each collection expression and element splitting
  • Payload inside versus after a For Each scope
  • For Each counter and root message variables
  • Variable changes across For Each iterations and after the scope
  • For Each batch size and sub-collection payloads
  • Error handling when a For Each element fails
  • For Each versus Parallel For Each
  • Batch job instance phases and what happens in each
  • Batch job XML structure and component nesting
  • Valid batch job input and the implicit record split
  • Record payload, variables and attributes inside batch steps
  • Batch step filtering with acceptExpression and acceptPolicy
  • Batch aggregator fixed size versus streaming
  • Failed records and the maxFailedRecords threshold
  • On Complete report and what the flow sees after the batch job
  • Choosing batch processing versus For Each and Parallel For Each
  • On Table Row listener events and per-row payload
  • On Table Row listener configuration and watermark settings
  • Object Store versus flow variables for state across flow executions
  • Object Store connector store and retrieve operation syntax
  • Persistent versus transient object stores and Object Store v2
  • Cache scope behaviour for repeated requests
  • Script header, output directive and inline DataWeave expressions
  • Default output type when the output directive is omitted
  • DataWeave data types, literal syntax and typeOf
  • Type coercion with the as operator
  • Parsing and serializing strings with read and write
  • JSON-to-XML conversion and XML output structure
  • map lambda parameters and the `$` and `$$` shorthand
  • mapObject versus map for object inputs
  • pluck for turning an object into an array
  • Array reshaping with flatten, flatMap and distinctBy
  • Concatenation and removal with `++` and `--`
  • Core string functions for splitting, joining, casing and replacing
  • Core numeric and aggregate functions
  • groupBy result structure
  • reduce accumulator initialization and iteration
  • log function for debugging DataWeave expressions
  • Key, multi-value, descendants and XML attribute selectors
  • Index, range and filter selectors on arrays
  • Filtering arrays with the filter function
  • Filtering object key-value pairs with filterObject
  • Sorting arrays and objects with orderBy
  • Conditional fields and if/else expressions in output
  • Number formatting with format and locale properties
  • Parsing and reformatting date and time strings
  • Custom DataWeave types for reusable formatting
  • Implicit coercion in comparison and equality operators
  • Chaining filter, orderBy, and map in a single expression
  • lookup function syntax for invoking a flow from DataWeave
  • Payload passed to and returned from a flow called with lookup
  • lookup function versus Flow Reference for calling flows
  • Global header variables versus local do-scope variables in DataWeave
  • DataWeave script variables versus Mule event variables
  • Declaring and calling custom DataWeave functions with fun
  • Lambdas in variables and functions passed as arguments
  • Custom DataWeave module file contents and project location
  • Import directive forms and calling functions from imported modules
  • Reusing DataWeave mapping files through the main function
  • Choice router XML structure and route configuration
  • Choice router route selection order and the default route
  • DataWeave when conditions on payload, attributes, and variables
  • Routing conditions on missing keys and null values
  • Mule event state after the Choice router completes
  • Choice router for content-based routing versus other routers
  • Scatter-Gather parallel route execution and event handoff
  • Scatter-Gather aggregated result structure
  • DataWeave expressions for combining Scatter-Gather route payloads
  • Variable propagation across Scatter-Gather routes
  • Scatter-Gather behaviour when a route fails or times out
  • Accessing route results and failures in a Scatter-Gather error handler
  • Scatter-Gather versus Parallel For Each for parallel processing
  • Validation module operations, scopes and XML syntax
  • Flow outcome when a validator passes or fails
  • Validator error types, custom messages and on-error matching
  • Validation module versus Choice router for rejecting invalid events

Apply correct processors/syntax to implement global error handlers, and predict outcomes

0/3

  • Defining and referencing a global error handler
  • Application default error handler in the global configuration element
  • Reusing named global On-Error components

Apply correct processors/syntax to implement on-error continue and on-error propagate handlers, and predict outcomes

0/5

  • Error handler and On-Error component XML structure and attributes
  • On Error Continue versus On Error Propagate effect on the owning flow or scope
  • HTTP Listener response when a flow error is continued versus propagated
  • Default error handling when no error handler is configured
  • Error object expressions inside an On-Error handler

Apply correct processors/syntax to combine multiple error handlers, and predict outcomes

0/5

  • Error type lists, ANY and the type hierarchy in On-Error matching
  • On-Error when conditions for expression-based error matching
  • On-Error component evaluation order within one error handler
  • Errors that no On-Error component matches
  • Error propagation across Flow Reference calls to child flows and subflows

Apply correct processors /syntax to implement try scopes, and predict outcomes

0/5

  • Try scope XML structure and its embedded error handler
  • Flow execution after On Error Continue handles an error in a Try scope
  • On Error Propagate inside a Try scope and the enclosing flow's handler
  • Payload and variable changes across a Try scope boundary
  • Try scope versus a separate flow or subflow for isolating errors

Apply correct processors/syntax to map custom errors, and predict outcomes

0/4

Custom error type namespaces and identifiers

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Raise Error component for custom error types

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Error mapping syntax on connector operations

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Handler matching for operation errors mapped to custom types

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  • System errors versus messaging errors
  • Running a Mule app in Anypoint Studio debug mode with breakpoints
  • Inspecting the Mule event at a breakpoint in the Mule Debugger view
  • Reading Mule error log entries to locate the failing processor
  • Logger component messages, expressions and log levels
  • Error object selectors for logging and diagnosis
  • Default error handling and the HTTP Listener response to a failed request
  • Tracing an error through On-Error matching to the flow result
  • Root causes of failing DataWeave expressions
  • Verbose connector logging and stack trace detail
  • Ways to deploy a Mule application to CloudHub
  • CloudHub application names and public domain URLs
  • HTTP Listener host and port configuration for CloudHub deployment
  • CloudHub worker size and worker count
  • Deploy-time application properties versus properties files
  • Redeploying and updating a running CloudHub application
  • CloudHub deployment prerequisites and failed deployments
  • API proxy versus API autodiscovery for managing an API
  • API autodiscovery global element configuration
  • Pairing a Mule application with an API Manager instance
  • Creating and deploying an API proxy from API Manager
  • Request path and policy enforcement through a deployed API proxy
  • API Manager metrics for usage, performance and policy violations
  • Purpose and enforcement point of API Manager policies
  • Prerequisites for applying policies to a Mule application
  • Applying and upgrading a policy in API Manager
  • Client ID enforcement policy and consumer credentials
  • Rate limiting versus spike control policy behaviour
  • SLA tiers with the SLA-based rate limiting policy
  • Choosing an API policy for an access or traffic requirement
  • API-wide versus resource-level policy application

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  1. MuleSoft Developer Checklist
  3. Handling Errors

Error mapping syntax on connector operations

Explainer

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Practice Question

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Next conceptHandler matching for operation errors mapped to custom types

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  1. MuleSoft Developer Checklist
  3. Handling Errors
Error mapping syntax on connector operations

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Practice Question

Studying for this exam?

This is one of 232 concepts on the Salesforce MuleSoft Developer exam.

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Keep going

Next conceptHandler matching for operation errors mapped to custom types

Explainer

When a connector operation fails, it throws a Mule error with a type such as HTTP:CONNECTIVITY. Error mapping lets you map that error type to a custom error type you choose, right on the operation. Your error handler can then tell which operation failed and react to each one differently.
Core information
  • Every Mule error type has a namespace and an identifier, such as HTTP:NOT_FOUND or DB:BAD_SYNTAX. On each operation in a flow, you can map the error types it may throw to a custom error type of your choosing.
More details and nuances
  • A custom namespace must not reuse an existing connector namespace. For example, an app that uses HTTP and Database operations cannot use HTTP or DB for its custom types. Pick a namespace tied to the app name or context, such as CUSTOMER for a customer aggregation API or ORDER for an order-processing API. Always include the namespace in a custom type to avoid unexpected behavior.

Explainer

When a connector operation fails, it throws a Mule error with a type such as HTTP:CONNECTIVITY. Error mapping lets you map that error type to a custom error type you choose, right on the operation. Your error handler can then tell which operation failed and react to each one differently.
Core information
  • Every Mule error type has a namespace and an identifier, such as HTTP:NOT_FOUND or DB:BAD_SYNTAX. On each operation in a flow, you can map the error types it may throw to a custom error type of your choosing.
More details and nuances
  • A custom namespace must not reuse an existing connector namespace. For example, an app that uses HTTP and Database operations cannot use HTTP or DB for its custom types. Pick a namespace tied to the app name or context, such as CUSTOMER for a customer aggregation API or ORDER for an order-processing API. Always include the namespace in a custom type to avoid unexpected behavior.