Describe the objectives of enterprise integration solution
Summarize how to architect for success with Anypoint Platform
Describe how integration solutions using Anypoint Platform are documented
Describe using an architecture template for the course case study
Identify and document the overall design intentions of Anypoint Platform
Explain MuleSoft’s proposal for closing the increasing IT delivery gap
Review API-led development techniques and options
Identify Anypoint Platform components used to design and govern web APIs
Explain event-driven API support in Anypoint Platform
Distinguish between Anypoint Platform service and deployment models
Identify how Mule application components are typically used to implement integration solutions
Apply Mule application components and capabilities to a range of use cases
Summarize how class loading isolation is implemented in Mule runtimes
Distinguish between Mule blocking, non-blocking, parallel, and reactive event processing options
Identify the event processing models used in various Mule scopes and components
Describe Mule streaming options and behaviors
Describe the fundamentals of web APIs and event-driven architecture
Describe the event processing options for JMS and VM connectors
Select appropriate event processing for an integration use case
Design integration use cases with batch, near real-time, and real-time data synchronization
Describe reusable ways to transform and process events
Explain how to simplify and decouple complex data mappings using common data models
Design transformations between data models
Choose the best event transformation, data validation, and event routing patterns to an integration use case
Explain why testing is important in an integration project
Identify the MuleSoft-provided framework and tools for testing during the software development lifecycle
Design testing strategies for a Mule® application
Define test coverage for flows in a Mule application
Identify the service and deployment models supported by Anypoint Platform
Distinguish between various Anypoint Platform deployment models
Design containerized deployments for Mule runtimes
Decide deployment options for various scenarios
Decide on the best way to store a Mule application state in persistent or non-persistent storage
Identify how to store a CloudHub application state using Object Store v2
Decide on the best way to manage storage of a Mule application state using persistent queues
Configure Mule application-provided caches to store a Mule application state
Avoid duplicate processing of previous records using watermarks and idempotency validation
Describe auditing and logging options for Mule applications
Design logging strategies for Mule applications
Choose logging policies for Mule application log files
Describe integration options with third-party log management systems
Specify Anypoint Platform monitoring, alerting, notification, visualization, and reporting options for APIs and integration solutions
Manage property files for Mule applications across different environments
Manage Anypoint Platform environments for Mule application deployments
Implement continuous integration and continuous delivery (CI/CD) for an organization
Automate deployment and management with Anypoint Platform
Identify why and when transactions are supported in Mule applications
Identify resources that participate in transactions in Mule applications
Demarcate transaction boundaries in Mule applications
Choose the correct transaction type based on the participating resources
Manage a transaction using the Saga pattern
Distinguish between competing non-functional requirements
Clarify and validate reliability goals for a scenario
Design Mule applications and their deployments to meet reliability goals
Identify reliability pattern for Mule applications
Clarify high availability (HA) goals for Mule applications
Balance HA goals with reliability and performance goals
Identify ways to achieve HA using Anypoint Platform, in CloudHub and customer-hosted runtime planes
Describe how clustering and load balancing works
Identify HA aware connectors and their design trade-offs
Clarify performance goals for Mule applications
Identify the need for performance optimization and associated trade-offs
Describe ways to search for and locate performance bottlenecks
Describe how to design, architect, and implement for performance
Describe ways to measure performance
Describe methods and best practices to performance-tune Mule applications and Mule runtimes
Identify Anypoint Platform security concepts and options
Describe how to secure APIs on Anypoint Platform
Explain the security needs addressed by Anypoint Platform edge security
Differentiate between MuleSoft and customer responsibilities related to Anypoint Platform security
Evaluate security risks for Mule applications
Describe how to secure Mule application properties and data in transit
Describe Anypoint Platform network security options and architectures
Describe how to secure Mule® applications using Java key stores
Design TLS communication and other network security options for an integration use case
Distinguish between various CloudHub deployments with load balancers
Properly size an Anypoint Virtual Private Cloud (VPC) to support deployment of all expected Mule applications
