Synopsis
Learn about the structure and the synopsis of this course.
We'll cover the following
This course discusses twenty design patterns useful for designing Apache Camel-based applications.
The following list is a quick reference with a short description for each pattern, followed by a mind map visualizing the patterns.
Patterns list
Following are the Camel design patterns listed in alphabetical order in the form of a table:
Pattern Name | Definition |
Bulkhead pattern | Enforces resource partitioning and damage containment to preserve partial functionality in the case of a failure. |
Canonical Data Model pattern | Minimizes dependencies between applications that use different data formats through an additional level of data format indirection. |
Circuit Breaker pattern | Improves a system's stability and resilience by guarding integration points against cascading failures and slow responses from external systems. |
Command Query Responsibility Segregation pattern | Decouples read from write operations to allow them to evolve independently. |
Data Integrity pattern | Maintains the data consistency and business integrity of a system of dispersed data sources in the case of a processing failure. |
Edge Component pattern | Encapsulates endpoint-specific details and prevents them from leaking into the business logic of an integration flow. |
Error Channel pattern | A set of patterns and principles used for error handling in integration applications with different conversation styles. |
External Configuration pattern | Parameterizes the configuration information of an application and externalizes it from the deployment archive. |
Idempotent Filter pattern | Filters out duplicate messages and ensures that only unique messages are passed through. |
Load Levelling pattern | Allows the handling of peak loads and slow-running tasks by introducing temporal decoupling between consumers and producers using message queues. |
Parallel Pipeline pattern | Allows concurrent execution of the steps of a multistep process by maintaining the message order. |
Retry pattern | Enables applications to handle anticipated transient failures by transparently retrying a failed operation with an expectation that it will be successful. |
Reusable Route pattern | Allows agnostic business logic to be repeatedly used in different service contexts. |
Runtime Reconfiguration pattern | Allows externalizing and runtime behavior variability without requiring an application redeployment. |
Saga pattern | Removes the need for distributed transactions by ensuring that the transaction at each step of the business process has a defined compensating transaction to undo the work completed in the case of partial failures. |
Service Consolidation pattern | Provides guidelines for grouping services together or isolating them from one another for a deployment purpose-driven by constraints. |
Service Instance pattern | Accommodates increasing workloads by distributing the loads on multiple service instances. |
Singleton Service pattern | Ensures that only a single instance of a service is active at a time. |
Throttling pattern | Controls the throughput of a processing flow to meet the service-level agreements and prevents the overloading of other systems. |
VETRO pattern | Combines multiple sequential actions taken on a message into a consistent structure and well-defined responsibilities. |
Patterns mind map
Every pattern has implications for multiple nonfunctional requirements (NFRs) and can contribute to various scenarios. The following mind map is a simplified view showing the main NFR that every pattern contributes to and its category.