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


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.