10 Project Reactor Best Practices

Project Reactor is a Java library that provides an efficient implementation of the Reactive Streams specification. It provides a comprehensive set of tools for building non-blocking, asynchronous, and event-driven applications.

In this article, we will discuss 10 best practices to keep in mind while developing applications with Project Reactor. We will discuss topics such as threading, error handling, and logging. By following these best practices, you can ensure that your application is robust and performant.

1. Implement Reactive Streams backpressure

Backpressure is a mechanism that allows the consumer of data to control how much data it receives from the producer. This helps prevent resource exhaustion and ensures that the system remains responsive. In Project Reactor, backpressure is implemented using the Subscription interface, which provides methods for requesting and canceling elements.

When implementing backpressure in Project Reactor, developers should use the onBackpressureXXX operators, such as onBackpressureDrop or onBackpressureBuffer. These operators allow developers to specify what action should be taken when the consumer cannot keep up with the rate of production. For example, onBackpressureDrop will drop any items produced faster than they can be consumed, while onBackpressureBuffer will buffer them until the consumer can catch up.

It’s also important to note that backpressure works best when used in combination with other techniques, such as batching and parallelism. Batching reduces the number of requests sent by the consumer, while parallelism increases the throughput of the system. Together, these techniques help ensure that the system remains responsive and resources are not exhausted.

2. Use the Schedulers API to optimize code execution

The Schedulers API allows developers to control the threading model of their reactive applications. By using this API, developers can specify which threads should be used for different operations and ensure that they are executed in an optimal way. This helps improve performance by avoiding unnecessary context switching between threads and ensuring that tasks are run on the most appropriate thread.

Using the Schedulers API also makes it easier to debug code since developers can easily identify which thread is running a particular operation. Additionally, it provides more flexibility when dealing with blocking operations as developers can choose to execute them on a dedicated thread pool or use one of the provided schedulers such as elastic() or single().

3. Utilize Flux and Mono operators appropriately

Flux and Mono are two types of reactive streams that Project Reactor provides. Flux is a stream of 0..N elements, while Mono is a stream of 0..1 element. Utilizing the correct type of stream for each operation ensures that the code is optimized to handle the expected data size. For example, if an operation is only expecting one result, then using a Mono will be more efficient than using a Flux since it won’t have to process any additional elements.

When utilizing these operators, it’s important to consider how they interact with each other. Some operators can take either a Flux or a Mono as input, but may return different results depending on which type was used. Additionally, some operators may not work correctly when given the wrong type of stream. Therefore, it’s important to understand what type of stream each operator expects in order to ensure that the code is running optimally.

It’s also important to note that certain operations may require multiple steps in order to achieve the desired result. In this case, chaining together multiple operators can help simplify the code and make it easier to read. However, it’s important to keep in mind that each operator has its own set of rules and limitations, so it’s important to understand how they interact with each other before attempting to chain them together.

4. Make use of reactive types such as Reactor Core’s Tuple, Pair and Triple

Reactive types are immutable, thread-safe and non-blocking data structures that allow for efficient composition of multiple values. This makes them ideal for use in reactive programming as they can be used to represent a single unit of data that is composed of multiple elements.

Tuple, Pair and Triple provide an easy way to create such units of data without having to write custom classes or wrappers. They also make it easier to pass around multiple values between different components of the application. For example, Tuple2 can be used to store two values, while Tuple3 can be used to store three values. These tuples can then be passed around as a single object instead of passing each value separately.

Furthermore, Reactor Core’s Tuples come with built-in methods for transforming and manipulating the data stored within them. This allows developers to easily perform operations on the data without having to manually extract the individual values from the tuple.

5. Leverage the Project Reactor Test library for unit testing

The Project Reactor Test library provides a set of testing utilities that make it easier to write unit tests for reactive code. It includes features such as StepVerifier, which allows developers to verify the behavior of their reactive streams and operators in an easy-to-read manner. Additionally, it also provides tools like VirtualTimeScheduler, which can be used to simulate time passing in order to test asynchronous operations.

Using the Project Reactor Test library makes it much simpler to write comprehensive unit tests for reactive code. This is because it provides all the necessary tools to easily create and manipulate virtual time, as well as verify the expected behavior of the reactive stream or operator under test. Furthermore, since the library is specifically designed for use with Project Reactor, it integrates seamlessly into existing projects and requires minimal setup.

6. Understand and adhere to non-blocking I/O principles

Non-blocking I/O is a programming technique that allows an application to perform multiple tasks simultaneously without waiting for any of them to finish. This means that the application can continue processing data while it waits for input or output from other sources, such as databases or web services. By using non-blocking I/O, Project Reactor can process more requests in less time and with fewer resources.

Project Reactor uses the Reactive Streams API to provide support for non-blocking I/O operations. The Reactive Streams API provides a set of interfaces and classes that allow developers to create asynchronous streams of data that can be processed in parallel. These streams are then used by Project Reactor to process incoming requests in a non-blocking manner.

To adhere to non-blocking I/O principles when using Project Reactor, developers should use the Reactive Streams API to create asynchronous streams of data and ensure that all operations on those streams are non-blocking. Additionally, developers should avoid blocking operations such as synchronous calls to external systems, which can cause performance issues. Finally, developers should also make sure that their code does not block the main thread, as this will prevent Project Reactor from being able to process requests efficiently.

7. Monitor application performance with Micrometer

Micrometer is a monitoring library that provides an abstraction layer over the most popular monitoring systems, such as Prometheus, Wavefront, Datadog, and more. It allows developers to instrument their code with metrics without having to worry about which monitoring system they are using. This makes it easy to switch between different monitoring systems if needed.

Using Micrometer with Project Reactor also has several advantages. Firstly, it allows developers to easily measure the performance of reactive applications by providing out-of-the-box support for measuring latency, throughput, errors, and other important metrics. Secondly, it enables developers to quickly identify any bottlenecks in their application’s performance and take corrective action. Finally, it helps developers gain insight into how their application is performing under various conditions, allowing them to make informed decisions on how to optimize their application.

8. Minimize blocking calls through the use of asynchronous APIs

Blocking calls are those that cause the current thread to wait for a response before continuing execution. This can lead to poor performance, as threads become blocked and unable to process other tasks. Asynchronous APIs allow multiple requests to be processed in parallel, without blocking any of the threads. By using asynchronous APIs with Project Reactor, developers can ensure that their applications remain responsive and performant even under heavy load. Additionally, asynchronous APIs make it easier to scale an application by allowing more requests to be handled concurrently. Finally, asynchronous APIs also help reduce latency, since they don’t require waiting for responses from external services.

9. Create custom schedulers when necessary

Creating custom schedulers allows for more control over the threading model of a reactive application. By creating a custom scheduler, developers can specify which threads are used to execute certain tasks and how many threads should be allocated for each task. This helps ensure that resources are not wasted on unnecessary threads or tasks, as well as allowing for better performance by ensuring that tasks are executed in an optimal manner.

Custom schedulers also allow for greater flexibility when it comes to dealing with different types of workloads. For example, if a particular task requires a large amount of CPU time, then a custom scheduler could be created to allocate more threads to this task than other tasks. Similarly, if a task needs to be completed quickly, then a custom scheduler could be created to prioritize this task over others.

Additionally, custom schedulers can help improve the scalability of a reactive application. By allocating specific threads to specific tasks, developers can ensure that their application is able to scale up or down depending on the current load. This ensures that applications remain responsive even under heavy loads.

10. Investigate using an event bus such as RSocket or Apache Kafka

Using an event bus allows for decoupling of components, which is important when using Project Reactor. This decoupling makes it easier to scale and maintain the system since components can be added or removed without affecting other parts of the system. It also helps with fault tolerance as components can continue to operate even if one component fails.

RSocket and Apache Kafka are two popular event buses that work well with Project Reactor. RSocket is a binary protocol designed for use in reactive systems, while Apache Kafka is a distributed streaming platform. Both provide reliable messaging capabilities, allowing messages to be sent between components reliably and quickly.

When integrating an event bus into a Project Reactor application, there are several steps to take. The first step is to create a message broker, such as RSocket or Apache Kafka, and configure it to send and receive messages. Then, the components need to be configured to connect to the message broker and exchange messages. Finally, the components need to be configured to react to incoming messages by performing the appropriate action.