In this article I’m going to describe two features of Spring Cloud Gateway: retrying based on
GatewayFilter pattern and timeouts based on a global configuration. In some previous articles in this series I have described rate limiting based on Redis, and circuit breaker built with Resilience4J. For more details about those two features you may refer to the following blog posts:
Continue reading “Timeouts and Retries In Spring Cloud Gateway”
I have already written about documentation for microservices more than two years ago in my article Microservices API Documentation with Swagger2. In that case I used project SpringFox for auto-generating Swagger documentation for Spring Boot applications. Since that time the SpringFox library is not being actively developed by the maintainers – the latest version has been released on June 2018. Currently, the most important problems with this library are a lack of support for OpenAPI in the newest version 3, and for Spring reactive APIs built using WebFlux. All these features are implemented by Springdoc OpenAPI library. Therefore, it may threaten as a replacement for SpringFox as Swagger and OpenAPI 3 generation tool for Spring Boot applications. Continue reading “Microservices API Documentation with Springdoc OpenAPI”
The main goal of this article is to show how to monitor Spring Boot applications running on Kubernetes with Spring Boot Admin. I have already written about Spring Boot Admin more than two years ago in the article Monitoring Microservices With Spring Boot Admin. You can find there a detailed description of its main features. During this time some new features have been added. They have also changed a look of the application to more modern. But the principles of working have not been changes anymore, so you can still refer to my previous article to understand the main concept around Spring Boot Admin. Continue reading “Spring Boot Admin on Kubernetes”
There are many tools, which may simplify your local development on Kubernetes. For Java applications you may also take an advantage of integration between popular runtime frameworks and Kubernetes. In this article I’m going to present some of available solutions. Continue reading “Local Java Development on Kubernetes”
Hazelcast is the leading in-memory data grid (IMDG) solution. The main idea behind IMDG is to distribute data across many nodes inside cluster. Therefore, it seems to be an ideal solution for running on a cloud platform like Kubernetes, where you can easily scale up or scale down a number of running instances. Since Hazelcast is written in Java you can easily integrate it with your Java application using standard libraries. Something what can also simplify a start with Hazelcast is Spring Boot. You may also use an unofficial library implementing Spring Repositories pattern for Hazelcast – Spring Data Hazelcast. Continue reading “Hazelcast with Spring Boot on Kubernetes”
Auto-configuration is probably one of the most important reasons you would decide to use such frameworks like Spring Boot. Thanks to that feature, it is usually enough just to include an additional library and override some configuration properties to successfully use it in your application. Spring provides an easy way to define auto-configuration using standard
@Configuration classes. Continue reading “A Magic Around Spring Boot Auto Configuration”
Micronaut provides a library that eases development of applications deployed on Kubernetes or on a local single-node cluster like Minikube. The project Micronaut Kubernetes is relatively new in Micronaut family, its current release version is
1.0.3. It allows you to integrate Micronaut application with Kubernetes discovery, and use Micronaut Configuration Client to read Kubernetes
Secret as a property sources. Additionally it provides health check indicator based on communication with Kubernetes API. Continue reading “Guide To Micronaut Kubernetes”
You might use Spring Cloud Kubernetes to build applications running both inside and outside Kubernetes cluster. The only problem with starting application outside Kubernetes is that there is no auto-configured registration mechanism. Spring Cloud Kubernetes delegates registration to the platform, what is an obvious behaviour if you are deploying your application internally using Kubernetes objects. With external application the situation is different. In fact, you should guarantee registration by yourself on the application side. Continue reading “Spring Cloud Kubernetes For Hybrid Microservices Architecture”
Spring Cloud and Kubernetes are the popular products applicable to various different use cases. However, when it comes to microservices architecture they are sometimes described as competitive solutions. They are both implementing popular patterns in microservices architecture like service discovery, distributed configuration, load balancing or circuit breaking. Of course, they are doing it differently. Continue reading “Microservices With Spring Cloud Kubernetes”
In the newest version of Spring Cloud Gateway (
2.2.1) we may take an advantage of a new implementation of circuit breaker built on top of project Resilience4J (https://github.com/resilience4j/resilience4j). Resilience4J has been selected as a replacement for Netflix’s Hystrix, that had been moved to the maintenance mode. Of course, you can still use Hystrix as circuit breaker implementation, however it is deprecated and probably won’t be available in the future versions of Spring Cloud. A new implementation is called no different than just Spring Cloud Circuit Breaker. Continue reading “Circuit Breaking In Spring Cloud Gateway With Resilience4J”
In this article I’m going to propose my list of “golden rules” for building Spring Boot applications, which are a part of microservices-based system. I’m basing on my experience in migrating monolithic SOAP applications running on JEE servers into REST-based small applications built on top of Spring Boot. This list of best practices assumes you are running many microservices on the production under a huge incoming traffic. Let’s begin. Continue reading “Spring Boot Best Practices for Microservices”
If you are building microservices architecture on top of Spring Boot and Spring Cloud I’m almost sure that one of projects you are using is Spring Cloud Config. Spring Cloud Config is responsible for implementing one of the most popular microservices pattern called distributed configuration. It provides server-side (Spring Cloud Config Server) and client-side (Spring Cloud Config Server) support for externalized configuration in a distributed system. In this article I focus on security aspects related to that project. If you are interested in some basics please refer to my previous article about it Microservices Configuration With Spring Cloud Config. Continue reading “Secure Spring Cloud Config”
Currently Spring Cloud Gateway is second the most popular Spring Cloud project just after Spring Cloud Netflix (in terms of number of stars on GitHub). It has been created as a successor of Zuul proxy in Spring Cloud family. This project provides an API Gateway for microservices architecture, and is built on top of reactive Netty and Project Reactor. It is designed to provide a simple, but effective way to route to APIs and address such popular concerns as security, monitoring/metrics, and resiliency. Continue reading “Rate Limiting In Spring Cloud Gateway With Redis”
This is the fourth part of my tutorial to Micronaut Framework – created after a longer period of time. In this article I’m going to show you some examples of reactive programming on the server and client side. By default, Micronaut support to reactive APIs and streams is built on top of RxJava. Continue reading “Micronaut Tutorial: Reactive”
The Spring Cloud Consul project provides integration for Consul and Spring Boot applications through auto-configuration. By using the well-known Spring Framework annotation style, we may enable and configure common patterns within microservice-based environments. These patterns include service discovery using Consul agent, distributed configuration using Consul key/value store, distributed events with Spring Cloud Bus, and Consul Events. The project also supports a client-side load balancer based on Netflix’s Ribbon and an API gateway based on Spring Cloud Gateway. Continue reading “Microservices with Spring Boot, Spring Cloud Gateway and Consul Cluster”
Reactive APIs and generally reactive programming become increasingly popular lately. You have a change to observe more and more new frameworks and toolkits supporting reactive programming, or just dedicated for this. Today, in the era of microservices architecture, where the network communication through APIs becomes critical for applications, reactive APIs seems to be an attractive alternative to a traditional, synchronous approach. It should be definitely considered as a primary approach if you are working with large streams of data exchanged via network communication. Continue reading “Using Reactive WebClient with Spring WebFlux”
Since Spring 5 and Spring Boot 2 there is a full support for reactive REST API with Spring WebFlux project. Also project Spring Data systematically includes support for reactive NoSQL databases, and recently for SQL databases too. Since Spring Data Moore we can take advantage of reactive template and repository for Elasticsearch, what I have already described in one of my previous article Reactive Elasticsearch With Spring Boot. Continue reading “Performance Comparison Between Spring MVC and Spring WebFlux with Elasticsearch”
One of more notable feature introduced in the latest release of Spring Data is reactive support for Elasticsearch. Since Spring Data Moore we can take advantage of reactive template and repository. It is built on top of fully reactive Elasticsearch REST client, that is based on Spring WebClient. It is also worth to mention about support for reactive Querydsl, which can be included to your application through
ReactiveQueryPredicateExecutor. Continue reading “Reactive Elasticsearch With Spring Boot”
I have already introduced my Spring Boot library for synchronous HTTP request/response logging in one of my previous articles Logging with Spring Boot and Elastic Stack. This library is dedicated for synchronous REST applications built with Spring MVC and Spring Web. Since version 5.0 Spring Framework also offers support for reactive REST API through Spring WebFlux project. I decided to extend support for logging in my library to reactive Spring WebFlux.
Continue reading “Reactive Logging With Spring WebFlux and Logstash”
Almost a year ago Spring Cloud has announced that most of Spring Cloud Netflix OSS projects will be moved to the maintenance mode starting from Spring Cloud Greenwich Release Train. In fact the maintenance mode only does not include Eureka, which still will be supported. I referred to that information in one of my previous articles The Future of Spring Cloud Microservices After Netflix Era. I have shared there some opinions about future of microservices with Spring Cloud. Of course, I also included an example of building microservices architecture without Netflix OSS using HashiCorp’s Consul, Spring Cloud Gateway and an early version of Spring Cloud LoadBalancer.
Continue reading “Using New Spring Cloud Load Balancer In Microservices Communication”
I have already described how to build microservices architecture entirely based on message-driven communication through Apache Kafka in one of my previous articles Kafka In Microservices With Micronaut. As you can see in the article title the sample applications and integration with Kafka has been built on top of Micronaut Framework. I described some interesting features of Micronaut, that can be used for building message-driven microservices, but I specially didn’t write anything about testing. In this article I’m going to show you how to test your Kafka microservice using Micronaut Test core features (Component Tests), Testcontainers (Integration Tests) and Pact (Contract Tests).
Continue reading “Part 1: Testing Kafka Microservices With Micronaut”
Stream API, which has been introduced in Java 8, is probably still the most important new feature that has been included to Java during last several years. I think that every Java developer has an opportunity to use Java Stream API in his career. Or I should rather told that you probably use it on a day-to-day basis. However, if you compare the built-in features offered for functional programming with some other languages – for example Kotlin – you will quickly realize that the number of methods provided by Stream API is very limited. Therefore, the community has created several libraries used just for extending API offered by pure Java. Today I’m going to show the most interesting Stream API extensions offered by the three popular Java libraries: StreamEx, jOOλ and Guava.
Continue reading “Overview of Java Stream API Extensions”
I have already described some implementation details related to my library
logstash-logging-spring-boot-starter for HTTP request/response logging in one of the previous articles Logging with Spring Boot and Elastic Stack. The article has been published some weeks ago, and since that time some important features has been added to this library. Today I’m going to summarise all those changes and describe all the features provided by the library.
Continue reading “Using logstash-logging-spring-boot-starter for logging with Spring Boot and Logstash”
More advanced deployments to Kubernetes or OpenShift are a bit troublesome for developers. In comparison to Kubernetes OpenShift provides S2I (Source-2-Image) mechanism, which may help reduce a time required for preparation of application deployment descriptors. Although S2I is quite useful for developers, it solves only simple use cases and does not provide unified approach to building deployment configuration from a source code. Dekorate (https://dekorate.io), the recently created open-source project, tries to solve that problem. This project seems to be very interesting. It appears to be confirmed by RedHat, which has already announced a decision on including Dekorate to Red Hat OpenShift Application Runtimes as a “Tech Preview”. Continue reading “Deploying Spring Boot Application on OpenShift with Dekorate”
You had an opportunity to read many articles about building microservices with such frameworks like Spring Boot or Micronaut on my blog. There is another one very interesting framework dedicated for microservices architecture, which is becoming increasing popular – Quarkus. It is being introduced as a next-generation Kubernetes/Openshift native Java framework. It is built on top of well-known Java standards like CDI, JAX-RS and Eclipse MicroProfile which distinguishes it from Spring Boot. Continue reading “Quick Guide to Microservices with Quarkus on Openshift”
When I have writing some articles comparing Spring and Micronaut frameworks recently, I have taken a note of many comments about lack of built-in ORM and data repositories support in Micronaut. Spring provides this feature for a long time through Spring Data project. The good news is that the Micronaut team is close to complete work on first version of their project with ORM support. The project called Micronaut Predator (short for Precomputed Data Repositories) is still under active development, and currently we may access just the snapshot version. However, the authors are introducing it is as more efficient with reduced memory consumption than competitive solutions like Spring Data or Grails GORM. In short, this could be achieved thanks to Ahead of Time (AoT) compilation to pre-compute queries for repository interfaces that are then executed by a thin, lightweight runtime layer, and avoiding usage of reflection or runtime proxies. Continue reading “JPA Data Access with Micronaut Data”
One of the reason you could decide to use OpenShift instead of some other containerized platforms (for example Kubernetes) is out-of-the-box support for continuous delivery pipelines. Without proper tools the process of releasing software in your organization may be really time-consuming and painful. The quickness of that process becoming especially important if you deliver software to production frequently. Currently, the most popular use case for it is microservices-based architecture, where you have many small, independent applications.
Continue reading “Continuous Delivery with OpenShift and Jenkins: A/B Testing”
In this article I’ll introduce my library for logging designed especially for Spring Boot RESTful web application. The main assumptions regarding this library are:
- Logging all incoming HTTP requests and outgoing HTTP responses with full body
- Integration with Elastic Stack through Logstash using
- Possibility for enabling logging on a client-side for most commonly used components in Spring Boot application:
- Generating and propagating correlationId across all communication within a single API endpoint call
- Calculating and storing execution time for each request
- A library should be auto-configurable – you don’t have to do anything more than including it as a dependency to your application to make it work
Continue reading “Logging with Spring Boot and Elastic Stack”
This is the third part of my tutorial to Micronaut Framework. This time we will discuss the most interesting Micronaut security features. I have already described core mechanisms for IoC and dependency injection in the first part of my tutorial, and I have also created a guide to building simple REST server-side application in the second part. For more details you may refer to:
Continue reading “Micronaut Tutorial: Security”
In this part of my tutorial to Micronaut framework we are going to create simple HTTP server-side application running on Netty. We have already discussed the most interesting core features of Micronaut like beans, scopes or unit testing in the first part of that tutorial. For more details you may refer to my article Micronaut Tutorial: Beans and Scopes.
Assuming we have a basic knowledge about core mechanisms of Micronaut we may proceed to the key part of that framework and discuss how to build simple microservice application exposing REST API over HTTP. Continue reading “Micronaut Tutorial: Server Application”
Micronaut is a relatively new JVM-based framework. It is especially designed for building modular, easy testable microservice applications. Micronaut is heavily inspired by Spring and Grails frameworks, which is not a surprise, if we consider it has been developed by the creators of Grails framework. It is based on Java’s annotation processing, IoC (Inversion of Control) and DI (Dependency Injection).
Micronaut implements the JSR-330 (
java.inject) specification for dependency injection. It supports constructor injection, field injection, JavaBean and method parameter injection. In this part of tutorial I’m going to give some tips on how to:
- define and register beans in the application context
- use built-in scopes
- inject configuration to your application
- automatically test your beans during application build with JUnit 5
Continue reading “Micronaut Tutorial: Beans and Scopes”
Today we will compare two frameworks used for building microservices on the JVM: Spring Boot and Micronaut. First of them, Spring Boot is currently the most popular and opinionated framework in the JVM world. On the other side of the barrier is staying Micronaut, quickly gaining popularity framework especially designed for building serverless functions or low memory-footprint microservices. We will be comparing version 2.1.4 of Spring Boot with 1.0.0.RC1 of Micronaut. The comparison criteria are:
- memory usage (heap and non-heap)
- the size in MB of generated fat JAR file
- the application startup time
- the performance of application, in the meaning of average response time from the REST endpoint during sample load testing
Continue reading “Performance Comparison Between Spring Boot and Micronaut”
If somebody would ask you about Spring Cloud, the first thing that comes into your mind will probably be Netflix OSS support. Support for such tools like Eureka, Zuul or Ribbon is provided not only by Spring, but also by some other popular frameworks used for building microservices architecture like Apache Camel, Vert.x or Micronaut. Currently, Spring Cloud Netflix is the most popular project being a part of Spring Cloud. It has around 3.2k stars on GitHub, while the second best has around 1.4k. Therefore, it is quite surprising that Pivotal has announced that most of Spring Cloud Netflix modules are entering maintenance mode. You can read more about in the post published on the Spring blog by Spencer Gibb https://spring.io/blog/2018/12/12/spring-cloud-greenwich-rc1-available-now. Continue reading “The Future of Spring Cloud Microservices After Netflix Era”
Elasticsearch is a full-text search engine especially designed for working with large data sets. Following this description it is a natural choice to use it for storing and searching application logs. Together with Logstash and Kibana it is a part of powerful solution called Elastic Stack, that has already been described in some of my previous articles.
Keeping application logs is not the only one use case for Elasticsearch. It is often used as a secondary database for the application, that has primary relational database. Such an approach can be especially useful if you have to perform full-text search over large data set or just store many historical records that are no longer modified by the application. Of course there is always question about advantages and disadvantages of that approach.
When you are working with two different data sources that contain the same data, you have to first think about synchronization. You have several options. Depending on the relational database vendor, you can leverage binary or transaction logs, which contain the history of SQL updates. This approach requires some middleware that reads logs and then puts data to Elasticsearch. You can always move the whole responsibility to the database side (trigger) or into Elasticsearch side (JDBC plugins). Continue reading “Elasticsearch with Spring Boot”
There are some things I really like in Spring Boot, and one of them is an externalized (external) configuration. Spring Boot allows you to configure your application in many ways. You have 17 levels of loading configuration properties into application. All of them are described in the 24th Chapter of Spring Boot documentation available here.
This article was inspired by some last talks with developers about problems with the configuration of their applications. They haven’t heard about some interesting features that may be used to make it more flexible and clear. Continue reading “A Magic Around Spring Boot Externalized Configuration”
Redis is an in-memory data structure store with optional durability, used as database, cache and message broker. Currently, it is the most most popular tool in the key/value stores category: https://db-engines.com/en/ranking/key-value+store. The easiest way to integrate your application with Redis is through Spring Data Redis. You can use Spring RedisTemplate directly for that or you might as well use Spring Data Redis repositories. There are some limitations when you integrate with Redis via Spring Data Redis repositories. They require at least Redis Server version 2.8.0 and do not work with transactions. Therefore you need to disable transaction support for RedisTemplate, which is leveraged by Redis repositories. Continue reading “Introduction to Spring Data Redis”
Micronaut Framework provides support for Kotlin built upon Kapt compiler plugin. It also implements the most popular cloud-native patterns like distributed configuration, service discovery and client-side load balancing. These features allows to include your application built on top of Micronaut into the existing microservices-based system. The most popular example of such approach may be an integration with Spring Cloud ecosystem. If you have already used Spring Cloud, it is very likely you built your microservices-based architecture using Eureka discovery server and Spring Cloud Config as a configuration server. Beginning from version 1.1 Micronaut supports both these popular tools being a part of Spring Cloud project. That’s a good news, because in version 1.0 the only supported distributed solution was Consul, and there were no possibility to use Eureka discovery together with Consul property source (running them together ends with exception). Continue reading “Kotlin Microservices with Micronaut, Spring Cloud and JPA”