原文地址:http://www.infoq.com/articles/microframeworks1-spring-boot
Spring Boot is a brand new framework from the team at Pivotal, designed to simplify the bootstrapping and development of a new Spring application. The framework takes an opinionated approach to configuration, freeing developers from the need to define boilerplate configuration. In that, Boot aims to be a front-runner in the ever-expanding rapid application development space.
The Spring IO platform has been criticized over the years for having bulky XML configuration with complex dependency management. During last year’s SpringOne 2GX conference, Pivotal CTO, Adrian Colyer acknowledged those criticisms, and made special note that a goal of the platform going forward is to embrace an XML-free development experience. Boot takes that mission statement to the extreme, not only freeing developers from the need for XML, but also, in some scenarios, releasing them from the tedium of writing import statements. In the days following its public beta release, Boot gained some viral popularity by demonstrating the framework’s simplicity with a runnable web application that fit in under 140-characters, delivered in a tweet.
Spring Boot is not, however, an alternative to the many projects that comprise the "Foundation" layer of the Spring IO platform. Indeed, the goal of Spring Boot is not to provide new solutions for the many problem domains already solved, but rather to leverage the platform in fostering a development experience that simplifies the use of those already-available technologies. This makes Boot an ideal choice for developers who are familiar with the Spring ecosystem, while also catering to new adopters by allowing them to embrace Spring technologies in a simplified manner.
In pursuit of such an improved development experience, Spring Boot — and, indeed, the entire Spring ecosystem — has embraced the Groovy programming language. Groovy’s powerful MetaObject protocol, pluggable AST transformation process, and embedded dependency resolution engine are what facilitate many of the shortcuts that Boot affords. At the core of its compilation model, Boot utilizes Groovy to build project files, so that it can decorate a class' generated bytecode with common imports and boilerplate methods, such as a class' main method. This allows applications written with Boot to remain concise, while still offering a breadth of functionality.
At its most fundamental level, Spring Boot is little more than a set of libraries that can be leveraged by any project’s build system. As a convenience, the framework also offers a command-line interface, which can be used to run and test Boot applications. The framework distribution, including the integrated CLI, can be manually downloaded and installed from the Spring repository. A more convenient approach is to use the Groovy enVironment Manager (GVM), which will handle the installation and management of Boot versions. Boot and its CLI can be installed by GVM with the command line, gvm install springboot
. Formulas are available for installing Boot on OS X through the Homebrew package manager. To do so, first tap the Pivotal repository with brew tap pivotal/tap
, followed by the brew install springboot
command.
Projects that are to be packaged and distributed will need to rely on build systems like Maven orGradle. To simplify the dependency graph, Boot’s functionality is modularized, and groups of dependencies can be brought in to a project by importing Boot’s so-called "starter" modules. To easily manage dependency versions and to make use of default configuration, the framework exposes a parent POM, which can be inherited by projects. An example POM for a Spring Boot project is defined in Listing 1.
<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>com.example</groupId> <artifactId>myproject</artifactId> <version>1.0.0-SNAPSHOT</version> <!-- Inherit defaults from Spring Boot --> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>1.0.0.RC1</version> </parent> <!-- Add typical dependencies for a web application --> <dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-actuator</artifactId> </dependency> </dependencies> <repositories> <repository> <id>spring-snapshots</id> <url>http://repo.spring.io/libs-snapshot</url> </repository> </repositories> <pluginRepositories> <pluginRepository> <id>spring-snapshots</id> <url>http://repo.spring.io/libs-snapshot</url> </pluginRepository> </pluginRepositories> <build> <plugins> <plugin> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-maven-plugin</artifactId> </plugin> </plugins> </build> </project>
For a more-simplified build configuration, developers can leverage the Gradle build system’s concise Groovy DSL, as depicted in Listing 1.1.
buildscript { repositories { maven { url "http://repo.spring.io/libs-snapshot" } mavenCentral() } dependencies { classpath("org.springframework.boot:spring-boot-gradle-plugin:1.0.0.RC1") } } apply plugin: 'java' apply plugin: 'spring-boot' repositories { mavenCentral() maven { url "http://repo.spring.io/libs-snapshot" } } dependencies { compile 'org.springframework.boot:spring-boot-starter-actuator:1.0.0.RC1' }
To help with getting Boot projects up and running quickly, Pivotal provides the so-called "Spring Initializr" web interface, which can be used to download pre-built Maven or Gradle build configurations. Projects can also be quick-started through the use of a Lazybones template, which will create the necessary project structure and gradle build file for a Boot application after executing the lazybones create spring-boot-actuator my-app
command.
The most popular example of a Spring Boot application is one that was delivered via Twitter shortly following the public announcement of the framework. As demonstrated in its entirety in Listing 1.2, a very simple Groovy file can be crafted into a powerful Spring-backed web application.
@RestController class App { @RequestMapping("/") String home() { "hello" } }
This application can be run from the Spring Boot CLI, by executing the spring run App.groovy
command. Boot analyzes the file and — through various identifiers known as "compiler auto-configuration" — determines that it is intended to be a web application. It then, in turn, bootstraps the Spring Application context inside of an embedded Tomcat container on the default port of 8080. Opening a browser and navigating to the provided URL will land you on a page with a simple text response, "hello". This process of providing a default application context and embedded container allows developers to focus on the process of developing application and business logic, and frees them from the tedium of otherwise boiler-plate configuration.
Boot’s ability to ascertain the desired functionality of a class is what makes it such a powerful tool for rapid application development. When applications are executed from the Boot CLI, they are built using the internal Groovy compiler, which allows the ability to programmatically inspect and modify a class while its bytecode is being generated. In this way, developers who use the CLI are not only freed from the need to define default configuration, but, to an extent, they also do not need to define certain import statements that can otherwise be recognized and automatically added during the compilation process. Additionally, when applications are run from the CLI, Groovy’s built-in dependency manager, "Grape", is used to resolve classpath dependencies that are needed to bootstrap the compilation and runtime environments, as determined by Boot’s compiler auto-configuration mechanisms. This idiom not only makes the framework more user-friendly, but also allows different versions of Spring Boot to be coupled with specific versions of libraries from the Spring IO platform, which in turn means that developers do not need to be concerned with managing a complex dependency graph and versioning structure. Additionally, it opens the door for rapid prototyping and quick generation of proof-of-concept project code.
For projects that are not built with the CLI, Boot provides a host of "starter" modules, which define a set of dependencies that can be brought into a build system in order to resolve the specific libraries needed from the framework and its parent platform. As an example of this, thespring-boot-starter-actuator
dependency pulls in a set of base Spring projects to get an application quickly configured and up-and-running. The emphasis of this dependency is on developing web applications, and specifically RESTful web services. When included in conjunction with the spring-boot-starter-web
dependency, it will provide auto-configuration to bootstrap an embedded Tomcat container, and will map endpoints useful to micro-service applications, like server information, application metrics, and environment details. Additionally, when the spring-boot-starter-security
module is brought in, the actuator will auto-configureSpring Security to provide the application with basic authentication and other advanced security features. For any application structure, it will also include an internal auditing framework that can be used for reporting purposes or application-specific needs, like developing an authenitcation-failure lock-out policy.
To demonstrate quickly getting a Spring web application up-and-running from within a Java Maven project, consider the application code outlined in Listing 1.3.
package com.infoq.springboot; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.EnableAutoConfiguration; import org.springframework.web.bind.annotation.*; @RestController @EnableAutoConfiguration public class Application { @RequestMapping("/") public String home() { return "Hello"; } public static void main(String[] args) { SpringApplication.run(Application.class, args); } }
The presence of the @EnableAutoConfiguration
annotation on the Application
class informs Boot that it should take an opinionated approach to configuring the application. This defers otherwise boilerplate configuration to the defaults assumed by the framework, which focuses on getting the application up-and-running as quickly as possible. The Application
class is also runnable, which means that the application, and its embedded container, can be started and actively developed by choosing to run the class as a Java application.
When it is time to build the project for distribution, Boot’s Maven and Gradle plugins hook into those build systems' packaging process to produce an executable "fat jar", which embeds all of the project’s depedencies and can be executed as a runnable jar. Packaging a Boot application with Maven is as simple as running the mvn package
command, and likewise with Gradle, executing the gradle build
command will output a runnable jar to the build’s target location.
Given Boot’s simplifications to Spring application development, its provided ability to import dependencies in a modular fashion, its inherent emphasis on developing RESTful web services, and its capability to produce a runnable jar, the framework is clearly a formidable utility in the development of deployable micro-services. As demonstrated in prior examples, getting a RESTful web application up-and-running is a fairly trivial task with Boot; but to realize the full potential of Boot, we will demonstrate the intricacies of developing a full-featured RESTful micro-service. Micro-services are an increasingly popular application architecture in enterprise infrastructure, as they allow for rapid development, smaller code-bases, enterprise integration, and modular deployables. There are many frameworks that are targeting this development vertical, and this section will discuss utilizing Boot’s simplifications for this purpose.
Micro-services can be built for a variety of purposes, but one guarantee is that most will need the ability to read and write to a database. Spring Boot makes database integration a trivial task with its ability to auto-configure Spring Data for database access. By simply including thespring-boot-starter-data-jpa
module as part of your project, Boot’s auto-configuration engine will detect that your project requires database access, and will create the necessary beans within the Spring application context, so that you can create and use repositories and services. To demonstrate this more specifically, consider the Gradle build file in Listing 1.4, which outlines the build structure of a Groovy-based Boot micro-service web application that uses Spring Data’s JPA support for database access.
buildscript { repositories { maven { url "http://repo.spring.io/libs-snapshot" } mavenCentral() } dependencies { classpath("org.springframework.boot:spring-boot-gradle-plugin:1.0.0.RC1") } } apply plugin: 'groovy' apply plugin: 'spring-boot' repositories { mavenCentral() maven { url "http://repo.spring.io/libs-snapshot" } } ext { springBootVersion = "1.0.0.RC1" } dependencies { compile 'org.codehaus.groovy:groovy-all:2.2.1' compile "org.springframework.boot:spring-boot-starter-web:$springBootVersion" compile "org.springframework.boot:spring-boot-starter-data-jpa:$springBootVersion" compile "org.springframework.boot:spring-boot-starter-actuator:$springBootVersion" }
In this configuration, Boot’s actuator
module provides a dependency on hsqldb
, and will set up all of the necessary configuration — including schema creation — so that Spring Data can use the relational in-memory database as its datasource. This shortcut frees developers from the need to create and manage complicated datasource XML configuration in development, and quickly opens the door to developing database-driven micro-services. This same auto-configuration capability exists if the H2 or Derby embedded databases are found on the classpath. An additional convenience offered by Boot is its ability to quickly and easily bootstrap an application’s database schema with relevant data. This is incredibly useful in development, where a database may be in-memory or otherwise volatile, and where developers need to be sure that certain data points are available when the application starts. To demonstrate this, consider the example JPA entity shown in Listing 1.5, which represents a "User" data structure that the micro-service will provide.
@Entity class User { @Id @GeneratedValue Long id String username String firstName String lastName Date createdDate Date lastAccessed Boolean isActive = Boolean.TRUE }
To bootstrap some common data that represents User
objects, we can simply create a file named schema.sql
or data.sql
, and include it on our classpath. This file will be executed after the schema has been created, so, given the entity depicted in Listing 1.5, we can bootstrap a user account with a SQL statement, as shown in Listing 1.6.
insert into user(username, first_name, last_name, created_date) values ('danveloper', 'Dan', 'Woods', now())
Upon startup, the provided SQL code will be executed, and we can be sure that we have a test account to work with. Now that the micro-service has a data point to begin with, Listing 1.7 demonstrates how we can follow Spring Data’s development pattern and create a Repository
interface that will act as the Data Access Object for the User
entity.
public interface UserRepository extends CrudRepository<User, Long> { }
The CrudRepository
provides some common interface methods for creating, retrieving, updating, and deleting objects and sets of objects. Any specific capabilities that our application may need beyond this can be defined by following Spring Data’s repository development conventions. Once the UserRepository
interface is created, Boot’s spring-data-jpa
layer will detect it within the project, and will bring it into the Spring application context, making it an autowire candidate for controllers and services. This automatic configuration occurs only when a Boot application requests that an opinionated approach be taken, which is identified by the presence of the @EnableAutoConfiguration
annotation. The micro-service can now define a RESTful endpoint for consumers to retrieve a list of users or an individual user through the controller implementation shown in Listing 1.8.
@RestController @EnableAutoConfiguration @RequestMapping("/user") class UserController { @Autowired UserRepository repository @RequestMapping(method=[RequestMethod.GET]) def get(Long id) { id ? repository.findOne(id) : repository.findAll() } public static void main(String[] args) { SpringApplication.run UserController, args } }
At startup, the application will output logging that shows Hibernate creating the database structure as defined by the User
entity, and, as well, will show Boot importing the data from theschema.sql
file as the final part of the application’s initialization.
It’s important to note the use of the @RequestMapping
annotation when developing a micro-service application. This is not an annotation that is Boot specific. However, because Boot installs its own endpoints for the purposes of monitoring the application’s performance, health, and configuration, we want to ensure that our application code doesn’t conflict with the resolution of those built-in detail providers. Given that, when there is a requirement to resolve a property (in this case, the id
of the user) from the request path, then we need to carefully consider how that dynamic property resolution will affect the rest of the micro-service’s behavior. In this case, simply mapping the controller to the /user
endpoint takes it out of the root context, and allows Boot’s endpoints to be accessible as well.
All data provided by our micro-service might not best fit into a relational structure, and for that, Spring Boot exposes modules that give developers the ability to work with Spring Data’s MongoDB and Redis projects, while still taking an opinionated approach to their configuration. Spring Data’s higher-level framework for defining Data Access Objects makes it easy to quickly interchange between JPA and non-JPA data sources. Consider the example in Listing 1.9, which demonstrates a redefined UserRepository
interface designed to work with MongoDB instead of JPA.
public interface UserRepository extends MongoRepository<User, Long> { }
The MongoRepository
interface also extends CrudRepository
, so the micro-service’s controller code from Listing 1.8 needn’t change. To facilitate MongoDB integration as demonstrated, the project must only include the spring-boot-starter-data-mongodb
module on the application’s classpath. The dependency block from the Gradle build file in Listing 1.4 will only need to change slightly, as demonstrated in Listing 1.10.
dependencies { compile 'org.codehaus.groovy:groovy-all:2.2.1' compile "org.springframework.boot:spring-boot-starter-web:$springBootVersion" compile "org.springframework.boot:spring-boot-starter-data-mongodb:$springBootVersion" compile "org.springframework.boot:spring-boot-starter-actuator:$springBootVersion" }
Now that the MongoDB dependency is on the classpath, Boot will auto-configure Spring Data to connect to the database on localhost, and by default to the test
database. From there, the User
collection will automatically be created (as is standard with MongoDB), and the micro-service is now backed by MongoDB. Bootstrapping data for non-JPA datastores is less trivial than otherwise, but this is mostly rooted in the fact that it wouldn’t make sense to run a SQL file against MongoDB’s document store or Redis' key-value store. Since Spring Data will be using persistent instances of these datastores, it also means that data that is created in development will survive a restart. To begin working with persistent data, we need to modify the micro-service controller so that User
instances can be created by consumers. We can also start to evolve the micro-service’s UserController
to conform to a common RESTful API structure by having the controller handle different HTTP methods in different ways. Listing 1.11 demonstrates adding the ability to create new User
instances through the controller.
@RestController @RequestMapping("/user") @EnableAutoConfiguration class UserController { @Autowired UserRepository repository @RequestMapping(method=[RequestMethod.GET]) def get(Long id) { id ? repository.findOne(id) : repository.findAll() } @RequestMapping(method=[RequestMethod.POST]) def create(@RequestBody User user) { repository.save user user } public static void main(String[] args) { SpringApplication.run UserController, args } }
When a consumer of the micro-service performs an HTTP POST to the application’s endpoint, Spring will coerce the request body into a User
instance. The code will then use theUserRepository
to store the object in the MongoDB collection. An example of using curl to create a new User
instance is shown in Listing 1.12.
curl -v -H "Content-Type: application/json" -d "{ \"username\": \"danveloper\", \"firstName\": \"Dan\", \"lastName\": \"Woods\", \"createdDate\": \"2014-02-02T00:00:00\" }" http://localhost:8080/user
With Boot providing an opinion about how the Mongo datasource should be configured, the newUser
instance will, by default, be persisted to the user
collection on the test
database within the Mongo instance running on localhost. If we open a web browser and make an HTTP GET request to the micro-service, we will see the user that we created returned in the list.
Spring Boot gets out of your way pretty quickly when you need to override its configuration defaults. By default, application configuration can be defined using a Java properties file at the root of the application’s classpath named application.properties
. A preferred approach, however, is to use YAML configuration, which gives structure and depth to nested configuration. Given the presence of the snakeyaml
dependency on the application’s runtime classpath, your project can then define configuration directives in an application.yml
file. To demonstrate this, consider the example YAML configuration in Listing 1.13, which outlines the various settings that are available for an application’s embedded HTTP server (Tomcat by default, Jetty by option).
# Server settings (ServerProperties) server: port: 8080 address: 127.0.0.1 sessionTimeout: 30 contextPath: / # Tomcat specifics tomcat: accessLogEnabled: false protocolHeader: x-forwarded-proto remoteIpHeader: x-forwarded-for basedir: backgroundProcessorDelay: 30 # secs
The ability to override Boot’s auto-configuration is what will allow you to take your application from prototype to production, and Boot makes this easy to do within the same application.yml
file. Auto-configuration directives are designed to be as short as possible, so when building your micro-service with actuator
, an endpoint for configuration properties, /configprops
is installed, and can be referred to when determining what directives to override. When we’re ready for our micro-service to use a persistent datasource, like MySQL, then we can simply add the MySQL Java Driver to the runtime classpath, and add the necessary configuration directive to theapplication.yml
file, as demonstrated in Listing 1.14.
spring: datasource: driverClassName: com.mysql.jdbc.Driver url: jdbc:mysql://localhost:3306/proddb username: root password
In scenarios where you need a more flexible configuration, Boot allows you to override much of its default configuration through the use of Java System properties. As an example, if your application needs a different database user when it is deployed to production, the username configuration directive can be passed to the application using standard Java System property switches to the command-line execution, -Dspring.datasource.username=user
. A more practical scenario for this is in a cloud deployment, like Cloud Foundry or Heroku, where those platforms require the application to start on a specific HTTP port, which is made available through an environment variable in the host operating system. Boot’s ability to derive configuration from System properties allows your application to inherit the HTTP port through the command line execution using, -Dserver.port=$PORT
. This is an incredibly useful feature of the framework when developing micro-services, because it allows a micro-service application to run on a variety of environment configurations.
One very important thing that a micro-service must be able to do is support externalizedconfiguration. This configuration can hold anything from placeholder messages to database configuration, and the architecture behind this is an area that must be considered during the initial planning and prototyping of an application. Various strategies for importing configuration exist today within the Spring IO platform, however supporting the various ways in which an application may want to consume configuration often results in verbose programmatic coupling.
A niche feature of Boot is its ability to automatically manage externalized configuration, and coerce it into an object structure that is usable throughout the application context. By creating a Plain Old Java/Groovy Object, and decorating it with the @ConfigurationProperties
annotation, that object will consume its defined name
subset of configuration from Boot’s configuration structure. To describe this more plainly, consider the POGO in Listing 1.15, which brings in configuration directives from under the application.
key.
@ConfigurationProperties(name = "application") class ApplicationProperties { String name String version }
When the ApplicationProperties
object is created within the Spring context, Boot will recognize that it is a configuration object, and will populate its properties in alignment with configuration directives from the application.properties
or application.yml
file on the runtime classpath. With that given, if we add an application
block to the micro-service’s application.yml
file, as shown in Listing 1.16, we will be able to access those directives in a programmatic fashion from the rest of our application.
application: name: sb-ms-custdepl version: 0.1-CUSTOMER
These configuration directives can be used for a variety of purposes, and the only requirement to gain access to them is that their represented POJO/POGO be a participant in the Spring application context. Boot lets us easily manage the configuration bean’s integration to the application context by allowing us to treat a controller as a Spring Java configuration object, as demonstrated in Listing 1.17.
@RestController @Configuration @RequestMapping("/appinfo") @EnableAutoConfiguration class AppInfoController { @Autowired ApplicationProperties applicationProperties @RequestMapping(method=[RequestMethod.GET]) def get() { [ name: applicationProperties.name, version: applicationProperties.version ] } @Bean ApplicationProperties applicationProperties() { new ApplicationProperties() } public static void main(String[] args) { SpringApplication.run UserController, args } }
The code in Listing 1.17 is a contrived example, though given a more-complex scenario, the principles remain the same for using Boot to set up access to application-specific configuration. Configuration classes can also support nested object graphs to give depth and meaning to the data as it’s coming from the configuration. For example, if we wanted to also have configuration directives for our application’s metrics keys under the application.
root, we can add a nested object to the ApplicationProperties
POGO to represent those values, as shown in Listing 1.18.
@ConfigurationProperties(name = "application") class ApplicationProperties { String name String version final Metrics metrics = new Metrics() static class Metrics { String dbExecutionTimeKey } }
Now our application.yml
file can be crafted as demonstrated in Listing 1.19 to include themetrics
configuration under the application.
block.
application: name: sb-ms-custdepl version: 0.1-CUSTOMER metrics: dbExecutionTimeKey: user.get.db.time
When we need access to the application.metrics.dbExecutionTimeKey
value, we can access it programmatically through the ApplicationProperties
object.
These configuration directives within the application.properties
or application.yml
file do not necessarily need to be coerced to an object graph for them to be usable throughout the application. Indeed, Boot also provides the Spring application context with aPropertySourcesPlaceholderConfiguration
, so that directives that are derived from either theapplication.properties
file, the application.yml
file, or from Java System property overrides can be utilized as Spring property placeholders. This mechanism of Spring allows you to define a placeholder value for a property using a specific syntax, and Spring will fill it in if it finds a placeholder configuration that provides it. As an example of this, we can use the @Value
annotation to directly access the application.metrics.dbExecutionTimeKey
within our controller, as shown in Listing 1.20.
@RestController @RequestMapping("/user") @EnableAutoConfiguration class UserController { @Autowired UserRepository repository @Autowired GaugeService gaugeService @Value('${application.metrics.dbExecutionTimeKey}') String dbExecutionKey @RequestMapping(method=[RequestMethod.GET]) def get(Long id) { def start = new Date().time def result = id ? repository.findOne(id) : repository.findAll() gaugeService.submit dbExecutionKey, new Date().time - start result } public static void main(String[] args) { SpringApplication.run UserController, args } }
There will be more discussion on the intricacies of metrics reporting later, but for now the important thing to understand is how the @Value
annotation can be used with a Spring property placeholder to have Boot auto-populate the value for our micro-service’s specific configuration needs.
In micro-service development, the need for a comprehensive security context will invariably arise. To service this need, Boot brings in the powerful, comprehensive Spring Security and provides auto-configuration to quickly and easily bootstrap a security layer. Just the presence alone of the spring-boot-starter-security
module on the application’s classpath will let Boot employ some of its security features like cross-site scripting protection and adding the headers that prevent click-jacking. Additionally, adding a simple configuration directive, as shown in Listing 1.21, will secure your application with basic authentication.
security: basic: enabled: true
Boot will provide you with a default user account of user
, a default role of USER
, and will output a randomly generated password to the console when the application starts up. Like most other things Boot, it is easy to specify a different username and password for the built-in user
account with explicitly defined configuration directives ("secured" and "foo" respectively), as demonstrated in Listing 1.22.
security: basic: enabled: true user: name: secured password: foo
Boot’s built-in faculties for quickly bootstrapping basic authentication within your micro-service prove very useful for simple, internal applications, or for development prototyping. As your requirements evolve, your application will undoubtedly need some granular level of security, such as the ability to secure endpoints to specific roles. From this perspective, we may want to secure read-only data (ie. GET requests) for consumers who are represented with the USER
role, while read-write data (ie. POST requests) should be secured with the ADMIN
role. To facilitate this, we’ll disable Boot’s basic authentication auto-configuration inside of the project’sapplication.yml
file, and define our own for both user
and admin
accounts for their respective roles. This is another example of an area where Boot gets out of your way quickly when you need to move beyond its by-default functionality. To demonstrate this more practically, consider the code outlined in Listing 1.23. This example can be expounded upon to make use of Spring Security’s full potential and leverage more-intricate authentication strategies, such as JDBC-backed, OpenID, or Single-Sign On.
@RestController @RequestMapping("/user") @Configuration @EnableGlobalMethodSecurity(securedEnabled = true) @EnableAutoConfiguration class UserController extends WebSecurityConfigurerAdapter { @Autowired UserRepository repository @RequestMapping(method = [GET]) @Secured(['ROLE_USER']) def get(Long id) { id ? repository.findOne(id) : repository.findAll() } @RequestMapping(method = [POST]) @Secured(['ROLE_ADMIN']) def create(@RequestBody User user) { repository.save user user } @Override void configure(AuthenticationManagerBuilder auth) { auth .inMemoryAuthentication() .withUser "user" password "password" roles "USER" and() withUser "admin" password "password" roles "USER", "ADMIN" } @Override void configure(HttpSecurity http) throws Exception { BasicAuthenticationEntryPoint entryPoint = new BasicAuthenticationEntryPoint() entryPoint.realmName = "Spring Boot" http.exceptionHandling().authenticationEntryPoint(entryPoint) http.requestMatchers().antMatchers("/**").anyRequest() .and().httpBasic().and().anonymous().disable().csrf().disable() } public static void main(String[] args) { SpringApplication.run UserController, args } }
Given the example in Listing 1.23, the application now configures authentication to explicitly provide access to user accounts of user
and admin
, both with the password, password
, and with respective roles of USER
and ADMIN
. The micro-service’s GET and POST endpoints are also secured for USER
and ADMIN
roles respectively, meaning that read-only data can now be accessed by regular users, while performing read-write operations require the admin
user credentials.
Basic authentication is a great choice for micro-services because it follows a very practical and widely usable authentication protocol. In other words, many API consumers, including mobile applications, can very easily make use of this to gain access to your micro-service. When your authentication needs out-grow basic authentication (ie. OpenID or OAuth), your micro-service can leverage the full capabilities of Spring Security for your requirement.
Messaging is a very powerful utility in the toolkit of any application, and micro-services are no exception when it comes to this. Developing these applications with a message-driven architecture can support reusability and scalability. Spring Boot allows developers to write micro-services with messaging as a core tenant of the architecture, through its use of the Spring IO platform’s implementation of the Enterprise Integration Patterns, Spring Integration. Spring Integration provides the structure for developing a message-driven architecture, as well as providing modules for integrating with a distributed enterprise platform. This capability allows micro-services to utilize business objects from an abstract messaging source, whether that source be within the application or provided from another service within the organization.
While Boot does not provide any explicit Spring context auto-configuration, it does offer a starter module for Spring Integration, which is responsible for bringing in a host of dependencies from the Spring Integration project. These dependencies include Spring Integration’s Core library, its HTTP module (for HTTP-oriented enterprise integration), its IP module (for Socket-based integration operations), its File module (for filesystem integration), and its Stream module (for working with Stream, like stdin and stdout). This starter module gives developers a robust toolkit of messaging functionality for adapting an existing infrastructure to a micro-service API.
In addition to the starter module, Boot also offers compiler auto-configuration for applications that are built through the CLI. This provides some shortcuts for developers who are rapidly prototyping micro-services, and are demonstrating viability. Applications that leverage an enterprise platform can be quickly developed, and their value rapidly determined before they are moved to a formal project and build system. Getting a message-driven micro-service up-and-running with Spring Boot and Spring Integration is as easy as the code sample depicted in Listing 1.24.
@RestController @EnableIntegrationPatterns class App { @Bean def userLookupChannel() { new DirectChannel() } @Bean def userTemplate() { new MessagingTemplate(userLookupChannel()) } @RequestMapping(method=[RequestMethod.GET]) def get(@RequestParam(required=false) Long id) { userTemplate().convertSendAndReceive( id ? id : "") } } class User { Long id } @MessageEndpoint class UserLookupObject { @ServiceActivator(inputChannel="userLookupChannel") def get(Long id) { id ? new User(id:id) : new User() } }
Taking a message-driven approach to micro-service development offers a high amount of code reusability and decoupling from the underlying service provider implementation. In a less contrived scenario, the code in Listing 1.18 may be responsible for the composition of data from database calls and external service integration within an enterprise organization. Spring Integration has built-in constructs for payload routing and handler chaining, which makes it an appealing solution to the composition of disparate data, to which we may find our micro-service being a provider.
Perhaps the most important feature of a micro-service is its ability to provide metrics to a reporting agent. Unlike thick web applications, micro-services are lightweight and aren’t designed with the intent of providing reporting screens or robust interfaces to analyze the service’s activity. These types of operations are best left to applications that are strictly responsible for the aggregation and analysis of data for the purposes of stability, performance, and business intelligence monitoring. With that as a given, a micro-service will provide endpoints for those reporting tools to easily consume data about its activity. From there, it is the responsibility of the reporting tool to compose that data into a view or report that makes sense to whomever cares about that data.
While some of the metrics about a micro-service, such as stability and performance, can be generalized across all applications, metrics related to business operations must be managed specifically by the application. For this purpose, Spring Boot’s actuator
module exposes a mechanism for developers to programmatically expose details about the micro-service’s state through the /metrics
endpoint. Boot breaks down metrics to the categories of "counters" and "gauges"; a counter is any metric that is represented as a Number, where a gauge is a metric that measures some calculation with double precision. To make working with metrics easy for micro-service developers, Boot exposes a CounterService
and a GaugeService
as autowirable candidates to the application context. Consider the example in Listing 1.25, which demonstrates exposing a hit count through the CounterService
.
@RestController @RequestMapping("/user") @EnableAutoConfiguration class UserController { @Autowired UserRepository repository @Autowired CounterService counterService @RequestMapping(method = [GET]) def get() { get(null) } @RequestMapping(value="/{id}", method = [GET]) def get(@PathVariable Long id) { counterService.increment id ? "queries.by.id.$id" : "queries.without.id" id ? repository.findOne(id) : repository.findAll() } }
After hitting the /user
endpoint with and without a provided ID, the /metrics
endpoint will report new keys under the counter.
parent. For example, if we simply query the /user
endpoint with no ID, then the counter.queries.without.id
metric will be registered and available. Likewise, when we do provide an ID, we will see the counter.queries.by.id.<id>
key shown to denote how many queries have been made for a provided ID. These metrics may provide some insight into the most commonly accessed User
objects, and may denote some actions that need to be taken, such as caching or database indexing. In the same manner of incrementing a metric count, the CounterService
also allows for a metric to be decremented to zero. This may be useful for tracking open connections or other histographic measurements.
Gauges are a slightly different type of metric, in that they provide heuristics for calculated or otherwise upon-request determined values. As the GaugeService
JavaDocs note, the "gauge" measurement can be anything from method execution time to the temperature of a meeting room. Those types of measurements are uniquely suited for the use of the GaugeService
when exposing details for a reporting tool. Gauge metrics will be prefixed in the /metrics
endpoint withgauge.
. They are registered in a slightly different manner than counters, which is demonstrated in Listing 1.26.
@RestController @RequestMapping("/user") @EnableAutoConfiguration class UserController { @Autowired UserRepository repository @Autowired CounterService counterService @RequestMapping(method = [GET]) def get() { get(null) } @RequestMapping(value="/{id}", method = [GET]) def get(@PathVariable Long id) { def start = new Date().time def result = id ? repository.findOne(id) : repository.findAll() def time = new Date().time - start gaugeService.submit("user.get.db.time", time.doubleValue()) result } }
By default, metrics will be stored in a volatile, in-memory database, but providing an implementation of a MetricsRepository
to the application context will allow for a more-persistent storage behavior. Boot ships with a RedisMetricsRepository
, which can be autowired to store metrics in a Redis keystore, though custom implementations for any datastore can be crafted to persist the metrics.
Boot also provides support for the Coda Hale Metrics library, and will coerce metrics that start with certain names to their respective Metrics types. For example, if a metric is provided that starts with histogram.
, then Boot will provide that value as a Histogram
object type. This automatic coercion also works for meter.
and timer.
keys, while regular metrics are sent asGauge
types.
Once micro-service metrics are being registered with Boot, they can then be retrieved by a reporting tool through the /metrics
endpoint. Named metrics can be provided to the /metrics
endpoint by providing the metric key name as part of the query string. For example, to accessonly the gauge metric, "user.get.db.time", a reporting tool can make a query to/metrics/gauge.user.get.db.time
.
As discussed earlier, Boot ships with plugins for both Maven and Gradle, which provide a hook into the build systems' packaging phase to produce the so-called "fat jar" with all of the project’s dependencies included. When the fat jar is executed, the application code will run inside of the same embedded container in which the project was developed. This shortcut gives developers the peace-of-mind that their deployable package has the same dependency structure and runtime environment from which they developed. This alleviates operations teams from worrying about deployment scenarios where a mis-configured runtime container may have one specification of dependencies, while the project was developed under another.
To perform the packaging under Maven, simply execute the mvn package
command. The Spring Boot plugin will make a backup of the originally created project jar and rename it with an appended ".original" to the filename. From here, the runnable jar will be available following the Maven artifact naming conventions, and can be deployed in the manner most suitable to the project. Building Boot projects with Gradle is equally as trivial, and requires only the execution of the standard gradle build
command. Similar to Maven, the Boot plugin installs a lifecycle event with Gradle that follows the original packaging task, and will produce the fat jar to the build/libs
directory. An examination of the produced fat jar will reveal all of the dependent jars in the lib/
directory of the archive.
Once packaged, the fat jar can be executed from the command line as a regular runnable jar file, using the command $JAVA_HOME/bin/java -jar path/to/myproject.jar
. When started, the Boot application logging will be shown in the console.
For applications that need the ability to deploy to a traditional servlet container, Boot provides a path for programmatically initializing a web configuration. To facilitate this, Boot offers an opinionated WebApplicationInitializer
, which registers the application with the servlet container through the Servlet 3.0 API to programmatically register servlets with the container’sServletContext
. By providing a subclass of SpringBootServletInitializer
, Boot applications can register their configuration with the embedded Spring context that is created during the container’s initialization. To demonstrate this functionality, consider the example code demonstrated in Listing 1.27.
@RestController @EnableAutoConfiguration class Application extends SpringBootServletInitializer { @RequestMapping(method = RequestMethod.GET) String get() { "home" } static void main(String[] args) { SpringApplication.run this, args } @Override SpringApplicationBuilder configure(SpringApplicationBuilder application) { application.sources Application } }
The Application
class' overridden configure
method is what is used to register the application code with the embedded Spring context. In a less-contrived scenario, this method may be used to register a Spring Java configuration class, which would define the beans for all of the controllers and services in the application.
When packaging the application for deployment to a servlet container, the project must be built as a war file. To accommodate this in a Maven project, the Boot plugin needs to be removed, and the packaging needs to be defined explicitly with a type of "war", as shown in Listing 1.28.
<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>com.example</groupId> <artifactId>myproject</artifactId> <version>1.0.0-SNAPSHOT</version> <packaging>war</packaging> <parent> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-parent</artifactId> <version>1.0.0.RC1</version> </parent> <dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-actuator</artifactId> </dependency> </dependencies> <repositories> <repository> <id>spring-snapshots</id> <url>http://repo.spring.io/libs-snapshot</url> </repository> </repositories> </project>
Executing a mvn install
command for this project will result in a myproject-1.0.0-SNAPSHOT.war
file being built to the target
directory. Projects that are built with Gradle can make use of the Gradle War Plugin, which exposes a war
task for building the war file. Similar to Maven configurations, Boot Gradle projects will also need to remove their inclusion of the Boot plugin. A sample Gradle build script for producing a war file can is depicted in Listing 1.29.
apply plugin: 'java' apply plugin: 'war' repositories { mavenCentral() maven { url "http://repo.spring.io/snapshot" } maven { url "http://repo.spring.io/milestone" } } ext { springBootVersion = '1.0.0.BUILD-SNAPSHOT' } dependencies { compile "org.springframework.boot:spring-boot-starter-web:${springBootVersion}" compile "org.springframework.boot:spring-boot-starter-actuator:${springBootVersion}" }
Running the Gradle war
task against a Boot project with this build script will output the war artifact to the build/libs
directory.
In either a Maven or Gradle configuration, once the war file is produced, it can then be deployed to any Servlet 3.0-compliant application container. Some compliant containers include Tomcat 7+, Jetty 8, Glassfish 3.x, JBoss AS 6.x/7.x, and Websphere 8.0.
The Spring Boot team has produced a comprehensive collection of guides and samples to demonstrate the framework’s capabilities. Blog posts, reference material, and API documentation can all be found on the Spring.IO website. Example projects can be found on theproject’s GitHub page, and additional low-level detail can be found in the Spring Boot reference manual. The SpringSourceDev YouTube channel has a webinar on Spring Boot, which outlines the project’s goals and capabilities. During last year’s Groovy & Grails Exchange in London, David Dawson gave a presentation on developing micro-services with Spring Boot.
Daniel Woods is a Senior Software Engineer at Netflix, where he develops continuous delivery and cloud deployment tools. He specializes in JVM stack technologies and is active in the Groovy, Grails, and Spring communities. Daniel can be reached via email at [email protected] or through Twitter @danveloper.