The Cloudflight Platform serves as foundation for all Cloudflight custom software projects running on the JVM. This contains 3 major parts:
- Unified Dependency Management on top of Spring Boot and Spring Cloud
- Utility Modules for cross-cutting-concerns like monitoring, JPA access, Elastic Search and much more that can (and should) be embedded into your production code
The Cloudflight Platform comes with two BOM packages (bill-of-materials) that provide dependency management for all platform artifacts as well as third party libraries, one of them for application code, the other one for test-code.
You can utilize Gradle's dependency management and add both BOMs as platform-dependencies to your root project:
dependencies {
api platform("io.cloudflight.platform.spring:platform-spring-bom:$cloudflightPlatformVersion")
testImplementation platform("io.cloudflight.platform.spring:platform-spring-test-bom:$cloudflightPlatformVersion")
}
While platform-bom
only provides dependency constraints, platform-bom-test
also puts the following libaries to
the testImplementation
classpath of all submodules of your project:
- JUnit 5 (including JUnit-Params)
- Mockk
- AssertJ
That means you do not need to add them on your own. The Cloudflight Platform handles that for you.
Why exactly those? Because not only we think that those are really valuable testing libraries.
In conjunction with the AutoConfigure Gradle Plugin, you
might add code like that to your root build.gradle
:
subprojects { proj ->
dependencies {
api platform("io.cloudflight.platform.spring:platform-spring-bom:$cloudflightPlatformVersion")
annotationProcessor platform("io.cloudflight.platform.spring:platform-spring-bom:$cloudflightPlatformVersion")
if (proj.plugins.hasPlugin(org.jetbrains.kotlin.gradle.plugin.KotlinPluginWrapper)) {
kapt platform("io.cloudflight.platform.spring:platform-spring-bom:$cloudflightPlatformVersion")
}
testImplementation platform("io.cloudflight.platform.spring:platform-spring-test-bom:$cloudflightPlatformVersion")
}
}
By adding the platform to your gradle root file, you can add any other submodule of the platform without entering the version number:
dependencies {
testImplementation('io.cloudflight.platform.spring:platform-spring-jpa-test')
}
These modules are meant to be embedded into your production code, either as api/implementation or as test dependency. Find more details about the modules on the according subpages.
Each module can be added to your code like that:
dependencies {
implementation('io.cloudflight.platform.spring:%MODULE_NAME%')
}
i.e.
dependencies {
implementation('io.cloudflight.platform.spring:platform-spring-profiling')
}
Whenever you have a module in your code-base that fires up a Spring Boot Server (typically modules with the suffix
-server
), then add the module io.cloudflight.platform.spring:platform-spring-server-config
to your implementation
classpath.
It not only adds other required modules for monitoring and logging config but also provides the interface
ServerModuleIdentification
as a Spring Bean which can be injected to your service. It provides you:
- the name of the server
- the current version (as provided from the build pipeline)
- the underyling Git Hash.
When Spring Boot applications get bigger, startup time often decreases. In order to have more insights on what is going on,
the module platform-server-config
comes with a utility which prints a detailled analysis of all startup phases of your
ApplicationContext
.
To enable that, you need to do two things:
- Set the logger
io.cloudflight.platform.spring.server.ApplicationStartupPrinter
toTRACE
- Set a
BufferingApplicationStartup
to yourSpringBootApplication
as described in the official docs.
public static void main(String[] args) {
SpringApplication app = new SpringApplication(MySpringConfiguration.class);
app.setApplicationStartup(new BufferingApplicationStartup(2048));
app.run(args);
}
The log itself gets quite huge and broad and would not fit into this documentation, but if you're interested, just try it out.
If you are running integration tests with @SpringBootTest
, you don't need to set this bean manually. All you need to do is to ensure you have platform-test
on your classpath.
The module io.cloudflight.platform.spring:platform-spring-context
provides the object ApplicationContextProfiles
which comes with
constants for our default Spring profile names that will be put into the environment.
The profile names to be used then (also in application.yaml
files) are the following:
Profile name | Description |
---|---|
development |
to be used for local development inside the IDE |
staging |
staging environment |
production |
production environment |
test |
default profile to be used in Spring Application tests |
testcontainer |
To be used in test cases when using TestContainers, those tests run reasonabily slower and it should be possible to not run them explicitely |
Whenever you are accessing one of those profile names from within the code (i.e. in a @Profile
annotation), use the according contstant
in ApplicationContextProfiles
. Application configuration files need to be suffixed with the strings mentioned above (i.e. application-development.yaml
).
Monitoring via Spring Boot Actuator and Prometheus will be activated automatically with the module
io.cloudflight.platform.spring:platform-spring-monitoring
(which comes together with platform-server-config
as mentioned above).
Important thing to know here is that it automatically sets the port to listen for actuator requests to server.port + 10000
.
That means, if your server is running on port 8080, you will find the actuator endpoints on 18080. We are doing this
to provide a clean and easy-to-manage security concept for these endpoints in production as we can simply restrict
accessing this port from outside and don't need to deal with Spring Security in parallel.
The module io.cloudflight.platform.spring:platform-spring-logging-server-config
(which is also being transitively loaded with)
platform-server-config
comes with a basic configuration for Logback, especially also preparing our logging mechanism
for the usage of the ELK stack on production.
Use this file as reference in your logback-spring.xml
files as follows:
<?xml version="1.0" encoding="UTF-8"?>
<configuration>
<include resource="io/cloudflight/platform/spring/logging/clf-base.xml" />
<logger name="io.cloudflight" level="INFO"/>
<root level="WARN"/>
</configuration>
The module platform-logging
wraps Slf4J and Kotlin Logging and also provides some annotations for more convenient
access for MDC values. MDC gives you the possibility to append
structured information to your log output which you can then easily filter and search in Kibana, see this blog entry
for more information.
While this is a great thing, coding is a bit verbose as you need to manually take care to clear the MDC context after your method call.
The code example from the above linked blog entry is not fully correct, as you also need to catch exceptions properly and clean up
in a finally
block. That means, the correct usage would be (here now in kotlin code):
fun sayHello(name: String) {
try {
MDC.put("name", name)
LOG.info("We are calling hello now")
} finally {
MDC.remove("name")
}
}
With platform-spring-logging
, you get the annotation io.cloudflight.platform.logging.annotation.LogParam
which you can append on method parameters. The
following code does exactly the same:
fun sayHello(@LogParam name: String) {
LOG.info("We are calling hello now")
}
@Transactional
).
The annotation @LogParam
can also be customized and chained, here are some examples:
@Service
class MySpringBean {
fun sayHello(@LogParam name: String) {
// calls MDC.put("name", name)
}
fun sayHelloWithNamedParameter(@LogParam(name = "myName") name: String) {
// calls MDC.put("myName", name)
}
fun sayHelloWithField(@LogParam(field = "firstName") person: Person) {
// calls MDC.put("person.firstName", person.firstName)
}
fun sayHelloWithFieldAndName(@LogParam(field = "firstName", name = "myFirstName") person: Person) {
// calls MDC.put("myFirstName", person.firstName)
}
fun sayHelloWithMultipleFieldNames(
@LogParams(
LogParam(field = "firstName"),
LogParam(field = "lastName")
) person: Person
) {
// calls MDC.put("person.firstName", person.firstName) and
// calls MDC.put("person.lastName", person.lastName)
}
data class Person(val firstName: String, val lastName: String)
}
Please note that the underyling io.cloudflight.platform.logging.interceptor.LogParamInterceptor
also takes care of cleaning
up the MDC context again after the method call.
If you cannot use @LogParam
for some reason platform-spring-logging
provides an additional convenient option.
The global function mdcScope
keeps track of all fields MDC manipulations done in the passed lambda and cleans up for you afterwards.
fun sayHello(name: String) {
mdcScope {
MDC.put("name", name)
MDC.put("name" to name) // this is equivalent to the line above
LOG.info("We are calling hello now")
}
}
If you need the mdcScope
to cover your whole function you can also use it as a single-expression function:
fun sayHello(name: String) = mdcScope {
MDC.put("name", name)
MDC.put("name" to name) // this is equivalent to the line above
LOG.info("We are calling hello now")
}
Please note that the MDC
available inside the mdcScope
-functions scope is not org.slf4j.MDC
but a wrapper build around it.
The module platform-spring-jpa
wraps all required libraries in order to access a relational database
with JPA/Hibernate and Spring Data, especially Spring's spring-data-jpa
and Spring Boot's spring-boot-starter-data-jpa
.
It also automatically applies @EnableTransactionManagement
.
If you want to use Query DSL, then
platform-spring-jpa
autoconfigures a JPQLQueryFactory
which you can use to create QueryDSL queries. Anyways,
you need to add QueryDSL to your classpath manually (it does not come by automatically), and also do not
forget to apply the annotation processor.
If you are using Kotlin entities (which is our preferred way), then your build.gradle
should look somehow like that:
dependencies {
implementation 'io.cloudflight.platform.spring:platform-spring-jpa'
implementation 'com.querydsl:querydsl-jpa::jakarta'
kapt 'com.querydsl:querydsl-apt::jpa'
kapt 'io.cloudflight.platform.spring:platform-spring-jpa'
}
Then, in order to use QueryDSL, create a custom repository and inject the JPQLQueryFactory
:
interface ArtifactRepository : JpaRepository<Artifact, Long>, QueryDslArtifactRepository { // <1>
fun findArtifactByProjectAndName(project: Project, name: String): Artifact?
}
interface QueryDslArtifactRepository { // <2>
fun findAllByGroupId(groupId: String): List<ArtifactListDto>
}
@Repository
class QueryDslArtifactRepositoryImpl( // <3>
private val queryFactory: JPQLQueryFactory // <4>
) : QueryDslArtifactRepository {
private val a = QArtifact.artifact
override fun findAllByGroupId(groupId: String): List<ArtifactListDto> {
return queryFactory.select(QArtifactListDto(a.name, a.packaging)) // <5>
.from(a)
.where(a.project.name.eq(groupId))
.fetch()
}
}
- Your default
JpaRepository
which extends from your custom repository interface - Your custom repository interface with all methods that you want to query with QueryDSL
- Implementation of your custom repository
- Inject
JPQLQueryFactory
- Use the
JPQLQueryFactory
to create your query instances
TBD
TBD
The module platform-spring-i18n
provides some additional utility services around Spring's i18n support:
- Tracking available locales
- Defining a default locale on the server
Add the module to your server build.gradle
like that:
dependencies {
implementation 'io.cloudflight.platform.spring:platform-spring-i18n'
}
Add configuration to your application.yaml
cloudflight:
i18n:
locales:
- GERMAN
default: GERMAN
spring:
messages:
basename: classpath:/messages
Inject the spring bean io.cloudflight.platform.i18n.I18nService
to query all available and the default locale on the backend.
Implement the interface io.cloudflight.platform.i18n.LocaleAccess
in any of your beans to get the the locale of the current thread.
If you want to handle exposing i18n keys to the frontend in some custom way, use the ListResourceBundleMessageSource
bean directly and disable automatic exposure of all the message-properties via /api/i18n
with this configuration:
cloudflight:
i18n:
httpendpoint:
enabled: false
The module platform-spring-validation
gives you client-side support for validating user input, triggered by validations on the server, and it
plays well together with platform-spring-i18n
.
Form-validations on client-side are insecure (no-one prevents an arbitrary client to bypass those validations), but on the other hand web clients (like Angular) cannot easily deal with Spring's Backend Validation Support.
This module builds the bridge between Spring's BindException
and DTOs which can be serialized as JSON and being used on the client
to display those validations.
All you need to do is to embed the module platform-spring-validation
, the PlatformValidationAutoConfiguration
will automatically create beans
to transform all instances of BindException
or MethodArgumentNotValidException
to ErrorResponse
instances which look like the following:
data class ErrorResponse(
val fieldMessages: List<FieldMessageDto> = emptyList(),
val globalMessages: List<GlobalMessageDto> = emptyList()
)
Behind the scenes, Spring's I18n support around MessageSource
is being utilized to transform technical error codes into human-readable
and localized strings. Simply create messages_[lang].properties
files on the backend
You can also use Springs JSR303 Validation Support with the according annotations @Valid
, @NotNull
and so on, as well as on DTOs
and on entities.
TBD
The Cloudflight Platform also provides some modules that help you create Unit or Integration Tests.
As described in the section dependency management, the platform dependency platform-spring-test-bom
automatically adds JUnit5, AssertJ and MockK to your testImplementation
configuration.
While those modules are handsome in each module and can be used everywhere, there exist additional test modules within the Cloudflight platform for more sophisticated tests (mostly for the server modules):
When projects get bigger, very often also the test cases get more complex (especially intergration tests) which often has negative impact on the compile/build performance.
In order to have more transparency of how long your tests, the module platform-spring-test
adds some profiling support on different levels:
First thing is that we automatically register a BufferingApplicationStartup
bean to your test case in order to be able to gain
insights of the performance of your ApplicationContext
when it starts up. Under the hood it uses the same mechanism as described in
"Startup time analysis", that means in order to see the logs, you need to set the logger io.cloudflight.platform.server.ApplicationStartupPrinter
to TRACE
in your logback-test.xml
.
This module transitively gives you support to test Spring and Spring Boot applications (spring-test
and spring-boot-starter-test
),
that means you can automatically use @SpringBootTest
in your integration tests.
Include the module platform-spring-test
as follows in your server module:
dependencies {
testImplementation 'io.cloudflight.platform.spring:platform-spring-test'
}
WARNING: Instances of @SpringBootTest
are costly during execution. If possible, write plain unit tests in your service modules, and use Spring Boot container tests only in your server modules.
Running a @SpringBootTest
is costly, and it should only be used in your Server-Module in order to reduce
test execution time. Anyways, you might then also use our support to test your APIs via the network, that means
starting up your whole server, dynamically creating a client based on your API interfaces, and then executing
HTTP requests. That way you are also testing your Spring WebMVC annotations without any mocking infrastructure.
Use the class FeignTestClientFactory
in connection with LocalServerPort
as shown in this snippet:
@SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.RANDOM_PORT) // <1>
class FeignTestClientFactoryTest(
@Autowired @LocalServerPort private val port: Int // <2>
) {
private val helloApi =
FeignTestClientFactory.createClientApi(HelloWorldApi::class.java, port) // <3>
@Test
fun helloWorld() {
assertThat(helloApi.helloWorld("John").name).isEqualTo("John")
}
}
// All subsequent classes usually come from the application itself, you don't need
// them in your test classes. We just want to give an impression here of what we are
// testing here
@SpringBootApplication
class TestApplication // <4>
@Api("Project")
interface HelloWorldApi { // <5>
@GetMapping("/hello/world")
fun helloWorld(@RequestParam("name") name: String): HelloWorldDto
}
data class HelloWorldDto(val name: String, val time: LocalDateTime)
@RestController
class HelloWorldController : HelloWorldApi { // <6>
override fun helloWorld(name: String): HelloWorldDto {
return HelloWorldDto(name, LocalDateTime.now())
}
}
- It's important to have
SpringBootTest.WebEnvironment.RANDOM_PORT
here aswebEnvironment
- Inject the
@LocalServerPort
as variable into your test case, it will have the value of of the random port of your server - Create a client using the
FeignTestClientFactory
by passing exactly that port. You may also inject your ownApplicationContext
here in order to add HTTP interceptors or similar. - Your application classes, usually from your Server-Module
- Any API from your -api-module
- The server implementation of your API
Additionally, the module platform-spring-test
comes with the great library QuickPerf.
QuickPerf is a testing library for Java to quickly evaluate and improve some performance-related properties. The QuickPerf extension
is being registered by platform-spring-test
, so you don't need to add @QuickPerfTest
on your test classes.
The module platform-spring-test-jpa
leverages QuickPerf support by also adding support to profile SQL queries.
That way, you can write test methods like that:
@Test
@ExpectSelect(1)
fun getArtifact() {
repositoryService.getArtifact("foo", "bar")
}
This test class will fail if the number of SQL queries being made within the body of that method is not equal to 1. Have a look at the QuickPerf website for all available annotations including configuration support.
Embed the module platform-spring-test-testcontainers
to get support for Testcontainers via
the wrapper library from playtika.
The playtika library provides wrappers for lots of containers (MariaDB, Postgres, RabbitMQ, Localstack, MinIO,...) which you have to add yourself in your Gradle scripts as shown below. You just don't need to care about versioning, that is being done by the platform, as the BOM of Playtika is being embedded. The list of available wrapper libraries can be found here.
Here is an example how to use the MariaDB testcontainer within your @SpringBootTest
. First, add the dependency to
platform-spring-test-testcontainers
along with embedded-mariadb
:
dependencies {
testImplementation 'io.cloudflight.platform.spring:platform-spring-test-testcontainers'
testImplementation 'com.playtika.testcontainers:embedded-mariadb'
}
Then configure your Spring DataSource with the exposed properties in your application-test.yaml
:
spring:
datasource:
url: jdbc:mariadb://${embedded.mariadb.host}:${embedded.mariadb.port}/${embedded.mariadb.schema}
username: ${embedded.mariadb.user}
password: ${embedded.mariadb.password}
Your test case then is as easy as to just use the test profile and start a @SpringBootTest
:
@SpringBootTest
@ActiveProfiles(ApplicationContextProfiles.TEST)
class ServerIntegrationTest(
@Autowired private val personService: PersonService
) {
@Test
fun listPersons() {
// your test comes here
}
}
The underlying libraries have automatically created a MariaDB instance for you in an own container. Use Flyway or Liquibase to initialize your database just as in production.
The module io.cloudflight.platform.spring:platform-spring-test-bdd
pulls the required libraries of JGiven to our classpath. It automatically
registers the JGivenExtension
on all test JUnit5 test cases, so you don't need to add something like @ExtendsWith(JGivenExtension.class)
to your test cases.
Have a look at the excellent JGiven documentation how to use the full strength of those tests. This module also ships a Kotlin extension for JGiven for better JGiven support in Kotlin.
The module io.cloudflight.platform.spring:platform-spring-test-archunit
embeds
embeds the ArchUnit CleanCode Verifier and provides
an AbstractCleanCodeTest
that you can use as follows:
import com.tngtech.archunit.core.importer.ImportOption.DoNotIncludeTests
import com.tngtech.archunit.junit.AnalyzeClasses
import io.cloudflight.platform.spring.test.archunit.AbstractCleanCodeTest
@AnalyzeClasses(packagesOf = [ArchitectureTest::class], importOptions = [DoNotIncludeTests::class])
class ArchitectureTest : AbstractCleanCodeTest() {
// your ArchUnit tests go here
}
It embeds all CleanCodeRuleSets
from the ArchUnit CleanCode Verifier.
Have a look at the documentation in that subproject.
We recommend to put that test into the root package of the module in your repository which
imports all other modules (typically a -server
-module). This way, your whole source code is
being analyzed