Improving the execution time of CI pipelines

Executing a large number of tests, especially integration tests, takes a lot of time. For instance, the pipeline of one of our projects for each Pull Request previously took nearly 30 minutes, including over 1 thousand test cases. This article guides you through several good techniques that we have discovered and applied to improve the time-consuming process.

Parallel stages

Analyze the current phases in your pipeline and categorize them in parallel. For example, we can separate the build and verify code of Node.js and Maven modules simultaneously in our Jenkins pipelines. Please mind using the setting failFast whether you want to abort the pipeline immediately.

Parallel test execution

If you use Maven, the plugin maven-failsafe-plugin is used to execute integration tests during phases integration-test and verify the build lifecycle. It allows us to execute tests in parallel. There are many settings related to parallel test execution, so make sure to configure them correctly for your environment. For example, we can execute tests in parallel using the classes mode and set threadCount=7 for the Jenkins Agent with 8 CPU cores.

Application profiles

There are certain integration tests that don't require the use of a database. These tests focus on scenarios like error handling, authentication filters, or loading configuration. For example, initializing the database with Testcontainers is time-consuming. If you use Spring Boot, you can utilize a different profile and use the H2 in-memory database for these tests. The test class will be annotated with the @ActiveProfiles annotation to run with the specified profile.

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The HelloWorld example of JSF 2.2 with Myfaces

I just did by myself create a very simple app "HelloWorld" of JSF 2.2 with a concrete implementation Myfaces that we can use it later on for our further JSF trying out. I attached the source code link at the end part. Just follow these steps below: 1. Create a Maven project in Eclipse (Kepler) with a simple Java web application archetype "maven-archetype-webapp". Maven should be the best choice for managing the dependencies , so far. JSF is a web framework that is the reason why I chose the mentioned archetype for my example. 2. Import dependencies for JSF implementation - Myfaces (v2.2.10) into file pom.xml . The following code that is easy to find from http://mvnrepository.com/ with key words "myfaces". <dependency> <groupId>org.apache.myfaces.core</groupId> <artifactId>myfaces-api</artifactId> <version>2.2.10</version> </dependency> <dependency> <groupId>org.apache.myfaces.core<...

Junit - Test fails on French or German string assertion

In my previous post about building a regex to check a text without special characters but allow German and French . I met a problem that the unit test works fine on my machine using Eclipse, but it was fail when running on Jenkins' build job. Here is my test: @Test public void shouldAllowFrenchAndGermanCharacters(){ String source = "ÄäÖöÜüß áÁàÀâÂéÉèÈêÊîÎçÇ"; assertFalse(SpecialCharactersUtils.isExistSpecialCharater(source)); } Production code: public static boolean isExistNotAllowedCharacters(String source){ Pattern regex = Pattern.compile("^[a-zA-Z_0-9_ÄäÖöÜüß áÁàÀâÂéÉèÈêÊîÎçÇ]*$"); Matcher matcher = regex.matcher(source); return !matcher.matches(); } The result likes the following: Failed tests: SpecialCharactersUtilsTest.shouldAllowFrenchAndGermanCharacters:32 null A guy from stackoverflow.com says: "This is probably due to the default encoding used for your Java source files. The ö in the string literal in the J...

How to apply Lean - Kanban for your business

This is the topic of Scrum Breakfast meetup this time, speaker: Ms. Phuong Bui - Technical Project Manager of YOOSE Pte. Ltd. http://www.meetup.com/Scrum-Breakfast-Vietnam-Agile-and-Scrum-Meetup/events/230313727/ Lean comes from Lean manufacturing is a method that focuses on elimination of wastes. In other words, this is a set of principles for archiving the quality, speed and customer alignment. The first time I knew about the term "Lean" is from the book Software Craftsmanship . Sandro recommends if we want to transform our pet projects into a real business, we should get familiar with Lean Startup concepts. In this talk, Ms. Phuong pointed out some major wastes includes information (ex: unclear requirements), processes (ex: waiting), physical environment and people. Knowing what the problems should be the best way to eliminate them. The difference between Single item flow and Batch processing is the second main point; and it is the Lean's idea. Batch pr...

Think like a Engineering Manager

Off-boarding Members can leave the company for various reasons, and as a manager, it is important to take action. Hoping for the best is not a strategy. In the case of a low-performing member, I can kindly issue an official warning, set clear objectives for improvement, and re-evaluate the results. If there is a conflict between members, I need to be mindful and go beyond the situation to list our expectations with corresponding actions. Finally, if a member has a big chance to grow at another company, I can have an honest discussion with that member about the trade-offs. Balance at Work As an engineering manager, it is important to balance involvement in meetings and getting your hands dirty on some topics. The goal is to become a companion to teams. Here are my two actions to deal with the situation: Dedicate time for important-but-not-urgent tasks and prioritize them daily. Categorize work into four lines including management, project support, OKRs, and self-study. Management Conduc...

Applying pipeline “tensorflow_embedding” of Rasa NLU

According to this nice article , there was a new pipeline released using a different approach from the standard one ( spacy_sklearn ). I wanted to give it a try to see whether it can help with improving bot’s accuracy. After applying done, I gave an evaluation of “tensorflow_embedding”. It seemed to work better a bit. For example, I defined intents “greet” and “goodbye” with some following messages in my training data. ## intent:greet - Hey! How are you? - Hi! How can I help you? - Good to see you! - Nice to see you! - Hi - Hello - Hi there ## intent:goodbye - Bye - Bye Bye - See you later - Take care - Peace In order to play around with Rasa NLU, I created a project here . You can have a look at this change from this pull request . Yay! When I entered message “hi bot”, then bot with “tensorflow_embedding” could detect intent “greet” with better confidence scores rather than bot with “spacy_sklearn”. The following are responses after executing curl -X POST loc...

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