Developer Productivity Engineering Blog

Developer Productivity Engineering at Elastic: Avoiding the Cost of Inaction

Like many companies, the software development experience at Elastic was starting to become negatively impacted under the increasing strain of slowing builds and inefficient process for testing and debugging. And, the pain was only expected to increase in line with the growth of development teams, code bases, and repositories. The cost of inaction was projected to soon become unbearable.

In this webcast, Mark Vieira, Senior Software Engineer at Elastic discusses with Gradle, Inc. CEO, Hans Dockter, how Elastic overcame the natural resistance to change their process and toolset by quantifying the Cost of Inaction and blazing a new path toward build engineering excellence.



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Preventing Flaky Tests from Ruining your Test Suite

Do you hate flaky tests? If your application interacts with browsers, external services, or has asynchronous behavior, it’s likely your team has suffered from flaky tests.

Non-deterministic tests are a ruinous infection that wastes developer time and reduces confidence in your test suite.



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Improve CI Performance by Optimizing Maven and Gradle Builds

A fast and efficient CI pipeline can make or break your team’s developer experience and productivity. But what are the biggest determinants of CI pipeline performance? How do CI platform infrastructure and build/test performance impact each other and where should you focus your efforts?



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Identifying and analyzing flaky tests in Maven and Gradle builds

Flaky, or non-deterministic, tests are a serious and prevalent problem in modern software development. If your application interacts with browsers, external devices or services, or has asynchronous behavior, it’s likely you have suffered from flaky tests. Martin Fowler has this to say about flaky tests:

Non-deterministic tests have two problems, firstly they are useless, secondly they are a virulent infection that can completely ruin your entire test suite. As a result they need to be dealt with as soon as you can, before your entire deployment pipeline is compromised. — Martin Fowler on Eradicating Non-Determinism in Tests

Flaky tests compromise deployment pipelines by slowing them down and decreasing confidence in the correctness of changes. When changes regularly fail due to unrelated flaky tests, time is wasted, features are delayed, and developers are demotivated to make changes.



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What’s New in Gradle 6.0

Gradle 6.0 is the culmination of several years of innovative improvements in Dependency Management. Embracing the idea that there is more to software composition and reuse than just putting a set of jar files on the classpath, Gradle now offers a new metadata format to richly define software components that are often made up of multiple files, different variants and specific constraints on their dependencies.



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Analyzing unstable and slow tests using Gradle Enterprise

Testing takes the overwhelming majority of time during software builds. A single test can waste countless hours of building time — a single failure may cause an entire CI pipeline to have to be re-run. Ugh.

In this post, I will show you how to identify slow and unstable tests using the new Tests Dashboard in Gradle Enterprise 2019.4 for Gradle and Maven builds. The dashboard visualizes test results across many builds for tests executed by Gradle’s built-in Test task and Maven’s SureFire plugin.



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The cost of downloading dependencies

Although ephemeral builds can be nice to test changes in isolation, there are trade-offs for doing so. One of those trade-offs is dependency download times.

In Gradle Enterprise 2019.3, the dependency download metrics in the performance and trends dashboards can be used to look at dependency download times and debug issues. For example, let’s look at the dependency download times for the Gradle project itself for all builds run in the last four weeks.



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Developer Productivity Engineering

In this webinar, Hans Dockter, CEO & Founder of Gradle, talked about the emerging practice of developer productivity engineering, a discipline of using data to improve essential development processes from build/test to CI/CD.



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