Develocity enables Applied Materials to reduce build time by 50% and recruit top talent by embracing DPE

Applied Materials, the $25 billion provider of semiconductor chips & materials engineering solutions, was challenged by slow builds and tests and a general lack of observability to performance and failure trends. Their investment in Develocity to address these pains took less than three months to be fully paid off. The company leveraged Build Cache to cut build times in half, Build Scan® to make troubleshooting more efficient, and failure analytics to improve the reliability of their toolchain.

Hinge was experiencing slow builds and tests, and this was putting a drag on team productivity and efficiency. When builds failed, there was a lack of observability to performance data, failure details, dependencies, plug-in usage build environment, and switch values. They implemented and tuned their build cache to speed up build and test feedback cycles and leveraged Build Scan to provide full observability to build and test failures, which greatly facilitates root causes determination. Addressing these points of friction accelerated the success of the Hinge DevOps initiative.

Revolut is a London-based FinTech company with over 30 million global customers. Their front-end Android development team was wasting too much time waiting on build and test feedback, both locally and on CI. This combined with their inability to easily troubleshoot and determine the root cause of build, test, and CI failures, negatively impacted their time to market. They leveraged Build Cache in combination with Build Scan® to reduce build times 75%, achieve a pay back on their investment in Develocity in less than three months, and get actionable insights on build and test performance and failure trends.

Delivery Hero was having difficulty achieving success with their DevOps initiatives due to points of friction in their development process like inefficient troubleshooting and feedback-cycle performance regressions. The problems were exacerbated by not having basic observability data and insights as to how builds were performing and why they occasionally failed. The company experienced a less-than-three-month payback period for their Develocity investment by leveraging Build Cache to cut build and test feedback cycle times in half, and a combination of Build Scan and Failure Analytics to address their performance and failure observability and remediation challenges.

Earnin was suffering from the trifecta of common developer productivity pain points; (1) slow builds and tests both locally and on CI (2) inefficient build and test troubleshooting due to a lack of basic build and test process metrics and data and (3) a lack of observability to build and test process trends to address more systemic potential issues like performance regressions and toolchain reliability issues. They leveraged a combination of DevelocityBuild Cache, Build Scan, and Failure Analytics to address each of these challenges respectively. 

When the opportunity arose to join the “Revved up by Develocity” OSS initiative, we didn’t think twice! We jumped on board and started optimising our builds. This post tells the story of how we integrated Develocity, our findings, and what it may look like if you integrate it in your project. Spoiler alert: Three months into our journey, our mean build time in CI went from ~28min to ~4min. The journey is not over. We are eager to enable the configuration cache and look at predictive test selection to see what additional savings we can get.

Jamf uses Develocity Predictive Test Selection (PTS) and Build Cache performance acceleration technologies to significantly reduce build and test feedback cycle time. The Performance Dashboard was leveraged to tune their Build Cache, resulting in a 60% “avoidance savings.” In a recent 28-day period, PTS reduced serial execution time by 66% and integration test serial execution time by 54%, resulting in 273 days of test execution time saved out of a 469-day total. In this Blog posted by the Jamf engineering team, you can get more result details including an in depth discussion of the Develocity initiative ROI.

This DPE Lowdown features Grant Jenks from LinkedIn’s Developer Productivity and Happiness organization. His Developer Insights team uses Develocity to gather data on millions of builds every quarter and then run analytics against that data. Grant talks about LinkedIn’s techniques to measure things like developer productivity, code quality, and test flakiness. They judge the success of their DPE efforts based on the hard data they get from Develocity. The end result: developer joy from his team’s constant improvements to the environments used by thousands of developers.

Microsoft’s Brian Houck is a Primary Productivity Engineer in the Windows Engineering Systems team. In this DPE Lowdown webinar, he talks about the metrics his team uses to find and remove friction in the development process. Brian’s team uses the tools and data of DPE, as you would expect, but he emphasizes the importance of talking with customers (LinkedIn developers) to make sure their efforts are effective and focused on the right issues. Interacting with developers through constant conversations and surveys is a key part of their DPE practice. That ongoing feedback lets his team stay in front of problems as they emerge, whether those problems are related to technology or culture.

In this case study based on a TechValidate survey, PicPay (the leading Brazilian mobile payments platform) reports a 3-month payback period after deploying Develocity’s build and test acceleration technology (Build Cache) and its performance profiling and failure troubleshooting service (Build Scan™). These solutions help PicPay address their challenges related to long build and test feedback cycle times (locally and on CI) and their inability to easily determine the root cause of build, test, and CI failures and debug them.

In this case study based on a TechValidate survey, fintech provider Paxos reports an immediate payback from deploying Develocity’s Build Cache and Build Scan solutions. Since integrating Develocity into their development process, the time savings experienced by accelerating build and test cycle times has dramatically improved developer productivity and Paxos now views Gradle as a strategic technology partner that exceeds their expectations for service and support.

In this Developer Productivity Engineering meetup we talked to Danny Thomas from the Netflix Productivity Engineering team. We explore the people, processes, and tools they put in place to improve the productivity of their engineers and ultimately ship new and better content to Netflix users faster. Specifically, he discusses the impetus for creating a dedicated DPE team, its size and structure, key goals and metrics, and biggest wins to date.

Aetna saw immediate payback with Develocity and credits it with addressing pains related to (1) observability of performance regressions, failures and productivity bottlenecks; (2) difficulty collaborating when troubleshooting failures; (3) and managing feedback cycles as the code base grows.  According to a TechValidate survey respondent, Gradle consistently exceeds the company’s expectations for a strategic technology partner, scales well, and will meet the service-level expectations of any enterprise-wide deployment.

Roger Taracha, senior Android engineer at Premise Data shares his company’s successful experience using build-cache node replication to serve their distributed teams across the globe. Roger begins with a conceptual recap of the Gradle Build Cache, its benefits, and general installation/configuration considerations. He then outlines the key benefits of node replication and the setup and configuration process, including connecting to Develocity.

Elasticsearch uses Develocity build and test acceleration technology to minimize CI build feedback cycle times and Build Scan™ data to monitor and optimize resource usage. In combination with Google Cloud Platform’s compute performance and cost advantages, Elastic delivers superior service levels to its customers and internal stakeholders. In this Webcast, Elastic’s Mark Vieira and GCP’s James Ward share best practices and technologies leveraged to achieve this result.

In 2020 COVID sent us home. This event produced a completely different scenario in companies where employees enjoyed fast corporate networks. The optimization in the build system of teams working remotely has an impact on the speed and productivity of the engineers. Learn how Tinder leveraged build caching strategies to optimize the build speed in a .droidcon Americas presentation led by Inaki Villar, Build Engineer at Tinder.

It didn’t take long for Stash, a web platform and mobile app provider of financial service, to see benefits after deploying Develocity. We caught up with Joel Parrish, Principal Engineer at Stash to get the low down and he shared his experience and results to date for their Android build. Joel discusses how Build Scan™ is used to determine the root cause of slow build and configuration times and quickly discover a dependency conflict that was crashing the application.

Like many companies, the software development experience at Elastic was starting to become negatively impacted under the increasing strain of slowing builds and inefficient debugging. This Webcast describes how Elastic overcame the natural resistance to augmenting their process and toolset by quantifying the Cost of Inaction and blazing a new path toward build-engineering excellence. In this webcast, you will learn the key developer productivity pain points that drive up the cost of inaction; key DPE concepts and solutions; and how to quantify the Cost of Inaction.

Android builds can be complex and challenging to optimize, yet Android teams usually have the fewest resources to work on the build. In this webinar, Jason Schroeder from Salesforce and Rooz Mohazzabi from Gradle discuss top Android build issues and how to solve them. Specific topics include using build modularization to make the most of your processing power, leveraging the build cache to accelerate developer and CI builds, and working collaboratively with the Build Scan™ service to optimize and debug.

In a dialogue between Sam Snyder, senior developer at Tableau, and Hans doctor, Gradle CEO, opportunities to take the developer experience and organizational productivity to the next level are discussed. Specifically, you will learn how Tableau makes developers happy by using data visualizations to improve build reliability and performance and how to use Tableau with Develocity for live build monitoring and debugging tricky performance and reliability issues.

In addition to modularization, avoiding work is another important part of the build time reduction puzzle, and build caching is one way to avoid work. This is the story about how SoundCloud solved some cache misses with remote build cache and, in turn, saved developer time, making them happier and more productive.

How does LinkedIn create a culture of developer productivity that is capable of building over 100,000 times a day? Szczepan Faber is an architect and technical leader for development tools at LinkedIn. Szczepan sat down with Hans Dockter, founder and CEO of Gradle, to discuss the transformation of build engineering, what a healthy build culture looks like, and the future of developer tools automation.