Join us for the next DPE Lowdown: How Spotify does DPE with Backstage – July 12, 2023. Register now.
Designed for Developers, Built for the Enterprise
Designed from Inception to Scale
From its first release, Gradle Enterprise has been designed with the explicit requirement that it scales to the largest build infrastructures on the planet. To that end, the Gradle engineering team has made extensive architectural and engineering investments to guarantee that as the platform ingests, processes, and analyzes an ever-growing amount of data, Gradle Enterprise delivers a consistently fast user experience.
Built on a Cloud-Native Foundation
The architecture of Gradle Enterprise is based on modern, cloud-native technologies that enable scalability and align with current DevOps best practices. Whether you deploy to a single node or a large cluster, Gradle Enterprise runs on a Kubernetes foundation and leverages Helm for deployments and software updates. Build Scan data can be stored to S3-compatible cloud storage services for nearly unlimited scale.
Starts Fast and Stays Fast
As a solution dedicated to speeding up build times, it’s essential that Gradle Enterprise adds minimal overhead to the build and test process. We’ve designed the platform to start quickly and be responsive from day one, and remain performant even under heavy load. From our intelligent caching to our powerful web interface, we’ve focused on the performance of every platform component.
Raw build data is consumed and acknowledged by the backend service immediately so that even under high load, transmitting Build Scan data is consistently fast.
Independently Scaled Services
Gradle Enterprise native support for Kubernetes allows each microservice to scale independently to maintain optimal performance. Configuring horizontal scaling provides full control over the number of replicas dedicated to each microservice.
Materialized Database Views
High traffic pages within Gradle Enterprise are backed by materialized views in the Postgres database, allowing for quick load times and fast searches across the most common data attributes of Build Scans.
For any given project, datasets don’t change significantly across multiple builds. By analyzing and segregating data that tends to change versus data that doesn’t, the size of data sets per build can be minimized.
Geo-Distributed Remote Cache Nodes
Support for intelligent replication allows remote cache nodes to be distributed geographically and located in low-latency network proximity to developers working around anywhere in the world.
Integrated Analytics Engine, No External Dependencies
Gradle Enterprise integrates sophisticated caching and preemptive parallel computation techniques to make querying build analytics data faster, without relying on external data processing systems like Spark or Hadoop.
Build Scan data is intelligently queued for processing and analysis. Users who are actively debugging builds will receive higher priority data processing, delivering Build Scan results quickly when they’re needed most.
Automatic Data Compression
Post-optimization, any data sent across the wire to the backend service is compressed before uploading, reducing the overall amount of bandwidth needed and processing latency.
More Gradle Enterprise Industrial-Strength Proof Points
|Enterprises rate Gradle Enterprise Scalability 4.95/5.00 on Gartner Peer Insights|
|The leading DevProd-focused companies as well as 10 of the top 30 U.S. companies have successfully deployed Gradle Enterprise at the massive scale necessary to support their dedicated teams.|
|LinkedIn uses Gradle Enterprise at massive scale, supporting over 300,000 daily builds of their application code! Read their story.|