Bacalhau provides powerful distributed compute capabilities that can be applied across various domains and scenarios. Explore the examples below to discover how Bacalhau can address your specific needs.
Below is a complete list of all available use case documentation:
📄️ Log Processing
Process logs efficiently at scale by running distributed jobs directly at the source, reducing costs, improving real-time insights, and enhancing security.
📄️ Distributed Data Warehousing
Efficiently query and analyze data across multiple regions by deploying compute tasks directly where your data resides, reducing latency, enhancing performance and ensuring compliance.
📄️ Fleet Management
Efficiently manage and operate a large fleet of distributed nodes with remote execution, real-time monitoring, targeted job execution, and automated software updates.
📄️ Distributed Machine Learning
Train and deploy machine learning models across a distributed compute fleet, optimizing performance, reducing data movement, and enabling large-scale parallelism.
📄️ Edge Computing
Run compute tasks closer to the data source, reducing latency, minimizing bandwidth costs, and enabling real-time processing for edge devices and remote environments.