The setup and configuration of Big Data tools can be very complex and daunting — Juju frees you to explore, test and evaluate Big Data solutions to choose the one that works best for you.
Reduce the time to deploy Hadoop and other solutions from days to minutes.
Experiment with different configurations and solutions to choose what works for you.
Port your solution from one infrastructure to another quickly and seamlessly.
Charms encapsulate best practice allowing you to focus on your work.
The reference implementation of the Anssr Data Platform, developed by Juju Experts at Spicule.
Apache Hadoop is a software framework that supports distributed storage and processing of vast amounts of data. This bundle provides a core set of proven Hadoop components from Apache Bigtop, coupled with monitoring and logging software to enable cluster observability.
Apache Spark is a fast processing engine for large-scale data processing. This bundle includes components from Apache Bigtop to provide Spark in standalone HA mode. Ganglia and rsyslog are included to monitor cluster health and syslog activity.
This bundle combines the capabilities of the above Hadoop and Spark bundles. This provides users with a flexible solution consisting of HDFS, MapReduce, and Spark that can process a wide variety of workloads.
Apache Kafka is an open-source message broker that aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Combine Kafka with Hadoop for a powerful stream/batch solution.
Key charms included in the bundle:
Apache HBase is known as the Hadoop database. Combined, HBase + Hadoop can process enormous tables — billions of rows by millions of columns — atop clusters of commodity hardware.
Key charms included in the bundle
An end-to-end Big Data solution that enables ingestion, processing, and visualization of log data. The ingestion component highlighted here is the Apache Flume service.
Use the bundles above, alter and extend them or create your own. Get involved and find out more by visiting the Big data community.