We are thrilled to announce the release of AppScale 3.2. The main theme for the next installment in the AppScale 3 series, has been the tuning and improvement of the Big Data capabilities of AppScale. So in this release we finely tuned the performance of Datastore, and TaskQueue APIs in order to support massive load with the MapReduce and Pipeline libraries. At high level the biggest changes:
- Improved support for Pull Queues (TaskQueue API), and full support for Rest API;
- Tuned TaskQueue API implementation to decrease latency and improve throughput for million tasks operations;
- Improved Datastore API to increase responsiveness, and support for handling million tasks bookkeeping;
- Improved support for MapReduce and Pipeline libraries;
- Improved implementation of AppServer to reduce latency and increase throughput to handle increased requests for tasks handling;
- Added beta support for LogService API;
- Improved handling of large cloud deployments (added support to keep the instances running to reduce restart latencies).
As usual for the detailed Changelog check our Github release pages.
We went through the code with a fine comb in order to squeeze more performances out of the existing resources:
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