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Mongoose is a high-load storage performance testing automation tool.
The Mongoose Load Engine is capable to work with:
- A million of concurrent connections
- A million of operations per second
- A million of items which may be processed multiple times in the circular load mode
- A million of items which may be stored in the storage mock
Basically, Mongoose may be started very simply:
java -jar mongoose.jar-
Mongoose has rich configuration subsystem. It supports mapping to provide a backward compatibility and the values generated using the pattern.
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Item is the unit of the load progress and metrics accounting. An item may be a file, cloud storage data object, some kind of token or something else. The [[data items|v3.2 User Guide#211-data-items]] describe the data to use to perform a load operation (some fixed or random size, content source, etc).
Mongoose may persist the items used in a run/job info to a specified output which later may be used as items input for another run/job.
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Different data may be used to perform a load on a storage. By default Mongoose uses random, uncompressible data. An user may supply custom data source instead.
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In contradiction to all other comparable performance testing software, Mongoose doesn't use the threads to set up a specified concurrency level. This allows to use very high concurrency (up to 1 million of simultaneous connections/open files) easily.
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The so called circularity feature allows to use the limited amount of items unlimited test run/load job by reusing these items again and again (circularly).
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A load job is an unit of a test run with its own configuration and metrics accounting. An user may consider a load job as a test step.
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Mongoose supports different storage types: a filesystem or a cloud storage. Currently, the following cloud storage APIs are supported: Amazon S3, EMC Atmos and OpenStack Swift.
- Overview
- Deployment
- User Guide
- Troubleshooting
- Reference