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com.netflix.ndbench:ndbench-api
Advanced tools
Netflix Data Benchmark (NDBench) is a pluggable cloud-enabled benchmarking tool that can be used across any data store system. NDBench provides plugin support for several data stores and can be extended to other client APIs.
Details about the features can be found in the Wiki
The stable version of NdBench is the master branch.
For questions or contributions, please consider reading CONTRIBUTING.md.
Java 8 recommended. Java 11+ is not supported.
NdBench comes with a Gradle wrapper
./gradlew build
The gradlew script will pull down all necessary gradle components/infrastructure automatically, then run the build.
NdBench provides several default implementations ( NdBenchConfiguration, LocalClusterDiscovery etc). You can use these or choose to create your own. NdBench currently works on AWS or your local environment. We are open to contributions to support other platforms as well.
The first step before building ndbench is to configure the interfaces related to your environment in the InjectedWebListener. Checkout the Wiki for further explanation on what interfaces to bind based on your environment.
ndbench-web.war
in your containerDISCOVERY_ENV
environment variable is responsible to bind the proper Cluster Discovery. Currently AWS, CF and Local are supported.
Hence set the environment variable DISCOVERY_ENV
based on the environment you are deploying the app.
For Amazon Web Services use AWS
, for Cloud Foundry use CF
, and for local deployments any other name.
For Cloud Foundry, build and upload the ndbench war to CF using cf push
.
./gradlew appRun
You can provide properties by using ndbench{version}.jar in your web container and then implementing IConfiguration Interface. More details on the how the configuration can be found in the Wiki.
Need some help with either getting up and going or some problems with the code?
Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0
FAQs
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We found that com.netflix.ndbench:ndbench-api demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 0 open source maintainers collaborating on the project.
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