You might want to tune the application services and run-time engines for big data processing to ensure that the application services and the run-time engines are allocated enough resources to perform jobs.

For example, the Model Repository Service and the Data Integration Service require resources to store run-time data. When you run mappings, you might deploy the mappings to the Data Integration Service and run the mappings on the Blaze engine. Similarly, the Blaze engine requires resources to run the mappings. You must allocate enough resources between the Model Repository Service, the Data Integration Service, and the Blaze engine to ensure that mapping performance is optimized.

You can tune the application services and run-time engines based on deployment type. A deployment type represents big data processing requirements based on concurrency and volume. The deployment type defines the amount of resources that application services and run-time engines require to function efficiently, and how resources should be allocated between the application services and run-time engines.

To tune the application services and run-time engines, assess the deployment type that best describes the environment that you use for big data processing. Then select the application services and the run-time engines that you want to tune. Tune the application services and the run-time engines using

infacmd autotune autotune

.