INSUBCONTINENT EXCLUSIVE:
materials for safety, and the massive requirements for data processing related to health and financial records.For computer scientists,
developers, engineers, or anyone who needs to run a batch processing job, the needs are even greater
Because of the massive data needs -- often at petabyte scale -- the jobs often need to be queued for processing and determined by the
compute resources for that local, on-premise data center
An example of this might be a simulation to determine the safety of a new material to be used in a future car.There are many variables --
the impact on the material, the temperature, and the speed of the driver not to mention the chemical properties of the material itself
AWS Batch allows companies, research institutions, universities, or any entity with massive data processing needs to run batch processing
jobs without the typical on-premise restrictions.Batch processing refers to a computing operation that runs multiple compute requests
without the need for the user to initiate another process
The name comes from the early days of computing when end-users had to initiate every computing process one by one
With batch processing, you can queue the requests for processing and then allow the service to do the heavy lifting in terms of scheduling
the requests, adjusting compute performance, and allocating the memory and storage need to run the batch jobs
And, you can schedule multiple batch processing jobs to run concurrently, tapping into the true power of cloud computing.Since this
scheduling occurs automatically between AWS Batch and the related Amazon services you need -- such as Amazon EC2 (Elastic Cloud Compute) --
there is no need to configure any software for IT management or processing
AWS Batch coordinates the IT services you need for the project at hand without further intervention from the user.For those with heavy
demands for data processing, this allows the staff to focus more on the actual project management and business requirements, the results of
the computations, queuing up more batch processing jobs, and analyzing the results and making decisions about what to do next
AWS Batch provides all of the necessary frameworks to do the batch processing.A side benefit to using AWS for batch processing with AWS
Batch is you can take advantage of Spot Instances, a service included with Amazon EC2
Spot Instances are unused compute resources that are lower in cost and available for batch processing instead of on-demand services
This cost savings comes into play as Spot Instances become available
In the end, it means great savings for all batch processing -- and configured automatically for you.Because of how the cloud storage,
performance, memory, and infrastructure and servers are all automated according to the batch processing requirements, and because the
terms of coordination across AWS
That is often the hardest and most time-consuming part of a Big Data project because the scientists and engineers who run the batch
storage arrays, server configuration, or how these components inside a data center all work in tandem to produce the desired results.Another
benefit has to do with costs
Instead, AWS Batch automatically allocates the exact compute resources you need for that project, and you pay only for the compute resources
This is true for every batch processing job including the concurrent jobs you might run.Not only does a company avoid the management chores
An example of this might be a massive genomic research project for drug discovery.A pharmaceutical might start out with basic needs for
batch processing using a minimal amount of storage, but normally as the project intensifies and the processing needs increase, the project
might stall out as the company coordinates the various services, such as storage, networking, endpoint security, or memory allocations
