INSUBCONTINENT EXCLUSIVE:
That’s particularly true when it comes to batch processing jobs for Big Data projects like genomic research, building an airplane and
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
It’s an extraordinary Big Data effort, but there are also time-to-market considerations and project timelines. Fortunately, with the
advent of cloud computing services, there isn’t the same restriction in terms of waiting for the compute resources to become free enough
to run batch processing jobs
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
end-user doesn’t need to configure any of those compute resources, AWS Batch helps simplify the entire Big Data endeavor, especially in
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
processing project are not necessarily experts in infrastructure or IT service management.They don’t need to know about memory
allocations, 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
When companies don’t have to manage and configure the compute environment for batch processing, they don’t have to take the time and
expense needed to make sure it is all up and running 24x7 and they don’t have to purchase any of the equipment
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
and costs of running an on-premise data center, but they don’t have to coordinate the various services needed for batch processing
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
There’s a cost savings in not having to manage those services, add them and maintain them, or making sure they are secure for all batch
