Rationalisation of business processes is vital to workload automation. Alongside its close cousin, job scheduling, both are software tools to schedule, start, and administer jobs related to business transactions and processes.
Workload automation can support multiple business applications and workflows within an organisation. It is, in many ways, a successor to job scheduling as its tries to cover the automation of entire systems within heterogeneous server infrastructure.
The components of a workload automation tool may comprise a scheduler, applications server, agents, database and a workload control centre.
The application server and scheduler store data about jobs on a database. This also contains details of schedules that need to be run on different agents. The scheduler connects to the database periodically to find any scheduled events and sends commands to agents to carry out those actions. The agents run the job after receiving the message and then sends a status update to the application server, which then updates the status on the database and sends another command back to the agent to mark the job as done.
These processes can be controlled and monitored via a web interface called a Workload Control Centre or a command line interface.
Workload automation has become increasingly popular among businesses as they deploy complex systems, such as enterprise resource planning (ERP) and supply chain management (SCM).
Workload automation use cases
There are a number of use cases where workload automation can be involved to good effect.
Retail: Point of sales systems can automatically feed sales data into an audit system on a daily basis. This can then be pushed through to both a general ledge system and a pricing system. The latter can automatically update retail pricing. Audited sales figures can be automatically emailed as reports to an executive's inbox.
Big data: With massive amounts of data coming into the business, workload automation can be used to efficiently process that all that data. Unstructured and structured data to be moved through a file transfer application, stored in Hadoop, and then extracted, transformed, and uploaded to a user dashboard via a business intelligence platform. Automation eases the movement of data across various systems, eradicating latency between jobs.
Optimising cloud utilisation: While there are many benefits of cloud, organisations still need to manage and monitor virtual and cloud resources. Automation can improve cloud resource utilisation with automatic provisioning and de-provisioning of virtualised and cloud systems.
Accounting: Formatting accounts statements and managing submissions of data can be made much easier with workload automation. Automated communication also means that relevant people can be notified as soon as documents are ready.
Benefits of workload automation
Workload automation can bring many benefits to organisations.
Productivity: There are greater demands on infrastructure with users creating more production batch jobs. Workload automation can execute scheduled jobs accurately and in the right sequence, reduce operator errors.
Efficiency: Manual operations will always take significantly more time than automated systems. By implementing workload automation for routine tasks, staff can be freed up to do higher-value tasks.
Availability: With a hard disk crash, data loss can be a serious problem. Workload automation can be used to automate disaster recovery to protect against data loss and other human error.
Reliability: Workload automation removes human error and thus removes most batch processing errors. Automation ensures that jobs are not forgotten, or run out of sequence. It can ensure that data is entered correctly and successfully completed.
The future of workload automation
Presently, we are seeing only the tip of the iceberg. As workload automation continues to incorporate new platforms and applications, it will future-proof more business processes.
Surveys show that workload automation is at the centre of future IT initiatives, spanning cloud, virtual, and big data. With IT decision makers becoming more aware of the benefits, adoption is on an upward trajectory. And as workload automation is constantly on the lookout for the latest technology to adapt to, several exciting trends are emerging.
Future software will be increasingly built on a singular automation platform, breaking down the silos of automation existing within enterprises today. Tools will work in unison, encouraging collaboration and advancing the capabilities of a DevOps strategy. A single pane, offering a view of all the automation processes across an enterprise, also simplifies the interface for end-users, and allows enterprises to have a consistent view of their automation requirements and processes.
Over the next few years, one can also expect workload automation to further integrate with hypervisors. Recent studies have found that such integration allows for smoother movement of workloads, with many IT decision makers reporting their intention to capitalise on it when the technology becomes more readily available.
