A look at some key requirements for retaining unified, holistic visibility of workload automation while contending with an expanding cloud footprint.
The implementation of workload automation took hold in enterprises over the course of decades. In the process, the number of tools and implementations began to grow, including in areas like ERP, batch processing, and more.
Without central control and visibility, administrators saw that they were contending with islands of automation, which led to spiraling complexity and inefficiency and increased risk of missed SLAs. For these reasons, the most successful organizations started to employ workload automation tools, so they could gain control of the traditionally siloed schedulers being used.
Cloud adoption poses new yet familiar challenges
Many companies are now consuming services from multiple cloud vendors, and the number of service providers, platforms, services, and workloads is poised for even more rapid proliferation. While these cloud solutions provide speed and agility, there often isn’t any kind of plan for how these new services will be managed after they are in operation.
With so many disparate apps and services running across multiple cloud provider environments, operations organizations encounter a number of challenges. Just as in past years, groups have to contend with islands of automation. Each cloud has its own unique technology and a way to integrate, which means administrators need deep technical expertise in each domain.
Given these underlying differences, operators, and architects cannot easily migrate services between different environments. Further, visibility is being fragmented by point cloud solutions. Consequently, these distinct cloud workload deployments threaten to disrupt the holistic visibility that IT operations groups have worked so hard to attain in recent years. This leaves organizations exposed to a number of negative ramifications:
- Increased risk. Lacking the unified visibility they need, administrators spend too much time triaging and troubleshooting individual workload automation failures and errors and not focusing on the end-to-end business process. And, with limited ability to conduct audits centrally, the business is faced with compliance risk.
- Reduced speed. Groups lack the integrations needed to adopt new services. This means they run the risk of going back to contending with the inefficiency of automation islands. This slows their delivery of new services and capabilities.
- Suboptimal service delivery. The lack of visibility and interconnection of processing means service delivery is more challenging, and more weak spots are found late in the process, causing more late deliveries, SLA breaches, fines – and worse, the loss of customers.
Ultimately, these issues result in organizations’ digital transformations being stifled.
See also: Why Automation Success Hinges on Effective Process Discovery
Workload automation solution requirements to tame digital transformation chaos
To combat these challenges, groups need intelligent enterprise automation platforms that address the following key requirements.
Unified automation observability
Operators need a unified view of hybrid workloads. They require solutions that provide a single, centralized view of automation tools and processes, including those that span multiple cloud and legacy environments. With this visibility, operators can more quickly identify the root cause of failures and more rapidly triage and resolve issues. In addition, IT operations leaders need advanced SLA management capabilities so they can better predict potential breaches and boost SLA compliance.
Multi-cloud orchestration
IT Ops teams, enterprise architects, and developers all need to employ a single platform that can orchestrate hybrid cloud workload technologies, so they can realize significantly simplified business processes. They must be able to leverage advanced workflow orchestration capabilities, so they can achieve the following objectives:
- Automate and integrate complex workloads, workflows, and business processes.
- Employ orchestration across automation platforms, ERP systems, and more.
- Leverage advanced scheduling capabilities for workloads in mainframes, distributed systems, and cloud platforms.
- Orchestrate disparate data pipelines, enabling more efficient, repeatable processes.
Automation intelligence
With advanced workload orchestration solutions, groups can more intelligently model, optimize, and predict cloud workloads, so they can boost staff and operational efficiency. Robust solutions promote workload optimization capabilities. By harnessing historical data and analytics, operators can improve batch cycle times and optimize resource utilization.
In addition, operators must have solutions that enable advanced change modeling capabilities, so they can simulate changes and identify and address potential issues before new services are implemented.
Finally, the right solution must provide business process visualization. With greater contextual intelligence around business processes, operators can manage automation more intelligently and better ensure the availability and performance of critical business services.
Automation benefits
By leveraging advanced enterprise workload automation solutions, IT operations organizations can realize several advantages:
- Reduce risk by gaining the actionable insights needed to improve automation outcomes.
- Speed delivery of new services by seamlessly connecting data and processes across all the hybrid cloud components business services rely upon.
- Optimize service delivery by leveraging the business insights needed to improve workload modeling and predictability.
With the right workload observability and orchestration solution, organizations can take advantage of cloud services and continue their digital transformation journey without establishing automation islands that sap productivity, visibility, and control.
