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Bringing Observability and Actionable Insights to FinServ Business Services

Bringing observability and actionable insights to FinServ business services
3 minute read
Greg Bukowski

When you’re in the hotly competitive and highly regulated finance industry, you can’t afford to take chances with the execution of your business services. Consider the end-of-day financial close process, for example. To ensure that your records are in order and that your systems will be ready for business the next morning, you’ve got to complete hundreds of intertwined workflows within a short window of time. Missing that deadline can impair service quality and put your firm at risk for significant fines.

New challenges will be posed by new industry regulation programs, such as the introduction of the FedNowSM Service, a program under development by the U.S. Federal Reserve enabling financial institutions to provide real-time, instant payment services around the clock. While the service is certainly beneficial to businesses and consumers, the new workflows and processes associated with FedNow will only increase the volume and complexity of daily IT operations—and introduce new opportunities for things to go wrong.

In the age of big data, it’s also critical to ensure that business users can access the business insights they need to make optimal decisions. As agile FinTech startups bring a new generation of digital services to market, firms need to be sure that their technology operations won’t fall short of the demands of their strategy.

As microservices transform business workflows and interdependencies increase across business services, it becomes more and more critical for financial services firms to focus on operations management. When a job fails to execute correctly, it’s not enough to simply restart it and move on—you need to understand exactly what went wrong, and why, to ensure that it doesn’t happen again. To ensure resilient service delivery, IT operations teams need visibility into the various workloads running in the environment, and actionable insights to ensure that they will have the right resources at the right time to complete accurately, reliably, and on time.

Getting visibility into after-hours workloads

Most financial services organizations already rely on workload automation to ensure that real-time workflows and processes are meeting those benchmarks, and in a fully auditable manner. If something goes wrong—if the runtime of a job is unusually long or short, or it fails to run at the right frequency—the service owner can quickly identify the abnormality and take action to ensure that the job is completed before service delivery is affected. However, there’s more to availability and performance management than ensuring successful workload execution during business hours. Financial services firms are running workloads around the clock, every day of the year, from financial processing, to bookkeeping, to analytics, to reporting, and their timely completion can be just as important to avoid regulatory fines, financial impact, or business impact.

When a workflow fails to execute correctly, there may be any number of issues at play in the environment: multiple business services competing for memory, storage, or CPU; a cluster that isn’t running; or a failure somewhere on-premises or in the cloud. Restarting the job may solve the immediate service delivery problem, but if you don’t address the underlying cause, the problem is likely to reoccur. And each time it occurs, the firm faces risks that range from impaired service availability and customer satisfaction, to interruptions in trading and transactions, to regulatory fines and increased business costs.

To manage performance and availability, ensure resilient service for customers, and control costs, IT operations needs visibility into all the microservices, business services, technology services, and business automation workloads running in the environment.

Delivering actionable insights at the nexus of development and operations

When operations teams have visibility into the workload automation platform, they can understand when and why the workloads that drive business services are experiencing issues, then deliver that actionable insight to developers and service owners to fix the problem for the future. In that sense, marrying operations management to digital business automation is similar to the convergence seen in DevOps and site reliability engineering (SRE): bridging gaps and breaking silos with shared visibility across the complete service lifecycle.

Operational observability and actionable insights are essential elements of the evolution to an Autonomous Digital Enterprise (ADE). As firms adopt principles and practices such as DevOps, SRE, automation-everywhere, and everything-as-code, they need tools for visibility and understanding at the microservices level to ensure resilient services for their customers. By understanding the underlying causes of workflow disruptions and then taking effective action to resolve them, they can ensure higher quality for existing services while gaining confidence to move forward with new strategies and market opportunities, from data-driven analytics, to new payment services like FedNow, to new digital service offerings designed to compete with disruptive FinTech startups.

Additional resources

Explore how financial services organizations are moving to becoming Autonomous Digital Enterprise (ADE)

Learn how becoming an Autonomous Digital Enterprise will ensure success and resilience and, using emerging tools that support Automation Everywhere and Enterprise DevOps, will unlock those goals.

These postings are my own and do not necessarily represent BMC's position, strategies, or opinion.

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About the author

Greg Bukowski

Greg Bukowski, Strategic CTO, helps customers understand how BMC’s technology solutions drive their business initiatives. Greg began his career as a Java architect and business analyst at Northern Trust, and then continued at Solstice and HomeDirectUSA before joining BMC Software in 2010. He has held positions as technology solutions director and advisory architect, and specializes in cloud computing, runbook and datacenter automation, APM, application discovery and resiliency, and DevOps. Greg received his BS in computer engineering at University of Notre Dame and is an AWS Certified Solutions Architect.