What’s the purpose of a service level agreement (SLA)? Ideally, SLAs provide a framework for ideal performance—a way to determine if actions are completed and timelines are met. But for many companies, SLAs that govern everything from order validation to supply chain monitoring and customer service can start to feel like tiny isolated nations each with their own citizenry of apps.
Missing the Mark
The biggest problem with SLAs? In most cases, objectives aren’t achieved. Consider a recent article from Cloud Tech, detailing a new study from CDW. According to its “Cloud 401” report, 76 percent of organizations surveyed said their cloud vendor failed to meet SLA targets, everything from guaranteed uptime to cost and integration promises. And failing to meet these promises—even if the cause is beyond your control—may raise customer ire and convince them to start looking elsewhere.
So what’s the problem? Why can’t companies define SLAs that are reasonable and attainable? The biggest issue lies with application sprawl. It starts with a single app designed to solve specific problems within an enterprise. But no app can do everything, and so another is added to solve new issues that emerge as the company grows. New servers, new employees, and a growing consumer base prompt the deployment of even more applications, each with their own set of metrics and a unique SLA.
The result? Visibility is quickly lost as borders between these apps harden and their ability to easily integrate and interact with legacy systems starts to fail. Employees are frustrated because they can’t find the information they need when they need it, and customers are upset as service begins to slow—exactly what companies want to avoid.
So what’s the solution? Consider the multi-step processes of a highly regulated industry like insurance. For new policies to be issued or claims to be processed, sensitive customer information must be accessed by multiple apps. If any of these apps fail to meet SLA targets, however, applications or claims could be stuck in limbo until customers call to complain. If data moving from an approval program to a policy builder program to a final cost estimate app experienced difficulty at any point in the process, IT would be stuck trying to find the communications disconnect rather than simply fixing the problem.
The answer is a kind of “universal translator” able to speak the language of any given app by using specific states to determine if workflow has been impaired. State machines track the progress of any entity across the entire lifecycle, moving from one state to another based on new events, new data, a change in property, or after a certain amount of time. What’s more, these tools integrate and monitor SLAs to determine if targets are being met.
Service-level agreements across multiple apps are necessary to ensure performance, but often have the opposite effect when they encounter app borders. State machines cross the lines and provide access to true, real-time visibility.
Curious? Learn more about how event processing with state machines can empower your operational decision-making and action in real-time.