Fact Sheets

2 ©2018 Dynatrace Microservices demand better monitoring Cloud-based applications rely on microservices for their significant business benefits, including accelerated application development, compartmentalized code streams, and independently scalable services. Industry analysts, such as Gartner in their blog "Microservices: Building Services with the Guts on the Outside," note that while microservices simplify an application environment, their complexity makes monitoring core to an implementation's success. The decoupled nature of services and applications in Red Hat® OpenShift environments require a more sophisticated application performance monitoring approach. Dynatrace addresses this need with their all-in-one, fully automated, Red Hat OpenShift monitoring solution that allows you to quickly and easily gain insight into the health of your applications and environment. Together, Dynatrace and Red Hat are redefining the way microservice environments are managed and monitored. Find the proverbial needle in the haystack It is impossible for humans to manually manage and troubleshoot such highly dynamic and distributed environments, where systems are composed of hundreds, if not thousands, of microservices. A simple alerting system would be of little help. Dynatrace employs artificial intelligence (AI) to inspect a system in real time, automatically discovering, baselining, and analyzing the architecture to understand the root cause of a problem and analyze the impact to your business. • Dynatrace uses automated machine learning to provide comprehensive visibility into all components quickly and easily. Its unique capabilities include: • Auto-discovery. Dynatrace Smartscape® technology automatically detects and displays all the components and dependencies that comprise your environment, providing you with a real-time blueprint of your application architecture. • Auto-baselining. Dynatrace uses AI to understand the difference between desirable and unwanted behaviors emerging from each component. It can also dive deep into the code to uncover methods being invoked and how they contribute to the overall performance of the system. • Auto-problem analysis. Dynatrace rapidly identifies failures, component involvement, and root causes. Machine learning helps evaluate issues, determine if it warrants an alert, and provide valuable insights for better business decisions. Dynatrace is the best tool for monitoring our fully dockerized application stack. Out of the box, Dynatrace offered deep insights into our hosts, docker containers, and the services they provide." — Axel Springer, Ideas Engineering GmbH Figure 1. Dynatrace Smartscape view of a complex microservices environment. Multiple failures are in red, but the display also confirms that system redundancies prevented any end-user impact

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