Dynatrace's open AI engine, Davis, now ingests platform service information from Microsoft Azure Monitor to simplify cloud operations and speed new workloads to the Azure cloud.
By combining Azure metrics with the rich user experience, application and cloud infrastructure data Dynatrace already captures, Davis can identify degradations and user/service impacting issues faster. This capability then enables precise root cause for rapid recovery. Additionally, new out-of-the-box dashboards give BizDevOps teams special, customized views against the same rich data-set, empowering teamwork and accelerating digital team success.
“Dynatrace was purpose-built to deal with the complexity and dynamic nature of the enterprise cloud,” explains Steve Tack, SVP of Product Management at Dynatrace. “With an open AI-engine built-in at the core of our platform, we continue to natively support the most important cloud technologies, so that Davis grows continually smarter and more specific to customers’ hybrid environments. This makes Dynatrace’s precise, causation-based answers even more powerful than alternative approaches, which require time consuming learning and leverage simple time-based correlation resulting in lots of extra work for little or no gain.”
The ingestion of Azure Monitor data into the Dynatrace AI engine provides actionable and precise insights that are tuned specifically to the Azure environment. By providing a set of out-of-the box dashboards specific to the Azure environment, customers gain more value faster, with less effort than ever before.
For most customers, Azure is just one of the many cloud services used to support microservices workloads. Out-of-the-box, Davis and the Dynatrace platform will automatically discover, learn and monitor the entire environment – whether companies are using Azure, AWS, Google Cloud Platform, or PaaS and orchestration environments from Pivotal, Red Hat and Kubernetes. Automatic, AI-powered support for these increasingly common multi-cloud environments is essential for effective workload management, optimization and success.
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