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Adopting AI to enhance efficiency and boost productivity is critical in a time of exploding data, cloud complexities, and disparate technologies. Dynatrace delivers AI-powered, data-driven insights and intelligent automation for cloud-native technologies including Azure.
As organizations adopt more cloud-native technologies, the risk—and consequences—of cyberattacks are also increasing. Through this integration, Dynatrace enriches data collected by Microsoft Sentinel to provide organizations with enhanced data insights in context of their full technology stack.
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My goal is always to deliver tangible bestpractices that can be implemented today, and that can help teams transform their organization to true software-centric, digital cloud-native businesses. Zeroing in on the current state of DevOps and autonomous cloud and advancing performance. Chef, Puppet, Ansible), or delivery tools (e.g.
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Perform serves yearly as the marquis Dynatrace event to unveil new announcements, learn about new uses and bestpractices, and meet with peers and partners alike. Learn more about Dynatrace and Microsoft in the whitepaper, Why modern, well-architected Azure clouds demand AI-powered observability.
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Let me walk you through how I have built my Dynatrace Performance Insights Dashboard showing SLIs split by Test Name as well as SLIs for the specific technology and infrastructure: Enriching your load testing scripts with meta data allows building test context specific SLI-dashboards in Dynatrace.
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For example, if the CMS is built on Microsoft’s.NET Framework, the front-end website would also be built on the same technology. Software Development Kits (SDKs) for various technologies, languages and platforms are available directly from the Headless vendor, an open-source initiative or a third-party. Free trials to try it out.
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