Full stack performance management, powered by artificial intelligence (Dynatrace SaaS and Managed were developed under the name Dynatrace Ruxit)
Within the Dynatrace platform, Dynatrace SaaS and Managed was built for cloud-based applications and microservices architectures as these highly dynamic application environments require a new approach to monitoring.
Dynatrace SaaS and Managed is the most efficient way to monitor web-scale applications:
“After deploying a new release, we spent over 30 hours trying to find a performance problem. Once we found the issue, it only took us 30 minutes to fix it. With Dynatrace application performance monitoring, finding a similar problem would only take us minutes to identify, saving us precious time and resources.”
As a web application developer, there are a few key questions you need to answer before selecting a 3rd party library. Before deciding on a library you want to know what the performance impact of the new library will be on your application, whether or not the library will be compliant with your existing standards, […]The post Simplified agentless real user monitoring setup appeared first on Dynatrace blog – monitoring redefined.
Dynatrace automatically detects and displays lots of metadata values related to the processes that run in your environment—including version numbers, port numbers, and the name of the script or JAR file that launches each process. Dynatrace also enables you to uses these metadata values to automate tagging as well as use environment variables to supply tags. The […]The post Define your own process group properties via environment variables and Kubernetes annotations appeared first on Dynatrace blog – monitoring redefined.
Dynatrace has provided topological queue support for over two years now. This has enabled Dynatrace to show you which requests in your environment communicate with which queues. It also enables topographical modeling of your queue-based service communications. Many metrics for queueing systems like ActiveMQ and RabbitMQ are also available. We’re now releasing major enhancements to our queuing support. We’re […]The post End-to-end request tracing across JMS and RabbitMQ queues appeared first on Dynatrace blog – monitoring redefined.
Dynatrace recently introduced the ability to capture Java method arguments and use them as request attributes. This valuable new service-monitoring feature enables fine-grain service filtering and performance analysis. By defining request attributes for your service’s requests, you can enable advanced filtering of service requests across all Dynatrace analysis views. Once configured, request attributes help you to […]The post Request attributes: Support for .NET method argument capture appeared first on Dynatrace blog – monitoring redefined.
Dynatrace Service flow is very useful for understanding what your services and requests are calling across your service landscape. To date, Service flow has only shown which services are called. We’ve now extended Service flow to reflect an important dimension: your underlying infrastructure, including hosts, processes, and load balancers. Load balancers and proxies For some time now, […]The post Easily understand which load balancers, processes, & hosts are part of your service flow appeared first on Dynatrace blog – monitoring redefined.
One of the big advantages of Dynatrace is its full-stack approach to monitoring. Dynatrace monitoring enables you to analyze how backend problems affect the customer experience your customers. Dynatrace OneAgent for Android and iOS injects an HTTP header into each request that’s sent by your mobile app. OneAgent—which runs on the backend—picks up this header […]The post Analyze the impact of backend services on your Android and iOS apps appeared first on Dynatrace blog – monitoring redefined.