Dynatrace Advances Application Environments as Code

Dynatrace, at its online Perform 2022 event, launched a batch of updates to its portfolio that make it easier for DevOps teams to programmatically embed observability and other software intelligence capabilities within applications.

At the same time, Dynatrace also revealed that it has extended the reach of its observability platform to now include all the major serverless computing platforms.

Additionally, the company extended its existing Application Security Module to provide the ability to detect vulnerabilities and block attacks against application runtimes in real-time using the framework defined by the Open Web Application Security Project (OWASP). That module is based on Dynatrace Smartscape topology software and a Davis artificial intelligence (AI) engine to provide real-time visibility into IT environments that enables DevSecOps teams to better prioritize which vulnerabilities to remediate first based on their intensity.

Dynatrace CEO Rick McConnell told conference attendees that all these capabilities are enabled by agent software that can be programmatically embedded within applications as code using application programming interfaces (APIs) and templates to automatically surface software intelligence. Rather than having to deploy multiple agents, McConnell said, IT teams can deploy a single agent to drive a wide range of analytics.

That capability makes it easier for IT organizations to achieve service level objectives (SLOs) for performance, quality, and security at a time when more responsibility for the management of applications is shifting left toward developers, he added.

It’s not quite clear how far responsibility for the management of applications after they are shifting left toward developers. It tends to vary widely by organization. The one thing that is certain is more applications are being instrumented. Adoption of application performance management (APM) platforms was previously limited by cost concerns and the challenges associated with embedding agent software in applications. As it becomes easier to instrument applications the data that can be collected and analyzed from logs, metrics and traces are now greater. As such, APM platforms are now being positioned as observability that platforms can correlate analytics collected from applications and the underlying infrastructure upon which they depend.

Much of that need for greater instrumentation is being driven by digital business transformation initiatives, noted McConnell. Many of those applications are being constructed using microservices that have dependencies on each other. A single agent makes it easier for IT teams to instrument cloud-native application environments, he noted.

There is no shortage of options when it comes to instrumenting and observing applications. The issue now is turning all the data being collected into actionable intelligence. As a result, observability platforms are being imbued with AI engines that make it possible to analyze massive amounts of data. Armed with those insights, it then becomes possible for an existing IT team to manage a much more complex IT environment at scale. In fact, it’s now no longer a question of whether AI engines will be injected into DevOps workflows as much as it is to what degree.

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