Dynatrace expands AI-powered observability for Kubernetes environments

Unified cloud native application and infrastructure observability improves cross-team collaboration and accelerates digital transformation.

  • 3 years ago Posted in
Dynatrace has extended its Software Intelligence Platform to provide AI-powered observability into the infrastructure layer of Kubernetes environments to include every container, pod, node, and cluster. This is the latest enhancement to Dynatrace®, which already provides automatic distributed tracing and deep code-level insights into applications and microservices running in Kubernetes.


The pressure to accelerate digital transformation has driven enterprises to increase their investment in cloud-native development using microservices and container architectures. According to a recent Cloud Native Computing Foundation survey, 84 percent of organizations are using containers in production, and 78 percent of these use Kubernetes as their preferred container management solution. Maintaining complete observability into applications and microservices, as well as the infrastructure they run on, is critical to ensure the performance and availability of complex and distributed Kubernetes environments. Bringing infrastructure, application, and site reliability engineering (SRE) teams together, with everyone using the same data, makes it faster and easier to optimize applications and infrastructure, resolve issues, and accelerate successful digital transformations.


“Our application team already relies on Dynatrace for AI-powered observability into the applications and microservices running in our Kubernetes environment,” said Manfred Immitzer, Managing Director and Chief Digital Officer from Porsche Informatik. “Now, our infrastructure team can use Dynatrace to optimize Kubernetes infrastructure with the same level of advanced observability into every container, pod, cluster, and node. The Dynatrace AI engine drives collaboration across our infrastructure and DevOps teams, prioritizing any anomalies it discovers, helping us resolve problems fast, and freeing up more time for us to deliver new innovation and customer experience improvements that drive our business forward.”


With this release, Dynatrace® customers can instantly understand the availability, health, and resource utilization of Kubernetes infrastructure. Because Kubernetes is highly dynamic, Dynatrace continuously discovers all infrastructure components, microservices, and interdependencies between entities to create and maintain a precise, real-time topology map. Dynatrace’s AI engine, Davis™, uses this map to automatically identify and prioritize anomalies, and as needed, enable automatic remediation.


“Dynatrace has always provided the deepest observability for applications and microservices running in Kubernetes,” said Steve Tack, SVP of Product Management, Dynatrace. “We’re now bringing this same AI-powered advanced observability to all layers of Kubernetes infrastructure. Dynatrace gives teams the benefits of an all-in-one platform, with distributed tracing and code-level detail for all Kubernetes apps and microservices, and infrastructure insights, including availability, health, and utilization, across every microservice, container, pod, node, and cluster. As a result, they can build and deploy cloud-native apps and continuously improve customer experiences with greater speed and confidence.” 

One year on from the launch of Chat GPT, new data from Slack based on 10,000 global workers (including 1,000 the UK) reveals that UK companies believe there is greater urgency to adopt Generative AI at work than US companies - yet uptake remains cautious in both markets.
IBM and Meta launch the AI Alliance
Ethics, Bias and Regulatory concerns slowing European adoption.
Market research shows more than 46% of European organisations say AI has already made an impact on smart video capabilities and will only continue to drive business optimization.
High workloads are preventing people from finding time to upskill, according to 44% of UK IT managers surveyed.
Companies are racing to operationalize generative AI, but many haven’t addressed how AI-driven disruption will impact employees — who are torn between AI optimism and anxiety.
49% of senior decision makers have low confidence in implementing the technology.
80% of organisations surveyed see great significance in technology’s role to achieve their goals with AI’s predictive analytics offering significant business opportunity.