Today at the Perform 2020 conference, Dynatrace announced the next generation of its Infrastructure Monitoring module in its all-in-one Software Intelligence Platform. The latest generation platform will include upgrades such as enhanced AI, expanded out-of-the-box observability and the ability to create custom metrics from log events. The company has also announced expanded support for Kubernetes with its explainable AI engine, Davis, now automatically ingesting additional Kubernetes events and metrics, enabling it to deliver precise answers in real time about performance issues and anomalies across the full stack of Kubernetes clusters, containers, and workloads.
Today at the Perform 2020 conference, Dynatrace announced the next generation of its Infrastructure Monitoring module in its all-in-one Software Intelligence Platform. The latest generation platform will include upgrades such as enhanced AI, expanded out-of-the-box observability and the ability to create custom metrics from log events. The company has also announced expanded support for Kubernetes with its explainable AI engine, Davis, now automatically ingesting additional Kubernetes events and metrics, enabling it to deliver precise answers in real time about performance issues and anomalies across the full stack of Kubernetes clusters, containers, and workloads.
Over the past few years, many companies have moved away from traditional data centers to some form of hybrid and/or multi-cloud approach. A majority of companies are also leveraging microservices. The above being the case, it is becoming more and more difficult to leverage existing monitoring tools. This leads many companies to develop their own tools that can introduce a slew of issues. Dynatrace has made enhancements to its Infrastructure Monitoring module to address the above.
New enhancements to the Dynatrace Infrastructure Monitoring module include:
- Extended out-of-the-box observability for cloud-native environments – Dynatrace now automatically ingests data from additional sources, including new AWS and Azure services, Kubernetes-native events, Prometheus OpenMetrics and Spring Micrometer metrics. This provides out-of-the-box, comprehensive observability at scale, plus more precise answers to enable faster problem resolution, improved productivity and rapid innovation in multi-cloud environments.
- Custom metrics and events from log monitoring – The Dynatrace platform can now create custom metrics and events based on log data so organizations can extend infrastructure observability to any application, script or process that writes to a log file. This facilitates tool consolidation and reduces the cost and effort involved in manual administration.
- Smarter infrastructure monitoring – The Dynatrace Davis AI engine now automatically provides thresholds and baselining algorithms for all infrastructure performance and reliability metrics, extending root-cause analysis and enabling organizations to easily scale infrastructure monitoring without manual configuration in dynamic cloud environments. As a result, organizations gain access to precise answers in real time, supporting faster innovation while ensuring infrastructure performance and availability.
Containers have really taken off in the last several years. Over two-thirds of organizations use some form of containers and we can only expect that number to grow. Kubernetes is a container orchestration system that has outpaced all the others and is by far the favorite. As Kubernetes become more omnipresent the ability to manage them or simply use a dashboard to see some metrics may become difficult. Piggy-backing on the above. Dynatrace has enhanced its platform to add further support to Kubernetes while making the full-stack observable and adding AI to the platform.
Key enhancements to the Dynatrace platform’s support for Kubernetes environments include:
- Precise, AI-powered answers – Davis has been enriched with the ability to ingest additional Kubernetes events and metrics, including state changes, workload changes and critical events across clusters, containers and run-times. As a result, Dynatrace better understands all dependencies and relationships across the entire Kubernetes stack, from clusters to containers, and the workloads running inside. This further enables Dynatrace to provide full-stack observability at scale, and deliver more precise, AI-powered answers to dramatically simplify Kubernetes roll-out and management.
- New cloud application and microservice analysis capabilities – With Dynatrace, organizations can now understand and optimize Kubernetes resource utilization, enabling administrators and application owners to identify and solve performance issues and improve business outcomes proactively.
- Extended automatic container instrumentation – Dynatrace now automatically discovers, instruments and maps heterogeneous container technologies within Kubernetes environments, including implementations based on Docker, CRI-O and containers. This makes it easy to deploy and manage even the largest containerized environments. New container resource usage analysis also provides broader coverage for the range of container run-times used by organizations.
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