Dynatrace announced at KubeCon that it is making its observability services applicable to OpenTelemetry. This includes Dynatrace’s AIOps and automation capabilities, including continuous discovery, proactive anomaly detection and optimisation over the full software lifecycle.
With these additional capabilities in OpenTelemetry, DevOps and SRE teams are better able to manage complex heterogeneous cloud environments and innovate faster, according to Dynatrace.
“Dynamic multicloud environments enable organizations to rapidly scale their digital capabilities but keeping up with the data they create is often manual and complicated, draining time from innovation”, the company said. “Dynatrace makes it easy to harness a broad set of observability data, including from the latest open-source standards. However, what really sets Dynatrace apart is that it also makes that data actionable, through its powerful AIOps and automation. This more intelligent approach enables Dynatrace to proactively show teams what the issues are, so they can focus on optimizing their service, rather than wasting time interrogating raw data and building dashboards.”
Neutral APIs for observability
OpenTelemetry is a collection of tools for observability. It is not dependent on specific vendors and therefore provides neutral APIs, SDKs and other tools to collect telemetry from cloud applications and the underlying infrastructure.
Dynatrace is one of the five largest contributors to the OpenTelemetry project. Splunk, Microsoft, Google and LightStep are also among the top contributors. The company thinks that with the further growth of OpenTelemetry, the project will serve as an additional data source that will further expand the scope of cloud observability.
Overview of data
According to Dynatrace, the risk of using OpenTelemetry is that the observability of multi-cloud environments will become more complex. Consolidating and analysing all this data, together with data from other sources, can be expensive, slow and difficult to manage. Dynatrace aims to solve this by collecting all observability data, including statistics, logs, traces, user experience data and the latest open source standards, such as OpenTelemetry. Then Dynatrace Smartscape automatically maps it all out. The Dynatrace AI engine, called Davis, constantly scans the environments for errors and anomalies and delivers insights ordered by the impact on the business.
Tip: Dynatrace improves AI-based observability of Kubernetes environments