Dynatrace Unveils Data Observability Solutions

Dynatrace Unveils

Dynatrace Data Observability works with other core Dynatrace platform technologies like Davis hypermodal AI, and generative AI capabilities.

Dynatrace, a unified observability and security platform, announced new AI-powered data observability capabilities for its analytics and automation platform. With Dynatrace Data Observability, teams can confidently rely on all observability, security, and business events data in Dynatrace to fuel the platform’s Davis AI engine to help eliminate false positives and deliver trustworthy business analytics and reliable automation.

Dynatrace Data Observability enables business analytics, data science, DevOps, SRE, security, and other teams to help ensure all data in the Dynatrace platform is high quality. This complements the platform’s existing data cleansing and enrichment capabilities provided by Dynatrace OneAgent to help ensure high quality for data collected via other external sources, including open source standards, such as OpenTelemetry, and custom instrumentation, such as logs and Dynatrace APIs. It enables teams to track the freshness, volume, distribution, schema, lineage, and availability of these externally sourced data, thereby reducing or eliminating the need for additional data cleansing tools.

Kulvir Gahunia, Director, Site Reliability Office at TELUS, said, “Dynatrace, with its OneAgent technology, provides us with a high level of confidence that the data powering our analytics and automation is healthy. The platform is also very flexible, which enables us to tap into custom data sources and open standards, like OpenTelemetry. New Dynatrace data observability capabilities will help ensure the data from these custom sources is also high-quality fuel for our analytics and automation. This will save us from having to cleanse the data manually and reduce the need for additional data cleansing tools.”

High-quality data is critical for organisations that rely on it to inform business and product strategies, optimize and automate processes, and drive continuous improvements. However, the scale and complexity of data from modern cloud ecosystems, combined with the increased use of open-source solutions, open APIs, and other customized instrumentation, make it hard to achieve this goal. Dynatrace Data Observability works with other core Dynatrace platform technologies, including Davis hypermodal AI, combining predictive, causal, and generative AI capabilities.