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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says.

Analytics 191
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 214
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Accelerate your cloud journey with Dynatrace observability for AWS S3 logs

Dynatrace

Logs complement metrics and enable automation Cloud practitioners agree that observability, security, and automation go hand in hand. Logs complement out-of-the-box metrics and enable automated actions for responding to availability, security, and other service events.

AWS 204
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Dynatrace PurePath 4 integrates OpenTelemetry and the latest cloud-native technologies and provides analytics and AI at scale

Dynatrace

The rapidly evolving digital landscape is one important factor in the acceleration of such transformations – microservices architectures, service mesh, Kubernetes, Functions as a Service (FaaS), and other technologies now enable teams to innovate much faster. New cloud-native technologies make observability more important than ever….

Analytics 159
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Dynatrace extends automatic and intelligent observability to cloud and Kubernetes logs for smarter automation at scale

Dynatrace

Every service and component exposes observability data (metrics, logs, and traces) that contains crucial information to drive digital businesses. To connect these siloes, and to make sense out of it requires massive manual efforts including code changes and maintenance, heavy integrations, or working with multiple analytics tools.

Cloud 261
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Flexible, scalable, self-service Kubernetes native observability now in General Availability

Dynatrace

From a cost perspective, internal customers waste valuable time sending tickets to operations teams asking for metrics, logs, and traces to be enabled. A team looking for metrics, traces, and logs no longer needs to file a ticket to get their app monitored in their own environments. This approach is costly and error prone.

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Dynatrace launches automatic end-to-end observability via traces for AWS Lambda (Preview program)

Dynatrace

Serverless functions extend applications to accelerate speed of innovation. Full integration with existing Dynatrace capabilities for AWS Lambda (for example, metric ingestion via AWS Cloud Watch). Fully integrated with existing Dynatrace capabilities for AWS Lambda, including metric ingestion via AWS Cloud Watch.

Lambda 300