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

Dynatrace

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. Logs on Grail Log data is foundational for any IT analytics. Grail and DQL will give you new superpowers.”

Analytics 195
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Dynatrace PurePath 4 integrates OpenTelemetry and the latest cloud-native technologies and provides analytics and AI at scale

Dynatrace

PurePath unlocks precise and actionable analytics across the software lifecycle in heterogenous cloud-native environments. Dynatrace provides information on every request, through every single microservice or serverless function, seamlessly integrating OpenTelemetry, with powerful analytics, including: Out-of-the-box service hotspot analysis.

Analytics 161
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Unlock end-to-end observability insights with Dynatrace PurePath 4 seamless integration of OpenTracing for Java

Dynatrace

Dynatrace is fully committed to the OpenTelemetry community and to the seamless integration of OpenTelemetry data , including ingestion of custom metrics , into the Dynatrace open analytics platform. With Dynatrace OneAgent you also benefit from support for traffic routing and traffic control. Deep-code execution details.

Java 242
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Build and operate multicloud FaaS with enhanced, intelligent end-to-end observability

Dynatrace

For example, to handle traffic spikes and pay only for what they use. Scale automatically based on the demand and traffic patterns. With Davis AI exploratory analytics , Dynatrace gives you a helping hand to understand correlations between anomalies across all the telemetry. Such anomalies can be caused by function cold-starts.

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How digital experience monitoring helps deliver business observability

Dynatrace

STM generates traffic that replicates the typical path or behavior of a user on a network to measure performance for example, response times, availability, packet loss, latency, jitter, and other variables). How automatic and intelligent AIOps makes DEM and business observability possible.

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Kubernetes vs Docker: What’s the difference?

Dynatrace

This opens the door to auto-scalable applications, which effortlessly matches the demands of rapidly growing and varying user traffic. For a deeper look into how to gain end-to-end observability into Kubernetes environments, tune into the on-demand webinar Harness the Power of Kubernetes Observability. What is Docker? Networking.

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Dynatrace simplifies StatsD, Telegraf, and Prometheus observability with Davis AI

Dynatrace

Open-source metric sources automatically map to our Smartscape model for AI analytics. Stay tuned for an upcoming blog series where we’ll give you a more hands-on walkthrough of how to ingest any kind of data from StatsD, Telegraf, Prometheus, scripting languages, or our integrated REST API. Stay tuned.