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Enhancing Azure data analytics and Azure observability with Dynatrace Grail

Dynatrace

Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. Dynatrace recently announced the availability of its latest core innovations for customers running the Dynatrace® platform on Microsoft Azure, including Grail.

Azure 245
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Microsoft Azure Event Hubs

DZone

Introduction With big data streaming platform and event ingestion service Azure Event Hubs , millions of events can be received and processed in a single second. Any real-time analytics provider or batching/storage adaptor can transform and store data supplied to an event hub.

Azure 306
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Discover the power of the Dynatrace platform on Azure with Azure Native Dynatrace Service

Dynatrace

Dynatrace ® AutomationEngine features a no- and low-code toolset and leverages Davis ® AI to empower teams to create and extend customized, intelligent, and secure workflow automation across cloud ecosystems. For more details, see the blog post, Set up AI-powered observability for your Microsoft Azure cloud resources in just one click.

Azure 264
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Unlock the power of contextual log analytics

Dynatrace

DevOps teams operating, maintaining, and troubleshooting Azure, AWS, GCP, or other cloud environments are provided with an app focused on their daily routines and tasks. This is explained in detail in our blog post, Unlock log analytics: Seamless insights without writing queries.

Analytics 304
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Full visibility into your serverless applications with AI-powered Azure Functions monitoring (GA)

Dynatrace

x runtime versions of Azure Functions running in an Azure App Service plan. This gives you deep visibility into your code running in Azure Functions, and, as a result, an understanding of its impact on overall application performance and user experience. Azure Functions in a nutshell. Simplify error analytics.

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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. Driving this growth is the increasing adoption of hyperscale cloud providers (AWS, Azure, and GCP) and containerized microservices running on Kubernetes.

Analytics 264
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The keys to selecting a platform for end-to-end observability

Dynatrace

Clearly, continuing to depend on siloed systems, disjointed monitoring tools, and manual analytics is no longer sustainable. This enables proactive changes such as resource autoscaling, traffic shifting, or preventative rollbacks of bad code deployment ahead of time.