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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 179
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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 294
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The top four log analytics and log management best practices

Dynatrace

By following key log analytics and log management best practices, teams can get more business value from their data. Challenges driving the need for log analytics and log management best practices As organizations undergo digital transformation and adopt more cloud computing techniques, data volume is proliferating.

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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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What is Azure Functions?

Dynatrace

What is Azure Functions? Similar to AWS Lambda , Azure Functions is a serverless compute service by Microsoft that can run code in response to predetermined events or conditions (triggers), such as an order arriving on an IoT system, or a specific queue receiving a new message. The growth of Azure cloud computing.

Azure 137
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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 209
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Dynatrace OpenPipeline: Stream processing data ingestion converges observability, security, and business data at massive scale for analytics and automation in context

Dynatrace

By putting data in context, OpenPipeline enables the Dynatrace platform to deliver AI-driven insights, analytics, and automation for customers across observability, security, software lifecycle, and business domains. This “data in context” feeds Davis® AI, the Dynatrace hypermodal AI , and enables schema-less and index-free analytics.

Analytics 194