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

Dynatrace

These functions are executed by a serverless platform or provider (such as AWS Lambda, Azure Functions or Google Cloud Functions) that manages the underlying infrastructure, scaling and billing. Observability is typically achieved by collecting three types of data from a system, metrics, logs and traces.

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What is observability? Not just logs, metrics and traces

Dynatrace

In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. If you’ve read about observability, you likely know that collecting the measurements of logs, metrics, and distributed traces are the three key pillars to achieving success.

Metrics 363
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Dynatrace extends automatic and intelligent observability to cloud and Kubernetes logs for smarter automation at scale

Dynatrace

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news.

Cloud 259
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Dynatrace PurePath 4 integrates OpenTelemetry and the latest cloud-native technologies and provides analytics and AI at scale

Dynatrace

The seamless integration enables enrichment of your OpenTelemetry metrics and traces with insights from the Dynatrace Software Intelligence Platform. PurePath 4 supports serverless computing out-of-the-box, including Kubernetes services from Amazon Web Services (AWS) , Microsoft Azure , and Google Cloud Platform (GCP).

Analytics 156
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Implementing AWS well-architected pillars with automated workflows

Dynatrace

And how can you verify this performance consistently across a multicloud environment that also uses Microsoft Azure and Google Cloud Platform frameworks? This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem.

AWS 246
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Modern observability is no longer optional on the path to digital transformation

Dynatrace

That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization. You have to get automation and analytical capabilities.” We start with data types—logs, metrics, traces, routes. You have to look at them collectively,” McConnell said.