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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. Data analysis : how to process, aggregate and query observability data from serverless functions effectively, accurately, and comprehensively?

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

Dynatrace

PurePath 4 supports serverless computing out-of-the-box, including Kubernetes services from Amazon Web Services (AWS) , Microsoft Azure , and Google Cloud Platform (GCP). FaaS like AWS Lambda and Azure Functions are seamlessly integrated with no code changes. Waterfall visualization of all requests.

Analytics 159
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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. All log streams from pods in Kubernetes environments.

Cloud 261
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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.” Throw in behavioral analytics, metadata, and real-user data. … But it is also about process automation.

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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 251
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. Let’s walk through the top use cases for Greenplum: Analytics.

Big Data 321