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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. Enable faster development and deployment cycles by abstracting away the infrastructure complexity.

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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. … It is about the collection of all of those together.”

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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. AI-powered answers and additional context for apps and infrastructure, at scale.

Cloud 260
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Data dependencies and framework intricacies require observing the lifecycle of an AI-powered application end to end, from infrastructure and model performance to semantic caches and workflow orchestration. Estimates show that NVIDIA, a semiconductor manufacturer, could release 1.5 million AI server units annually by 2027, consuming 75.4+

Cache 206
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Artificial Intelligence in Cloud Computing

Scalegrid

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making. Key among these trends is the emphasis on security and intelligent analytics.

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Mastering Hybrid Cloud Strategy

Scalegrid

Key Takeaways A hybrid cloud platform combines private and public cloud providers with on-premises infrastructure to create a flexible, secure, cost-effective IT environment that supports scalability, innovation, and rapid market response. The architecture usually integrates several private, public, and on-premises infrastructures.

Strategy 130