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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

VMware commercialized the idea of virtual machines, and cloud providers embraced the same concept with services like Amazon EC2, Google Compute, and Azure virtual machines. In a serverless architecture, applications are distributed to meet demand and scale requirements efficiently. Creating a prototype (for example, on Azure ).

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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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Implementing AWS well-architected pillars with automated workflows

Dynatrace

This is a set of best practices and guidelines that help you design and operate reliable, secure, efficient, cost-effective, and sustainable systems in the cloud. The framework comprises six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and Sustainability.

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Driving your FinOps strategy with observability best practices

Dynatrace

In a Dynatrace Perform 2024 session, Kristof Renders, director of innovation services, discussed how a stronger FinOps strategy coupled with observability can make a significant difference in helping teams to keep spiraling infrastructure costs under control and manage cloud spending. ” But Dynatrace goes further.

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What is container as a service? How CaaS compares to PaaS, IaaS, and FaaS

Dynatrace

The containerization craze has continued for enterprises, with benefits such as portability, efficiency, and scalability. Managed orchestration uses solutions such as Kubernetes or Azure Service Fabric to provide greater container control and customization. million in 2020. Managed orchestration. Serverless container services.

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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+

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OpenShift vs. Kubernetes: Understanding the differences

Dynatrace

Container orchestration allows an organization to digitally transform at a rapid clip without getting bogged down by slow, siloed development, difficult scaling, and high costs associated with optimizing application infrastructure. Like Kubernetes, it allocates resources efficiently and ensures high availability and fault tolerance.