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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. This creates latency when they need to restart.

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Understanding What Kubernetes Is Used For: The Key to Cloud-Native Efficiency

Percona

It simplifies infrastructure management and is the driving force behind many cloud-native applications and services. For some background, Kubernetes was created by Google and is currently maintained by the Cloud Native Computing Foundation (CNCF). It has become the industry standard for cloud-native container orchestration.

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Optimizing your Kubernetes clusters without breaking the bank

Dynatrace

Its ability to densely schedule containers into the underlying machines translates to low infrastructure costs. To illustrate how Akamas approach works for Kubernetes microservices applications the webinar, the example of Google Online Boutique is used during the webinar. below 500ms) and error rates (e.g. lower than 2%.).

Latency 192
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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.

AWS 236
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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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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 196
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Site reliability engineering: 5 things you need to know

Dynatrace

Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. ” According to Google, “SRE is what you get when you treat operations as a software problem.”