Remove 2007 Remove Latency Remove Performance Remove Tuning
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InnoDB Performance Optimization Basics

Percona

This blog is in reference to our previous ones for ‘Innodb Performance Optimizations Basics’ 2007 and 2013. Although there have been many blogs about adjusting MySQL variables for better performance since then, I think this topic deserves a blog update since the last update was a decade ago, and MySQL 5.7

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DevOps automation: From event-driven automation to answer-driven automation [with causal AI]

Dynatrace

The evolution of DevOps automation Since the concept of DevOps emerged around 2007 and 2008 in response to pain points with Agile development, DevOps automation has been continuously evolving. For instance, in the case of poor performance, you can seamlessly toggle a feature flag and mitigate any detrimental effects.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. This architecture shift greatly reduced the processing latency and increased system resiliency. Video Inspection Service (VIS): This service takes a mezzanine as the input and performs various inspections.

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The Netflix Cosmos Platform

The Netflix TechBlog

It supports both high throughput services that consume hundreds of thousands of CPUs at a time, and latency-sensitive workloads where humans are waiting for the results of a computation. The first generation of this system went live with the streaming launch in 2007.

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Good Management Can Work Miracles

The Agile Manager

IT reward systems are also often based on individual performance tied to granular and highly focused statements of accomplishment. electing to continue to perform technical tasks), and also be highly unleveraged in a team (one manager to dozens of direct reports.) 6 “What we are is a high performance team.” August 2007.

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A Decade of Dynamo: Powering the next wave of high-performance, internet-scale applications

All Things Distributed

We were pushing the limits of what was a leading commercial database at the time and were unable to sustain the availability, scalability and performance needs that our growing Amazon business demanded. Performant – The service would need to be able to maintain consistent performance in the face of diverse customer workloads.

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