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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. These essential data points heavily influence both stability and efficiency within the system.

Metrics 130
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Interpreting A/B test results: false negatives and power

The Netflix TechBlog

Martin Tingley with Wenjing Zheng , Simon Ejdemyr , Stephanie Lane , and Colin McFarland This is the fourth post in a multi-part series on how Netflix uses A/B tests to inform decisions and continuously innovate on our products. Have a look at Part 1 (Decision Making at Netflix), Part 2 (What is an A/B Test?), Need to catch up?

Testing 202
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For your eyes only: improving Netflix video quality with neural networks

The Netflix TechBlog

While conventional video codecs remain prevalent, NN-based video encoding tools are flourishing and closing the performance gap in terms of compression efficiency. We employed an adaptive network design that is applicable to the wide variety of resolutions we use for encoding. How do we apply neural networks at scale efficiently?

Network 292
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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 243
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

Model observability provides visibility into resource consumption and operation costs, aiding in optimization and ensuring the most efficient use of available resources. For model explainability, they can implement custom regression tests, providing indicators of model reputation and behavior over time.

Cache 201
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Artificial Intelligence in Cloud Computing

Scalegrid

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Using AI for Enhanced Cloud Operations The integration of AI in cloud computing is enhancing operational efficiency in several ways.

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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.

Tuning 210