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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

The Machine Learning Platform (MLP) team at Netflix provides an entire ecosystem of tools around Metaflow , an open source machine learning infrastructure framework we started, to empower data scientists and machine learning practitioners to build and manage a variety of ML systems. For many of our applications, model explainability matters.

Systems 226
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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. For example, a Stanford University and UC Berkeley team noted in a research study that ChatGPT behavior deteriorates over time. Failure to provide timely and accurate answers erodes user trust, hinders adoption, and harms retention.

Cache 203
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Engineers want their alerting system to be realtime, reliable, and actionable. A few years ago, we were paged by our SRE team due to our Metrics Alerting System falling behind — critical application health alerts reached engineers 45 minutes late! In other words, false positives are bad but false negatives are the absolute worst!

Storage 288
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. Cache Hit Ratio The cache hit ratio represents the efficiency of cache usage.

Metrics 130
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Sustainable IT: Optimize your hybrid-cloud carbon footprint

Dynatrace

You might optimize your cooling system or move your data center to a colder region with reduced cooling demands. And while these examples were resolved by just asking a few questions, in many cases, the answers are more elusive, requiring real-time and historical drill-downs into the processes and dependencies specific to each host.

Cloud 207
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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Behind the scenes, a myriad of systems and services are involved in orchestrating the product experience. These backend systems are consistently being evolved and optimized to meet and exceed customer and product expectations. It provides a good read on the availability and latency ranges under different production conditions.

Traffic 339
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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. For example, optimizing resource utilization for greater scale and lower cost and driving insights to increase adoption of cloud-native serverless services.

AWS 245