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

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. This approach has a handful of benefits.

Traffic 339
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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. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Deployment: Cache To produce business value, all our Metaflow projects are deployed to work with other production systems. In other cases, it is more convenient to share the results via a low-latency API. A Streamlit app houses the visualization software and data aggregation logic.

Systems 226
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5.5 mm in 1.25 nanoseconds

Randon ASCII

The Xbox 360 CPU had three PowerPC cores and a 1 MB L2 cache and these features are clearly visible on the wafer. In the die picture to the right (which looks to be about 14 mm by 12 mm) you can see the regular pattern of small black rectangles in the bottom right corner – that’s the L2 cache. register files? arithmetic units?)

Cache 126
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MySQL Key Performance Indicators (KPI) With PMM

Percona

This includes metrics such as query execution time, the number of queries executed per second, and the utilization of query cache and adaptive hash index. query cache: Disable (query_cache_size: 0, query_cache_type:OFF) innodb_adaptive_hash_index: Check adaptive hash index usage to determine its efficiency.

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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

There is no way to model how much more traffic you can send to that system before it exceeds it’s SLA. Every opportunity for delay due to more work than the best case or more time waiting than the best case increases the latency and they all add up and create a long tail. Mu is the mean of each component, the latency.

Lambda 98
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. With traffic growth, a single leader node handling all request volume started becoming overloaded.

Cache 224