Architecture Latency Tuning 
The Netflix TechBlog
MAY 4, 2023
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. Logging is selective to cases where the old and new responses do not match.
The Netflix TechBlog
SEPTEMBER 18, 2024
These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination. Data Model At its core, the KV abstraction is built around a two-level map architecture. Useful for keeping “n-newest” or prefix path deletion.
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Scalegrid
JUNE 4, 2020
Compare Latency. lower latency compared to DigitalOcean for PostgreSQL. Now, let’s take a look at the throughput and latency performance of our comparison. Next, we are going to test and compare the latency performance between ScaleGrid and DigitalOcean for PostgreSQL. PostgreSQL DigitalOcean Latency Averages (ms).
The Netflix TechBlog
MARCH 5, 2024
Reduced tail latencies In both our GRPC and DGS Framework services, GC pauses are a significant source of tail latencies. In fact, we’ve found for our services and architecture that there is no such trade off. No explicit tuning has been required to achieve these results. There is no best garbage collector.
Dynatrace
MAY 23, 2024
Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.
Dynatrace
JANUARY 14, 2022
Tuning thousands of parameters has become an impossible task to achieve via a manual and time-consuming approach. The following figure shows the high-level architecture where any load testing solution (e.g. SREcon21 – Automating Performance Tuning with Machine Learning. The Akamas approach. lower than 2%.).
The Netflix TechBlog
OCTOBER 8, 2024
Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.
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