Infrastructure Latency Tuning 
The Netflix TechBlog
NOVEMBER 12, 2024
By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.
The Netflix TechBlog
MARCH 28, 2025
Yet, many are confined to a brief temporal window due to constraints in serving latency or training costs. It facilitates the distribution of these learnings to other models, either through shared model weights for fine tuning or directly through embeddings.
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Scalegrid
FEBRUARY 6, 2025
Its partitioned log architecture supports both queuing and publish-subscribe models, allowing it to handle large-scale event processing with minimal latency. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency. Apache Kafka, designed for distributed event streaming, maintains low latency at scale.
The Netflix TechBlog
OCTOBER 19, 2020
Now let’s look at how we designed the tracing infrastructure that powers Edgar. If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls.
The Netflix TechBlog
DECEMBER 17, 2024
The Challenge of Title Launch Observability As engineers, were wired to track system metrics like error rates, latencies, and CPU utilizationbut what about metrics that matter to a titlessuccess? This approach provides a few advantages: Low burden on existing systems: Log processing imposes minimal changes to existing infrastructure.
Dynatrace
MAY 23, 2024
Failures can occur unpredictably across various levels, from physical infrastructure to software layers. Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively. This significantly increases event latency.
Dynatrace
JANUARY 14, 2022
Its ability to densely schedule containers into the underlying machines translates to low infrastructure costs. Tuning thousands of parameters has become an impossible task to achieve via a manual and time-consuming approach. SREcon21 – Automating Performance Tuning with Machine Learning. The Akamas approach.
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