Remove Latency Remove Servers Remove Tuning
article thumbnail

Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

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.

Latency 251
article thumbnail

Introducing Impressions at Netflix

The Netflix TechBlog

These events are promptly relayed from the client side to our servers, entering a centralized event processing queue. Automating Performance Tuning with Autoscalers Tuning the performance of our Apache Flink jobs is currently a manual process. This queue ensures we are consistently capturing raw events from our global userbase.

Tuning 166
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

RabbitMQ vs. Kafka: Key Differences

Scalegrid

Its partitioned log architecture supports both queuing and publish-subscribe models, allowing it to handle large-scale event processing with minimal latency. Kafka clusters can be deployed in Kubernetes using Helm charts to simplify scaling and management across multiple servers.

Latency 147
article thumbnail

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. We will examine these alternatives in the upcoming sections.

Traffic 347
article thumbnail

Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination. It also serves as central configuration of access patterns such as consistency or latency targets. Useful for keeping “n-newest” or prefix path deletion.

Latency 260
article thumbnail

Migrating Netflix to GraphQL Safely

The Netflix TechBlog

Before GraphQL: Monolithic Falcor API implemented and maintained by the API Team Before moving to GraphQL, our API layer consisted of a monolithic server built with Falcor. A single API team maintained both the Java implementation of the Falcor framework and the API Server. To launch Phase 1 safely, we used AB Testing.

Traffic 357
article thumbnail

Best Practice for Creating Indexes on your MySQL Tables

Scalegrid

95th Percentile Latency. The 95th percentile latency of queries was also 1.8 times higher when the index creation happened on the master server. The 95th percentile latency of queries was also 1.8 times higher when the index creation happened on the master server. Workload Throughput (Queries Per Second).