Remove Data Remove Infrastructure Remove Latency
article thumbnail

Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

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.

Latency 236
article thumbnail

Investigation of a Workbench UI Latency Issue

The Netflix TechBlog

Overview At Netflix, the Analytics and Developer Experience organization, part of the Data Platform, offers a product called Workbench. Workbench is a remote development workspace based on Titus that allows data practitioners to work with big data and machine learning use cases at scale. We then exported the .har

Latency 211
Insiders

Sign Up for our Newsletter

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

article thumbnail

Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Vidhya Arvind , Rajasekhar Ummadisetty , Joey Lynch , Vinay Chella Introduction At Netflix our ability to deliver seamless, high-quality, streaming experiences to millions of users hinges on robust, global backend infrastructure. To overcome these challenges, we developed a holistic approach that builds upon our Data Gateway Platform.

Latency 248
article thumbnail

Comparing Approaches to Durability in Low Latency Messaging Queues

DZone

A significant feature of Chronicle Queue Enterprise is support for TCP replication across multiple servers to ensure the high availability of application infrastructure. Little’s Law and Why Latency Matters. In many cases, the assumption is that as long as throughput is high enough, the latency won’t be a problem.

Latency 275
article thumbnail

Next-level interaction and customization of data visualizations in Dynatrace Dashboards and Notebooks

Dynatrace

Take your monitoring, data exploration, and storytelling to the next level with outstanding data visualization All your applications and underlying infrastructure produce vast volumes of data that you need to monitor or analyze for insights.

Latency 212
article thumbnail

Why applying chaos engineering to data-intensive applications matters

Dynatrace

The jobs executing such workloads are usually required to operate indefinitely on unbounded streams of continuous data and exhibit heterogeneous modes of failure as they run over long periods. Failures can occur unpredictably across various levels, from physical infrastructure to software layers.

article thumbnail

Analyze OpenTelemetry traces and log data at scale: Accelerate troubleshooting and optimize application performance

Dynatrace

Considering the latest State of Observability 2024 report, it’s evident that multicloud environments not only come with an explosion of data beyond humans’ ability to manage it. It’s increasingly difficult to ingest, manage, store, and sort through this amount of data. You can find the list of use cases here.