Remove 2007 Remove Code Remove Efficiency Remove Latency
article thumbnail

So many bad takes?—?What is there to learn from the Prime Video microservices to monolith story

Adrian Cockcroft

They were able to re-use most of their working code by combining it into a single long running microservice that is horizontally scaled using ECS, and which is invoked via a lambda function. This is only one of many microservices that make up the Prime Video application.

article thumbnail

DevOps automation: From event-driven automation to answer-driven automation [with causal AI]

Dynatrace

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. This evolution in automation, referred to as answer-driven automation, empowers teams to address complex issues in real time, optimize workflows, and enhance overall operational efficiency.

DevOps 217
Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

Progress Delayed Is Progress Denied

Alex Russell

After 20 years of neck-in-neck competition, often starting from common code lineages, there just isn't that much left to wring out of the system. Efficiently enables new styles of drawing content on the web , removing many hard tradeoffs between visual richness , accessibility, and performance. Form-associated Web Components.

Media 145
article thumbnail

Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. This architecture shift greatly reduced the processing latency and increased system resiliency. Thus, depending on when the code change was merged, it could take anywhere between two and four weeks to reach production.

article thumbnail

The Netflix Cosmos Platform

The Netflix TechBlog

It supports both high throughput services that consume hundreds of thousands of CPUs at a time, and latency-sensitive workloads where humans are waiting for the results of a computation. The first generation of this system went live with the streaming launch in 2007. Productivity?—?Local Delivery?—?A