The Netflix TechBlog

JUNE 1, 2021

clinical data was often small enough to fit into memory on an average computer and only in rare cases would its computation require any technical ingenuity or massive computing power. There was not enough scope to explore the distributed and large-scale computing challenges that usually come with big data processing.

Data Engineering 130

Data Engineering Engineering Big Data Healthcare 130

The Netflix TechBlog

MARCH 2, 2021

Our experimentation and causal inference focused data scientists help shape business decisions, product innovations, and engineering improvements across our service. In this post, we discuss a day in the life of experimentation and causal inference data scientists at Netflix, interviewing some of our stunning colleagues along the way.

Analytics 207

Analytics C++ Innovation Engineering 207

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” But what is AIOps, exactly? And how can it support your organization? What is AIOps?

Artificial Intelligence 208

Artificial Intelligence DevOps Innovation Metrics 208

The Netflix TechBlog

FEBRUARY 16, 2021

However, with our rapid product innovation speed, the whole approach experienced significant challenges: Business Complexity: The existing SKU management solution was designed years ago when the engagement rules were simple?—?three three plans and one offer homogeneously applied to all regions. What’s Next?

Mobile 209

Mobile Engineering Infrastructure Scalability 209

The Netflix TechBlog

SEPTEMBER 10, 2019

Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute. The two main challenges with this approach are establishing an easy contribution framework and handling Netflix’s scale of data.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

The Netflix TechBlog

APRIL 29, 2019

Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud.

Open Source 279

Open Source Network Infrastructure Big Data 279

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. From AI to ML, the shifting technology world is constantly innovating and making significant progress. Sign up for free for the simplest and most efficient way to simplify your testing with Testsigma!

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

All Things Distributed

DECEMBER 20, 2017

The founders had noticed that in many companies, product designers worked in a very detached manner from the rest of production. In this way, designers are part of an ecosystem in which the functionalities of simulations, data and people come together, enabling them to develop better products faster. Value creation through data.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

All Things Distributed

JUNE 29, 2011

Often we think about innovation as going after new unchartered territories, but it is also important to innovate in those existing dimensions that will remain important for customers. Our account managers periodically call customers to work with them to see if there are opportunities to create better efficiencies and lower bills.

AWS 104

AWS Retail Innovation Strategy 104

All Things Distributed

DECEMBER 13, 2009

Spot Instances are an innovation that is made possible by the unparalleled economies of scale created by the tremendous growth of the AWS Infrastructure Services. The broad Amazon EC2 customer base brings such diversity in workload and utilization patterns that it allows us to operate Amazon EC2 with extreme efficiency.

Cloud 63

Cloud AWS Storage Innovation 63

Highly Scalable

MARCH 10, 2015

More specifically, the article was inspired by three major case studies from Albert Heijn [KOK07], the largest supermarket chain in the Netherlands, Zara [CA12], an international apparel retailer, and RueLaLa [JH14], an innovative online fashion retailer. The design of the model heavily depends on the problem. Propensity to churn.

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

DECEMBER 13, 2016

UK companies are using AWS to innovate across diverse industries, such as energy, manufacturing, medicaments, retail, media, and financial services and the UK is home to some of the world's most forward-thinking businesses. Take Peterborough City Council as an example. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

ACM Sigarch

NOVEMBER 1, 2019

As is the case for many high-quality computer systems conferences, the papers presented here involve a significant amount of engineering and experimentation on real hardware to convincingly evaluate innovative concepts end-to-end in a realistic setting. ATC ’19 was refreshingly different.

Architecture 12

Architecture Hardware Cache Storage 12

All Things Distributed

NOVEMBER 15, 2010

Today Amazon Web Services takes another step on the continuous innovation path by announcing a new Amazon EC2 instance type: The Cluster GPU Instance. We believe that making these GPU resources available for everyone to use at low cost will drive new innovation in the application of highly parallel programming models. Comments ().

AWS 136

AWS Latency Programming Architecture 136