The Netflix TechBlog

MARCH 2, 2021

While working on my PhD in political science, I realized my curiosity was always more piqued by methodological coursework, which led me to take as many stats/data science courses as I could. Later I enrolled in a data science program focused on helping academics transition to industry roles.

Analytics 207

Analytics C++ Innovation Engineering 207

KeyCDN

OCTOBER 2, 2018

Check out the Almanac for CSS property and selector-specific insights, or dive straight into the Snippets to grab some reusable code. It’s awesome for discovering how grid systems, CSS animation, Big Data, etc all play roles in real-world web design. Visit website 4. Visit website 12. Visit website 14. Visit website 17.

Development 75

Development Website Design Code 75

Highly Scalable

JUNE 5, 2012

When this short mask of common elements is obtained, we have to efficiently copy out common elements. This sounds like an extremely efficient approach for intersection of sorted lists, but in its basic form this approach is limited by 16-bit values in the lists. in this article.

C++ 102

C++ Java Performance Testing Efficiency 102

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. But before that new code can be deployed, it needs to be tested and reviewed from a security perspective. How AI helps human operators.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. This is required for understanding how I intend to improve the efficiency of (manual) alert ticket handling. With R (or RStudio) you can efficiently perform analysis on large data sets. But that didn’t work for me.

Tuning 263

Tuning Architecture Monitoring Big Data 263

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.” This means data sources typically come from disparate infrastructure monitoring tools and second-generation APM solutions.

Artificial Intelligence 213

Artificial Intelligence DevOps Innovation Metrics 213

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications – including your customers and employees. Websites, mobile apps, and business applications are typical use cases for monitoring.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20.

Cloud 104

Cloud Big Data Latency Architecture 104

Dynatrace

JUNE 1, 2020

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course end-users that access these applications – including your customers and employees. Websites, mobile apps, and business applications are typical use cases for monitoring. Performance monitoring.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

Highly Scalable

MAY 1, 2012

On the other hand, when one is interested only in simple additive metrics like total page views or average price of conversion, it is obvious that raw data can be efficiently summarized, for example, on a daily basis or using simple in-stream counters. what is the cardinality of the data set)? bits per unique value.

Analytics 191

Analytics Traffic Big Data Efficiency 191

Highly Scalable

MARCH 1, 2012

Of course, in many cases joins are inevitable and should be handled by an application. One of the reasons why powerful transactional machinery is an inevitable part of the relational databases is that normalized data typically require multi-place updates. Applicability : Ordered Key-Value Stores, BigTable-style Databases. (10)

Database 279

Database Ecommerce Efficiency Engineering 279

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. Of course, responsibilities and organizations will change as a result of these developments.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76