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. It works without having to identify training data, then training and honing. CloudOps: Applying AIOps to multicloud operations.

DevOps 198

DevOps Artificial Intelligence Healthcare Innovation 198

The Netflix TechBlog

APRIL 29, 2019

We are heavy users of Jupyter Notebooks and nteract to analyze operational data and prototype visualization tools that help us detect capacity regressions. CORE The CORE team uses Python in our alerting and statistical analytical work. We also use Python to detect sensitive data using Lanius.

Open Source 279

Open Source Network Infrastructure Big Data 279

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.” They require extensive training, and real-user must spend valuable time filtering any false positives. What is AIOps?

Artificial Intelligence 215

Artificial Intelligence DevOps Innovation Metrics 215

The Netflix TechBlog

NOVEMBER 20, 2023

IPS enables users to continue to use the data processing patterns with minimal changes. Introduction Netflix relies on data to power its business in all phases. As our business scales globally, the demand for data is growing and the needs for scalable low latency incremental processing begin to emerge. append, overwrite, etc.).

Processing 210

Processing Big Data Efficiency Engineering 210

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

APRIL 27, 2011

We use high-performance transactions systems, complex rendering and object caching, workflow and queuing systems, business intelligence and data analytics, machine learning and pattern recognition, neural networks and probabilistic decision making, and a wide variety of other techniques. Driving down the cost of Big-Data analytics.

Technology 151

Technology Technology AWS Storage 151

Highly Scalable

MARCH 10, 2015

Although there are many books on data mining in general and its applications to marketing and customer relationship management in particular [BE11, AS14, PR13 etc.], The rest of the article is organized as follows: We first introduce a simple framework that ties together a retailer’s actions, profits and data.

Retail 152

Retail C++ Analytics Metrics 152

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. The workplace of the future.

Artificial Intelligence 77

Artificial Intelligence Technology Technology IoT 77

Smashing Magazine

JULY 29, 2019

Notice the async keyword on the Google analytics script? Google analytics has ‘low’ priority. It’s difficult to detect if someone on a desktop is on a broadband connection or is tethering through a data-limited dongle or mobile. The format that keeps the best quality for the smallest size may not be the one you expect.

Cache 96

Cache Google Mobile Network 96

All Things Distributed

NOVEMBER 30, 2016

automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g.

AWS 166

AWS Lambda Artificial Intelligence Mobile 166