Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. Capabilities for handling diverse data management functions are necessary. It should offer user-friendly operation.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

The Netflix TechBlog

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 243

Latency Storage Big Data Tuning 243

Dynatrace

JANUARY 16, 2023

The immense growth of Kubernetes presents new security challenges in runtime and increased complexity in hardening CI/CD pipelines in development. Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments.

Open Source 347

Open Source Java Operating System Programming 347

Dynatrace

APRIL 25, 2023

Exploratory analytics with collaborative analytics capabilities can be a lifeline for CloudOps, ITOps, site reliability engineering, and other teams struggling to access, analyze, and conquer the never-ending deluge of big data. These analytics can help teams understand the stories hidden within the data and share valuable insights.

Analytics 206

Analytics Big Data Media Operating System 206

Dynatrace

AUGUST 10, 2021

Dynatrace CMO Mike Maciag talked about the dangers of “status quo” and failing to get where you need to go because of loyalty to legacy APM software, or hanging onto outdated processes. On the other hand, every single step you take towards intelligently observing data across your organization brings increasingly greater rewards.

DevOps 246

DevOps Innovation Big Data Cloud 246

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.” AIOps is often presented as a way to reduce the noise of countless alerts, but it can and should be more than that.

Artificial Intelligence 218

Artificial Intelligence DevOps Innovation Metrics 218

Dynatrace

MARCH 11, 2021

I took a big-data-analysis approach, which started with another problem visualization. During the implementation of the real-time visualization I presented in part three , I had an idea for another visualization; I wanted to visualize the number of detected problems globally, for a longer timeframe. But that didn’t work for me.

Tuning 264

Tuning Architecture Monitoring Big Data 264

O'Reilly

SEPTEMBER 19, 2023

Each time, the underlying implementation changed a bit while still staying true to the larger phenomenon of “Analyzing Data for Fun and Profit.” ” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize.

Hardware 97

Hardware Storage Big Data Blockchain 97

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 203

Storage Latency Efficiency Data Engineering 203

Testsigma

MAY 14, 2021

Data is present on the local server and hence cannot be accessed from everywhere. Data is present on the cloud hence can be accessed from any location. It provides better and simple disaster recovery because the process is automated. Process: Chalking out the strategy to make a move to cloud-based testing.

Cloud 67

Cloud Testing Testing Tools Internet 67

All Things Distributed

NOVEMBER 30, 2016

There are many more application areas where we use ML extensively: search, autonomous drones, robotics in fulfillment centers, text processing and speech recognition (such as in Alexa) etc. And this process must be repeated for every object, face, voice, and language feature in an application.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165

Testsigma

FEBRUARY 12, 2021

The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. With all of these processes in place, cost optimization is also a high concern for organizations worldwide. Many changes are rendered through automated testing. Hyperautomation. billion in 2019 to $40.74

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Testsigma

JULY 14, 2020

According to Wikipedia, Data-Driven Testing(DDT) is a software testing methodology that is used in the testing of computer software to describe testing done using a table of conditions directly as test inputs and verifiable outputs as well as the process where test environment settings and control are not hard-coded. Reusability.

Testing 63

Testing Artificial Intelligence DevOps Big Data 63

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

All Things Distributed

AUGUST 16, 2011

ITAR is the International Traffic in Arms Regulatory framework which stipulates for example that data must be stored in an environment where physical and logical access is restricted to US Persons. Government and Big Data. One particular early use case for AWS GovCloud (US) will be massive data processing and analytics.

AWS 111

AWS Government Big Data Cloud 111

ACM Sigarch

APRIL 8, 2019

big-data processing, machine learning, quantum computing, and so on). Below we present some thoughts on the why and one solution to address the issue. Computer architecture is an important and exciting field of computer science, which enables many other fields (eg. Why is that? Should we be alarmed as a community?

Architecture 74

Architecture Open Source Hardware Software Engineering 74

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

All Things Distributed

FEBRUARY 17, 2011

The other document you can specify is a customer error page that is presented to your customers when a 4XX class error occurs (e.g. Driving down the cost of Big-Data analytics. This enables Amazon S3 to know what document to serve if one isnt explicitly requested: for example [link]. the index.html from that subdirectory.

AWS 134

AWS Website Storage Servers 134

Rigor

SEPTEMBER 11, 2019

Reading time 16 min Whether you’re a web performance expert, an evangelist for the culture of performance, a web engineer incorporating performance into your process, or someone new to the web performance entirely, you probably identify as curious, excited about new ideas, and always learning. Here is our (ever-growing!) Rachel Andrew.

Performance 89

Performance Education Google Website 89

All Things Distributed

APRIL 27, 2011

For example, to construct a product detail page for a customer visiting Amazon.com, our software calls on between 200 and 300 services to present a highly personalized experience for that customer. Technology infuses all of our teams, all of our processes, our decision-making, and our approach to innovation in each of our businesses.

Technology 151

Technology Technology AWS Storage 151

SQL Server According to Bob

FEBRUARY 15, 2018

When I started to write this post I thought I knew who all was presenting but then I had to go back over the session lineup to see for myself. Best practices on Building a Big Data Analytics Solution – Michael Rys. If you want to learn about Azure Data Lake, there is no one better. I want to come to this one myself.

Engineering 40

Engineering Azure Best Practices Servers 40

SQL Server According to Bob

JANUARY 15, 2020

Using the ​​ kubectl get pods ​​ and ​​ get nodes ​​ I determined the target node and studied the time range of events present in the journal. ​​​​ The journal of the node is what told the real story and allowed me to understand the behavior.

Servers 40

Servers Metrics Big Data Operating System 40

Smashing Magazine

AUGUST 9, 2021

A lot of issues with that where they’re allowing someone to have more control because he could just not give me the answers and then I wouldn’t have access to our finances without having to call the bank or go through something and go through a different process. Drew: Yes, it presents all sorts of challenges, doesn’t it?

Design 98

Design Education Network Google 98

Highly Scalable

MARCH 10, 2015

More specialized data mining applications like supply chain optimization and fraud detection are out of scope, as well as the implementation details of the data mining process (such as evaluation of model quality). It reduces the noise by discarding minor fluctuations that simply do not fit the smaller basis. Sale channels.

Retail 152

Retail C++ Analytics Metrics 152

ACM Sigarch

NOVEMBER 1, 2019

This blog post gives a glimpse of the computer systems research papers presented at the USENIX Annual Technical Conference (ATC) 2019, with an emphasis on systems that use new hardware architectures. The second work presented a novel scalable distributed capability mechanism for security and protection in such systems.

Architecture 12

Architecture Hardware Cache Storage 12