ScaleOut Software

NOVEMBER 24, 2020

However, telematics architectures face challenges in responding to telemetry in real time. Current Telematics Architecture. The volume of incoming telemetry challenges current telematics systems to keep up and quickly make sense of all the data. Challenges for Current Architectures. Solution: Real-Time Digital Twins.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Rigor

JANUARY 13, 2020

Take, for example, The Web Almanac , the golden collection of Big Data combined with the collective intelligence from most of the authors listed below, brilliantly spearheaded by Google’s @rick_viscomi. Information Architecture. Site speed & SEO go hand in hand. Web Performance Daybook-Volume-2. The Art of SEO.

Performance 75

Performance Social Media Website Website Performance 75

Scalegrid

MARCH 28, 2024

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load.

Cache 130

Cache Storage Scalability Architecture 130

All Things Distributed

DECEMBER 20, 2017

Marketers use big data and artificial intelligence to find out more about the future needs of their customers. Breuninger uses modern templates for software development, such as Self-Contained Systems (SCS), so that it can increase the speed of software development with agile and autonomous teams and quickly test new features.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

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. Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data management.

Artificial Intelligence 209

Artificial Intelligence Analytics Storage Government 209

Dynatrace

FEBRUARY 16, 2023

As teams try to gain insight into this data deluge, they have to balance the need for speed, data fidelity, and scale with capacity constraints and cost. To solve this problem, Dynatrace launched Grail, its causational data lakehouse , in 2022. Logs on Grail Log data is foundational for any IT analytics. .

Analytics 186

Analytics Innovation Metrics Database 186

All Things Distributed

JULY 13, 2010

During my academic career, I spent many years working on HPC technologies such as user-level networking interfaces, large scale high-speed interconnects, HPC software stacks, etc. Driving down the cost of Big-Data analytics. There has been no easy way for developers to do this in Amazon EC2. until today.

Cloud 118

Cloud AWS Automotive Latency 118

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. A huge advantage of this approach is speed. It works without having to identify training data, then training and honing.

DevOps 196

DevOps Artificial Intelligence Healthcare Innovation 196

The Netflix TechBlog

MAY 26, 2020

These characteristics allow for an on-call response time that is relaxed and more in line with traditional big data analytical pipelines. Spark could look up and retrieve the data in the s3 files that the Mouthful represented. After several iterations of this architecture and some tuning, Sqooby has proven to be able to scale.

Network 150

Network Tuning AWS Big Data 150

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.” A huge advantage of this approach is speed. It works without having to identify training data, then training and honing.

Artificial Intelligence 212

Artificial Intelligence DevOps Innovation Metrics 212

The Netflix TechBlog

NOVEMBER 20, 2023

For example, a job would reprocess aggregates for the past 3 days because it assumes that there would be late arriving data, but data prior to 3 days isn’t worth the cost of reprocessing. Backfill: Backfilling datasets is a common operation in big data processing. ETL pipelines keep all the benefits of batch workflows.

Processing 210

Processing Big Data Efficiency Engineering 210

Abhishek Tiwari

DECEMBER 27, 2017

A common theme across all these trends is to remove the complexity by simplifying data management as a whole. In 2018, we anticipate that ETL will either lose relevance or the ETL process will disintegrate and be consumed by new data architectures. Unified data management architecture.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

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. As a consequence, the vast majority of the papers in the past has usually focused on conventional X86 or GPU-accelerated architectures.

Architecture 12

Architecture Hardware Cache Storage 12

The Netflix TechBlog

SEPTEMBER 10, 2019

This enables us to optimize their experience at speed. 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. Getting Data with the Metrics Repo 2. Computing Statistics with Causal Models 3.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

All Things Distributed

NOVEMBER 15, 2016

The reality is that many traditional BI solutions are built on top of legacy desktop and on-premises architectures that are decades old. The cost and complexity to implement, scale, and use BI makes it difficult for most companies to make data analysis ubiquitous across their organizations. Enter Amazon QuickSight.

Analytics 152

Analytics Availability Media Social Media 152