ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

JULY 6, 2022

IT automation is the practice of using coded instructions to carry out IT tasks without human intervention. At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Big data automation tools.

Artificial Intelligence 178

Artificial Intelligence Tuning Strategy Big Data 178

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. Memcached shines in scenarios where a simple, fast, and efficient caching solution is required without data persistence.

Cache 130

Cache Storage Scalability Architecture 130

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time.

Analytics 52

Analytics IoT Lambda Big Data 52

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.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

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. Achieving autonomous operations.

DevOps 185

DevOps Artificial Intelligence Healthcare Innovation 185

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 comprehensive, modern approach to AIOps is a unified platform that encompasses observability, AI, and analytics.

Artificial Intelligence 201

Artificial Intelligence DevOps Innovation Metrics 201

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. Using Webpagetest. Professional Website Performance. Professional Website Performance.

Performance 75

Performance Social Media Website Website Performance 75

ScaleOut Software

APRIL 3, 2020

Within seconds, the software performs aggregate analysis of this data for all real-time digital twins. By avoiding the need to create or connect to complex databases and ship data to offline analytics systems, it can provide timely answers quickly and easily.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

Within seconds, the software performs aggregate analysis of this data for all real-time digital twins. By avoiding the need to create or connect to complex databases and ship data to offline analytics systems, it can provide timely answers quickly and easily.

Logistics 52

Logistics Analytics Scalability Cloud 52

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. At Netflix, we also heavily embrace a microservice architecture that emphasizes separation of concerns.

Latency 243

Latency Storage Big Data Tuning 243

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. append, overwrite, etc.).

Processing 210

Processing Big Data Efficiency Engineering 210

All Things Distributed

APRIL 27, 2011

To our shareowners: Random forests, naïve Bayesian estimators, RESTful services, gossip protocols, eventual consistency, data sharding, anti-entropy, Byzantine quorum, erasure coding, vector clocks. Look inside a current textbook on software architecture, and youll find few patterns that we dont apply at Amazon.

Technology 151

Technology Technology AWS Storage 151