Scalegrid

JANUARY 8, 2024

The partnership between AI and cloud computing brings about transformative trends like enhanced security through intelligent threat detection, real-time analytics, personalization, and the implementation of edge computing for quicker on-site decision-making. Key among these trends is the emphasis on security and intelligent analytics.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., That’s hard for many reasons, including the differing trade-offs between throughput and latency that need to be made across the use cases. Oh, and in additional to low latency, “ we require access to fresh data.” VLDB’19.

Analytics 75

Analytics Latency Cache Google 75

ScaleOut Software

JULY 14, 2021

Whether it’s health-tracking watches, long-haul trucks, or security sensors, extracting value from these devices requires streaming analytics that can quickly make sense of the telemetry and intelligently react to handle an emerging issue or capture a new opportunity.

IoT 52

IoT Azure Analytics Serverless 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

Dynatrace

DECEMBER 15, 2022

Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. The primary goal of ITOps is to provide a high-performing, consistent IT environment.

Artificial Intelligence 208

Artificial Intelligence DevOps Hardware Virtualization 208

Dynatrace

SEPTEMBER 13, 2023

Because Google offers its own Google Cloud Architecture Framework and Microsoft its Azure Well-Architected Framework , organizations that use a combination of these platforms triple the challenge of integrating their performance frameworks into a cohesive strategy. SRG validates the status of the resiliency SLOs for the experiment period.

AWS 252

AWS Efficiency Azure Cloud 252

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

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. In-Memory Data Grids for Fast-Changing Data.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. In-Memory Data Grids for Fast-Changing Data.

Analytics 52

Analytics Airlines Cache Scalability 52

The Netflix TechBlog

SEPTEMBER 2, 2020

While this abundance of dashboards and information is by no means unique to Netflix, it certainly holds true within our microservices architecture. In one request hitting just ten services, there might be ten different analytics dashboards and ten different log stores. As you can imagine, this comes with very real storage costs.

Latency 296

Latency Transportation Engineering Traffic 296

Percona

JULY 17, 2023

It’s a good setup for real-time analytics and high-speed logging. Redis can handle a high volume of operations per second, making it useful for running applications that require low latency. Storing large datasets can be a challenge, as Redis’ storage capacity is limited by available RAM. Couchbase — No.

Open Source 74

Open Source Database Scalability Software 74

ACM Sigarch

DECEMBER 6, 2018

smart cameras & analytics) to interactive/immersive environments and autonomous driving (e.g. Each of these categories opens up challenging problems in AI/visual algorithms, high-density computing, bandwidth/latency, distributed systems. cameras) in many usages ranging from digital security/surveillance and automated retail (e.g.

Wireless 54

Wireless IoT Analytics Architecture 54

Abhishek Tiwari

DECEMBER 27, 2017

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. Delta implements the unified data management layer by extending the Amazon S3 object storage for ACID transactions and automatic data indexing.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

Abhishek Tiwari

JULY 12, 2018

It can be used to power new analytics, insight, and product features. It can be used to power new analytics, insight, and product features. These nodes and edges require a good amount of compute and storage which is typically distributed across a large number servers either running in the cloud or your own data center.

Latency 63

Latency Analytics Scalability Engineering 63

All Things Distributed

JANUARY 18, 2012

Amazon DynamoDB offers low, predictable latencies at any scale. This architectural pattern was a response to the scaling challenges that had challenged Amazon.com through its first 5 years, when direct database access was one of the major bottlenecks in scaling and operating the business. The growth of Amazonâ??s Consistency.

Scalability 167

Scalability Database Ecommerce Latency 167

All Things Distributed

NOVEMBER 15, 2010

Building general purpose architectures has always been hard; there are often so many conflicting requirements that you cannot derive an architecture that will serve all, so we have often ended up focusing on one side of the requirements that allow you to serve that area really well.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

JULY 13, 2010

In particular this has been true for applications based on algorithms - often MPI-based - that depend on frequent low-latency communication and/or require significant cross sectional bandwidth. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. until today. At werner.ly Syndication.

Cloud 118

Cloud AWS Automotive Latency 118

Abhishek Tiwari

NOVEMBER 3, 2018

Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. Unfortunately, other than cost advantage Wordpress and Drupal have similar deficiencies i.e. legacy monolith architecture.

Systems 63

Systems Cache Website Network 63

Alex Russell

MARCH 6, 2021

A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage. Sadly, data on latency is harder to get, even from Google's perch, so progress there is somewhat more difficult to judge. The Moto G4 , for example.

Performance 124

Performance Network Cache Metrics 124

All Things Distributed

NOVEMBER 19, 2010

Understanding Throughput-Oriented Architectures - background article in CACM on massively parallel and throughput vs latency oriented architectures. Driving Storage Costs Down for AWS Customers. Expanding the Cloud - The AWS Storage Gateway. Driving down the cost of Big-Data analytics. At werner.ly

AWS 67

AWS Cloud Benchmarking Storage 67

All Things Distributed

DECEMBER 5, 2010

While registrars manage the namespace in the DNS naming architecture, DNS servers are used to provide the mapping between names and the addresses used to identify an access point. This achieves very low-latency for queries which is crucial for the overall performance of internet applications. At werner.ly Syndication. or rss feed.

Cloud 117

Cloud Internet Internet AWS 117

HammerDB

OCTOBER 12, 2018

As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. InnoDB is the storage engine that will deliver the best OLTP throughput and should be chosen for this test. . maximum transition latency: Cannot determine or is not supported. .

Best Practices 40

Best Practices Scalability Performance C++ 40

Highly Scalable

AUGUST 20, 2013

This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs. The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. Marz, “Big Data Lambda Architecture”.

Big Data 154

Big Data Processing Lambda Database 154

ScaleOut Software

MAY 4, 2014

Usually this means moving to a server with more CPU cores, greater memory capacity, and higher-end networking and storage options. Now CPU, memory, and storage resources can grow without predefined limits. At some point, scaling up becomes costly, and workloads grow beyond what even a high end server can handle.

Network 40

Network Servers Analytics Storage 40

Smashing Magazine

JANUARY 11, 2021

This guide has been kindly supported by our friends at LogRocket , a service that combines frontend performance monitoring , session replay, and product analytics to help you build better customer experiences. Study common complaints coming into customer service and sales team, study analytics for high bounce rates and conversion drops.

Performance 145

Performance Cache Media Metrics 145

Smashing Magazine

JANUARY 6, 2020

Study common complaints coming into customer service and sales team, study analytics for high bounce rates and conversion drops. Run performance experiments and measure outcomes — both on mobile and on desktop (for example, with Google Analytics ). Yet often, analytics alone doesn’t provide a complete picture.

Performance 145

Performance Cache Network Metrics 145

ScaleOut Software

MAY 15, 2014

For example, the IMDG must be able to efficiently create millions of objects in each server to make use of its huge storage capacity. Likewise, object access paths must be heavily multi-threaded and avoid lock contention to minimize access latency and maximize throughput.

Cache 40

Cache Servers Network Design 40

Smashing Magazine

JANUARY 7, 2019

To get accurate results and goals though, first study your analytics to see what your users are on. Estimated Input Latency tells us if we are hitting that threshold, and ideally, it should be below 50ms. Keeping progressive enhancement as the guiding principle of your front-end architecture and deployment is a safe bet.

Performance 104

Performance Cache Network Metrics 104

Alex Russell

JULY 14, 2021

Here, native apps are doing work related to their core function; storage and tracking of user data are squarely within the four corners of the app's natural responsibilities. Commenters forwarding these claims, as a rule, do not understand browser architecture. How can that be? have invested almost nothing in clarifying the situation.

Google 121

Google Mobile Engineering Internet 121