ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. At the same time, telemetry snapshots are stored in a data lake, such as HDFS , for offline batch analysis and visualization using big data tools like Spark.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. These questions can be answered using the latest data as it streams in from the field. What are real-time digital twins and why are they useful here?

Logistics 52

Logistics Analytics Scalability Cloud 52

The Morning Paper

JUNE 23, 2019

After all, we’ve been doing that forever with the 2nd-level cache of ORMs , and it is highly encouraged in e.g. the AWS Lambda programming model — which was born on the cloud— to help mitigate function start-up times. I say go ahead and use local state as a performance boost, so long as you’re fine to have that state wiped out at any moment.

Cache 79

Cache Latency Google Lambda 79

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

ScaleOut Software

JUNE 15, 2020

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source. The list goes on.

Analytics 52

Analytics IoT Lambda Big Data 52

Brendan Gregg

APRIL 30, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 43

DevOps Network Best Practices Programming 43

Brendan Gregg

APRIL 29, 2018

In this year's CFP we’re looking for topics covering the latest trends and best practices in cloud computing, containerization, machine learning, big data, infrastructure, scalability, DevOps, IT management, automation, reliability, monitoring, performance tuning, security, databases, programming, datacenters, and more.

DevOps 40

DevOps Network Best Practices Programming 40

Percona

JANUARY 14, 2019

However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node). With the latest ClickHouse version, all of these features are available, but some of them may not perform fast enough. So can we use it as our main datastore? Deleting messages. Text search.

Database 40

Database Analytics Blockchain Healthcare 40

KeyCDN

OCTOBER 2, 2018

Its videos and blog articles address issues such as web performance, extensible component development and the intersection of CSS with other technologies, like HTML and JavaScript. It’s awesome for discovering how grid systems, CSS animation, Big Data, etc all play roles in real-world web design. Visit website 3.

Development 75

Development Website Design Code 75

ACM Sigarch

NOVEMBER 1, 2019

Alongside more traditional sessions such as Real-World Deployed Systems and Big Data Programming Frameworks, there were many papers focusing on emerging hardware architectures, including embedded multi-accelerator SoCs, in-network and in-storage computing, FPGAs, GPUs, and low-power devices. Heterogeneous ISA.

Architecture 12

Architecture Hardware Cache Storage 12

The Netflix TechBlog

OCTOBER 18, 2022

As Big data and ML became more prevalent and impactful, the scalability, reliability, and usability of the orchestrating ecosystem have increasingly become more important for our data scientists and the company. Another dimension of scalability to consider is the size of the workflow.

Java 202

Java Scalability Traffic Architecture 202

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

Highly Scalable

MARCH 10, 2015

The goal is to find a set of the most promising candidates who should receive the resource in order to maximize the overall performance of the targeted group of customers. Moreover, gross margin is not the only performance metric that is important for retailers. The resource can be homogenous (i.e. Applications.

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

NOVEMBER 15, 2010

Werner Vogels weblog on building scalable and robust distributed systems. This incredible power is available for anyone to use in the usual pay-as-you-go model, removing the investment barrier that has kept many organizations from adopting GPUs for their workloads even though they knew there would be significant performance benefit.

AWS 136

AWS Latency Programming Architecture 136

All Things Distributed

MAY 18, 2010

Werner Vogels weblog on building scalable and robust distributed systems. This new storage option enables customers to reduce their costs by storing non-critical, reproducible data at lower levels of redundancy. Four years later it stores over 100 billion objects and routinely performs well over 120,000 storage operations per second.

Storage 71

Storage Cloud AWS Scalability 71