Cloud Musings

DECEMBER 11, 2015

When it comes to big data analytics, Teradata delivers these Platform-as-a-Service advantages by delivering industry andbusiness process aligned components within their PaaS. Through this strategy, the company was relieved of most of the care and feeding of its data warehouse.

Disaster Recovery 70

Disaster Recovery Healthcare Load Balancer Applications 70

Dataconomy

APRIL 18, 2023

By distributing tasks among multiple processors, parallel processing can help to maximize the use of available resources and minimize idle time. This can be especially beneficial for organizations that handle large amounts of data or require real-time data processing.

Load Balancer 41

Load Balancer Applications Big Data Resources 41

Fountainhead

JUNE 2, 2009

The instantiation of these observations was a product that put almost all of the datacenter on "autopilot" -- Servers, VMs, switches, load-balancers, even server power controllers and power strips. And it worked, all-the-time making most efficient use of IT resources and power. Big Data. (6). Syndications.

Data Center 100

Data Center Load Balancer Virtualization Analysis 100

All Things Distributed

FEBRUARY 25, 2011

Often an application requires several infrastructure resources to be created and AWS CloudFormation helps customers create and manage these collections of AWS resources in a simple and predictable way. There are several resources required: Elastic Load Balancers, EC2 instances, EBS volumes, SimpleDB domains and an RDS instance.

Applications 123

Applications Resources Cloud Load Balancer 123

Dataconomy

MAY 22, 2023

Understanding machine learning Distributed learning refers to the process of training machine learning models using multiple computing resources that are interconnected. In the context of traditional machine learning, training a large-scale model on a single machine can be time-consuming and resource-intensive.

Training 93

Training Resources Data Load Balancer 93

Data Center Knowledge

JULY 17, 2013

He has more than 20 years of experience in assisting cloud, storage and data management technology companies as well as cloud service providers to address rapidly expanding Infrastructure-as-a-Service and big data sectors. PAUL SPECIALE. Cloud Management. Cloud Application Management.

Data Center 203

Data Center Cloud Data Applications 203

Fountainhead

OCTOBER 6, 2009

A specific angle I want to address here is that of infrastructure automation ; that is, the dynamic manipulation of physical resources (virtualized or not) such as I/O, networking, load balancing, and storage connections - Sometimes referred to as "Infrastructure 2.0". a Fabric), and network switches, load balancers, etc.

Load Balancer 100

Load Balancer Virtualization Data Center Network 100

Fountainhead

DECEMBER 8, 2009

The next step is to define in software the converged network, its switching, and even network devices such as load balancers. Provisioning of the network, VLANs, IP load balancing, etc. The transition you speak of -- from I/O as a fixed resource to infrastructure-as-a-service -- is actually well along. Big Data. (6).

Data Center 113

Data Center Virtualization Load Balancer Network 113

Fountainhead

MAY 6, 2010

Converged Infrastructure and Unified Computing are both terms referring to technology where the complete server profile, including I/O (NICs, HBAs, KVM), networking (VLANs, IP load balancing, etc.), The result is a pooling of physical servers, network resources and storage resources that can be assigned on-demand.

Data Center 100

Data Center Virtualization Storage Network 100

All Things Distributed

NOVEMBER 15, 2010

We believe that making these GPU resources available for everyone to use at low cost will drive new innovation in the application of highly parallel programming models. The different stages were then load balanced across the available units. Driving down the cost of Big-Data analytics. From CPU to GPU.

Architecture 136

Architecture Programming Web Services Applications 136