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What is Prosimo?

Applications are frequently dispersed and fragmented across multiple platforms. The extensive adoption of varied infrastructure stacks in multi-cloud settings contributes to heightened complexity as users attempt to access applications and interact efficiently. As a result, this complexity leads to a diminished experience with applications, increased operational costs, and insufficient security measures. In today's multi-cloud environment, there is an urgent demand for a new Application eXperience Infrastructure (AXI) that not only enhances user engagement with applications but also guarantees secure access and optimizes cloud spending, thereby enabling organizations to focus on realizing their business objectives. The Prosimo Application eXperience Infrastructure serves as a cohesive, cloud-native framework that positions itself in front of applications, delivering consistently enhanced, secure, and cost-efficient experiences. This innovative solution provides cloud architects and operations teams with an intuitive, decision-driven platform. By leveraging sophisticated data insights and machine learning capabilities, the Prosimo AXI platform can achieve remarkable results in just minutes, establishing itself as a crucial asset for contemporary businesses. Additionally, with the AXI, organizations can simplify their workflows and significantly boost the overall performance of their applications, ensuring they remain competitive in a rapidly evolving digital landscape.

What is Amazon Elastic Inference?

Amazon Elastic Inference provides a budget-friendly solution to boost the performance of Amazon EC2 and SageMaker instances, as well as Amazon ECS tasks, by enabling GPU-driven acceleration that could reduce deep learning inference costs by up to 75%. It is compatible with models developed using TensorFlow, Apache MXNet, PyTorch, and ONNX. Inference refers to the process of predicting outcomes once a model has undergone training, and in the context of deep learning, it can represent as much as 90% of overall operational expenses due to a couple of key reasons. One reason is that dedicated GPU instances are largely tailored for training, which involves processing many data samples at once, while inference typically processes one input at a time in real-time, resulting in underutilization of GPU resources. This discrepancy creates an inefficient cost structure for GPU inference that is used on its own. On the other hand, standalone CPU instances lack the necessary optimization for matrix computations, making them insufficient for meeting the rapid speed demands of deep learning inference. By utilizing Elastic Inference, users are able to find a more effective balance between performance and expense, allowing their inference tasks to be executed with greater efficiency and effectiveness. Ultimately, this integration empowers users to optimize their computational resources while maintaining high performance.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
AWS Marketplace
Amazon EC2
AppDynamics
Google Cloud Platform
HashiCorp Consul
Istio
MXNet
Microsoft Intune
Okta
Opsgenie
Oracle APEX
PagerDuty
PyTorch
Splunk APM
Splunk Cloud Platform
TensorFlow
Terraform
ThousandEyes
VMware Cloud

Integrations Supported

Amazon Web Services (AWS)
AWS Marketplace
Amazon EC2
AppDynamics
Google Cloud Platform
HashiCorp Consul
Istio
MXNet
Microsoft Intune
Okta
Opsgenie
Oracle APEX
PagerDuty
PyTorch
Splunk APM
Splunk Cloud Platform
TensorFlow
Terraform
ThousandEyes
VMware Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Prosimo

Date Founded

2019

Company Location

United States

Company Website

prosimo.io

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/machine-learning/elastic-inference/

Categories and Features

Application Development

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Infrastructure-as-a-Service (IaaS)

Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring

Categories and Features

Infrastructure-as-a-Service (IaaS)

Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring

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