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What is Request Metrics?

Request Metrics enhances web performance by utilizing real-user testing alongside automated Lighthouse assessments. This dual approach allows for significant improvements in Core Web Vitals and SEO while simultaneously elevating the overall user experience. With features that track actual visitors, rather than relying solely on laboratory tests, automatic noise cancellation ensures that the data is accurate and relevant. You will gain valuable insights and comprehensive attribution for various elements on your site. By scheduling Lighthouse tests, you can spot regressions before they impact your search rankings. Access to real-user data provides a clear picture of your site's performance in everyday conditions. You can filter results by device, region, vendor, or specific pages to pinpoint performance issues and receive immediate notifications. Additionally, the platform enables you to determine which third-party scripts may be hindering your website's loading speed. The system is designed for ease of use, eliminating the need for complex setups or code modifications, and focuses on delivering fast and dependable performance tracking tailored for contemporary websites. Begin your journey today with a free account and unlock the potential for enhanced web performance!

What is Amazon SageMaker Debugger?

Improve machine learning models by capturing real-time training metrics and initiating alerts for any detected anomalies. To reduce both training time and expenses, the training process can automatically stop once the desired accuracy is achieved. Additionally, it is crucial to continuously evaluate and oversee system resource utilization, generating alerts when any limitations are detected to enhance resource efficiency. With the use of Amazon SageMaker Debugger, the troubleshooting process during training can be significantly accelerated, turning what usually takes days into just a few minutes by automatically pinpointing and notifying users about prevalent training challenges, such as extreme gradient values. Alerts can be conveniently accessed through Amazon SageMaker Studio or configured via Amazon CloudWatch. Furthermore, the SageMaker Debugger SDK is specifically crafted to autonomously recognize new types of model-specific errors, encompassing issues related to data sampling, hyperparameter configurations, and values that surpass acceptable thresholds, thereby further strengthening the reliability of your machine learning models. This proactive methodology not only conserves time but also guarantees that your models consistently operate at peak performance levels, ultimately leading to better outcomes and improved overall efficiency.

Media

Media

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Autodesk A360
Change Healthcare Data & Analytics
GitHub
Google
Keras
MXNet
Microsoft Teams
PyTorch
Slack
TensorFlow

Integrations Supported

AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Autodesk A360
Change Healthcare Data & Analytics
GitHub
Google
Keras
MXNet
Microsoft Teams
PyTorch
Slack
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

$34 per month
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

Request Metrics

Date Founded

2000

Company Location

United States

Company Website

requestmetrics.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Website Monitoring

Availability Testing
Event Logs
Event-Based Notifications
FTP Monitoring
Mail Server Monitoring
Maintenance Scheduling
Performance Metrics
Real Time Monitoring
Transaction Monitoring
Uptime Reporting

Website Optimization Tools

Competitor Analysis
Content Management
Keyword Research Tools
Link Management
Performance Metrics
Problem Area Alerts

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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