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What is HttpWatch?

Enhance your skills in debugging and web performance with a sophisticated in-browser HTTP sniffer that enables you to examine network traffic generated by a website directly, eliminating the need for external tools. This powerful utility offers accurate assessments of a web page's network efficiency while revealing opportunities for speed improvements, all without requiring any extra configurations or proxies—even for secured HTTPS connections! You can quickly pinpoint weak SSL setups and other security issues present on your web server. The free Basic Edition lets users send you detailed log files, simplifying remote error resolution and performance diagnostics. Additionally, the HttpWatch API allows for the collection of performance data during automated website evaluations. Fully compatible with Chrome, Edge, and Internet Explorer, HttpWatch reveals the HTTP and HTTPS traffic created during web page visits, and by selecting individual requests, you can access all pertinent details arranged in a user-friendly tabbed format. This seamless integration not only provides you with essential insights but also equips you with the tools needed to enhance the efficiency of your web applications while ensuring security measures are in place. Ultimately, with this tool, you gain a comprehensive understanding of your web performance metrics and areas for improvement.

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
Keras
MXNet
PyTorch
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
Keras
MXNet
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

$395 one-time payment
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

Neumetrix

Date Founded

2016

Company Location

United Kingdom

Company Website

www.httpwatch.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Performance Testing

API Testing
Benchmarking
Cross Browser Testing
Debugging
Historical Reporting
Load Testing
Mobile Testing
Parallel Testing
Regression Testing
UI Testing
Web Testing

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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