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What is Bugsnag?

Bugsnag delivers in-depth monitoring of application stability, which helps teams decide whether to focus on new feature development or fix existing issues. As a comprehensive full-stack stability monitoring tool specifically designed for mobile applications, it provides sophisticated diagnostics that allow for effective error replication. Featuring an intuitive interface, Bugsnag enables seamless management of all your applications from a unified dashboard. It plays a critical role in evaluating app health, enhancing collaboration between product and engineering teams. Not every bug necessitates urgent resolution, which allows you to prioritize issues that have a substantial effect on your business. Its extensible libraries are equipped with thoughtful defaults and numerous customization possibilities. Moreover, the team consists of dedicated experts who are deeply committed to reducing errors and maintaining the overall health of your applications, making Bugsnag an essential resource for developers. By leveraging these capabilities, developers can enhance their workflow and deliver a more stable user experience.

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

Amazon Web Services (AWS)
ActiveCollab
Autodesk A360
Azure DevOps Services
Bugify
ClickUp
Craft CMS
GitHub
Indent
Jira Work Management
LiquidPlanner
Microsoft Teams
OpsLevel
PagerDuty
Runway
Slack
Sprintly
Teamstack
TensorFlow
UserVoice

Integrations Supported

Amazon Web Services (AWS)
ActiveCollab
Autodesk A360
Azure DevOps Services
Bugify
ClickUp
Craft CMS
GitHub
Indent
Jira Work Management
LiquidPlanner
Microsoft Teams
OpsLevel
PagerDuty
Runway
Slack
Sprintly
Teamstack
TensorFlow
UserVoice

API Availability

Has API

API Availability

Has API

Pricing Information

$59 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

Bugsnag

Date Founded

2013

Company Location

United States

Company Website

www.bugsnag.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Application Performance Monitoring (APM)

Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions

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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