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What is Errsole?

Errsole is an open-source logging tool designed for Node.js applications, offering a free solution that comes equipped with a log viewer for convenient log management, filtering, and searching. 1) Simple Integration: Integrating the Errsole package into your existing codebase is straightforward—there's no requirement for dedicated servers, complex installations, or intricate setups. 2) Enhanced Logging: Errsole captures all console logs from Node.js automatically and features enhanced logging capabilities that allow for multiple log levels and the option to add metadata to each log entry. 3) Flexible Storage: You have the freedom to store your logs in any preferred location, be it a file or a database of your choice, and you can also set up log rotation to determine how long each log should be kept. 4) Intuitive Log Dashboard: The built-in Web Dashboard lets you view, filter, and search through logs easily, with secure authentication and team management features ensuring controlled access to log data. 5) Immediate Error Alerts: Receive prompt notifications if your application crashes or faces critical errors, including essential details such as the error message, app name, environment, server name, and a direct link for quick access to the relevant logs. 6) User-Friendly Experience: With Errsole, developers can enjoy a user-friendly logging experience that streamlines the process of monitoring application performance and addressing issues efficiently.

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
Gmail
Keras
MXNet
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
Gmail
Keras
MXNet
PyTorch
Slack
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

0
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

Errsole

Date Founded

2023

Company Location

India

Company Website

errsole.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Log Management

Archiving
Audit Trails
Compliance Reporting
Consolidation
Data Visualization
Event Logs
Network Logs
Remediation
Syslogs
Thresholds
Web Logs

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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