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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Amazon Managed Grafana is a comprehensive service designed to streamline the visualization and analysis of operational data on a large scale. This platform enables users to establish workspaces, which are isolated Grafana servers that can be automatically provisioned, configured, scaled, and maintained. These dedicated workspaces facilitate the visualization and analysis of operational data sourced from a variety of channels, including AWS services like Amazon CloudWatch, AWS X-Ray, and Amazon Managed Service for Prometheus, as well as external data providers. The service is fully integrated with AWS security features, ensuring adherence to corporate security policies. Furthermore, Amazon Managed Grafana allows for seamless migration from self-hosted Grafana systems, enabling users to keep their existing dashboards and settings intact. It also includes collaborative tools such as live dashboard viewing and modification, version control, and sharing options, which significantly boost team efficiency. Overall, Amazon Managed Grafana stands out by simplifying complex data operations while enhancing collaborative efforts within teams.

Description

Enhance machine learning model performance by capturing real-time training metrics and issuing alerts for any detected anomalies. To minimize both time and expenses associated with the training of ML models, the training processes can be automatically halted upon reaching the desired accuracy. Furthermore, continuous monitoring and profiling of system resource usage can trigger alerts when bottlenecks arise, leading to better resource management. The Amazon SageMaker Debugger significantly cuts down troubleshooting time during training, reducing it from days to mere minutes by automatically identifying and notifying users about common training issues, such as excessively large or small gradient values. Users can access alerts through Amazon SageMaker Studio or set them up via Amazon CloudWatch. Moreover, the SageMaker Debugger SDK further enhances model monitoring by allowing for the automatic detection of novel categories of model-specific errors, including issues related to data sampling, hyperparameter settings, and out-of-range values. This comprehensive approach not only streamlines the training process but also ensures that models are optimized for efficiency and accuracy.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon CloudWatch
Amazon Web Services (AWS)
AWS Lambda
AWS X-Ray
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Change Healthcare Data & Analytics
Grafana Cloud
Keras
MXNet
PyTorch
TensorFlow

Integrations

Amazon CloudWatch
Amazon Web Services (AWS)
AWS Lambda
AWS X-Ray
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Change Healthcare Data & Analytics
Grafana Cloud
Keras
MXNet
PyTorch
TensorFlow

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/grafana/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/debugger/

Product Features

Product 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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