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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Amazon DevOps Guru leverages machine learning technology to enhance the operational efficiency and reliability of applications. This service identifies unusual behaviors that stray from standard operational patterns, allowing teams to pinpoint potential operational errors before they impact users. By utilizing machine learning models informed by years of data from Amazon.com and AWS Operational Excellence, DevOps Guru can recognize anomalous behaviors in applications, such as spikes in latency, rising error rates, and resource constraints. Furthermore, it plays a crucial role in spotting significant errors that may lead to service disruptions. Upon detecting a critical issue, DevOps Guru promptly issues an alert and supplies a comprehensive summary of the associated anomalies, potential root causes, and contextual information regarding the timing and location of the problem, thereby facilitating quicker resolution and minimizing downtime. This proactive approach not only helps maintain service quality but also empowers teams to respond effectively to incidents.

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 Web Services (AWS)
AWS AI Services
AWS App Mesh
AWS App2Container
AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Change Healthcare Data & Analytics
Keras
MXNet
PyTorch
TensorFlow

Integrations

Amazon Web Services (AWS)
AWS AI Services
AWS App Mesh
AWS App2Container
AWS Lambda
Amazon CloudWatch
Amazon SageMaker
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Change Healthcare Data & Analytics
Keras
MXNet
PyTorch
TensorFlow

Pricing Details

$0.0028 per resource per hour
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/es/devops-guru/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/debugger/

Product Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Machine Learning

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

Product Features

Machine Learning

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

Alternatives