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What is Memfault?

Memfault enhances the capabilities of Android and MCU-based smartphones, minimizing risks, expediting product launches, and swiftly addressing issues. By incorporating Memfault into the infrastructure of smart devices, developers and IoT manufacturers can efficiently oversee and manage the complete lifecycle of their devices, which encompasses both feature updates and ongoing development. This integration allows for remote monitoring of firmware and hardware performance, the ability to troubleshoot problems from afar, and the phased rollout of targeted updates to devices, all while ensuring minimal disruption to customers. Moreover, the platform provides more than just application monitoring; it delivers comprehensive device and fleet-level insights including battery health, connectivity status, and firmware crash statistics. With automated detection, alerts, and deduplication processes in place, resolving issues becomes significantly more manageable and quicker. Ultimately, customers benefit from a more reliable experience when bugs are rectified promptly, and features are delivered more frequently through organized rollouts tailored to specific device cohorts. Memfault ultimately empowers companies to foster innovation while maintaining customer satisfaction.

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
Golioth
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
Golioth
Keras
MXNet
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Memfault

Date Founded

2018

Company Location

United States

Company Website

memfault.com

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/debugger/

Categories and Features

Industrial IoT

Condition Monitoring
Data Visualization
Factory Data Analytics
Machine Learning
Machine Workflow Creation
Predictive Maintenance
Production Line / Factory Insights
Real-Time Monitoring
Reporting / Analytics
Smart Alerts / Notifications

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

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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