Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Utilize data gathered from current sensors to develop machine learning models tailored to your machinery. Ensure swift and accurate automatic monitoring of equipment that identifies problematic sensors. Speed up the resolution of issues with instant alerts and automatic responses when anomalies are identified. Enhance the effectiveness and precision of alerts by integrating trends in anomalies and user feedback. Amazon Lookout for Equipment serves as a machine learning monitoring solution for industrial machinery, identifying unusual operational behavior so you can respond proactively and prevent unexpected downtime. By automatically recognizing atypical equipment behavior, you can effectively avert unplanned interruptions. Lookout for Equipment systematically evaluates sensor data from your industrial systems to uncover abnormal machine activity. This capability enables you to swiftly identify equipment irregularities, diagnose concerns promptly, and take action to prevent unexpected downtime—all without needing prior machine learning expertise. Furthermore, consistent monitoring ensures that your models remain relevant and effective over time.
Description
Glasnostic seamlessly integrates into the network data path without the need for agents, allowing it to monitor the interaction patterns among various services while identifying anomalies and implementing effective control mechanisms in real-time. The value of visibility diminishes if it is not linked to actionable responses, and Glasnostic empowers engineers to react proactively to system behaviors as they unfold. By embedding transparent controllers within the network data plane, Glasnostic functions like a centralized brain that continuously detects and addresses behaviors instantaneously. Interaction metrics are relayed to the control plane for both storage and the identification of anomalies, facilitating either automated responses or manual interventions. It is compatible with all leading cloud technologies and can seamlessly integrate with existing AIOps, workflow, and security tools through APIs and webhooks. Additionally, Glasnostic is designed to operate across all significant technology stacks, providing a comprehensive view of system behaviors in a holistic, consistent, and omnipresent manner, ensuring that engineers have the insights they need to maintain optimal operational efficiency. As a result, organizations can achieve greater reliability and responsiveness in their IT environments.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
AWS Gateway Load Balancer
No
AWS Marketplace
No
AWS Storage Gateway
No
Amazon S3
Yes
Azure Application Gateway
No
Istio
No
Kubernetes
No
Micromerce
Yes
Integrations
AWS Gateway Load Balancer
Yes
AWS Marketplace
Yes
AWS Storage Gateway
Yes
Amazon S3
No
Azure Application Gateway
Yes
Istio
Yes
Kubernetes
Yes
Micromerce
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
$250 per month
Free Trial
Yes
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/lookout-for-equipment/
Vendor Details
Company Name
Glasnostic
Country
United States
Website
glasnostic.com/product
Product Features
Preventive Maintenance
Condition Monitoring
No
Inspection Management
No
Maintenance Scheduling
No
Mobile Access
No
Predictive Maintenance
No
Purchasing
No
Reminders
No
To-Do List
No
Vendor Management
No
Work Order Management
No