Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Minimize false positives and leverage machine learning (ML) to effectively identify anomalies in business performance indicators. Investigate the underlying causes of these anomalies by clustering similar outliers together for analysis. Provide a summary of these root causes and prioritize them based on their impact. Ensure a smooth integration with AWS databases, storage services, and external SaaS platforms for comprehensive metrics monitoring and anomaly detection. Set up automated alerts and responses tailored to the detection of anomalies. Utilize Lookout for Metrics, which employs ML to both discover and analyze anomalies in business and operational datasets. The challenge of recognizing unexpected anomalies is compounded by the limitations of traditional manual methods that are prone to errors. Lookout for Metrics simplifies the detection and diagnosis of data inconsistencies without requiring any expertise in artificial intelligence (AI). Monitor irregular fluctuations in subscriptions, conversion rates, and revenue to remain vigilant about sudden market shifts, ultimately enhancing strategic decision-making capabilities. By adopting these advanced techniques, businesses can improve their overall performance management and response strategies.
Description
Safeguard business service-level agreements by utilizing dashboards that enable monitoring of service health, troubleshooting alerts, and conducting root cause analyses. Enhance mean time to resolution (MTTR) through real-time event correlation, automated incident prioritization, and seamless integrations with IT service management (ITSM) and orchestration tools. Leverage advanced analytics, including anomaly detection, adaptive thresholding, and predictive health scoring, to keep an eye on key performance indicators (KPIs) and proactively avert potential issues up to 30 minutes ahead of time. Track performance in alignment with business operations through ready-made dashboards that not only display service health but also visually link services to their underlying infrastructure. Employ side-by-side comparisons of various services while correlating metrics over time to uncover root causes effectively. Utilize machine learning algorithms alongside historical service health scores to forecast future incidents accurately. Implement adaptive thresholding and anomaly detection techniques that automatically refine rules based on previously observed behaviors, ensuring that your alerts remain relevant and timely. This continuous monitoring and adjustment of thresholds can significantly enhance operational efficiency.
API Access
Has API
Yes
API Access
Has API
No
Integrations
AWS Lambda
Yes
AXYVOR
No
Amazon CloudWatch
Yes
Amazon Redshift
Yes
Amazon S3
Yes
Amazon Simple Notification Service (SNS)
Yes
BlueCat Gateway
No
CloudApper iPaaS
No
CloudFabrix
No
Evolven
No
Integrations
AWS Lambda
No
AXYVOR
Yes
Amazon CloudWatch
No
Amazon Redshift
No
Amazon S3
No
Amazon Simple Notification Service (SNS)
No
BlueCat Gateway
Yes
CloudApper iPaaS
Yes
CloudFabrix
Yes
Evolven
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
Yes
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
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/lookout-for-metrics/
Vendor Details
Company Name
Cisco
Founded
1984
Country
United States
Website
www.splunk.com/en_us/products/it-service-intelligence.html
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
IT Alerting
Alert Noise Reduction
No
Alert Routing
No
Dynamic Notifications
No
Enriched Incident Context
No
Escalation Policies
No
Incident History Audit
No
Multi-User Alerting
No
Multiple Alert Types
No
On-Call Management
No
Rich HTML Email Notifications
No
IT Service
Contract Management
No
IT Asset Management
No
Incident Management
No
Knowledge Management
No
Release Management
No
Self Service Portal
No
Service Catalog
No
Service Reporting
No
Ticket Management
No