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Average Ratings 0 Ratings

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ease
features
design
support

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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

Nazar was developed to address the challenges of managing several databases across multi-cloud or hybrid settings. Fully equipped for the primary database engines, it effectively removes the necessity for juggling multiple tools. By providing a standardized and user-friendly method for establishing new servers on the platform, it significantly reduces setup time. Users can obtain a cohesive overview of their database performance on a singular dashboard, eliminating the hassle of interfacing with various tools that offer inconsistent views and metrics. The real competition lies not in the tedious setup, log tracing, or querying of data dictionaries; rather, Nazar leverages the inherent capabilities of the DBMS for monitoring, thus eliminating the need for additional agents. Furthermore, Nazar automates both anomaly detection and root-cause analysis, which leads to a decrease in mean time to resolution (MTTR) while proactively identifying issues to prevent incidents, ensuring optimal application and business performance. With its comprehensive approach, Nazar not only enhances efficiency but also empowers users to focus on strategic initiatives rather than mundane tasks.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon S3
Amazon Simple Notification Service (SNS)

Integrations

AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon S3
Amazon Simple Notification Service (SNS)

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/lookout-for-metrics/

Vendor Details

Company Name

Nazar

Country

Brazil

Website

nazar.io

Product Features

Machine Learning

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

Product Features

Application Performance Monitoring (APM)

Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions

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Alternatives

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