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What is Causely?

The integration of observability with automated orchestration facilitates the creation of self-managing and robust applications on a grand scale. Constantly, a tremendous volume of data is generated from observability and monitoring systems that gather metrics, logs, and traces from all components of complex and evolving applications. Nevertheless, the task of interpreting and troubleshooting this data remains a significant hurdle for humans. They find themselves trapped in an endless cycle of responding to alerts, identifying root causes, and determining appropriate remediation measures. This conventional methodology has not seen fundamental changes over the years, remaining resource-intensive, reactive, and costly. Causely revolutionizes this landscape by removing the necessity for human involvement in troubleshooting, as it effectively captures causality within software, thus linking observability with actionable insights. For the first time, the entire sequence of detecting, analyzing root causes, and rectifying application defects is fully automated. With Causely, issues are identified and resolved in real-time, allowing applications to scale while preserving peak performance. This groundbreaking approach not only boosts operational efficiency but also transforms the way software reliability is established in contemporary environments. As a result, organizations can focus more on innovation rather than being bogged down by persistent technical challenges.

What is Azure Time Series Insights?

Azure Time Series Insights Gen2 stands out as a flexible and all-encompassing analytics platform tailored for IoT, offering users a superior experience along with powerful APIs that facilitate the integration of its innovative features into existing applications or workflows. This platform is designed to handle the entire lifecycle of data—collecting, processing, storing, querying, and visualizing it—specifically targeting the expansive needs of the Internet of Things (IoT), with an emphasis on contextualized data ideal for time series analysis. Whether for exploratory data analysis or operational insights, it equips users with the tools to uncover hidden trends, detect anomalies, and conduct thorough root-cause investigations with ease. Serving as a robust and adaptable solution, it meets the varied demands of industrial IoT applications while promoting scalability and user-friendliness. Moreover, the platform's advanced capabilities can greatly improve decision-making and operational efficiency across multiple industries, ultimately driving better outcomes. In addition, it fosters a data-driven culture, encouraging organizations to leverage insights for continuous improvement.

Media

Media

Integrations Supported

Azure Data Explorer
Azure Marketplace
Kubernetes

Integrations Supported

Azure Data Explorer
Azure Marketplace
Kubernetes

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$36.208 per unit per month
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

Causely

Company Location

United States

Company Website

www.causely.io

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/pricing/details/time-series-insights/#overview

Categories and Features

Container Security

Access Roles / Permissions
Application Performance Tracking
Centralized Policy Management
Container Stack Scanning
Image Vulnerability Detection
Reporting
Testing
View Container Metadata

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