All Case StudyAutonomous Anomaly Detection and Automation in Multi-Cloud Micro-Services environment
Background
Challenges and Opportunities
There were a whole host of challenges faced by our client :
- Inability to detect performance anomalies, in real-time, through monitoring KPIs.
- Maintenance of a Large team to manage the cloud.
- Painfully long durations in root-cause tracing.
- Lack of provision for triggering self-remediation actions.
- Decrease the cost of managing cloud environments.
- Breaking the siloed Domain expertise to boost the ability to support cross domain cloud platforms.
- Minimizing the manual processes that drive cost of management.
- To shift from traditional tools and teams presently used in operations management and optimization of cloud services.
- To extend current automation platforms provisioning and configuration to operations management and optimization.
Our Solution
Here are the essential elements of our solution we built :
- AI-based Automated Anomaly Detection – Our platform provides an automated prediction-based anomaly detection and localization system, capable of detecting performance anomalies of a microservice using machine learning techniques and determining their root-causes using a localization process.
- Remedial Action – The system can intelligently identify remedial actions to fix anomalies based on an intelligent domain experience learning system.
- Intelligent Bot – Anomaly detection and remediation, compliance enforcer, migration assistance, and multi-cloud hope.
- AIops – ML models for anomaly detection and clustering, Natural Language Processing for context awareness, Machine learning driven tracing.
- Integrated data ingestion – from multi cloud environments.
- Integrated CI/CD pipeline analytics and automation of deployment
- Dynamic application tracing across cloud native environments.
- Autonomous Compliance management
Technology Stack
Technology
React Js
ASP.NET
C#
SQL Server
JavaScript
Azure
Agile Methodology
Platform
Web/Desktop
Android
iOS
Impact and Business value
- The value creation via our platform was direct and significant.
- The platform made the management of a multi-cloud environment a breeze.
- There was a reduction in the cost of managing the cloud as it required fewer people to be on the watch.
- Indirect value creation bye prevention of application failure and functioning.
- Seamless user experience due to real-time identification and remediation of issues.
- Greater confidence in launching upgraded as the AI-enabled anomaly detection provided instrumental assistance to the IT team.
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