An AI-led Application Management Service leverages artificial intelligence, automation, and analytics services in Azure to modernize traditional application support and maintenance. The solution shifts from reactive issue resolution to predictive, proactive, and self-healing operations, reducing costs, improving performance, and enhancing user experience for all applications hosted in Azure.
- An ITSM platform to enable an Industry standard Governance model for All Apps hosted on Azure Platform
- Setting up a CICD using Azure DevOps and onboarding applications to streamline CI/CD processes across modules in Azure.
- Multilingual Managed service support for SAP & Non-SAP applications to cater to user requests with 24X7 coverage integrated with Azure Monitor, application insights, Azure Monitor Alerts and Log Analytics workspace.
- Integrated operations (L1-L3 support) leveraging BrillioOne.ai- monitoring & management of SAP & Non-SAP applications.
- Built enhanced knowledge repositories & SOP’s for application issues.
- Modernization of SAP applications from legacy applications to Azure cloud.
Highlights:
- Proactive Incident Management: AI models detect anomalies and predict failures using Azure AI and Azure native services before they impact users.
- Self-Healing Automation: Automated remediation scripts reduce MTTR and operational overhead.
- Intelligent Insights: ADAM integrated with Azure Monitor, Log Analytics Workspace, and AI-driven dashboards provide real-time performance and usage analytics using Azure Machine Learning and Azure Cost Management.
- Continuous Optimization: Recommendations for cost savings, performance tuning, scaling, Azure Advisor, Azure Cost Management and AI-based forecasting using ADAM.
- Secure Operations: Integrated with Microsoft Defender and Sentinel for proactive threat detection and compliance monitoring.
Core responsibilities:
- AI led Application Observability
- AI led Application Remediation
- AI led Application Self-healing
Challenges and Opportunities in AMS:
Growing Complexity of Applications - Businesses are seeking AMS providers with expertise in managing complex application ecosystems across Azure Platform, keeping up with the required skills and volume of people is a challenge
AI Driven UX enhancement- Investing in AI-driven AMS capabilities along with power of Azure Services can help organizations to achieve higher user experience with faster resolutions, proactive and predictive services.
AI Driven Cost Optimization & Operational Efficiency - Offering cost-efficient AMS solutions integrated with Azure native services can help Brillio capture a larger share of the market, especially from organizations seeking to reduce operational expenses.
A fully implemented Generative AI enabled AMS workflow can drive ~40% productivity improvements
50% of the value from Gen AI in AMS will be realized in incident management and service request management workflows
GenAI will initially reduce application services spending but drive long-term growth through established use cases.
Solution:
The solution addresses these bottlenecks through six core solution pillars:
- Enhanced Monitoring and Analytics (Azure Monitor, Application Insights and Log Analytics workspace)
- Real-time analytics and insights into application performance and user behavior.
- Actionable insights targeting proactive management and improved decision-making.
- Predictive Maintenance (Azure Monitor Alerts, Azure Performance, Azure Availability)
- ML to predict potential system failures or performance issues before they occur.
- Reduces downtime, minimizes disruptions, and optimizes system reliability
- Intelligent Support and Conversational AI (Azure Managed Services)
- Conversational AI and virtual assistants to handle routine support queries and tasks.
- Enhances user experience, provides 24/7 support, and reduces the workload on human agents.
- Automated Incident Management (Azure Monitoring)
- Intelligent automation for RCA and resolution
- Accelerates issue resolution, reduces manual effort, and improves response times.
- Dynamic & Contextual Product Behaviors (Azure Workload Management and Governance)
- AI algorithms to optimize resource allocation based on application demands and usage patterns.
- Improves efficiency, reduces costs, and ensures optimal performance.
Highlights:
H1: Faster Delivery.: 95% reduction in lead time.
H2: Reliability and service Performance: 40% REDUCTION in Mean Time To Resolve (MTTR)
H3: Availability: 30-40% Application availability and proactive issue prevention lowers business disruption
H4: Unified experience: Enhanced digital experience and reliable applications
The Brillio team will assess the client ecosystem to perform the necessary integrations with the solution.