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• Monitoring and Observability for Cloud-Native Applications

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• AI-Powered Data Observability & Governance Agent for Cloud Analytics: Transforming Enterprise Data Management

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• Cloud-Native Platform Engineering: Scalable Design Patterns for Global Enterprise Resilience

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• Training Generative AI to Ingest Logs and Detect Anomalies in Large-Scale Applications

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• Self-Healing Infrastructure in CI/CD Pipelines: Automating Resilience in Cloud-Native Applications

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• AI-Assisted Incident Management in SRE: The Role of LLMs and Anomaly Detection

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• Designing High-Throughput FastAPI Gateways for Microservice Communication

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• Cross-Contextual Vision: Architecting Privacy-Preserving Multi-Modal AI Systems for Public Safety and Retail in Mixed Spaces

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• Operationalizing Machine Learning in Regulated Healthcare Systems: A Case Study of Provider Search Engine Deployment

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• Building Resilient Financial Systems: Engineering Practices for the Digital Banking Era

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• Blueprints for Scaling Machine Learning Systems in Ad Technology

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• Centralized VoIP Monitoring Architecture: A Scalable Framework for Real-Time Quality Assurance and Proactive Fault Management in Distributed Telecommunications Networks

  Pardhiva Janardhana Krishna Munnaluru

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• Orchestrating the Chaos: Scalable Event-Driven Architectures for Distributed Ride-Sharing Platforms in Multi-Region Cloud Environments

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• Architecting Real-Time Data Systems: Best Practices for Scalable Integration

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• Cloud-Native Enterprise Integration: Architectures, Challenges, and Best Practices

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• Automation Testing in Microservices and Cloud-Native Applications: Strategies and Innovations

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• Microservices Architecture: A Modern Approach to Cloud-Native Development

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• Demystifying Cloud-Native Architectures – Building Scalable, Resilient, and Agile Systems

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• Real-Time Analytics: Integrating Cloud-Native Data Processing and Warehousing Platforms

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