Optimizing Cloud Database Performance, High Availability, and Troubleshooting in AWS & Multi-Cloud Environments

This presentation explores my professional experience in cloud database engineering, focusing on troubleshooting, optimizing, and securing large-scale distributed systems. Drawing on my hands-on work with Amazon RDS, Aurora PostgreSQL, MySQL, Oracle, and SQL Server, I discuss how I diagnose performance issues, manage HA/DR, optimize queries, secure cloud workloads, and automate database operations using Python, Shell, and Go. I also highlight database migration strategies across AWS, Azure, and on-prem environments, sharing practical insights into minimizing downtime, handling replication, monitoring infrastructure, and reducing operational overhead through automation. This session provides real-world examples, best practices, and lessons learned from supporting critical production systems in high-pressure enterprise environments.
Who is this presentation for?
• Cloud Engineers and DevOps Engineers • Database Administrators (DBAs) • SRE / Production Engineers • Software Engineers working with data-intensive applications • Students or professionals transitioning into cloud or data engineering roles • Teams responsible for cloud migration, database reliability, or performance tuning
Prerequisite knowledge:
To understand this presentation effectively, the audience should have: • Basic knowledge of cloud platforms (AWS, Azure, or GCP) • Understanding of relational databases and SQL • Familiarity with Linux basics and networking concepts (TCP/IP, DNS, HTTP/S) • Introductory awareness of monitoring tools like CloudWatch, Performance Insights, Prometheus, etc. • Optional but helpful: Experience with scripting (Python/Shell)
What you'll learn?
By the end of this presentation, the audience will learn: Cloud Database Troubleshooting • How to diagnose slow queries, high CPU, WAL issues, deadlocks, and storage problems • Techniques for analyzing PostgreSQL and MySQL performance logs High Availability & Disaster Recovery • Designing Multi-AZ, failover, replication, PITR, snapshot strategies • Understanding Aurora read-replica behavior and replication troubleshooting Performance Optimization • Using pg_stat_statements, indexing, autovacuum tuning, and resource allocation • Identifying performance bottlenecks using CloudWatch and Performance Insights Database Security Best Practices • IAM authentication, SSL/TLS, Secrets Manager integration, RBAC, encryption Automation & DevOps for Databases • Building automation scripts in Python, Shell, and Go • Reducing manual work with automated monitoring, backup, and recovery flows Database Migration Strategies • Migrating databases across on-prem, AWS, and Azure using DMS • Handling schema drift, CDC lag, and downtime planning

My name is Shiva Santosh Allenki, and I am an AWS Cloud Support Engineer with over five years of experience specializing in database management, cloud computing, and advanced troubleshooting. I hold a Master’s degree in Computer Engineering from Texas A&M University–Kingsville with a 3.85 GPA, and a Bachelor’s in Electronics and Communication Engineering from JNTU, India. Throughout my career, I have worked extensively with MySQL, PostgreSQL, Oracle, SQL Server, and Amazon Aurora across AWS, Azure, and hybrid environments. I have a strong background in performance tuning, cloud migrations, security best practices, scripting automation, and high-availability solutions. My professional journey includes roles at Amazon Web Services, Bank of America, UnitedHealth Group, and Children’s Health, where I solved complex system issues, improved performance, and automated mission-critical operations.