Optimizing AWS Infra to achieve 99% Uptime for an EdTech Giant - OpsTree Global
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Optimizing AWS Infra to achieve 99% Uptime for an EdTech Giant

The client is a leading education services provider, offering comprehensive resources such as college reviews, exam preparation, and career counseling to over 15 million online users annually.

The Problem Statement

The client was struggling with database performance issues that required optimization, including indexing, query tuning, and sharding strategies to handle growing traffic efficiently. Additionally, their AWS infrastructure was over-provisioned, leading to unnecessary costs and inefficient resource use. Slow API response times were affecting user experience, and frequent service outages demanded a solution to improve system reliability and uptime.

Challenges

The client’s database needed tuning, including indexing, query optimization, and sharding, to handle growing traffic and higher loads efficiently.

The existing AWS setup was over-provisioned, leading to inefficient resource utilization and unnecessary operational costs.

The client experienced slow API performance, affecting user experience and requiring caching, code refactoring, and the use of CDNs to reduce latency.

Regular service outages disrupted operations, calling for a solution to improve reliability, ensure high availability, and increase uptime.

Solutions

The client faced database performance issues requiring optimization strategies like indexing, query tuning, and sharding to handle growing traffic. Over-provisioned AWS infrastructure increased costs and inefficiencies, while slow API response times and frequent outages hurt user experience and reliability.

Implemented advanced query optimization and indexing strategies, enhancing database performance and enabling the system to manage increased loads seamlessly.

Right-sized EC2 instances based on workload requirements, achieving cost savings while improving infrastructure efficiency.

Deployed AWS ElastiCache to cache frequently requested data, significantly reducing API latency and improving overall responsiveness.

Implemented multi-AZ deployments with AWS Elastic Load Balancer, ensuring high availability and fault tolerance, minimizing service disruptions.

Outcomes

50% Cost Efficiency →

Achieved a 50% reduction in AWS costs through strategic optimization, including instance right-sizing and performance tuning, leading to substantial operational savings.

40% Performance Enhancement →

Reduced API response times by an average of 40%, improving application responsiveness and significantly enhancing user experience.

99% Reliability & Uptime →

Achieved 99% uptime by eliminating major outages, providing continuous service availability and reinforcing overall system reliability.

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