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DevOps
How Does AWS Cloud Computing Help Businesses Reduce Costs and Optimize Performance?

How Does AWS Cloud Computing Help Businesses Reduce Costs and Optimize Performance?

Contact Center AI

AWS CloudWatch
AWS CloudFormation
AWS-arch
AWS Lambda
AWS EC2
Amazon S3

About project

Callchecker is an AI-powered automation system for call centers, designed to optimize call summarization and quality checks using GPU-based processing and a serverless architecture on AWS.

Tech stack

AWS S3
AWS Lambda
AWS EC2 with GPU
Amazon MQ (RabbitMQ)
AWS CloudWatch &Metrics
AWS CloudFormation
AWS Billing & Cost Management

Team

1 PM
2 DevOps Engineers

Industry

Telecom & Contact Center Solution

Challenges We Solved

Business Challenges

Performance Bottlenecks: The need to provide real-time call analysis on a daily basis to meet business demands and ensure operational efficiency.
High Infrastructure Costs: Expensive GPU costs for AI-heavy workloads. Our focus was on reducing AWS costs while maintaining performance.
Scalability Issues: Difficulty handling increased call volumes without excessive costs. We aimed to help reduce AWS cloud costs by scaling resources dynamically.

Technical Challenges

Costly GPU Servers: Optimizing expensive compute resources to achieve AWS performance and cost optimization best practice.
Task Distribution Problems: Lack of reliable and efficient task processing. We implemented a solution that improved efficiency and optimized performance.
Manual Deployment: Manual management leading to inconsistencies and delays. We automated this process to reduce errors and improve system reliability.

AWS-Powered Solution

Optimized GPU Costs with AWS EC2: By choosing the right AWS EC2 instances for AI tasks and utilizing AWS Lambda for cost performance optimization, we optimized GPU usage and scaled resources dynamically based on demand. This led to significant cost reductions while improving performance and reducing AWS cloud cost.
Reliable Task Distribution with Amazon MQ: We integrated Amazon MQ for asynchronous task processing, ensuring tasks were distributed smoothly and increasing system reliability. This streamlined workflows and improved fault tolerance, contributing to cloud cost optimization.
Automated Infrastructure Management with AWS CloudFormation: Using AWS CloudFormation and GitLab CI/CD, we automated deployment, making the system more scalable, consistent, and error-free. This setup ensured AWS EBS optimized performance and improved resource management across the board.

Key results

Cost Savings: Reduced cloud infrastructure costs by 30-40% and saved 25% annually on GPU-related expenses thanks to AWS-powered solutions, helping reduce cloud costs.
Increased Performance: Throughput increased by 50%, enabling the system to handle 1.5x the previous call volume without additional costs. This was made possible by AWS performance and cost optimization.
Scalability & Reliability: Achieved 99.99% uptime and the ability to scale up to 3x the original capacity, all with seamless service availability, thanks to AWS's serverless and scalable architecture, ensuring AWS optimize performance at scale.

Why AWS Matters

For call centers, efficiency, scalability, and cost optimization are essential. By integrating AWS’s cloud services, we ensured CallChecker was a flexible, high-performance solution that drastically reduces operational costs while improving overall customer experience. This was achieved by applying AWS Lambda cost performance optimization strategies.

Want to optimize your AWS architecture & lower costs?

We specialize in AWS DevOps service, improving AWS performance, and reducing AWS costs. Contact us today for a free audit and get tailored recommendations to optimize your cloud setup!

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