Problem Statement
A leading Real-Time Streaming Analytics Platform provider in the United States was struggling with outdated data pipelines. They were managing an ever-increasing load of 10 million user events per minute, but the legacy system could not keep up. As a result, insight generation lagged, decision-making slowed, and end users occasionally experienced interruptions. Moreover, these inefficiencies increased operational risks and threatened customer satisfaction and business growth.

Therefore, the company urgently needed a scalable, future-ready Real-Time Streaming Analytics Platform that could process millions of events in real time, ensure zero downtime, and provide actionable insights. Additionally, it needed to support advanced analytics and handle future growth seamlessly.

Solution Provided
A Real-Time Streaming Analytics Platform was designed and implemented to overcome these challenges. In addition, it integrated seamlessly with analytics tools such as Google Analytics and BigQuery, providing instant access to actionable insights.

Key components included:

• Visual ETL pipeline to standardize data flows, enrich datasets, and filter data for analytics readiness.
• Blue-green deployment strategy, ensuring zero downtime during system upgrades or feature rollouts.
• Real-time capture of hundreds of user data points, enabling advanced analytics, personalized insights, and smarter decision-making.
• Robust tech stack: AWS (EKS, Redpanda/Kafka, Cassandra, Redis, Elasticsearch), JavaScript, and React.js for high performance, fault tolerance, and scalability.

Tools / Tech Stack

• AWS: EKS, Redpanda/Kafka, Cassandra, Redis, Elasticsearch
• Programming & Frontend: JavaScript, React.js

Results
The Real-Time Streaming Analytics Platform delivered significant business and technical impact. For example, it processed 10 million+ events per minute seamlessly, empowering teams to make instant, data-driven decisions. Additionally, it improved visibility into user engagement and technical performance, enabling quick bottleneck identification and service optimization.

Moreover, workflows were streamlined, reducing manual effort, increasing efficiency, and lowering operational risks. Ultimately, the shift to a modern, resilient architecture positioned the company as a future-ready analytics leader, capable of scaling effortlessly while delivering reliable, real-time insights that enhance customer satisfaction and business agility.