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24/7 Uninterrupted User Experience With Cloud Platform Resilience & Efficient Scaling
About Customer The leading Indian e-commerce company specializes in multi-beauty and personal care products. It houses 1,500+ brands and over 1.8 million products, catering to diverse consumers’ journeys across its platform.
Challenges faced Needed extensive Managed DevSecOps support to decrease the cognitive load of their engineering teams. Given the huge incoming traffic, it was getting difficult to balance platform scaling and cost optimization. Required fine-tuning of Redis for reducing response times during sales, as the high volumes of data being sent overwhelmed Redis, leading to congestion. During the peak sale, they were facing issues with EFK and Kafka which made it difficult to view the logs if any application crashed. Wanted to cut down their time on self managing MongoDB which was cumbersome to manage and usually resulted in downtime while performing any software upgrades. Given the diverse services they were dealing with – alerts from every single component were getting populated which increased the mean time to resolution.
Solutions Implemented Managed multiple AWS services – From rightsizing them to ensuring their optimum performance by analyzing the associated metrics via Cloudwatch. Reduced noisy alerts with intelligent threshold values and managed their precedence during the sale period. Analyzed the root cause of repeated alerts to reduce the MTTR. Set up parallel sending of logs to Amazon S3 alongside Kafka, ensuring no loss of logs. Set up dashboards and alarms of all services on Grafana and Cloudwatch. Categorized alerts on the basis of criticality, source, and service for efficient prioritization and enabling quick action on genuine incidents. Many cost-optimization processes are established. End-to-end management of their Ad tech platform from the planning of resources during sales, logs handling, new services onboarding, and streamlining daily operations. Migration of MongoDB to DocumentDB for eliminating the operational overhead involved with managing underlying infrastructure scaling, updates, etc. Fine-tuned Redis performance by adding shards to the Redis cluster, which optimized the network bandwidth and eliminated congestion — scaled performance effectively during sales. Implemented AWS IAM Policy for fine-grained access controls of workloads. ● ● ● ● ● ● ● ● ● ●
Final Outcomes Dedicated support during the sale for ensuring seamless scale of the platform to maintain high availability. Assessed their business lines for gaps and introduced automated remediation and 360-degree visibility across all services. Real-time dashboard creation for newly created services through automation scripts. Suppressed noisy alerts by priority, alert source, tag, and enabled auto-resolve of non-critical alerts. Fortified defenses with SOC implementation to maintain a robust security posture under high-volume user requests. Prompt incident response and robust governance enabled uninterrupted user experience. .
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