MedTech

Contextual Ad Intelligence AdTech Platform Migration and Modernization

The client is a leading digital advertising company specializing in real-time contextual ad targeting, and user analytics. Their legacy hybrid/On-prem AdTech infrastructure was struggling to scale with increasing traffic, resulting in latency issues, limited fault tolerance, and operational bottlenecks.

Challenges

High latency (400ms+) in ad serving, impacting user experience and revenue.
Poor scalability during campaign traffic spikes, leading to dropped requests.
Siloed data systems, causing delays in optimization and analytics.
Complex operations with multiple self-managed services across hybrid environments.
High total cost of ownership (TCO) from hardware refresh cycles and manual processes.

Solution

We designed and deployed a scalable, AWS-native AdTech platform to deliver sub-100ms ad response times and real-time analytics. The transformation was executed through a phased approach: Assess → Mobilize → Migrate → Modernize.

  • AWS EKS for auto-scaling AdServer, Trackers, and UserSync workloads.
  • Amazon DynamoDB + DAX for high-speed contextual data retrieval.
  • Amazon RDS (MySQL) for ad configuration with Multi-AZ failover.
  • Amazon MSK (Kafka) for ad event ingestion and reliable data streaming.
  • Databricks + Amazon S3 for event processing and analytics data lake.
  • Snowflake for campaign and performance analytics.
  • AWS Lambda + Amazon SQS for asynchronous cache flush/warm-up workflows.
  • High availability architecture across multiple AZs with failover and disaster recovery strategy.
  • ALB, EKS nodes, RDS MySQL, DAX, and MSK distributed across ≥2 Availability Zones


Third-Party Integrations:

  • Snowflake – Data warehouse for analytics.
  • Databricks – Streaming ETL and data processing.
  • ScyllaDB – Optimization data store.
  • Publisher ad servers and external advertising APIs.

Impact Generated

Low latency ad serving at internet scale.
Elastic scalability during campaign peaks.
Reliable analytics pipeline for optimization and reporting.
Simplified operations through managed AWS services.
Lower costs by replacing hardware with pay-as-you-go cloud model

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