Migrating Analytics Workload from AWS to GCP
SquareShift team has worked closely & extensively with Edcast in migrating their analytics infrastructure from AWS to GCP using Big Query, Cloud Function, API Gateway, Cloud Storage, Cloud Key Management and Confluent Kafka.
Challenge
The client wanted to migrate to a large scale, near-real-time data platform from AWS to GCP to:
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Capture and process millions of user events and metadata from CloudSQL in a near real-time environment.
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Consolidate business data from multiple sources, dedup, and enrich for integration with event data
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Make the data available to customers and data science team self service way
Solution
GCP certified solution architects from SquareShift Technologies worked with the customer and GCP solution architect and designed a blueprint architecture with 100% Serverless components from GCP. A detailed TCO analysis was also done so that the customer is clearly aware about the benefits of GCP serverless architecture.
Results
Customer analytics infrastructure is migrated to GCP and new customers are onboarded. Insights are computed and available to the end users in near real time Internal data science team and external customers can run the adhoc queries using BigQuery in a secured way Usage based cost of BigQuery and CloudFunction reduced the cost overall.
The new serverless analytics infrastructure in GCP helps the customer to save cost and provides near realtime insights. This new system also allows the customer to run AI/ML models to provide deep insights to their customers.
Client

EdCast Inc. (EdCast) is an award-winning, AI-powered Knowledge Cloud for unified discovery and personalized learning.
The company has customers including Fortune 500 companies and governments. The platform helps companies to attract, develop and retain a high-performance and future-ready workforce
Technologies
