Server-less Architecture for Enterprise-level Data Processing
Our client, one of USA’s largest commercial offerings, wanted to implement an organization-wide data strategy with advanced analytics capabilities (people, processes and systems), so they could make data-driven business decisions.
The Knowledge Lens Solution:
Loaded external data sources from various locations such as MoveIT, S3, Oracle/SQL Server, Redshift, SalesForce.
Used Spark's in-memory computation to reduce traditional IO problem and speed up efficiency.
Provided visual layout to all the orchestration processes using Airflow.
Converted existing applications into server-less architecture using AWS Lambda and API Gateway.
Developed multiple traditional engines from ground up, using Spark dataframes.
Benefits and ROI:
Our client could plug the server-less apps as a rest service throughout their domains.
Databricks was used as a Big Data Platform to utilize the integration between compute and storage.
Databricks's custom built run-time Spark environment was utilized to achieve job optimization.