Data Platform Serverless

Modern data platforms now enable the creation of highly scalable infrastructures using serverless components that operate on a pay-as-you-go model. Services like BigQuery on Google Cloud Platform (GCP) and Synapse Analytics on Microsoft Azure allow data processing and analysis on demand, eliminating the need to manage complex underlying infrastructure.

Serverless platforms provide enhanced scalability, automatically adjusting to fluctuating demand. They also reduce upfront costs by eliminating the need for hardware or software license investments, making them particularly beneficial for Small and Medium Enterprises (SMEs) looking to quickly launch their data platform. Additionally, they simplify operational management through tools like PyAirbyte or DLT (open-source data extraction tools) that run on Cloud Run (GCP’s managed container deployment service), automating data integration processes.

However, these solutions come with challenges:

• Costs can increase unpredictably as data volumes grow, making it essential to implement a FinOps strategy to manage operational expenses.
• Vendor lock-in may limit flexibility when migrating or renegotiating contracts with cloud providers.
• Serverless services offer less control over infrastructure, restricting advanced optimization possibilities.

Theodo’s point of view

We recommend that SMEs looking to develop their data platform adopt serverless cloud solutions for their flexibility and fast deployment. However, it is crucial to complement this adoption with a FinOps strategy and rigorous data governance to control costs and ensure data security and quality.