Icertis boosts performance over 80 percent and lowers costs on Azure SQL

Udgivet den 8 februar, 2021

Senior Product Marketing Manager, CADD & AI

As customers grow their mission critical workloads, scaling up to manage spiky workloads in house can become an expensive proposition. Icertis, a leading provider of contract lifecycle management in the cloud, had one such workload managing over 7.5 million contracts spanning over a trillion dollars. The Icertis Contract Intelligence (ICI) platform is hosted entirely on Azure, providing their customers with new flexibility and scale to suit any size organization. Managing the growing number of customers and the volatility of daily spikes in database workload demand required manual interventions through an in-house solution that soon proved costly to maintain. Icertis needed an automated solution that could instantly scale when they needed it and chose Azure SQL Database serverless, improving their client query response times by over 80 percent while managing costs better.

Azure SQL Database serverless is a compute tier that optimizes price-performance and simplifies performance management for databases with intermittent, unpredictable usage. Serverless automatically scales compute when needed and pauses during inactive periods. With per-second billing, customers only pay for the compute resources used, potentially saving significant money in the process.

“Billing with serverless is per second, versus per hour using provisioned compute, and scaling up and down is fully automatic. That itself ends up reducing costs, especially given the usage patterns we typically see. In fact, the savings are often around 70 percent versus provisioned compute.” —Monish Darda, CTO, Icertis

With more flexibility and scale with serverless, Icertis is expanding its investments to deliver more AI and machine learning-based services. Join Jeremy Chapman as he speaks with Icertis’ Monish Darda in the latest episode of Microsoft Mechanics and get a customer’s perspective on implementing SQL Database serverless through a hands-on use case. 

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