Who is DataScan?

DataScan is a financial services company that provides lenders with wholesale asset financing and inventory risk management solutions; their expertise spans 50 clients, more than $80 billion of loan collateral in their systems (Wholesale Intelligence), and over 225,000 audits (Audit Intelligence) conducted per year. It’s part of JM Family Enterprises a 15 billion diversified automotive company identified by Forbes as one of America’s largest private Companies and Best employers. Lenders to automotive dealers and dealerships use Datascan’s Web platform to manage risk and audit inventory loans.

Challenges

Like many infrastructure teams, the engineering team at DataScan is concerned with ensuring uptime of their system close to 100%, keeping customer data secure and their costs down. As a financial service provider, their clients are concerned with data privacy. As a result, DataScan opted for an on-premise environment to protect data and easily identify the device where the data is stored to provide a degree of security for their business partners. 

One of the biggest challenges the engineering team were facing was managing on-premise nodes so they were secure and upgraded with the latest patches and required upgrades. Patching nodes manually was time consuming, resulting in a lot of down time for DataScan’s engineering team.

In addition like many organizations of that size, infrastructure costs are a big concern. Based on their client portfolio size and usage patterns, demands are constantly changing which can become expensive.

“We interviewed several players in the container management space to identify their direction and get a better idea of their capabilities Many of the products fit our requirements, but a few either had a management plan that was not on-premise or had a cost model that was resource usage-based and not a predictable environment based cost model.” Lance Allred, Director of Infrastructure

DataScan decided to move forward with Kubernetes Platform (WKP) across all environments due to it’s flexibility and on-premise Kubernetes capabilities.

“We would recommend WKP which allowed us to own and manage our infrastructure while building a consistent technical bridge to a client-facing cloud presence. Having worked with the Weaveworks client success team for our cluster deployments, service testing, specific use cases to deploy configuration changes and management of in-place upgrades, we are genuinely impressed with their organizational dedication to our success.”

Read the case study to learn how DataScan was able to create secure and consistent Kubernetes platforms for all of their environments which reduced their deployment times and overall costs, while increasing their mean time to recovery and their deployment density.

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