June 22, 2021

Dataiku Online’s approach to SaaS

In this edition of Before DevBreak, Louis-Philippe Kronek, the General Manager at Dataiku Online walks us through the solutions they built or bought while creating their product, and how they made those decisions.

SaaSification of the world

From email to repositories, ticket systems to task management, and many other functions, there’s an increased reliance on software-as-a-service tools. With this trend growing, software providers have gradually noticed a change in users’ expectations.

In comparison to legacy software, there’s greater demand for a smooth user experience that requires minimal intervention from IT personnel. There’s also a need for a self-service approach coupled with usage-based pricing.

Another important demand is for SaaS tools to be able to integrate with the wider ecosystem, sharing data and enabling more cohesive workflows with other cloud-native tools.

Dataiku Online’s approach to SaaS

Dataiku started with:

  • Going beyond large organizations to cater to the increasing number of small- and medium-sized enterprises adopting SaaS
  • Offering an enhanced trial experience for clients that could also help in testing new features and gathering feedback

Going forward, Dataiku wants to:

  • Increase readiness, shortening time spent moving from the website to accessing their tool with simplified customisation
  • Improving accessibility for academy and community members
  • Enable the building of complete data flows in days rather than months

The approach to achieving these improvements

Building on the already great and cloud-ready product, Dataiku needed to:

  1. Scale the number of instances run, and volume processed per instance. This would require multi-tenant infrastructure with heightened security, auto-scaling and self-healing capabilities.

They adopted Kubernetes technology, with Amazon Web Services as a provider. Dataiku opted for Amazon EKS instead of running the Kubernetes cluster themselves. They chose this setup because they had limited bandwidth and expertise for this effort, with no evidence of substantial value to be derived from running the Kubernetes themselves.

  1. Offer a self-service counter where clients could manage their access to the service, select appropriate subscriptions and track payments. Dataiku opted for Python as the language to build this element, the Flask framework and Vue.js for the frontend.

This was largely because the self-service counter was a core of the managed experience and they needed to have maximum creative control over it. Additionally, even though the core product wasn’t largely driven by these technologies, they were still widely used at Dataiku.

Furthermore, the initial team was comfortable and familiar with these technologies so it would be easy to ramp up the team if/when need be. They also chose Stripe as a payment gateway and subscription manager since they didn’t have a lot of unique needs in this area that Stripe couldn’t offer.

Where advancement was needed, they were able to migrate to Chargebee for enhanced capabilities.

  1. Have analytics, monitoring and alerting, and security monitoring. Dataiku chose Fullstory for a complete analytics stack, Grafana and Prometheus for deploy monitoring and alerting, and Sqreen for security monitoring.
📹 To get a better understanding of the factors that influence the decision to build or buy solutions when creating products and services, watch the full talk here.

About talent.io and DevBreak

Before DevBreak is a series of live, online, tech talks. Each session features a senior tech expert from an innovative company, who demonstrates how they solved major programming challenges in their business. This series is part of DevBreak, the ultimate 2-day tech festival organised by talent.io.

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