When StackState and XITA organized a breakfast seminar on SRE and AIOps, a few representatives from NS International (NSI) showed up, including Pascal Reijnder, Head of IT. Based in the Netherlands, NSI operates on the busiest railway network in the world and transports about 1.2 million people every day, with annual revenue of five billion euro. In 2012, the rail operator suffered a reputation loss after on-boarding a new high-speed train that, ultimately, never went into long-term operation. The organization needed to change its “mindset” and it set an ambitious goal for itself: to double the number of its international travelers by 2030. Impressed by what they learned at the seminar, NSI teamed up with StackState to help them achieve both.
Double the Number of Travelers
As NSI already had multiple, business-oriented teams in place and was focusing on the customer journey, the collaboration with StackState supported their new mindset. Data analysis and data science became crucial for measuring the indicators and outcomes of experiments and regular business.
Complex Hybrid IT Landscape
Tasked with providing an integrated sales solution, traveling information, data and personalization, logistics and more for all international customers, NSI handles more than one million monthly online visitors. It sells two million online tickets annually and approximately four hundred thousand offline tickets for more than 3,500 destinations across Europe. Its hybrid on-premise and cloud IT landscape are currently monitored by:
- AWS CloudWatch
- Google Analytics (business metrics)
Challenges - Reducing Time to Market
In this complex environment, the growth teams were mainly challenged in shortening the time to market of new initiatives. Platform operations needed to be super-efficient so the majority of the IT resourcing could focus on development inside the DevOps teams instead. To support the rapid experimentation of new initiatives, the DevOps and business-oriented growth teams needed to perfectly align. The following questions had to be answered:
- How to create a shared understanding of the entire IT stack across teams and tools?
- How to create a rapid feedback loop from the business team to the DevOps team?
- How to get more control over critical business processes?
- How to decrease “mean time to discover” and “mean time to repair” for major incidents?
- How to predict the business impact caused by IT: towards pro-active monitoring?
Solution - Rapid Experimenting
While maintaining current monitoring solutions, NS International consolidated all its monitoring data into StackState’s AIOps platform. With this data, StackState AIOps generates full stack visibility and shared understanding across teams and tools. As a result, NSI can now understand how its DevOps and business-oriented growth teams are related, including up- and downstream dependencies.
Google Analytics is integrated into StackState AIOps platform as a top-level business metric. This ensures that the DevOps teams understand the impact they have on important (business) metrics, for example, the impact on tickets sold per hour. StackState deployed their own tracing agent on top of their AIOps platform, to get end-to-end insight and performance analysis—generating the broadest context possible to make faster (business) decisions. The deployment enables rapid experimenting of new initiatives while maintaining stability and business performance throughout the organization, with fast feedback loops across teams. As a result, they minimized downtime and increased revenue.
Client interaction now falls under the purview of growth teams and, supported by seven different DevOps teams, NS International is rapidly experimenting and scaling new solutions to deliver the best customer experience. Pascal Reijnder, head of IT at NS International said, “StackState acts as a lens that focuses our data through a single, cross-domain perspective and analysis. This ensures higher productivity and rapid experimenting across our business- and DevOps teams while maintaining stability and business performance.”
The data from the different sources are used to feed and optimize the StackState AI prediction algorithms. Together with StackState, NS International works towards predictive insights to anticipate and prevent IT outages and speed up its transformation.
Business Impact - Increased Revenue
- 3-4 times increase in DevOps efficiency
- Accelerated root-cause analysis by 90%