ING Bank Netherlands
ING Bank Netherlands is a global bank with a strong European base, with shares listed in Amsterdam (INGA NA, INGA.AS), Brussels and New York (ADRs: ING US, ING.N). They employ 53,000 employees, serve around 38.4 million customers, corporate clients and financial institutions in over 40 countries. The bank’s products include those of a typical bank, such as savings, loans, mortgages, etc. as well as specialized lending, tailored corporate finance, debt and equity market solutions, payments & cash management and trade and treasury services to wholesale clients. ING Bank Netherlands uses InfluxDB for two distinct use cases.
Use Case 1: The mortgage team at ING Bank Netherlands sought a means of perfecting client experiences and complementing their expertise with metrics. They began moving towards becoming a more data-driven organization, and chose to deploy InfluxDB. The team was able to transition from a pure knowledge- and experience-based diagnostic of anomalies in their production environment, to a metrics-first approach enabled by InfluxDB and the TICK Stack. This transition empowered them to decrease their Mean Time to Resolution (MTTR), discover overbooking in virtual appliances, and much more.
Use Case 2: ING uses the TICK Stack to monitor its application health and has integrated such that their applications will send status metrics directly to InfluxDB. ING created a dashboard in Chronograf with InfluxDB measurements to find anomalies. For specific measurements, ING has created alerts using Kapacitor. which sends notifications through email. The bank uses Telegraf to get-OS related measurements and a few standard applications like RabbitMQ.
ING also utilizes other custom script-based monitoring that uses restAPI to send measurements to InfluxDB. Kapacitor generates events once an incident has occured, and all application metrics sent to InfluxDB are monitored through Chronograf.
Karthigaivelu Sundaramoorthi, an Ops Engineer at ING, likes that InfluxDB is easy to deploy and that the different components (Telegraf, Kapacitor, and Chronograf) integrate well with each other. The query language is very powerful, fetching data quickly and effectively. Centralized management using Chronograf also helps to administer alerts and dashboards effectively. He suggests looking at the documentation for those who don’t know InfluxDB well.
ING Bank Netherlands’ Mortgage team presented at InfluxDays San Francisco 2019. In this talk, they described their learning path with the platform, the cultural challenges of a mature organization facing new processes, and the benefits of resourcing, to reduce their Mean Time To Resolution (MTTR) in practice. They also demonstrated how they moved from an expert-first to a metrics-first approach to diagnosing anomalies in their production environment.
34.8 Million +
Customers, corporate clients and financial institutions served in over 40 countries.
Average number of mortgages sold per week
Visibility has resulted in faster DevOps resolutions
“It was very important that whatever technology decision we made, there [was] an entry strategy and an exit strategy. We have that with InfluxDB.”
- Herminio Vasquez, Machine Learning Engineer, ING Bank Netherlands
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