The Client

KLM was established on October 7th, 1919, making it the world’s oldest airline still operating under its original name. Operating out of its home base in Amsterdam, the KLM Group serves its global network with a fleet of 214 aircraft in 2019, employing 33,000 people. In May 2004, Air France and KLM joined forces and is today the largest European airline group: 1 group, 2 airlines, and 3 businesses. Each airline has retained its individual identity, trade name, and brand. The 3 core businesses are Passenger Business, Cargo, and Engineering & Maintenance.

KLM Engineering & Maintenance (E&M). The department is part of Air France Industries KLM Engineering & Maintenance (AFI KLM E&M). Their role is to guarantee the smooth operation of the aircraft. They are classified as a major multi-product MRO (maintenance, repair, overhaul) provider. With a workforce of over 14,000, AFI KLM E&M offers comprehensive technical support ranging from engineering and line maintenance to engine overhaul, aerostructure, and fan thrust reverser support, as well as management, repair, and supply of components backed by a powerful logistics network. They support almost 3,000 aircraft operated by 200 major airlines.

The Project

Organizing a fleet of aircraft is a logistical challenge. KLM needs to ensure that all aircraft are in use as much as possible while safeguarding their proper working condition and foreseeing problems that can occur daily. The managers of the aircraft and parts of the fleet meet frequently (a couple of times a day) to discuss these issues. This is very time consuming and not effective.


  • Java 8, JS, Typescript
  • Spring Boot, Angular 6
  • MongoDB
  • Cloud computing: Pivotal Cloud Foundry
  • Junit
  • GraphQL

The solution for most problems came in the form of a collaboration tool that was easy to understand and use. It also provided a clear picture of the status of the fleet in general and of every specific aircraft. The tool allowed managers to take ownership of the ETR (estimated time of release) faster, thus reducing the need for one-on-one meetings or conference calls. Predictive maintenance was an added bonus afforded by such a tool because it allowed KLM to take preemptive action to ensure that both the health of the aircraft and its usage were optimal.

Sytac helped shape the above concept and designed and delivered it in a timely manner, to the great satisfaction of the KLM. In its design, the project team kept in mind that the tool should be future-proof with low maintenance costs.

Sytac’s experts in integration saw the opportunity to split out data acquisition and analysis from the layer that provides data to the presentation layer. This allowed for a loosely-coupled microservices architecture in which every part of the system has a very specific scoped role. Easy scaling and resilience came out of the box. In the design phase, Sytac selected the following tech stack: GraphQL. Looking at how the domain could be modelled as a series of documents, Sytac opted for fast MongoDB storage. For the backend, Spring Boot with Java 8 was selected as offering proven technology and an open-source industry standard. The frontend was realized in Angular (with Typescript). The data acquisition layer was carried out with Spring Boot and combined with Spring Batch for batch processing. The datasets needing full-text search were implemented in cooperation with the KLM internal Elasticsearch team. All these components were deployed and orchestrated on the Pivotal Cloud foundry selected by KLM as the cloud solution.


The solution provides timely and accurate information about each and every part of the fleet. Whether the aircraft was in operation or on the ground, the managers and KLM could always account for it. This increased the predictability and accountability of the status reports. With notifications options, the users never overlooked an important event in the hectic daily work of an airline.