The Tech Landscape From 2004 to 2020: What changed?

Last week I found the university material from my computer science lectures from 2004. It felt like time travel to some extent because so much changed and computer science learned so much about how best practices may look like.

In the last 16 years, the Tech Landscape changed dramatically. The general bandwidth is increasing while at the same time the costs are shrinking.

Therefore you don’t read “brb” anymore - like in the early years of this millennium. We simply never have to leave the cyber world and can consume the offered content 24/7 for a low price.

Also, it was never that easy to set up the most complex systems from all over the world at any point in time. Therefore the possible business opportunities increased a lot and a good amount of traditional companies lost their share in this digital transformation to new competitors.

But what changed?

You don’t have to become an IT house. The fewer backend servers there are to maintain, the more you can focus on developing your core product instead of worrying about availability and the latest security updates. This is why we strongly advocate for managed third party services instead of traditional self-hosted IT solutions. We leverage cost-effective off-the-shelf managed solutions backed by large cloud providers such as AWS or Azure to ship cost-effective solutions quickly and securely.

Digital design trends change. Your business logic doesn’t need to. Decoupling the customer-facing frontend application using an API-first approach enables us to focus our efforts on building a seamless user experience without being bottlenecked by the development of the core backend logic. Each part of the solution can be developed individually using well-defined API contracts, while also enabling future extensibility.

Built to leverage data. Building the product on top of standard cloud components using an event-driven architecture unlocks access to the full cloud ecosystem. You’ll be ready to leverage powerful cloud features such as Data Lakes, BI analytics, AI product offerings, as well as being able to bring in other vendors to build on top of the foundations we build during the MVP.