Fredrik Bekkevold
Principal Developer at Norsk Helsenett
Trondheim, Norway
With 20 years of experience from creating solutions, I have seen a lot. The last 6 years I have worked primarily in healthcare and Fin-Tech. Both domains have similarities and are both seen as complex. By using the right mindset, technology and just being polite, I try to reduce complexity and make things happen. And sometimes great things do happen.
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When securing access to data is about life and death
The Norwegian health care sectors success is dependent on the security and availability of enormous amounts of critical data. The state of affairs is that data does not flow. At Norsk helsenett we have recently started using Kafka to secure this flow.
Our critical data is your critical data, and a matter of life and death. This I how we do that:
- Redundancy to us starts with the number 3, creating the infrastructure and using it to manage "always available" services and data, working towards zero downtime and data loss.
- Security is paramount, how did we implement mTLS?
- How do we monitor and support usage of data we cannot look at using the benefits of .Net and SignalR in Blazor together with Kafka.
Becoming Healthy with Kafka
Our stories from the trenches. Bruises, broken bones, bleeding wounds and how we fixed them using Kafka.
In this talk we will look at some of the problems we have in the health care sector. How we failed, how we fixed it, and what we learned.
Join us for a deep dive into how we help the Norwegian health care sector become healthier with Kafka.
How our critical systems fail, and what we do about it
In the health sector we have lots of life and mission critical systems. Changes must happen, but they cannot happen in a way that puts people's health in jeopardy. We also need to deal with loads of unstructured data which needs to move quickly in various unpredictable patterns. Through trial and error we have learned a lot, and we hope that our experience can be of use to others. Therefore, we want to show how our deployment process ensures that critical systems don't need intensive care immediately upon hitting production.
Using Kubernetes to enable our new untested changes to live side by side with the current. Processing the same data and leveraging Kafka to assess the differences in real time. We have built a system that lets us catch the subtle deviations arising from our organic data and usage without need for rollbacks.
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