Current trends in the market:
- There is an increase in the footprint of customers that are moving or adopting Kubernetes as a platform.
- The skills shortage around Kubernetes and the cloud-native ecosystem is apparent.
- There is a flourishing community around AI/ML Ops of data scientists, edge and IoT, the traditional virtualization admins, cloud engineers, DevOps engineers, SREs, platform engineers that are pushing for potentially different things or similar things.
- There are not enough maintainers to create what we need to push all industries forward. KubeCon and the Linux Foundation are encouraging more people to contribute and to maintain projects. There are still a large number of projects on CNCF that are evolving to suit the needs of all members of the community.
- The next big evolution is around automation, where what is abstracted is your time, not a layer of manageability.
- With tools, infrastructures, and organizational structures evolving at a rapid pace, there’s a lot of pushback among seasoned IT professionals who don’t want to retrain and learn new skills.
- As soon as people outside of the IT industry start to adopt a piece of technology and actually use it in their own homes, companies will absolutely double-down on that, from an industry point of view.
- ChatGPT, for example, shows the power of what API does and enables automation level. It may help squash the barrier to entry and the learning curve for some of the new technologies.
- Big vendors are bringing out their VR, and their ability to jump into an immersive world only opens up the door for bigger tech firms to do more of that kind of stuff.
In an economic downturn, companies need to:
- mitigate risks because threats around cybersecurity are not going away.
- leverage your data to offer better business outcomes
- understand selling trends and how people use your application.
Kasten by Veeam helps companies by:
- Providing data management services and protection for data within or outside the Kubernetes cluster, as well as the whole Veeam data platform.
- Providing backup and recovery of that data, as well as the ability to clone a copy of that data from the backup, instead of having to use production.
Is there a lot of awareness around AI/ML workloads, data, data recovery, etc.?
Yes. The conversation has started even more so over the last 9 months. KubeCon Detroit’s theme was AI/ML Ops. The release cadence of Kubernetes is 3 per year and each one of those, at least for the last 2-2.5 years, has been focused on data and data at scale.
This summary was written by Camille Gregory.