Julian Fischer, CEO and founder of anynines, feels that 2022 will be an interesting year for Kubernetes, data service automation and the Cloud Foundry ecosystem. He says that although every larger organization has identified the need to use Kubernetes, they still fall short of a central IT strategy on how to use and adopt Kubernetes systematically. “So they’ve learned that using this technology provides a lot of utility, but also creates a lot of questions they don’t have answers for. And a lot of these questions revolve around how to operate a large number of Kubernetes clusters, how to join and connect workloads, and how to abstract from the underlying infrastructure in a meaningful way, while still being able to utilize some of the services of the infrastructure that are highly interesting,” explains Fischer.
Check out the above video to know what else Fischer is setting his sights on for the year ahead.
Swapnil Bhartiya: Hi, this is your host, Swapnil Bhartiya, and welcome to our 2022 predictions series. And we have with us once again, Julian Fischer, CEO and founder of anynines. Julian, it’s good to have you on the show again.
Julian Fischer: Yeah, great to be back. It’s always a pleasure.
Swapnil Bhartiya: Before I ask you to share your predictions, please quickly tell us what anynines is all about.
Julian Fischer: We’re actually a digital transformation company with a strong focus on building application developer platform. So it’s all about developers and their experience and experience in writing and deploying software. We do that with Cloud Foundry with more and more Kubernetes, as well as a lot of data service automation. So it’s about providing people with fully grown solutions managed as well as a distribution.
Swapnil Bhartiya: Excellent. Thank you for telling us about the company. Now it’s time for you to pick your crystal ball and tell us what predictions you have for 2022.
Julian Fischer: Well, due to the focus we have, I think it’s interesting to see what happens in Kubernetes, in data service automation, as well as in the Cloud Foundry ecosystem. We’re constantly talking to our clients and we can see some patterns there. For example, in Kubernetes, we can see that now every larger organization has identified the need to use Kubernetes. They’re already playing with it for quite a while, some of them even for years, and they also have workloads in production. However, they are still lacking a, let’s say, central IT strategy on how to use and adopt Kubernetes systematically.
So they’ve learned that using this technology provides a lot of utility, but also creates a lot of questions they don’t have answers for. And a lot of these questions revolve around how to operate a large number of Kubernetes clusters, how to join and connect workloads, and how to abstract from the underlying infrastructure in a meaningful way, while still being able to utilize some of the, let’s say services of the infrastructure that are highly interesting.
So give you an example, if you have an app, how do you use Kubernetes without touching the underlying infrastructure but at the same time, let’s say consume a speech recognition service that’s rather unique for the infrastructure provider? So we see a lot of problems in that area, resulting from that we can also see if customers have large Cloud Foundry organizations as well. How to connect Kubernetes and Cloud Foundry in a meaningful way. So also when to use Cloud Foundry, when to use Kubernetes, and how to connect the two.
And I think data services are providing a missing link there because they all need to store data and storing data in a way that it’s independent from the underlying infrastructure is if you need or want infrastructure agnosticism key. So in both scenarios, you have to figure out how to do that properly.
And, and my predictions are basically in the Kubernetes ecosystem, a lot will revolve around how to manage a lot of clusters systematically while still preserving some degree of local autonomy to the actual cluster owners. In Cloud Foundry, we can see the adoption of Kubernetes goes on. There was a draft about the future of Cloud Foundry and Kubernetes in April. And this has moved forward, so all of the… or most of the development and engineering capacity in Cloud Foundry has been shifted to move forward with those experiments.
And if you are a bit familiar with Cloud Foundry you’d know that there’s a Cloud Foundry on BOSH, the classic Cloud Foundry stack, Cloud Foundry for virtual machines, there’s KubeCF, and are tooling around it. There’s Cloud Foundry for Kubernetes, and there’s this vision even be more radical about the Kubernetes adoption.
So we get a lot of questions where this whole thing is headed and our opinion here still is classic Cloud Foundry if you have one, or if you need a Cloud Foundry that works at scale, but the Cloud Foundry on Kubernetes vision is so drastically different from the existing Cloud Foundry for Kubernetes that engineering capacity has shifted towards these experiments, which is to some degree a reimplementation, more idiomatic in Kubernetes. Very interesting to see that moving forward, so I think that’s the future for Cloud Foundry and they will definitely make that a pleasant experience I’m sure. So my prediction is that it will move forward while the other solutions, for example, KubeCF and the current implementation of Cloud Foundry for Kubernetes will be stale in the future.
Our last partner at least in the data service automation, we can that if they’re a large centralized IT departments within an organization, the data service automation on virtual machines is actively adopted, adoption continues, which means that people start to trust the automation and that the organizations have learned how to use it. We see usage ramping up, at the same time we see a trend toward so-called micro regions, for example, where Kubernetes clusters… this is Kubernetes territory to some degree. Where there are, let’s say plans or retail shops where there’s IT infrastructure locally in something that’s not a large data center, and they’re still… you want to operate workloads there using cloud tooling.
And in those regions in particular, the adoption of having data services on Kubernetes is very strong. And it also shows that in the broader audience, even in larger data centers, more and more operators are being used in conjunction with Kubernetes and that this is a trend moving forward. We did ourself start developing an operator and we see good adoption here too. I don’t think they solve the same problem, data services on containers and data services on virtual machines. They do have slightly different qualities. And I think that will remain for a while, but we can see that data service automation on Kubernetes gets more momentum.
Swapnil Bhartiya: Julian, thanks for sharing this prediction. Now, if I ask you what is going to be the focus for anynines in 2022? Because as you rightly said a lot of things are changing in this space, so share where we are heading.
Julian Fischer: Yeah, especially the dynamics in the Kubernetes ecosystem are interesting. We can see that the CNCF is growing. We can see that there are more projects and there’s a lot of dynamic in there. And if you combine that with the uncertainty some of these large organizations have and how to adopt Kubernetes in a meaningful way, that’s room where we actually invest a lot of time. So we screen different technologies from the CNCF landscape and put them into our anynines platform as modules so that we can offer clients tailored solutions on let’s say built them application developer stacks that match their particular needs.
We look, for example, into lift and shift projects where all the applications are to be moved out of either physical machines or virtual machines into Kubernetes based deployments. But we also seek new trade field developments where projects are to be operated where Kubernetes can be handy with its particular strength. And our platform modules in this area are a lot of our focus with building new operators but also Kubernetes-based automation around it, including management of dependencies and inter cluster workloads.
Swapnil Bhartiya: Julian, thank you so much for taking time out today and share these predictions and also focus of the company. Thanks for your time today and as usual I look forward to our next discussion. Thank you.
Julian Fischer: And thank you for having me. Have a wonderful Christmas and see you soon.