I think this is going to be a pretty contrary comment, let's see how this goes.
I don't know what everyone is doing with kubernetes that takes up so much time and effort, especially in a SME environment.
I'm currently operating three separate kubernetes clusters for three different clients. And this is just me, there are no other tech people involved day-to-day. These clusters require minimal maintenance, just the occasional upgrade.
These clusters are small (1-10 nodes), and are on either GKE or bare metal. The biggest is around 100-200 running pods. I have a CI/CD pipeline setup in GitHub actions for each client. Development & CI uses docker-compose.
I used to do the old-hat 'scp your code to the server' kind of deployment, and this was a lot more pain. Kubernetes is big, but it solves so many problems. Ensuring everything is actually running, networking, SSL certs, persistence, configuration, etc etc.
I've been running this setup for 3+ years now. If I cast my mind back, I think I spent a weekend reading the k8s docs concepts section, then pretty quickly deployed a cluster on GKE. Given it was a team of one, I ditched RBAC which removed some complexity. Getting the CI/CD pipeline setup took some time (maybe a few more days), and I built more tooling as a went.
I really think kubernetes can be really useful for tiny teams, but there is a lot in there that is aimed at big teams. Use the bare minimum possible at first, and grow from there.
---
Now here is a bonus unsolicited contrary comment.
Deploying k8s used to really require a cloud provider, particularly for persistent volumes and load balancing. But I think that has changed over the last few years. OpenEBS and MetalLB look like they are really addressing this.
Also, has anyone noticed that dedicated servers are cheap as chips now? I think the equivalent dedicated server would cost around 10x as much as an AWS instance. (I'm looking at Hetzner in particular, but OVH isn't far behind)
Given what is currently available from the k8s ecosystem, there seems to be a really strong case for deploying on bare metal these days.
For example, at a ballpark you can get a 400GB+/40core cluster for around $300/month (which also includes another 80GB/10cores of ancillary gubbins). The cost for that easily comes in at around $3,000 on AWS (ex any storage).
OpenEBS gives you replicated storage, MetalLB gives you your load balancing, and each instance has a couple of terabytes of NVMe too. And, if you're worried about reliability of physical servers, at that price you could replicate your setup across datacenters at minimal cost.
---
I should add a caveat here. I've been working freelance in tech for 15 years and I am a massive generalist. I do everything from business consulting to design, devops to development, and I also run an ISP so know my way around networking/BGP etc. That being said, setting up a quick cluster on GKE doesn't require many of those skills.
Having written this ambling comment I guess I'll also say that I am am available if anyone wants a cluster setting up. I'm also about to start providing managed k8s services.
I don't know what everyone is doing with kubernetes that takes up so much time and effort, especially in a SME environment.
I'm currently operating three separate kubernetes clusters for three different clients. And this is just me, there are no other tech people involved day-to-day. These clusters require minimal maintenance, just the occasional upgrade.
These clusters are small (1-10 nodes), and are on either GKE or bare metal. The biggest is around 100-200 running pods. I have a CI/CD pipeline setup in GitHub actions for each client. Development & CI uses docker-compose.
I used to do the old-hat 'scp your code to the server' kind of deployment, and this was a lot more pain. Kubernetes is big, but it solves so many problems. Ensuring everything is actually running, networking, SSL certs, persistence, configuration, etc etc.
I've been running this setup for 3+ years now. If I cast my mind back, I think I spent a weekend reading the k8s docs concepts section, then pretty quickly deployed a cluster on GKE. Given it was a team of one, I ditched RBAC which removed some complexity. Getting the CI/CD pipeline setup took some time (maybe a few more days), and I built more tooling as a went.
I really think kubernetes can be really useful for tiny teams, but there is a lot in there that is aimed at big teams. Use the bare minimum possible at first, and grow from there.
---
Now here is a bonus unsolicited contrary comment.
Deploying k8s used to really require a cloud provider, particularly for persistent volumes and load balancing. But I think that has changed over the last few years. OpenEBS and MetalLB look like they are really addressing this.
Also, has anyone noticed that dedicated servers are cheap as chips now? I think the equivalent dedicated server would cost around 10x as much as an AWS instance. (I'm looking at Hetzner in particular, but OVH isn't far behind)
Given what is currently available from the k8s ecosystem, there seems to be a really strong case for deploying on bare metal these days.
For example, at a ballpark you can get a 400GB+/40core cluster for around $300/month (which also includes another 80GB/10cores of ancillary gubbins). The cost for that easily comes in at around $3,000 on AWS (ex any storage).
OpenEBS gives you replicated storage, MetalLB gives you your load balancing, and each instance has a couple of terabytes of NVMe too. And, if you're worried about reliability of physical servers, at that price you could replicate your setup across datacenters at minimal cost.
---
I should add a caveat here. I've been working freelance in tech for 15 years and I am a massive generalist. I do everything from business consulting to design, devops to development, and I also run an ISP so know my way around networking/BGP etc. That being said, setting up a quick cluster on GKE doesn't require many of those skills.
Having written this ambling comment I guess I'll also say that I am am available if anyone wants a cluster setting up. I'm also about to start providing managed k8s services.