I'm diving into Kubernetes for the first time as I plan to set up a GenAI environment. I have a solid grip on Ansible and Docker, including Docker Swarm, so I'm familiar with automating workflows and dealing with containers. My initial plan is to follow these bootstrap steps: 1. Set up bare metal with drivers and necessary packages, 2. Create a minimal infrastructure like a local Docker registry and Python virtual environments, 3. Build applications, including LLM models and Docker images, 4. Deploy and run workloads. From my research, it looks like Kubernetes mainly comes into play during deployment. Am I overlooking anything significant? What do people generally use for the first three steps in a Kubernetes setup? I can transition all these processes with Ansible, including deployment, so why would I let Kubernetes handle that part instead? I'm eager to hear how others view this and where they think Kubernetes excels in the broader DevOps picture.
5 Answers
While some prefer to keep everything inside Kubernetes, it can also work well with external infrastructure. Just remember, when all you have is Kubernetes, everything starts to look like it needs to be in there!
I’ve worked a lot with Ansible, and while Kubernetes is definitely involved more at the deployment phase, it offers abstraction. You don’t just deploy on random hosts anymore; you update manifests directly, which makes scaling and deployments cleaner.
If browsing through tons of guides about Kubernetes hasn’t cleared things up for you, I’d recommend just getting your hands dirty and trying it out yourself!
I’d love some recommended guides focused on bootstrapping solutions in the Kubernetes environment, especially for bare metal setups.
Kubernetes effectively abstracts your infrastructure and deployed applications, which is crucial if you're managing a large environment. It allows for more efficient handling of deployments and scaling, especially when you're running numerous containerized applications.
I totally agree! Kubernetes can manage not only running services but also important tools like Grafana and Prometheus for monitoring.
K8s can start from the very first step of your setup! Tools like Tinkerbell can be used to bootstrap your infrastructure. It’s all about creating a self-healing environment with proper role-based access controls, which is what makes it powerful.
Kubernetes simplifies management across many services and avoids having to SSH into each one. Plus, you deal with replicas and scaling naturally.