docker run -d --rm -p 8080:8080 ghcr.io/sozercan/llama3.1:8b
export OPENAI_ENDPOINT="http://localhost:8080/v1"
export OPENAI_DEPLOYMENT_NAME="llama-3.1-8b-instruct"
export OPENAI_API_KEY="n/a"wget https://github.com/sozercan/kubectl-ai/releases/download/v0.0.13/kubectl-ai_linux_amd64.tar.gz
tar zxf kubectl-ai_linux_amd64.tar.gz
sudo mv kubectl-ai /usr/local/bin/
alias k=kubectlWrite prompt and save result to file
k ai "create deploy redis" --raw > redis-deploy.yaml| NAME | PROMPT | DESCRIPTION | EXAMPLE |
|---|---|---|---|
| app | Create a Kubernetes Pod manifest where should have labels and contain k8s image with expose http port | A basic Pod definition with labels and an exposed HTTP port. | link |
| app-livenessProbe | Create a Kubernetes Pod named "app-livenessprob" in the "demo" namespace using the image "gcr.io/k8s-k3s/demo:v1.0.0" with a liveness probe checking "/" on port 8000 and exposing port 8080 for HTTP | A Pod with a liveness probe and an exposed port in the "demo" namespace. | link |
| app-readinessProbe | Create a Kubernetes Pod named "app-readinessprob" using the image "gcr.io/k8s-k3s/demo:v2.0.0" with liveness and readiness probes checking "/" and "/ready" on port 8000, and exposing port 8000 for HTTP. | A Pod with both liveness and readiness probes, and an exposed HTTP port. | link |
| app-volumeMounts | Create a Kubernetes Pod named "app-volume" using the image "gcr.io/kuar-demo/kuard-amd64:1" with liveness and readiness probes checking "/healthy" and "/ready" on port 8080, exposing port 8080 for HTTP, and mounting the host path "/var/lib/app" to "/data". | A Pod with volume mounts and probes, sharing a volume between containers. | link |
| app-cronjob | Create a Kubernetes CronJob named "app-cronjob" that runs every 5 minutes, using the "bash" image to execute the command echo "Hello world" with a restart policy of "OnFailure". | A CronJob that prints "Hello world" every 5 minutes with an "OnFailure" restart policy. | link |
| app-job | Create a Kubernetes Job named "app-job-rsync" using the "google/cloud-sdk:275.0.0-alpine" image to run sutil, mounting a GCE Persistent Disk to /data/input, and set the restart policy to "Never" with a backoff limit of 0. | A Job for syncing data with gsutil, using a GCE Persistent Disk, and a "Never" restart policy. | link |
| app-multicontainer | Create a Kubernetes Pod named "app-multi-containers" with two containers: the first using the "nginx" image and mounting an empty directory at nginx/html, and the second using the "debian" image, which writes the current date to index.html every second, with both containers sharing the same empty directory volume. | A Pod with multiple containers sharing a volume, where one container serves content and the other updates it regularly. | link |
| app-resources | Create a Kubernetes Pod named "app-resource" using the image "gcr.io/kuar-demo/kuard-amd64:1" with liveness and readiness probes on port 8080, exposing the same port, and specify resource requests of 100m CPU and 128Mi memory, with limits of 100m CPU and 256Mi memory. | A Pod with specified resource requests and limits, including liveness and readiness probes. | link |
| app-secret-env | Create a Kubernetes Pod named "app-secret-env" using the "redis" image, with environment variables SECRET_USERNAME and SECRET_PASSWORD populated from the username and password keys in the mysecret1 secret, and set the restart policy to "Never". | A Pod that uses secret values for environment variables and has a "Never" restart policy. | link |
LLama is smart model but need manual review and fixes. Maybe try another AI or more clearly prompts!?