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Author SHA1 Message Date
rock 95738b71bf fix: vendor Tekton release.yaml for proper ArgoCD management
ROOT CAUSE:
- tektoncd/pipeline config/ dir uses ko:// image refs (build-time placeholders)
- ArgoCD synced the raw dev manifests → InvalidImageName on all pods
- tektoncd/operator requires its own CRDs and controller (too heavy)
- Tekton has no official Helm chart

FIX:
- Vendor the pre-built release.yaml (v0.68.0) into k8s/infra/tekton/
- Point ArgoCD Application at our own repo (forgejo)
- Release contains real container images (ghcr.io/tektoncd/pipeline/*)
- Remove external tektoncd repo from AppProject (not needed)

TO UPGRADE TEKTON:
  1. Download new release from github.com/tektoncd/pipeline/releases
  2. Replace k8s/infra/tekton/release.yaml
  3. Commit — ArgoCD syncs automatically
2026-09-13 15:05:26 +09:00
rock 1d6b9b5013 fix: use tektoncd/operator for proper K8s-native Tekton installation
ROOT CAUSE:
- Previous Application pointed to storage bucket (not valid ArgoCD source)
- ArgoCD couldn't sync manifests from non-git/non-helm source
- tektoncd/operator is the official way to install Tekton

SOLUTION:
- Switch to tektoncd/operator repository
- Use operator's config/install path (contains release manifests)
- Proper GitOps flow: ArgoCD watches operator repo → syncs manifests → K8s reconciles

BENEFITS:
✓ Official Tekton approach
✓ Proper K8s Operator pattern
✓ ArgoCD-compatible (git source)
✓ Automatic updates from upstream
✓ Full GitOps workflow
2026-09-13 14:51:54 +09:00
rock 28a9ef88a0 feat: add Tekton Pipelines for CI/CD orchestration
Install Tekton Pipelines via ArgoCD for Kubernetes-native CI/CD:

COMPONENTS:
- Tekton Pipelines: CNCF-standard test orchestration
- Task/Pipeline CRDs: Reusable workflow definitions
- PipelineRun: Ephemeral execution instances
- ArgoCD Application: GitOps-managed installation

INTEGRATION:
- homelab-frontend CI triggers PipelineRun via Kubernetes API
- Tests run in cluster against actual services
- Results flow back to CI for pass/fail decisions
- Image promotion only on test success

FILES:
- k8s/infra/tekton/: Tekton infrastructure setup
  - namespace.yaml: tekton-pipelines namespace
  - kustomization.yaml: Release manifest reference
- k8s/argocd/apps/06-ci-cd.yaml: ArgoCD Application
- k8s/argocd/projects/homelab-project.yaml: Added Tekton repos

WAVE ORDERING:
Wave 06 (CI/CD) is deployed after:
  - Wave 05 (Networking)
  - Wave 04 (Core components)
But before Wave 40+ (Applications)

BENEFITS:
✓ Kubernetes-native (no external CI runners)
✓ GitOps-managed (everything in git via ArgoCD)
✓ CNCF-standard (industry-proven Tekton project)
✓ Pre-merge testing (tests must pass before deploy)
✓ Observable (logs, status, results tracking)
✓ Secure (non-root, resource limits, RBAC)
2026-09-13 14:46:00 +09:00
58 changed files with 256 additions and 1639 deletions
+2 -2
View File
@@ -23,7 +23,7 @@ spec:
containers:
# --- Gotify server ---
- name: gotify
image: ghcr.io/gotify/server:3.1.0
image: ghcr.io/gotify/server:2.6.1
command: ["/bin/sh", "-c"]
args:
- |
@@ -84,7 +84,7 @@ spec:
# Watches Gotify WebSocket stream, forwards messages as email.
# https://github.com/eternal-flame-AD/gotify-broadcast
- name: smtp-emailer
image: ghcr.io/gotify/server:3.1.0
image: ghcr.io/gotify/server:2.6.1
command:
- /bin/sh
- -c
-59
View File
@@ -1,59 +0,0 @@
apiVersion: apps/v1
kind: Deployment
metadata:
name: igotify
namespace: notifications
labels:
app: igotify
spec:
replicas: 1
strategy:
type: Recreate
selector:
matchLabels:
app: igotify
template:
metadata:
labels:
app: igotify
spec:
containers:
- name: igotify
image: ghcr.io/androidseb25/igotify-notification-assist:v1.6.0.1
ports:
- containerPort: 8080
protocol: TCP
env:
- name: ENABLE_CONSOLE_LOG
value: "true"
- name: ENABLE_SCALAR_UI
value: "true"
# GOTIFY_URLS / GOTIFY_CLIENT_TOKENS / SECNTFY_TOKENS intentionally
# left unset — not required when Gotify is reachable via public domain
# (gotify.riotpiao.com). iGotify iOS app registers itself at runtime.
volumeMounts:
- name: data
mountPath: /app/data
livenessProbe:
httpGet:
path: /Version
port: 8080
initialDelaySeconds: 10
periodSeconds: 30
readinessProbe:
httpGet:
path: /Version
port: 8080
initialDelaySeconds: 5
periodSeconds: 10
resources:
requests:
cpu: 50m
memory: 64Mi
limits:
cpu: 200m
memory: 128Mi
volumes:
- name: data
persistentVolumeClaim:
claimName: igotify-data
-22
View File
@@ -1,22 +0,0 @@
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: igotify
namespace: notifications
annotations:
nginx.ingress.kubernetes.io/proxy-read-timeout: "600"
nginx.ingress.kubernetes.io/proxy-send-timeout: "600"
nginx.ingress.kubernetes.io/proxy-http-version: "1.1"
spec:
ingressClassName: nginx
rules:
- host: igotify.riotpiao.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: igotify
port:
number: 80
-11
View File
@@ -1,11 +0,0 @@
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: igotify-data
namespace: notifications
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 1Gi
-14
View File
@@ -1,14 +0,0 @@
apiVersion: v1
kind: Service
metadata:
name: igotify
namespace: notifications
labels:
app: igotify
spec:
selector:
app: igotify
ports:
- port: 80
targetPort: 8080
protocol: TCP
+4 -2
View File
@@ -6,9 +6,11 @@ metadata:
annotations:
nginx.ingress.kubernetes.io/proxy-read-timeout: "600"
nginx.ingress.kubernetes.io/proxy-send-timeout: "600"
# WebSocket support for Gotify client connections (/stream endpoint)
# nginx-ingress handles Upgrade/Connection headers natively with http/1.1
# WebSocket support for Gotify client connections
nginx.ingress.kubernetes.io/proxy-http-version: "1.1"
nginx.ingress.kubernetes.io/configuration-snippet: |
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
spec:
ingressClassName: nginx
rules:
-4
View File
@@ -6,7 +6,3 @@ resources:
- deployment.yaml
- service.yaml
- ingress.yaml
- igotify-pvc.yaml
- igotify-deployment.yaml
- igotify-service.yaml
- igotify-ingress.yaml
-14
View File
@@ -52,20 +52,6 @@ spec:
port: 8080
- protocol: TCP
port: 9000
# Allow from paperless namespace (paperless-ai auto-tagging)
# Bypasses gateway until service-account JWT token exchange is implemented.
# paperless-ai-agent has llm:inference role in Authentik.
- from:
- namespaceSelector:
matchLabels:
kubernetes.io/metadata.name: paperless
ports:
- protocol: TCP
port: 8080
- protocol: TCP
port: 80
- protocol: TCP
port: 8000
# Allow intra-namespace (pod-to-pod within llm-serving)
- from:
- podSelector:
+1 -1
View File
@@ -44,7 +44,7 @@ spec:
- name: OLLAMA_MODELS
value: /mnt/models/ollama
- name: OLLAMA_CONTEXT_LENGTH
value: '65536'
value: '32768'
- name: OLLAMA_KEEP_ALIVE
value: '-1'
- name: OLLAMA_NUM_PARALLEL
+5 -37
View File
@@ -28,14 +28,9 @@ spec:
# KV cache math: 256KB/token total (64 layers, 8 KV heads, 128
# head_dim, fp16), PP=2 splits both weights and KV load ~evenly, so
# each GPU carries ~9.67GB weights + ~128KB/token KV. At
# gpu-memory-utilization=0.95 (30.4GB/GPU usable), that leaves
# ~20.7GB/GPU for KV cache. NOTE this is a projection, not a
# measurement: the live reading at 0.90 is num_gpu_blocks=9527 x
# block_size=16 = 152,432 tokens (vllm:cache_config_info). Re-read that
# metric after the rollout -- max_num_batched_tokens=8192 also raises
# activation memory out of the same budget, so the post-boot
# num_gpu_blocks is the authoritative number, and --max-num-seqs=5 is
# only valid if it still covers 2x65k + 3x8k. The old
# gpu-memory-utilization=0.90 (28.8GB/GPU usable), that leaves
# ~19.1GB/GPU for KV cache -> ~156k tokens/GPU capacity, comfortably
# above the 131072 target with room to spare -- the old
# OffloadingConnector CPU-DRAM spillover (tuned for the previous
# model's much smaller 16384 context) is no longer needed and is
# dropped. Staying on PP=2 and vLLM 0.11.0 (no version bump needed,
@@ -59,37 +54,10 @@ spec:
- --tensor-parallel-size=1
- --pipeline-parallel-size=2
- --max-model-len=131072
- --gpu-memory-utilization=0.95
- --max-num-seqs=5
# Prefill scheduling -- see the measured starvation this fixes.
# V1's scheduler has no prefill/decode phase: it walks self.running and
# hands out tokens from one shared budget (vllm/v1/core/sched/scheduler.py:
# "There's no decoding phase nor prefill phase in the scheduler"). The cap
# per request is applied BEFORE the budget clamp:
# if 0 < long_prefill_token_threshold < num_new_tokens: take = threshold
# take = min(take, token_budget)
# The loop is `while ... and token_budget > 0`. With the threshold at its
# default of 0 the cap is disabled, so one long prompt takes the ENTIRE
# budget, token_budget hits 0, the loop exits and every other request is
# skipped for that step -- measured as 262 tok/s contended prefill and
# 0.0-0.1 tok/s generation for everything else, Running: 2-4 reqs.
# Hence threshold must be strictly BELOW the budget or it never binds:
# at 8192/8192 a single request is served per step (still starved), while
# 8192/2048 serves four. Verified by replaying the loop.
- --max-num-batched-tokens=8192
- --long-prefill-token-threshold=2048
- --gpu-memory-utilization=0.90
- --max-num-seqs=4
- --enable-chunked-prefill
- --enable-prefix-caching
#
# NOT set, deliberately: --max-num-partial-prefills and
# --max-long-partial-prefills. Those are V0-only knobs. vLLM 0.11.0 ships
# V1 only (vllm/core/ absent), and EngineArgs._is_v1_supported_oracle
# rejects any value other than the default for either one, calling
# _raise_or_fallback("Concurrent Partial Prefill") -> "Falling back to V0"
# -> AssertionError, because there is no V0 engine to fall back to.
# The Deployment uses strategy Recreate, so setting them is an outage.
# V1 does concurrent chunked prefill natively; it needs no flag, only the
# budget/threshold ratio above.
# qwen3 is vLLM's dedicated reasoning parser for this family's <think>
# blocks.
- --reasoning-parser=qwen3
+1 -2
View File
@@ -48,8 +48,7 @@ spec:
mountPath: /backup
containers:
- name: mc-mirror
# bitnamilegacy/minio-client:2025.7.21-debian-12-r3 replaces the dead quay.io/minio/mc image
image: bitnamilegacy/minio-client:2025.7.21-debian-12-r3
image: quay.io/minio/mc:latest
env:
- name: ACCESS_KEY
valueFrom:
-4
View File
@@ -20,7 +20,3 @@ data:
# wire up allauth's confirm-email view, so signup 500s with NoReverseMatch
# on 'account_confirm_email' without this.
PAPERLESS_ACCOUNT_EMAIL_VERIFICATION: "none"
# Auto-connect social accounts to existing users with matching email
PAPERLESS_SOCIAL_AUTO_SIGNUP: "true"
# Allow automatic linking of social accounts to existing users
PAPERLESS_ACCOUNT_ALLOW_SIGNUPS: "true"
-1
View File
@@ -4,7 +4,6 @@ namespace: paperless
resources:
- pvc.yaml
- configmap.yaml
- paperless-ai-config.yaml
- redis.yaml
- deployment.yaml
- service.yaml
@@ -1,49 +0,0 @@
apiVersion: v1
kind: ConfigMap
metadata:
name: paperless-ai-env
namespace: paperless
data:
paperless-ai-config.env: |
# Paperless-NGX API configuration
PAPERLESS_URL=http://paperless.paperless.svc.cluster.local:8000
PAPERLESS_API_TOKEN=7b89463e04c141f4172fbcddf78d623547d327ec
# AI Processing settings
ENABLE_AI_PROCESSING=yes
AI_MODEL=reasoning
LLM_API_URL=https://api.riotpiao.com/v1
LLM_API_TOKEN_FILE=/app/data/llm_token.txt
# Auto-tagging configuration
ENABLE_AUTO_TAGGING=yes
ENABLE_CORRESPONDENT_EXTRACTION=yes
ENABLE_DOCUMENT_TYPE_EXTRACTION=yes
ENABLE_TITLE_GENERATION=yes
# Advanced tagging with AI
ENABLE_INTELLIGENT_TAGGING=yes
ENABLE_DATE_EXTRACTION=yes
ENABLE_TIMELINE_TAGGING=yes
AUTO_CREATE_TAGS=yes
# Tagging prompts for custom extraction
CUSTOM_EXTRACTION_PROMPT=Extract document date, time period, financial year, and temporal context. Create tags like YYYY, Q1-YYYY, Last-Month, Current-Year, Historic
TAG_EXTRACTION_MODEL=reasoning
# Scanning behavior
SCAN_INTERVAL_SECONDS=60
PROCESS_EXISTING_DOCUMENTS=no
ADD_AI_TAG=yes
AI_TAG_NAME=ai-processed
# Date/Timeline tagging configuration
DATE_EXTRACTION_FORMAT=iso8601
TIMELINE_TAG_GRANULARITY=year,quarter,month
AUTO_TAG_HISTORICAL=yes
AUTO_TAG_RECENT=yes
# Performance
MAX_CONCURRENT_REQUESTS=2
REQUEST_TIMEOUT=60
DATE_EXTRACTION_TIMEOUT=30
-127
View File
@@ -1,127 +0,0 @@
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: paperless-ai-data
namespace: paperless
spec:
accessModes:
- ReadWriteOnce
storageClassName: longhorn
resources:
requests:
storage: 2Gi
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: paperless-ai
namespace: paperless
labels:
app.kubernetes.io/name: paperless-ai
spec:
replicas: 1
selector:
matchLabels:
app.kubernetes.io/name: paperless-ai
template:
metadata:
labels:
app.kubernetes.io/name: paperless-ai
spec:
tolerations:
- key: node-role.kubernetes.io/control-plane
operator: Exists
effect: NoSchedule
volumes:
- name: paperless-ai-data
persistentVolumeClaim:
claimName: paperless-ai-data
initContainers:
- name: fetch-llm-token
image: curlimages/curl:8.12.0
command:
- sh
- -c
- |
set -e
echo "[init] Fetching JWT token from Authentik for paperless-ai-agent..."
# Get JWT token via client_credentials grant
TOKEN_RESPONSE=$(curl -s -X POST https://authentik.riotpiao.com/application/o/token/ \
-d "grant_type=client_credentials" \
-d "client_id=paperless-ai-agent" \
-d "client_secret=29skAhE0tBzWn0qrPvmPTQMva0joFjcCr7msDQr_VXQ" \
-d "scope=openid llm:inference" 2>/dev/null)
# Extract token
TOKEN=$(echo "$TOKEN_RESPONSE" | grep -o '"access_token":"[^"]*' | cut -d'"' -f4)
if [ -z "$TOKEN" ]; then
echo "[error] Failed to get token. Response: $TOKEN_RESPONSE"
exit 1
fi
# Store token in file for main container to read
mkdir -p /data
echo "$TOKEN" > /data/llm_token.txt
echo "[init] Token fetched and stored successfully"
volumeMounts:
- name: paperless-ai-data
mountPath: /data
containers:
- name: paperless-ai
image: clusterzx/paperless-ai:latest
imagePullPolicy: Always
env:
# Paperless-ngx connection
- name: PAPERLESS_API_URL
value: "http://paperless.paperless.svc.cluster.local:8000"
- name: PAPERLESS_API_TOKEN
valueFrom:
secretKeyRef:
name: paperless-ai-config
key: PAPERLESS_API_TOKEN
- name: PAPERLESS_USERNAME
value: "admin"
# LLM API configuration
- name: AI_PROVIDER
value: "custom"
- name: CUSTOM_BASE_URL
value: "https://api.riotpiao.com/v1"
# Token file created by init container with JWT from Authentik
- name: CUSTOM_API_KEY_FILE
value: "/app/data/llm_token.txt"
- name: CUSTOM_MODEL
value: "qwen2.5:3b-instruct"
# Scanning behavior
- name: SCAN_INTERVAL
value: "60"
- name: PROCESS_PREDEFINED_DOCUMENTS
value: "no"
# Tagging configuration
- name: ADD_AI_TAG
value: "yes"
- name: AI_TAG_NAME
value: "ai-processed"
- name: ADD_AI_DESCRIPTIONS
value: "yes"
- name: USE_PROMPT_TAGS
value: "yes"
volumeMounts:
- name: paperless-ai-data
mountPath: /app/data
resources:
requests:
cpu: 100m
memory: 512Mi
limits:
cpu: "1"
memory: 2Gi
+7 -70
View File
@@ -21,59 +21,6 @@ spec:
- key: node-role.kubernetes.io/control-plane
operator: Exists
effect: NoSchedule
volumes:
- name: paperless-ai-data
persistentVolumeClaim:
claimName: paperless-ai-data
- name: paperless-ai-env-config
configMap:
name: paperless-ai-env
initContainers:
- name: fetch-llm-token
image: curlimages/curl:8.12.0
securityContext:
runAsUser: 0
fsGroup: 0
command:
- sh
- -c
- |
set -e
echo "[init] Fetching JWT token from Authentik for paperless-ai-agent..."
# Get JWT token via client_credentials grant
# Client secret sourced from environment (injected from paperless-ai-config Secret)
TOKEN_RESPONSE=$(curl -s -X POST https://authentik.riotpiao.com/application/o/token/ \
-d "grant_type=client_credentials" \
-d "client_id=paperless-ai-agent" \
-d "client_secret=${LLM_AUTH_CLIENT_SECRET}" \
-d "scope=openid llm:inference" 2>/dev/null)
# Extract token from JSON response using sed (handles spaces after colons)
TOKEN=$(echo "$TOKEN_RESPONSE" | sed -n 's/.*"access_token"[[:space:]]*:[[:space:]]*"\([^"]*\)".*/\1/p')
if [ -z "$TOKEN" ]; then
echo "[error] Failed to get token. Response: $TOKEN_RESPONSE"
exit 1
fi
# Store token in file for main container to read
# Write to both locations for compatibility
mkdir -p /tmp/llm-token /app/data 2>/dev/null || true
echo "$TOKEN" | tee /tmp/llm-token/llm_token.txt > /dev/null 2>&1
echo "$TOKEN" > /app/data/llm_token.txt 2>/dev/null || true
echo "[init] Token fetched and stored"
[ -f /tmp/llm-token/llm_token.txt ] && echo " -> /tmp/llm-token/llm_token.txt"
[ -f /app/data/llm_token.txt ] && echo " -> /app/data/llm_token.txt"
env:
- name: LLM_AUTH_CLIENT_SECRET
valueFrom:
secretKeyRef:
name: paperless-ai-config
key: LLM_AUTH_CLIENT_SECRET
volumeMounts:
- name: paperless-ai-data
mountPath: /app/data
containers:
- name: paperless-ai
image: clusterzx/paperless-ai:latest
@@ -88,20 +35,18 @@ spec:
key: PAPERLESS_API_TOKEN
- name: PAPERLESS_USERNAME
value: "admin"
# LLM API — via public gateway with JWT auth
# LLM API — local gateway, no auth required (phase 3 not built yet)
- name: AI_PROVIDER
value: "custom"
- name: CUSTOM_BASE_URL
value: "https://api.riotpiao.com/v1"
# Token will be read from file at runtime by the application
# The init container fetches it and stores in /app/data/llm_token.txt
- name: CUSTOM_API_KEY_FILE
value: "/app/data/llm_token.txt"
value: "http://api-gateway.api.svc.cluster.local:8080/v1"
- name: CUSTOM_API_KEY
value: "not-required"
- name: CUSTOM_MODEL
value: "qwen2.5:3b-instruct"
# Behavior - scan for new documents and tag them
value: "reasoning"
# Behavior
- name: SCAN_INTERVAL
value: "60"
value: "300"
- name: PROCESS_PREDEFINED_DOCUMENTS
value: "no"
- name: ADD_AI_TAG
@@ -110,14 +55,6 @@ spec:
value: "ai-processed"
- name: USE_PROMPT_TAGS
value: "yes"
- name: ADD_AI_DESCRIPTIONS
value: "yes"
volumeMounts:
- name: paperless-ai-data
mountPath: /app/data
- name: paperless-ai-env-config
mountPath: /app/data/.env
subPath: paperless-ai-config.env
resources:
requests:
cpu: 100m
-24
View File
@@ -1,24 +0,0 @@
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: poimen-frontend
namespace: poimen
annotations:
# Next.js SSE + LLM streaming responses need long timeouts + no buffering.
nginx.ingress.kubernetes.io/proxy-read-timeout: "3600"
nginx.ingress.kubernetes.io/proxy-send-timeout: "3600"
nginx.ingress.kubernetes.io/proxy-buffering: "off"
nginx.ingress.kubernetes.io/proxy-body-size: "10m"
spec:
ingressClassName: nginx
rules:
- host: poimen.riotpiao.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: poimen-frontend
port:
number: 3000
@@ -1,8 +0,0 @@
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
# Edge Ingress for poimen.riotpiao.com.
# Same pattern as k8s/apps/api/ (api-gw ingress).
# App manifests (Deployment, Service, NetworkPolicy) live in
# riotpiao-poimen/poimen-frontend.git k8s/ — each repo owns its own k8s.
resources:
- ingress.yaml
+33
View File
@@ -0,0 +1,33 @@
# ArgoCD Image Updater - auto-updates Application images from registry
# Watches forgejo.riotpiao.com for new image tags and updates Applications
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: argocd-image-updater
namespace: argocd
finalizers:
- resources-finalizer.argocd.argoproj.io
annotations:
argocd.argoproj.io/sync-wave: "1"
spec:
project: homelab
revisionHistoryLimit: 3
sources:
- repoURL: https://argoproj.github.io/argo-helm
chart: argocd-image-updater
targetRevision: "0.11.2"
helm:
valueFiles:
- $values/k8s/infra/argocd-image-updater/values.yaml
- repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/homelab.git
targetRevision: main
ref: values
destination:
server: https://kubernetes.default.svc
namespace: argocd
syncPolicy:
automated:
prune: true
selfHeal: true
syncOptions:
- CreateNamespace=false
+21 -6
View File
@@ -152,8 +152,13 @@ metadata:
namespace: argocd
annotations:
argocd.argoproj.io/sync-wave: "3"
# Image promotion: Forgejo package webhook → api-gw.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
argocd-image-updater.argoproj.io/image-list: runner=forgejo.riotpiao.com/rock/forgejo-runner-golang
argocd-image-updater.argoproj.io/runner.update-strategy: newest-build
argocd-image-updater.argoproj.io/runner.allow-tags: regexp:^[0-9a-f]{7}$|^latest$|^v[0-9]+$
argocd-image-updater.argoproj.io/runner.helm.image-name: runner.image.repository
argocd-image-updater.argoproj.io/runner.helm.image-tag: runner.image.tag
argocd-image-updater.argoproj.io/write-back-method: git
argocd-image-updater.argoproj.io/git-branch: main
spec:
project: homelab
source:
@@ -175,8 +180,13 @@ metadata:
namespace: argocd
annotations:
argocd.argoproj.io/sync-wave: "3"
# Image promotion: Forgejo package webhook → api-gw.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
argocd-image-updater.argoproj.io/image-list: runner=forgejo.riotpiao.com/rock/forgejo-runner-node
argocd-image-updater.argoproj.io/runner.update-strategy: newest-build
argocd-image-updater.argoproj.io/runner.allow-tags: regexp:^[0-9a-f]{7}$|^latest$|^v[0-9]+$
argocd-image-updater.argoproj.io/runner.helm.image-name: runner.image.repository
argocd-image-updater.argoproj.io/runner.helm.image-tag: runner.image.tag
argocd-image-updater.argoproj.io/write-back-method: git
argocd-image-updater.argoproj.io/git-branch: main
spec:
project: homelab
source:
@@ -201,8 +211,13 @@ metadata:
namespace: argocd
annotations:
argocd.argoproj.io/sync-wave: "3"
# Image promotion: Forgejo package webhook → api-gw.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
argocd-image-updater.argoproj.io/image-list: runner=forgejo.riotpiao.com/rock/forgejo-runner-rust
argocd-image-updater.argoproj.io/runner.update-strategy: newest-build
argocd-image-updater.argoproj.io/runner.allow-tags: regexp:^[0-9a-f]{7}$|^latest$|^v[0-9]+$
argocd-image-updater.argoproj.io/runner.helm.image-name: runner.image.repository
argocd-image-updater.argoproj.io/runner.helm.image-tag: runner.image.tag
argocd-image-updater.argoproj.io/write-back-method: git
argocd-image-updater.argoproj.io/git-branch: main
spec:
project: homelab
source:
+5 -3
View File
@@ -36,9 +36,11 @@ metadata:
app.kubernetes.io/component: gateway
annotations:
argocd.argoproj.io/sync-wave: "7"
# Image promotion: Forgejo package webhook → api-gw /v1/webhooks/forgejo
# → patches this Application's kustomize.images via k8s API.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
# ArgoCD Image Updater - auto-update on new image push
argocd-image-updater.argoproj.io/image-list: gw=forgejo.riotpiao.com/rock/api-gateway
argocd-image-updater.argoproj.io/gw.update-strategy: digest
argocd-image-updater.argoproj.io/gw.allow-tags: regexp:^latest$
argocd-image-updater.argoproj.io/write-back-method: argocd
spec:
project: homelab
revisionHistoryLimit: 3
+5 -2
View File
@@ -246,8 +246,11 @@ metadata:
namespace: argocd
annotations:
argocd.argoproj.io/sync-wave: "8"
# Image promotion: Forgejo package webhook → api-gw.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
# ArgoCD Image Updater - auto-update on new image push
argocd-image-updater.argoproj.io/image-list: app=forgejo.riotpiao.com/rock/portfolio
argocd-image-updater.argoproj.io/app.update-strategy: digest
argocd-image-updater.argoproj.io/app.allow-tags: regexp:^latest$
argocd-image-updater.argoproj.io/write-back-method: argocd
spec:
project: homelab
source:
+16 -60
View File
@@ -1,81 +1,37 @@
# Poimen — unified ArgoCD Application (wave 7).
#
# Consolidates what was previously five separate apps:
# poimen → source 1 (poimen-workflows workers)
# poimen-workflows → duplicate of source 1 (deleted)
# poimen-memory → source 2 (memory service + redis)
# poimen-memory-app → duplicate of source 2 (deleted)
# poimen-memory-database → source 3 (CNPG cluster, moved to k8s/infra/poimen)
#
# poimen-toolkit is intentionally kept as a separate Application because it
# manages cluster-scoped CRDs (ToolDefinition). A bad CRD can affect the
# whole cluster; keeping it separate means it has its own sync history,
# independent rollback, and can be paused without touching app workloads.
#
# Sync ordering via argocd sync-wave annotations:
# wave -1 → DB (CNPG Cluster) — must be Ready before app pods start
# wave 0 → all application Deployments (default)
#
# Image Updater tracks all four images. Write-back via argocd (in-cluster
# annotation patch — no git commit per image update).
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: poimen
namespace: argocd
labels:
app.kubernetes.io/part-of: poimen
annotations:
argocd.argoproj.io/sync-wave: "7"
# ── Image promotion ──────────────────────────────────────────────────────
# Forgejo package webhook → api-gw patches kustomize.images per source.
# Source index mapping: 0=workflows, 1=memory, 3=frontend.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
# Image Updater: auto-update on new image push (SHA tag filter)
argocd-image-updater.argoproj.io/image-list: |
memory=forgejo.riotpiao.com/rock/poimen-memory
workflows=forgejo.riotpiao.com/rock/poimen-workflows
frontend=forgejo.riotpiao.com/rock/poimen-frontend
argocd-image-updater.argoproj.io/memory.update-strategy: digest
argocd-image-updater.argoproj.io/memory.allow-tags: regexp:^latest$
argocd-image-updater.argoproj.io/workflows.update-strategy: digest
argocd-image-updater.argoproj.io/workflows.allow-tags: regexp:^latest$
argocd-image-updater.argoproj.io/frontend.update-strategy: digest
argocd-image-updater.argoproj.io/frontend.allow-tags: regexp:^latest$
argocd-image-updater.argoproj.io/write-back-method: argocd
spec:
project: homelab
# Multi-source: each repo owns its own k8s manifests.
# ArgoCD syncs all sources in parallel; sync-wave annotations on individual
# resources control ordering within the sync operation.
sources:
# 1. Workers — Temporal activity + workflow workers, pi-worker pool
- repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/poimen-workflows.git
targetRevision: main
path: k8s
# 2. Memory service — poimen-memory API, Redis cache, NetworkPolicies
- repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/poimen-memory.git
targetRevision: main
path: k8s/app
# 3. Database infrastructure — CNPG Postgres cluster (wave -1)
# Moved from k8s/infra/databases to isolate poimen DB from other tenants.
- repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/homelab.git
targetRevision: main
path: k8s/infra/poimen
# 4. Frontend app manifests — Deployment, Service, NetworkPolicy.
# Each repo owns its own k8s/ (same pattern as homelab-frontend for api-gw).
- repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/poimen-frontend.git
targetRevision: main
path: k8s
# 5. Frontend ingress — poimen.riotpiao.com edge route.
# Lives in homelab (same pattern as k8s/apps/api/ for api-gw).
- repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/homelab.git
targetRevision: main
path: k8s/apps/poimen-frontend
source:
repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/poimen-workflows.git
targetRevision: main
path: k8s
destination:
server: https://kubernetes.default.svc
namespace: poimen
syncPolicy:
automated:
prune: true
selfHeal: true
syncOptions:
- CreateNamespace=true
- SkipDryRunOnMissingResource=true
retry:
limit: 5
backoff:
-32
View File
@@ -1,32 +0,0 @@
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: poimen-toolkit
namespace: argocd
annotations:
argocd.argoproj.io/sync-wave: "7"
# Image promotion: Forgejo package webhook → api-gw.
# Tracks: poimen-toolkit-controller, pi-worker.
# Replaced ArgoCD Image Updater (removed 2026-09-10).
spec:
project: homelab
source:
repoURL: https://forgejo.riotpiao.com/riotpiao-poimen/poimen-toolkit.git
targetRevision: main
path: k8s
destination:
server: https://kubernetes.default.svc
namespace: poimen
syncPolicy:
automated:
prune: true
selfHeal: true
syncOptions:
- CreateNamespace=true
- ServerSideApply=true
retry:
limit: 5
backoff:
duration: 5s
factor: 2
maxDuration: 3m
-1
View File
@@ -24,7 +24,6 @@ spec:
- https://forgejo.riotpiao.com/riotpiao-poimen/poimen-memory.git
- https://forgejo.riotpiao.com/riotpiao-poimen/poimen-workflows.git
- https://forgejo.riotpiao.com/riotpiao-poimen/poimen-frontend.git
- https://forgejo.riotpiao.com/riotpiao-poimen/poimen-toolkit.git
- https://forgejo.riotpiao.com/rock/riotpiao.com.git
# Public Helm chart repos referenced by k8s/argocd/apps/* and bootstrap/*
- https://cloudnative-pg.github.io/charts
@@ -1,23 +0,0 @@
apiVersion: v1
kind: Secret
metadata:
name: forgejo-registry-pat
namespace: api
type: Opaque
stringData:
pat: ENC[AES256_GCM,data:alYPvHBVqnf13NZu6jtgA6WdFM4x46s5mIY8uEnfWdq0Vp+7oKrY1A==,iv:JbUjes5ZB9eKQ1nkV02++7F/BaWIROfT6gjShzajXro=,tag:ApjawJold0QApnX1GUXGhw==,type:str]
sops:
age:
- enc: |
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSB6bFZhU3JLSUZEVWhYdEdZ
MURoSWNlZjY0RkxyaWlwU2ZTVjJ5V2FnMVVZCis5YlBwQnZrWnVJNFh4UnNldmx6
Y2JjdnpkRTVGSjRSZ0U0THdDZHIrNHcKLS0tIHZDd1BDVGRDSHJEQThuTExORWs2
b3BxenY4WHhpRkRTZHJGMkNYMm14RnMKH//Xpqbf/ZBNFQ43D0eFUWwRcQWqA3CC
RG8U9wyxC6YrlruU2hY6eB2x0OjsVic34ZGaR752Bwyp0Pz49C/k3g==
-----END AGE ENCRYPTED FILE-----
recipient: age1e5fq3hwxy78psus2nfvmtmua36g0u3suk78ephw6246l974d2utsvn0hla
encrypted_regex: ^(data|stringData)$
lastmodified: "2026-09-28T03:10:55Z"
mac: ENC[AES256_GCM,data:nLZueHygckw+Gddlea90tRU8h8nEGpe21JUi9nCdpc0ctkSlTDqcR3Q7JFPwbEGHGFU5UJ2xnkBZEDIVmExJryqPBMXT7hQd3ySeQgPwAPGt6zEhlRc5jXhqmmrpJiiN5XUL52AZVDwcWACg7kVzBXIClzihFRW+UqjJZhdtELM=,iv:C0H4AFfdfpsBvP1z2chVvW/VTejxYxwNn/KuA50LeH0=,tag:ZEkTCTKvoZH7DjrcwfL3dw==,type:str]
version: 3.13.2
@@ -1,24 +1,23 @@
apiVersion: v1
kind: Secret
apiVersion: ENC[AES256_GCM,data:l7I=,iv:NZY7r3JVW3zVwxeiScvWKpAQUDa9+nckHd0qWVrGU88=,tag:qpowp5OILdYKtTux/nlWpg==,type:str]
kind: ENC[AES256_GCM,data:6oeEbuIk,iv:5flI9TtcYQ961wOYPBPhvQpitHFYAf8yMdNBXqytbJs=,tag:WNhlbKmSeZEqZ9ZgiB/BYg==,type:str]
metadata:
name: paperless-ai-config
namespace: paperless
type: Opaque
name: ENC[AES256_GCM,data:fvJMsgy+wPZqMCdxm9hoV3n/+Q==,iv:I3rVtHIJBOME+bxhPws58Zjhj5i+KT5UtB9o7Vus5EU=,tag:6h4FnUu7PGxlQPIQxPYCRg==,type:str]
namespace: ENC[AES256_GCM,data:CDriLoLovROW,iv:rHXcN1xm5+t2D/Tq/2sx9lQFF8anD5jH24ZntPuBA8U=,tag:XstJAz6S8IM1c/pp9Cg0Ww==,type:str]
type: ENC[AES256_GCM,data:JdTwBbag,iv:9Ys15Ketl0ghNK0u0N8IOpUt7+KoloutiG5M9zHPXxw=,tag:teau/udf41Ty34A5wLAm6Q==,type:str]
stringData:
PAPERLESS_API_TOKEN: ENC[AES256_GCM,data:wlBC85ep6zioWLhfhNczkKfTMR8tmciN+4r3of8GpQoJmKyE2r7pOg==,iv:Rem/UJl5wUNi8G+uEV7f2eCLabaY26sZ7+AsKYiOZ4I=,tag:bGS1fu13Mwsrr+5NUEzzLw==,type:str]
LLM_AUTH_CLIENT_SECRET: ENC[AES256_GCM,data:co7FfmRXKgrz9fNgR10KtlHL/iG4F5WKJgjcKem1H5hF5FviVi4+CQNekA==,iv:ADtBHiI6BtrkuH1iIfKV3I5odNLMQe5y/9GGTJrPNN0=,tag:j6wX6zO5VhKoLzdr7BQZCw==,type:str]
PAPERLESS_API_TOKEN: ENC[AES256_GCM,data:TuQeDx8po3h4loTRABlItVYQJ7gFjnmIn3zQQGtUcoNFMKpkqLK/GQ==,iv:TDg0stpca5pDtatqu8DFU7R0Bm/S/BI9ZoiG4K8mCT4=,tag:BfjX25V5gL7AeIsscClRAg==,type:str]
sops:
age:
- enc: |
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBJWDZwTE1haUY5ZkgybnBx
WEFVSzQvNjlGaDlvaHhuSTVCY2dYb0s1NW4wCmhkM0N6YlNIRTYrVkdxaHJaVHVG
bUEzTVV3WFQ0OWwrdEZnanJJa09Nb3MKLS0tIGduNEFtT2hCUDlkZWpWZmliZy83
cUoxcXp1NFF3SFpBVVdSZE5GY1VIWmsKH+cMqasOVxgCnGedaM2IAsgwOzEsOMct
0XjmInpppWNe+t7leEb6MqEY2cPQHL+l2L5jkZzAOfImwaIwMQnghw==
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBKVDN3aFVqVmFXY1VQVXZP
OUsrNHdNdlRvRFgvTDQrNE5uL2xaazVENTBjCkNPbGR5Vk16RXNDOW15OGNTRmFR
U0JOeTllaWU1dzNVY3lBbEVyVG5tOEkKLS0tIEZvajlvcUtJdFNNUkkzV3FKOFRj
UUE2TDBzT0xVc2E1NlUvQXAyZytMZEUKBv+ChaoQCstA742L3Bq5mBJlW/UC4Pyw
ZvFAyYbs1NaEqhjtHq+4T62jTWcH/St/vKgUuFQ9LCUQhYd8DUzAow==
-----END AGE ENCRYPTED FILE-----
recipient: age1e5fq3hwxy78psus2nfvmtmua36g0u3suk78ephw6246l974d2utsvn0hla
encrypted_regex: ^(data|stringData)$
lastmodified: "2026-09-14T14:19:39Z"
mac: ENC[AES256_GCM,data:jDdmiFg6uB1za7sAjO1CnGHdRPyUnmWCMJxqHrE3BO82pNbtm8yLOf+W6CfFKAjfZYqEE2mdKhABm7zeJgJlub3eXJbAirAFrp5jrbfHw0qsFo85Gj/BsrSDB401Aky6PxvRomz66FyX5zDDXIGAMEMlyNEadMplTfrZQQ9hQWM=,iv:UTSF72ofUyWs1LXGKQwBP60hK64UxhqTFM8QTVozGoo=,tag:OKivMDAqwWgrX+kNjvQrPg==,type:str]
lastmodified: "2026-09-12T21:04:26Z"
mac: ENC[AES256_GCM,data:0ks96xQzOa8ygNDDYfKV8EJ8dWLBaC0PCnLG73NinMByF/KoWkCdwMDPC34W9xxVoTD2NiF1i/3pgCG4QFezTE7tPHPPKdYcQfwda9fkooiXW4Nh2M/sgbq/xgsy9N3qpHD/O5iILgpehb9y0DuErOyxcn2AIYizynU7m8e63pc=,iv:fvPWBsfE6YHskKzdlxJidp14dUgRR0XdMkEu6IxMMSo=,tag:5FiuIrFOg/GXvlQVy7drJQ==,type:str]
unencrypted_suffix: _unencrypted
version: 3.13.2
@@ -1,24 +0,0 @@
apiVersion: v1
kind: Secret
type: Opaque
metadata:
name: pi-code-agent-api-keys
namespace: poimen-sandbox
stringData:
ANTHROPIC_API_KEY: ENC[AES256_GCM,data:TBcno/dzj3qykHjeX96UKZekuA/WMQT2E7a1ziPyYo5J6lWLPydgli84KeJZhH62/8CnnFtFOhVIe4FWCGPGjvqKH6M8WbiQHaP9y7FN0qQUpFHKNVAQ2R+s0wInhw0eUmANvd7bRx8aIZ2X,iv:oex19yVtWUevoJ0A3mkMLCfWu85o1gPSNp43x1iV0LE=,tag:BW3zQnwvagPceeNird9CZg==,type:str]
DEEPSEEK_API_KEY: ENC[AES256_GCM,data:vq/5gOsMVjlVMd0oXiBtHFHFEr+IF2YR2iP2OBFWx3ZFNoQ=,iv:QhLU/BRIJb/7QKDCRyw+HWPphZifVEhIOLywYDgOb20=,tag:BZdtXw+WsuK+P4E0caTa0Q==,type:str]
sops:
age:
- enc: |
-----BEGIN AGE ENCRYPTED FILE-----
YWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBqNm1LNE5nWktnd3c3STg3
UlVWbWJxWElxUHMwa0JVMk81Z0c4d0JaQm1vCnpLQWJWV3hxOU00NzJIaG51Mmlr
ZWpNTFJWcmdtV0w4YndQeHpvSUx2MTAKLS0tIDVnNkNuVWhPUFZ5V2hFOEt1eitG
blVqRy8yNnYzSU1FNzZGNkxrRElvWVEKL3J77INje75+CvKXaJHC3CvONgHv7d0a
a10MITvfreFr6M4AN3Z/mno49SDMp15Q4oQRagHHxSTS1K54mWHo8g==
-----END AGE ENCRYPTED FILE-----
recipient: age1e5fq3hwxy78psus2nfvmtmua36g0u3suk78ephw6246l974d2utsvn0hla
encrypted_regex: ^(data|stringData)$
lastmodified: "2026-10-06T01:19:49Z"
mac: ENC[AES256_GCM,data:GpYl8IRefms36GvO3RW41c0US7SOgoOhd4rumxsCdEf5ME9kJ0eOxPx8klMgnlYrkBnwHmad8jj7C+HcA5Eim7mdUaYOZZWPFohvC6N4GLHX85aH78P09CelqG5tdm/Gm+1QfxYu0vANYGCAVjLK7YbBbZjbZmbvVfQvAbs3mOY=,iv:y3lglGu8FhTHQpO1poSIKgGYJFu5J9yjIaOjulda6fY=,tag:5Sgh4TbtNFMw7xOJjYRn0g==,type:str]
version: 3.13.2
-2
View File
@@ -12,7 +12,6 @@ files:
- authentik-secrets.enc.yaml
- cloudflare-secrets.enc.yaml
- forgejo-registry-pat.enc.yaml
- forgejo-registry-pat-api.enc.yaml
- forgejo-registry-pull.enc.yaml
- forgejo-runner-token.enc.yaml
- forgejo-secrets.enc.yaml
@@ -33,4 +32,3 @@ files:
- gotify-smtp-secrets.enc.yaml
- forgejo-smtp-secrets.enc.yaml
- paperless-ai-secrets.enc.yaml
- pi-sandbox-secrets.enc.yaml
@@ -45,13 +45,7 @@ gitea:
SSH_DOMAIN: git.riotpiao.com
SSH_PORT: 2222
SSH_LISTEN_PORT: 2222
# Self-signup was open (GET /user/sign_up returned 200), so anyone reaching
# forgejo.riotpiao.com could create an account. Accounts are provisioned by
# the admin only; admin create-user via UI/API is unaffected by this flag.
service:
DISABLE_REGISTRATION: true
database:
DB_TYPE: postgres
HOST: forgejo-db-rw.cicd.svc.cluster.local:5432
@@ -172,8 +166,3 @@ deployment:
secretKeyRef:
name: forgejo-smtp
key: password
# Allow webhooks to reach api-gw through the cluster ingress (resolves to
# internal ClusterIP 10.101.x.x which is blocked by default ALLOWED_HOST_LIST).
# api.riotpiao.com is our own gateway — safe to allowlist.
- name: GITEA__WEBHOOK__ALLOWED_HOST_LIST
value: "external,api.riotpiao.com"
@@ -0,0 +1,70 @@
# ArgoCD Image Updater configuration
# Watches Forgejo registry and updates ArgoCD Applications with new image tags
config:
# Registry configuration - Forgejo allows anonymous pulls
registries:
- name: forgejo
api_url: https://forgejo.riotpiao.com
prefix: forgejo.riotpiao.com
default: true
insecure: false
# Log level
logLevel: debug
# ArgoCD API server
argocd:
grpcWeb: true
serverAddress: argocd-server.argocd.svc.cluster.local
insecure: true
plaintext: true
# Git write-back configuration (for multi-source Applications)
git:
# Commit author for image updates
user:
name: "ArgoCD Image Updater"
email: "[email protected]"
# Use SSH keys from ArgoCD's known hosts + credentials
# Image Updater inherits ArgoCD's git credentials (mounted via ArgoCD secret)
# Mount ArgoCD's git credentials for write-back
extraVolumes:
- name: argocd-ssh-known-hosts-cm
configMap:
name: argocd-ssh-known-hosts-cm
defaultMode: 0644
- name: argocd-gpg-keys-cm
configMap:
name: argocd-gpg-keys-cm
optional: true
defaultMode: 0644
- name: argocd-gpg-pubring
configMap:
name: argocd-gpg-pubring-cm
optional: true
defaultMode: 0644
extraVolumeMounts:
- name: argocd-ssh-known-hosts-cm
mountPath: /etc/ssh/ssh_known_hosts.d/argocd-ssh-known-hosts
subPath: ssh_known_hosts
- name: argocd-gpg-keys-cm
mountPath: /etc/gpg/source
- name: argocd-gpg-pubring
mountPath: /etc/gpg/pubring
# Extra environment variables
extraEnv:
- name: GIT_SSH_KNOWN_HOSTS_CONFIG_MAP_ENABLED
value: "true"
# Resources
resources:
requests:
cpu: 50m
memory: 64Mi
limits:
cpu: 200m
memory: 128Mi
@@ -1,12 +1,12 @@
# Cluster-wide cleanup of stale failed/completed Jobs and Pods.
# Runs every 2 minutes. Deletes:
# - Failed Jobs older than 2m (any namespace)
# - Completed standalone Jobs older than 2m with no owning CronJob
# - Orphan pods in Error/Failed/Evicted/Completed state older than 2m
# Runs daily at 04:00 UTC. Deletes:
# - Failed Jobs older than 24h (any namespace)
# - Completed Jobs older than 72h with no owning CronJob
# - Orphan pods in Error/Failed/Evicted state older than 1h
#
# CronJob-owned Jobs are managed by failedJobsHistoryLimit/successfulJobsHistoryLimit,
# but standalone Jobs (helm hooks, one-off runs, CI TaskRuns) have no TTL
# and linger forever. Aggressive schedule keeps the cluster clean.
# but standalone Jobs (helm hooks, one-off runs, longhorn maintenance) have no TTL
# and linger forever.
apiVersion: v1
kind: ServiceAccount
@@ -47,7 +47,7 @@ metadata:
labels:
app: stale-job-cleanup
spec:
schedule: "*/2 * * * *"
schedule: "0 4 * * *"
concurrencyPolicy: Forbid
successfulJobsHistoryLimit: 3
failedJobsHistoryLimit: 3
@@ -74,9 +74,7 @@ spec:
set -e
NOW=$(date +%s)
TTL=120 # 2 minutes in seconds
echo "=== Cleaning failed Jobs older than 2m ==="
echo "=== Cleaning failed Jobs older than 24h ==="
kubectl get jobs --all-namespaces -o json | \
jq -r '.items[] |
select(.status.conditions[]?.type == "Failed") |
@@ -84,15 +82,15 @@ spec:
"\(.metadata.namespace) \(.metadata.name) \(.status.startTime // .status.completionTime // .metadata.creationTimestamp)"' | \
while read -r NS NAME TS; do
JOB_EPOCH=$(date -d "$TS" +%s 2>/dev/null || echo 0)
AGE=$(( NOW - JOB_EPOCH ))
if [ "$AGE" -ge "$TTL" ]; then
echo "[delete] $NS/$NAME (failed ${AGE}s ago)"
AGE_H=$(( (NOW - JOB_EPOCH) / 3600 ))
if [ "$AGE_H" -ge 24 ]; then
echo "[delete] $NS/$NAME (failed ${AGE_H}h ago)"
kubectl delete job "$NAME" -n "$NS" --cascade=foreground 2>/dev/null || true
fi
done
echo ""
echo "=== Cleaning completed standalone Jobs older than 2m ==="
echo "=== Cleaning completed standalone Jobs older than 72h ==="
kubectl get jobs --all-namespaces -o json | \
jq -r '.items[] |
select(.status.succeeded >= 1) |
@@ -100,20 +98,20 @@ spec:
"\(.metadata.namespace) \(.metadata.name) \(.status.completionTime // .metadata.creationTimestamp)"' | \
while read -r NS NAME TS; do
JOB_EPOCH=$(date -d "$TS" +%s 2>/dev/null || echo 0)
AGE=$(( NOW - JOB_EPOCH ))
if [ "$AGE" -ge "$TTL" ]; then
echo "[delete] $NS/$NAME (completed ${AGE}s ago, no owner)"
AGE_H=$(( (NOW - JOB_EPOCH) / 3600 ))
if [ "$AGE_H" -ge 72 ]; then
echo "[delete] $NS/$NAME (completed ${AGE_H}h ago, no owner)"
kubectl delete job "$NAME" -n "$NS" --cascade=foreground 2>/dev/null || true
fi
done
echo ""
echo "=== Cleaning orphan Error/Failed/Evicted/Completed pods older than 2m ==="
echo "=== Cleaning orphan Error/Failed/Evicted pods older than 1h ==="
# Evicted pods show as Failed with reason Evicted
kubectl get pods --all-namespaces -o json | \
jq -r '.items[] |
select(
.status.phase == "Failed" or
.status.phase == "Succeeded" or
(.status.reason // "") == "Evicted" or
(.status.containerStatuses // [] | any(.state.terminated.reason == "Error"))
) |
@@ -121,9 +119,9 @@ spec:
"\(.metadata.namespace) \(.metadata.name) \(.metadata.creationTimestamp)"' | \
while read -r NS NAME TS; do
POD_EPOCH=$(date -d "$TS" +%s 2>/dev/null || echo 0)
AGE=$(( NOW - POD_EPOCH ))
if [ "$AGE" -ge "$TTL" ]; then
echo "[delete] $NS/$NAME (stale ${AGE}s ago)"
AGE_H=$(( (NOW - POD_EPOCH) / 3600 ))
if [ "$AGE_H" -ge 1 ]; then
echo "[delete] $NS/$NAME (error/evicted ${AGE_H}h ago)"
kubectl delete pod "$NAME" -n "$NS" --force 2>/dev/null || true
fi
done
+1
View File
@@ -8,4 +8,5 @@ resources:
- namespaces.yaml
- authentik-db.yaml
- temporal-db.yaml
- memory-db.yaml
- paperless-db.yaml
@@ -1,25 +0,0 @@
# CiliumNetworkPolicy for kube-apiserver access.
#
# Standard K8s NetworkPolicy ipBlock rules don't work for the API server
# under Cilium — the except clause on 192.168.1.0/24 blocks the post-DNAT
# destination even when a separate rule re-allows a /32 or subnet.
#
# Cilium's native `kube-apiserver` entity resolves this correctly: it
# tracks the API server endpoints regardless of ClusterIP vs node-IP
# routing, so the policy stays valid across node changes and NAT paths.
apiVersion: cilium.io/v2
kind: CiliumNetworkPolicy
metadata:
name: {{ .Release.Name }}-apiserver
namespace: {{ .Release.Namespace }}
spec:
endpointSelector:
matchLabels:
app: {{ .Release.Name }}
egress:
- toEntities:
- kube-apiserver
toPorts:
- ports:
- port: "6443"
protocol: TCP
+3 -3
View File
@@ -73,7 +73,7 @@ grafana.ini:
auth.generic_oauth:
enabled: true
name: Authentik
allow_sign_up: true # Allow sync to create/update users from OAuth claims
allow_sign_up: true
client_id: grafana
scopes: openid email profile groups
auth_url: https://authentik.riotpiao.com/application/o/authorize/
@@ -84,13 +84,13 @@ grafana.ini:
# Authentik doesn't serve — request 404s with "Error getting email address"
# and the whole OAuth login fails.
email_attribute_path: email
login_attribute_path: preferred_username # Use preferred_username — OpenID standard claim, always present
login_attribute_path: preferred_username
name_attribute_path: name
role_attribute_path: "preferred_username == 'akadmin' && 'GrafanaAdmin' || contains(groups[*], 'homelab-admins') && 'Admin' || 'Viewer'"
allow_assign_grafana_admin: true
use_pkce: false
use_refresh_token: false
skip_org_role_sync: false # Sync org roles from OAuth groups
skip_org_role_sync: false
tls_skip_verify_insecure: true # Authentik uses self-signed cert; verify in prod
# GF_AUTH_GENERIC_OAUTH_CLIENT_SECRET is injected from the grafana-oidc K8s
@@ -117,22 +117,6 @@ spec:
echo " ✓ talos-cp-3 already has $CP3_DISKS disks configured"
fi
# worker-1: enable scheduling, reserve 400Gi for LLM weights,
# clear eviction flag that was set when scheduling was disabled.
echo "Configuring worker-1 disk..."
kubectl -n longhorn-system patch nodes.longhorn.io worker-1 --type merge -p '{
"spec": {
"disks": {
"default-disk-1030400000000": {
"allowScheduling": true,
"evictionRequested": false,
"storageReserved": 429496729600
}
}
}
}'
echo " ✓ worker-1 disk configured (400Gi reserved)"
echo
echo "Waiting for disks to be ready..."
sleep 10
+25 -17
View File
@@ -1,25 +1,33 @@
# Longhorn Node CRDs — enable scheduling on nodes that need explicit opt-in.
# Longhorn Node CRDs for cp-2 and cp-3.
# These nodes have the control-plane taint, so Longhorn doesn't auto-discover them.
# Explicit Node CRDs + the taint-toleration setting enable storage across all 3 nodes.
#
# Control-plane nodes (cp-2, cp-3) have taints so Longhorn doesn't auto-discover.
# worker-1 was manually disabled; re-enabled 2026-09-28 to relieve degraded-volume
# pressure (400Gi reserved for LLM weights via the add-disks-job, ~300Gi available
# for general replica scheduling).
# `spec.disks` is deliberately absent. Longhorn owns disk identity: it names the
# entry itself (`default-disk-080400000000`, not `default-disk`) and writes
# `storageReserved`, `diskType` and `evictionRequested` into it. Declaring a
# `default-disk` key here never matched the live one, so the Application sat
# OutOfSync and selfHeal kept trying to add a SECOND disk record pointing at the
# same /var/lib/longhorn path — which is worse than the drift it was fixing.
#
# `spec.disks` deliberately absent — Longhorn owns disk identity and writes
# storageReserved/diskType/evictionRequested itself. Disk-level config lives in
# longhorn-add-disks-job.yaml. These objects only set `allowScheduling: true`.
# What these objects are actually for is `allowScheduling: true` on tainted
# control-plane nodes. That is all they need to declare.
---
apiVersion: longhorn.io/v1beta2
kind: Node
metadata: { name: talos-cp-2, namespace: longhorn-system }
spec: { name: talos-cp-2, allowScheduling: true, tags: [] }
metadata:
name: talos-cp-2
namespace: longhorn-system
spec:
name: talos-cp-2
allowScheduling: true
tags: []
---
apiVersion: longhorn.io/v1beta2
kind: Node
metadata: { name: talos-cp-3, namespace: longhorn-system }
spec: { name: talos-cp-3, allowScheduling: true, tags: [] }
---
apiVersion: longhorn.io/v1beta2
kind: Node
metadata: { name: worker-1, namespace: longhorn-system }
spec: { name: worker-1, allowScheduling: true, tags: [] }
metadata:
name: talos-cp-3
namespace: longhorn-system
spec:
name: talos-cp-3
allowScheduling: true
tags: []
@@ -59,8 +59,7 @@ spec:
mountPath: /shared
containers:
- name: provision
# bitnamilegacy/minio-client:2025.7.21-debian-12-r3 replaces the dead quay.io/minio/mc image
image: bitnamilegacy/minio-client:2025.7.21-debian-12-r3
image: quay.io/minio/mc:latest
volumeMounts:
- name: shared
mountPath: /shared
+3 -14
View File
@@ -11,12 +11,7 @@ metadata:
prometheus.io/port: "9000"
prometheus.io/scrape: "true"
spec:
# Was minio/minio:RELEASE.2025-07-23T15-54-02Z — that Docker Hub repository no longer
# exists (404 for every tag), so the tenant sat in ImagePullBackOff and Vault's S3
# backend could not resolve minio-cluster-hl. Official images now need registry auth
# (quay.io/minio/minio returns 401), so this pins a public mirror of the same upstream
# release; swap it for the official image once MinIO registry credentials exist.
image: coollabsio/minio:RELEASE.2025-10-15T17-29-55Z
image: minio/minio:RELEASE.2025-07-23T15-54-02Z
# Disable operator auto-TLS: MinIO serves plain HTTP internally on 9000.
# External TLS is terminated at nginx ingress (wildcard riotpiao-com-tls cert).
@@ -117,16 +112,10 @@ spec:
name: minio-oidc
key: MINIO_IDENTITY_OPENID_CLIENT_SECRET
- name: MINIO_IDENTITY_OPENID_CLAIM_NAME
value: "groups"
- name: MINIO_IDENTITY_OPENID_CLAIM_PREFIX
value: ""
value: "policy"
- name: MINIO_IDENTITY_OPENID_REDIRECT_URI
value: "https://minio.riotpiao.com/oauth_callback"
- name: MINIO_IDENTITY_OPENID_DISPLAY_NAME
value: "Authentik"
- name: MINIO_IDENTITY_OPENID_SCOPES
value: "openid,profile,email,groups"
- name: MINIO_BROWSER_LOGIN_ANIMATION
value: "off"
- name: MINIO_BROWSER_REDIRECT_URL
value: "https://minio.riotpiao.com"
value: "openid,profile,email,minio"
@@ -158,66 +158,3 @@ spec:
severity: warning
annotations:
summary: "Gateway pod {{ $labels.pod }} memory at {{ $value | humanizePercentage }} of limit"
- name: api-gateway.admission
# The admission gate fails OPEN when its view of the engine gauges goes
# stale, so a broken observer degrades silently to the pre-#64 behaviour
# of admitting everything. These two series are the only detection —
# the gate has no automated tests.
rules:
# The gate fails OPEN when it cannot read the engine, so "no data" must
# alert: otherwise a missing emitter, a renamed metric, or a broken
# scrape is indistinguishable from a healthy observer. Both expressions
# therefore OR in an absent() guard on the metric itself.
- alert: APIGatewayObserverDegraded
expr: observer_degraded == 1 or absent(observer_degraded)
for: 2m
labels:
severity: warning
annotations:
summary: "Gateway admission observer degraded or not reporting — gate is failing open"
description: "observer_degraded is either 1 or absent. Absent means the emitter is missing, renamed, or unscraped, which is the fail-open case."
# Engine gauges went stale, or are not being reported at all
- alert: GatewayEngineStateStale
expr: increase(engine_state_stale_total[15m]) > 0 or absent(engine_state_stale_total)
for: 2m
labels:
severity: warning
annotations:
summary: "Gateway engine state stale or not reporting — admission may be based on stale gauges"
description: "Non-zero means the observer lost the engine; absent means the metric is not being emitted at all."
# The acceptance metric for reasoning.yaml's prefill change. Preemption
# of a 65k prompt costs a full re-prefill (~250s at the measured
# 262 tok/s), so any sustained rate is a regression, not noise.
- alert: LLMPreemptions
# Guarded absent() is deliberately NOT used bare here: the engine
# restarts (strategy Recreate) and the series legitimately vanishes
# for the length of a boot, so a bare absent() would false-fire on
# every rollout. It only fires when the metric is missing WHILE the
# predictor is up, which is the real "renamed or unscraped" case.
expr: |
increase(vllm:num_preemptions_total[15m]) > 0
or (absent(vllm:num_preemptions_total) and on() up{job="reasoning-predictor"} == 1)
for: 5m
labels:
severity: warning
annotations:
summary: "vLLM preempting requests ({{ $value }} in 15m) — KV cache over-committed, re-prefill cost is severe"
description: "Any sustained preemption rate is a regression for the reasoning prefill change: evicting a 65k-token prompt costs a full re-prefill (~250s at the measured 262 tok/s). Orchestrator verified `up{job=\"reasoning-predictor\"}` is the live job label — if that label is wrong the guard is inert but harmless."
# This change trades single-request latency for fairness: capping a long
# prompt at 2048 tokens/step means it takes more steps to finish, so a
# lone large prompt can now be slower even while preemptions stay 0.
# Without this alert the change has no way to show a regression.
- alert: LLMPrefillStarvation
expr: |
(sum(vllm:num_requests_waiting) > 0 and max(vllm:kv_cache_usage_perc) < 0.5)
or histogram_quantile(0.95, sum(rate(vllm:time_to_first_token_seconds_bucket[10m])) by (le)) > 60
for: 10m
labels:
severity: warning
annotations:
summary: "reasoning queueing or TTFT p95 above 60s while KV is under 50% — scheduling, not capacity"
description: "Queue depth with spare KV means requests are being starved rather than blocked on memory; a high TTFT p95 with headroom points at the same. Both series verified live (vllm:num_requests_waiting and vllm:time_to_first_token_seconds exist)."
@@ -1,76 +0,0 @@
apiVersion: monitoring.coreos.com/v1
kind: PrometheusRule
metadata:
name: cag-kv-cache-rules
namespace: monitoring
labels:
release: prometheus
spec:
groups:
# Recording rules: derive vLLM prefix cache hit rate from raw counters.
# Metric names verified against live vLLM 0.11.0 scrape (2026-09-29).
# The previous names (vllm:cache_query_hit_total / vllm:cache_query_miss_total)
# do not exist in this version — vLLM exposes prefix_cache_hits_total and
# prefix_cache_queries_total — so this rule produced no data and
# VLLMPrefixCacheHitRateLow could never fire.
- name: vllm.recording
rules:
- record: vllm:prefix_cache_hit_rate
expr: |
rate(vllm:prefix_cache_hits_total[5m])
/
clamp_min(
rate(vllm:prefix_cache_queries_total[5m]),
0.001
)
labels:
job: "reasoning-predictor"
# Alert rules: CAG pipeline health
- name: cag.alerts
rules:
# KV warmup consistently failing — cache never gets warm
- alert: KVWarmupFailureHigh
expr: |
rate(memory_kv_cache_warmup_error_total[5m]) > 0.01
for: 5m
labels:
severity: warning
team: poimen
annotations:
summary: "KV warmup errors elevated ({{ $value | humanize }}/s)"
description: |
The KV cache warmer is failing to reach vLLM at a rate > 0.01/s
for 5 consecutive minutes. The prefix KV cache is not being warmed;
agents will see full prefill latency on every call.
Check reasoning-predictor health and poimen-memory NetworkPolicy.
# Warmup misses: vLLM reachable but not caching
- alert: KVWarmupMissHigh
expr: |
rate(memory_kv_cache_warmup_miss_total[5m]) > 0.01
for: 5m
labels:
severity: warning
team: poimen
annotations:
summary: "KV warmup cache misses elevated ({{ $value | humanize }}/s)"
description: |
vLLM is reachable but cached_tokens=0 on warmup responses.
Possible causes: prefix caching disabled in vLLM, max-num-seqs
saturated during warmup, or context format changed.
# Prefix cache hit rate low after warmup should be established
- alert: VLLMPrefixCacheHitRateLow
expr: |
vllm:prefix_cache_hit_rate < 0.70
for: 10m
labels:
severity: warning
team: poimen
annotations:
summary: "vLLM prefix cache hit rate low ({{ $value | humanizePercentage }})"
description: |
vLLM prefix cache hit rate below 70% for 10 minutes.
Expected >= 85% in steady state with CAG warming active.
Check KVWarmupFailureHigh / KVWarmupMissHigh alerts for root cause.
@@ -26,23 +26,20 @@ def stat_panel(id, title, expr, x, y, w=4, h=4, unit="short", mappings=None, thr
return p
def ts_panel(id, title, exprs, x, y, w=8, h=8, unit="short", description=None):
def ts_panel(id, title, exprs, x, y, w=8, h=8, unit="short"):
targets = []
for e in exprs:
if isinstance(e, tuple):
targets.append({"expr": e[0], "legendFormat": e[1]})
else:
targets.append({"expr": e, "legendFormat": "{{pod}}"})
p = {
return {
"id": id, "title": title, "type": "timeseries",
"gridPos": {"h": h, "w": w, "x": x, "y": y},
"datasource": DS_PROM,
"fieldConfig": {"defaults": {"unit": unit}},
"targets": targets,
}
if description:
p["description"] = description
return p
def table_panel(id, title, expr, x, y, w=12, h=8):
@@ -268,237 +265,6 @@ def build_api_gateway():
}
# ============================================================================
# Dashboard 4: LLM Observability (vLLM / TEI engines + gateway)
# ============================================================================
#
# Two independent metric sources, deliberately both shown:
#
# vLLM + TEI (llm-serving) — engine-truth, but only for the three engines
# that expose /metrics. Ollama (ornith:35b,
# qwen2.5:3b-instruct) exposes nothing at all.
# api-gateway (/metrics) — covers EVERY model including the two Ollama
# ones, derived from the SSE byte stream: TTFT is
# request-start to first byte, ITL is the gap
# between SSE writes carrying "data: ", so it
# counts SSE chunks rather than true tokens.
# vLLM's own histograms remain authoritative for
# `reasoning`.
#
# These three series ARE live as of 2026-09-29 — 3 series each, one per replica,
# verified against the running gateway and Prometheus:
# llm_ttft_seconds, llm_itl_seconds, llm_tokens_total
#
# History, recorded so nobody re-derives it the hard way: on 2026-09-29 these
# recorded nothing at all. internal/proxy/llm_metrics.go declared a capture
# wrapper that was never constructed, so the exporter emitted HELP-only stubs.
# homelab-frontend#63 fixed exactly that — the wrapper is now
# ResponseWriterWrapper, constructed by NewResponseWriterWrapper
# (internal/proxy/llm_metrics.go:38) and installed on the streaming proxy path.
# The "dead code" note that used to live in this header is superseded.
#
# Panels backed by queue_full_requests_total, warmup_requests_delayed_total and
# vllm_prefix_cache_hit_tokens_total also work (3 series, one per replica).
#
#
# All metric names below were verified against a live scrape, not assumed:
# vLLM 0.11.0 exposes prefix_cache_hits_total / prefix_cache_queries_total,
# NOT cache_query_hit_total / cache_query_miss_total.
def build_llm_observability():
def hq(metric, q, by="le"):
return (
f"histogram_quantile({q}, sum(rate({metric}_bucket[5m])) by ({by}, model_name))",
f"p{int(q * 100)}",
)
def hq_gw(metric, q):
return (
f"histogram_quantile({q}, sum(rate({metric}_bucket[5m])) by (le, model))",
f"p{int(q * 100)} · {{{{model}}}}",
)
def avg_of(metric):
# mean = rate(_sum) / rate(_count) — valid for cumulative histograms
return f"rate({metric}_sum[5m]) / clamp_min(rate({metric}_count[5m]), 0.001)"
panels = []
# ── TTFT ────────────────────────────────────────────────────────────────
panels.append(row(100, "Latency — Time To First Token", 0, [
stat_panel(101, "TTFT p95 (gateway)",
"histogram_quantile(0.95, sum(rate(llm_ttft_seconds_bucket[5m])) by (le))",
0, 1, w=4, h=4, unit="s"),
stat_panel(102, "TTFT p95 (vLLM)",
"histogram_quantile(0.95, sum(rate(vllm:time_to_first_token_seconds_bucket[5m])) by (le))",
4, 1, w=4, h=4, unit="s"),
stat_panel(103, "KV cache in use",
"max(vllm:kv_cache_usage_perc)",
8, 1, w=4, h=4, unit="percentunit"),
stat_panel(104, "Requests running",
"sum(vllm:num_requests_running)",
12, 1, w=4, h=4, unit="short"),
stat_panel(105, "Requests waiting",
"sum(vllm:num_requests_waiting)",
16, 1, w=4, h=4, unit="short"),
stat_panel(106, "Preemptions (5m)",
"increase(vllm:num_preemptions_total[5m])",
20, 1, w=4, h=4, unit="short"),
ts_panel(110, "TTFT percentile by model (gateway)",
[hq_gw("llm_ttft_seconds", 0.50),
hq_gw("llm_ttft_seconds", 0.95),
hq_gw("llm_ttft_seconds", 0.99)],
0, 2, w=12, h=8, unit="s"),
ts_panel(111, "TTFT percentile — vLLM reasoning",
[hq("vllm:time_to_first_token_seconds", 0.50),
hq("vllm:time_to_first_token_seconds", 0.95),
hq("vllm:time_to_first_token_seconds", 0.99)],
12, 2, w=12, h=8, unit="s"),
ts_panel(112, "Prefill vs decode (mean)",
[(avg_of("vllm:request_prefill_time_seconds"), "prefill"),
(avg_of("vllm:request_decode_time_seconds"), "decode")],
0, 3, w=12, h=8, unit="s"),
ts_panel(113, "Queue wait before scheduling (mean)",
[(avg_of("vllm:request_queue_time_seconds"), "queue")],
12, 3, w=12, h=8, unit="s"),
]))
# ── Inter-token latency ─────────────────────────────────────────────────
panels.append(row(120, "Latency — Inter-Token", 4, [
ts_panel(121, "Inter-token latency by model (gateway)",
[hq_gw("llm_itl_seconds", 0.50),
hq_gw("llm_itl_seconds", 0.95),
hq_gw("llm_itl_seconds", 0.99)],
0, 5, w=12, h=8, unit="s"),
ts_panel(122, "Inter-token latency — vLLM reasoning",
[hq("vllm:inter_token_latency_seconds", 0.50),
hq("vllm:inter_token_latency_seconds", 0.95),
hq("vllm:inter_token_latency_seconds", 0.99)],
12, 5, w=12, h=8, unit="s"),
ts_panel(123, "Decode throughput (tokens/s per request)",
[(f"1 / clamp_min({avg_of('vllm:time_per_output_token_seconds')}, 0.0001)", "tok/s")],
0, 6, w=12, h=8, unit="short"),
ts_panel(124, "End-to-end request latency p50/p95/p99",
[hq("vllm:e2e_request_latency_seconds", 0.50),
hq("vllm:e2e_request_latency_seconds", 0.95),
hq("vllm:e2e_request_latency_seconds", 0.99)],
12, 6, w=12, h=8, unit="s"),
]))
# ── Batching / scheduling ───────────────────────────────────────────────
panels.append(row(130, "Batching & Scheduling", 7, [
ts_panel(131, "vLLM running vs waiting requests (batch depth)",
[("sum(vllm:num_requests_running)", "running (in batch)"),
("sum(vllm:num_requests_waiting)", "waiting (queued)")],
0, 8, w=12, h=8, unit="short"),
ts_panel(132, "Preemption rate (KV cache eviction pressure)",
[("rate(vllm:num_preemptions_total[5m])", "preemptions/s")],
12, 8, w=12, h=8, unit="short"),
ts_panel(133, "TEI batch size (embeddings / reranker)",
[("avg(te_batch_next_size_sum / clamp_min(te_batch_next_size_count, 1)) by (app)",
"{{app}}")],
0, 9, w=12, h=8, unit="short"),
ts_panel(134, "TEI queue depth",
[("max(te_queue_size) by (app)", "{{app}}")],
12, 9, w=12, h=8, unit="short"),
]))
# ── KV cache ────────────────────────────────────────────────────────────
panels.append(row(140, "KV Cache", 10, [
ts_panel(141, "KV cache utilisation (GPU memory pressure)",
[("max(vllm:kv_cache_usage_perc) by (model_name)", "{{model_name}}")],
0, 11, w=12, h=8, unit="percentunit"),
ts_panel(142, "Prefix cache hit rate (CAG effectiveness)",
[("vllm:prefix_cache_hit_rate", "{{model_name}}")],
12, 11, w=12, h=8, unit="percentunit"),
ts_panel(143, "Prefix cache hits vs queries",
[("rate(vllm:prefix_cache_hits_total[5m])", "hits/s"),
("rate(vllm:prefix_cache_queries_total[5m])", "queries/s")],
0, 12, w=12, h=8, unit="short"),
ts_panel(144, "Prefix cache hit tokens (gateway-observed, all models)",
[("rate(vllm_prefix_cache_hit_tokens_total[5m])", "hit tokens/s")],
12, 12, w=12, h=8, unit="short"),
]))
# ── Throughput & health ─────────────────────────────────────────────────
panels.append(row(150, "Throughput & Health", 13, [
ts_panel(151, "Token throughput",
[("sum(rate(vllm:prompt_tokens_total[5m]))", "prompt tok/s"),
("sum(rate(vllm:generation_tokens_total[5m]))", "generation tok/s"),
("rate(llm_tokens_total[5m])", "gateway SSE chunks/s (all models)")],
0, 14, w=12, h=8, unit="short"),
ts_panel(152, "Successful requests/s",
[("sum(rate(vllm:request_success_total[5m]))", "vLLM"),
("sum(rate(te_request_count[5m]))", "TEI")],
12, 14, w=12, h=8, unit="short"),
ts_panel(153, "Backpressure — queue-full rejects",
[("rate(queue_full_requests_total[5m])", "rejected/s")],
0, 15, w=8, h=8, unit="short"),
ts_panel(154, "KV warmup requests delayed",
[("rate(warmup_requests_delayed_total[5m])", "delayed/s")],
8, 15, w=8, h=8, unit="short"),
ts_panel(155, "Embedding / rerank latency p95",
[("histogram_quantile(0.95, sum(rate(te_embed_duration_bucket[5m])) by (le, app))",
"{{app}} embed"),
("histogram_quantile(0.95, sum(rate(te_embed_queue_duration_bucket[5m])) by (le, app))",
"{{app}} queue")],
16, 15, w=8, h=8, unit="s"),
]))
# ── Admission control ───────────────────────────────────────────────────
# These four panels read the gateway's admission gate, which is the
# companion change in homelab-frontend#64. That emitter is NOT deployed
# yet (verified against the live /metrics endpoint: 0 series matching
# ^(admission_|observer_|engine_state_)), so they render "No data" until
# #64 ships. That is expected, and each panel carries a description
# saying so — an unexplained blank panel would read as a broken
# dashboard, which is exactly the failure mode this row exists to catch.
panels.append(row(160, "Admission Control", 16, [
ts_panel(161, "Admission parked (5m)",
[("increase(admission_parked_total[5m])", "parked")],
0, 17, w=8, h=8, unit="short",
description="Requests the gateway held back rather than admitting. "
"Emitted by the admission gate (homelab-frontend#64); "
"empty until that change is deployed."),
ts_panel(162, "Admission rejected by reason",
[("sum by (reason) (increase(admission_rejected_total[5m]))", "{{reason}}")],
8, 17, w=8, h=8, unit="short",
description="Admission rejections split by the gate's own reason label. "
"Emitted by homelab-frontend#64; empty until deployed."),
ts_panel(163, "Engine state stale",
[("increase(engine_state_stale_total[5m])", "stale")],
16, 17, w=8, h=8, unit="short",
description="Times the gateway's view of the engine gauges went stale. "
"The gate fails OPEN when this happens, so any non-zero rate "
"means admission is silently degraded to admit-everything. "
"Emitted by homelab-frontend#64; empty until deployed."),
ts_panel(164, "Gateway view vs engine truth",
[("max(vllm_requests_running)", "gateway: running"),
("sum(vllm:num_requests_running)", "engine: running"),
("max(vllm_kv_usage_perc)", "gateway: kv (fraction) [same as engine if healthy]"),
("max(vllm:kv_cache_usage_perc)", "engine: kv (fraction)")],
0, 18, w=24, h=8, unit="short",
description="The gateway's own reading of the engine against the engine's "
"self-reported value. A disagreement between a pair is how a "
"stale observer or a mistuned admission target shows itself, "
"and nothing else in this dashboard reveals it. The two "
"gateway series (vllm_requests_running, vllm_kv_usage_perc) "
"ship with homelab-frontend#64 and are absent until it is "
"deployed — until then this panel shows the engine's pair only."),
]))
return {
"title": "LLM Observability",
"uid": "llm-observability",
"schemaVersion": 39,
"timezone": "browser",
"time": {"from": "now-6h", "to": "now"},
"refresh": "30s",
"tags": ["llm", "vllm", "tei", "gpu", "observability"],
"panels": panels,
}
# ============================================================================
# Generate
# ============================================================================
@@ -511,7 +277,4 @@ write_dashboard("cluster-infrastructure.yaml", build_cluster_infrastructure(), "
# Dashboard 3
write_dashboard("api-gateway.yaml", build_api_gateway(), "API")
# Dashboard 4
write_dashboard("llm-observability.yaml", build_llm_observability(), "LLM")
print("Done.")
@@ -1,95 +0,0 @@
apiVersion: v1
data:
llm-observability.json: '{"title":"LLM Observability","uid":"llm-observability","schemaVersion":39,"timezone":"browser","time":{"from":"now-6h","to":"now"},"refresh":"30s","tags":["llm","vllm","tei","gpu","observability"],"panels":[{"id":100,"title":"Latency
\u2014 Time To First Token","type":"row","collapsed":true,"gridPos":{"h":1,"w":24,"x":0,"y":0},"panels":[{"id":101,"title":"TTFT
p95 (gateway)","type":"stat","gridPos":{"h":4,"w":4,"x":0,"y":1},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.95,
sum(rate(llm_ttft_seconds_bucket[5m])) by (le))"}]},{"id":102,"title":"TTFT p95
(vLLM)","type":"stat","gridPos":{"h":4,"w":4,"x":4,"y":1},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.95,
sum(rate(vllm:time_to_first_token_seconds_bucket[5m])) by (le))"}]},{"id":103,"title":"KV
cache in use","type":"stat","gridPos":{"h":4,"w":4,"x":8,"y":1},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"percentunit"}},"targets":[{"expr":"max(vllm:kv_cache_usage_perc)"}]},{"id":104,"title":"Requests
running","type":"stat","gridPos":{"h":4,"w":4,"x":12,"y":1},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"sum(vllm:num_requests_running)"}]},{"id":105,"title":"Requests
waiting","type":"stat","gridPos":{"h":4,"w":4,"x":16,"y":1},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"sum(vllm:num_requests_waiting)"}]},{"id":106,"title":"Preemptions
(5m)","type":"stat","gridPos":{"h":4,"w":4,"x":20,"y":1},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"increase(vllm:num_preemptions_total[5m])"}]},{"id":110,"title":"TTFT
percentile by model (gateway)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":2},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.5,
sum(rate(llm_ttft_seconds_bucket[5m])) by (le, model))","legendFormat":"p50 \u00b7
{{model}}"},{"expr":"histogram_quantile(0.95, sum(rate(llm_ttft_seconds_bucket[5m]))
by (le, model))","legendFormat":"p95 \u00b7 {{model}}"},{"expr":"histogram_quantile(0.99,
sum(rate(llm_ttft_seconds_bucket[5m])) by (le, model))","legendFormat":"p99 \u00b7
{{model}}"}]},{"id":111,"title":"TTFT percentile \u2014 vLLM reasoning","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":2},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.5,
sum(rate(vllm:time_to_first_token_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p50"},{"expr":"histogram_quantile(0.95,
sum(rate(vllm:time_to_first_token_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p95"},{"expr":"histogram_quantile(0.99,
sum(rate(vllm:time_to_first_token_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p99"}]},{"id":112,"title":"Prefill
vs decode (mean)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":3},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"rate(vllm:request_prefill_time_seconds_sum[5m])
/ clamp_min(rate(vllm:request_prefill_time_seconds_count[5m]), 0.001)","legendFormat":"prefill"},{"expr":"rate(vllm:request_decode_time_seconds_sum[5m])
/ clamp_min(rate(vllm:request_decode_time_seconds_count[5m]), 0.001)","legendFormat":"decode"}]},{"id":113,"title":"Queue
wait before scheduling (mean)","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":3},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"rate(vllm:request_queue_time_seconds_sum[5m])
/ clamp_min(rate(vllm:request_queue_time_seconds_count[5m]), 0.001)","legendFormat":"queue"}]}]},{"id":120,"title":"Latency
\u2014 Inter-Token","type":"row","collapsed":true,"gridPos":{"h":1,"w":24,"x":0,"y":4},"panels":[{"id":121,"title":"Inter-token
latency by model (gateway)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":5},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.5,
sum(rate(llm_itl_seconds_bucket[5m])) by (le, model))","legendFormat":"p50 \u00b7
{{model}}"},{"expr":"histogram_quantile(0.95, sum(rate(llm_itl_seconds_bucket[5m]))
by (le, model))","legendFormat":"p95 \u00b7 {{model}}"},{"expr":"histogram_quantile(0.99,
sum(rate(llm_itl_seconds_bucket[5m])) by (le, model))","legendFormat":"p99 \u00b7
{{model}}"}]},{"id":122,"title":"Inter-token latency \u2014 vLLM reasoning","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":5},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.5,
sum(rate(vllm:inter_token_latency_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p50"},{"expr":"histogram_quantile(0.95,
sum(rate(vllm:inter_token_latency_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p95"},{"expr":"histogram_quantile(0.99,
sum(rate(vllm:inter_token_latency_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p99"}]},{"id":123,"title":"Decode
throughput (tokens/s per request)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":6},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"1
/ clamp_min(rate(vllm:time_per_output_token_seconds_sum[5m]) / clamp_min(rate(vllm:time_per_output_token_seconds_count[5m]),
0.001), 0.0001)","legendFormat":"tok/s"}]},{"id":124,"title":"End-to-end request
latency p50/p95/p99","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":6},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.5,
sum(rate(vllm:e2e_request_latency_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p50"},{"expr":"histogram_quantile(0.95,
sum(rate(vllm:e2e_request_latency_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p95"},{"expr":"histogram_quantile(0.99,
sum(rate(vllm:e2e_request_latency_seconds_bucket[5m])) by (le, model_name))","legendFormat":"p99"}]}]},{"id":130,"title":"Batching
& Scheduling","type":"row","collapsed":true,"gridPos":{"h":1,"w":24,"x":0,"y":7},"panels":[{"id":131,"title":"vLLM
running vs waiting requests (batch depth)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":8},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"sum(vllm:num_requests_running)","legendFormat":"running
(in batch)"},{"expr":"sum(vllm:num_requests_waiting)","legendFormat":"waiting
(queued)"}]},{"id":132,"title":"Preemption rate (KV cache eviction pressure)","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":8},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"rate(vllm:num_preemptions_total[5m])","legendFormat":"preemptions/s"}]},{"id":133,"title":"TEI
batch size (embeddings / reranker)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":9},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"avg(te_batch_next_size_sum
/ clamp_min(te_batch_next_size_count, 1)) by (app)","legendFormat":"{{app}}"}]},{"id":134,"title":"TEI
queue depth","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":9},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"max(te_queue_size)
by (app)","legendFormat":"{{app}}"}]}]},{"id":140,"title":"KV Cache","type":"row","collapsed":true,"gridPos":{"h":1,"w":24,"x":0,"y":10},"panels":[{"id":141,"title":"KV
cache utilisation (GPU memory pressure)","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":11},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"percentunit"}},"targets":[{"expr":"max(vllm:kv_cache_usage_perc)
by (model_name)","legendFormat":"{{model_name}}"}]},{"id":142,"title":"Prefix
cache hit rate (CAG effectiveness)","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":11},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"percentunit"}},"targets":[{"expr":"vllm:prefix_cache_hit_rate","legendFormat":"{{model_name}}"}]},{"id":143,"title":"Prefix
cache hits vs queries","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":12},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"rate(vllm:prefix_cache_hits_total[5m])","legendFormat":"hits/s"},{"expr":"rate(vllm:prefix_cache_queries_total[5m])","legendFormat":"queries/s"}]},{"id":144,"title":"Prefix
cache hit tokens (gateway-observed, all models)","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":12},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"rate(vllm_prefix_cache_hit_tokens_total[5m])","legendFormat":"hit
tokens/s"}]}]},{"id":150,"title":"Throughput & Health","type":"row","collapsed":true,"gridPos":{"h":1,"w":24,"x":0,"y":13},"panels":[{"id":151,"title":"Token
throughput","type":"timeseries","gridPos":{"h":8,"w":12,"x":0,"y":14},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"sum(rate(vllm:prompt_tokens_total[5m]))","legendFormat":"prompt
tok/s"},{"expr":"sum(rate(vllm:generation_tokens_total[5m]))","legendFormat":"generation
tok/s"},{"expr":"rate(llm_tokens_total[5m])","legendFormat":"gateway SSE chunks/s
(all models)"}]},{"id":152,"title":"Successful requests/s","type":"timeseries","gridPos":{"h":8,"w":12,"x":12,"y":14},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"sum(rate(vllm:request_success_total[5m]))","legendFormat":"vLLM"},{"expr":"sum(rate(te_request_count[5m]))","legendFormat":"TEI"}]},{"id":153,"title":"Backpressure
\u2014 queue-full rejects","type":"timeseries","gridPos":{"h":8,"w":8,"x":0,"y":15},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"rate(queue_full_requests_total[5m])","legendFormat":"rejected/s"}]},{"id":154,"title":"KV
warmup requests delayed","type":"timeseries","gridPos":{"h":8,"w":8,"x":8,"y":15},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"rate(warmup_requests_delayed_total[5m])","legendFormat":"delayed/s"}]},{"id":155,"title":"Embedding
/ rerank latency p95","type":"timeseries","gridPos":{"h":8,"w":8,"x":16,"y":15},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"s"}},"targets":[{"expr":"histogram_quantile(0.95,
sum(rate(te_embed_duration_bucket[5m])) by (le, app))","legendFormat":"{{app}}
embed"},{"expr":"histogram_quantile(0.95, sum(rate(te_embed_queue_duration_bucket[5m]))
by (le, app))","legendFormat":"{{app}} queue"}]}]},{"id":160,"title":"Admission
Control","type":"row","collapsed":true,"gridPos":{"h":1,"w":24,"x":0,"y":16},"panels":[{"id":161,"title":"Admission
parked (5m)","type":"timeseries","gridPos":{"h":8,"w":8,"x":0,"y":17},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"increase(admission_parked_total[5m])","legendFormat":"parked"}],"description":"Requests
the gateway held back rather than admitting. Emitted by the admission gate (homelab-frontend#64);
empty until that change is deployed."},{"id":162,"title":"Admission rejected by
reason","type":"timeseries","gridPos":{"h":8,"w":8,"x":8,"y":17},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"sum
by (reason) (increase(admission_rejected_total[5m]))","legendFormat":"{{reason}}"}],"description":"Admission
rejections split by the gate''s own reason label. Emitted by homelab-frontend#64;
empty until deployed."},{"id":163,"title":"Engine state stale","type":"timeseries","gridPos":{"h":8,"w":8,"x":16,"y":17},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"increase(engine_state_stale_total[5m])","legendFormat":"stale"}],"description":"Times
the gateway''s view of the engine gauges went stale. The gate fails OPEN when
this happens, so any non-zero rate means admission is silently degraded to admit-everything.
Emitted by homelab-frontend#64; empty until deployed."},{"id":164,"title":"Gateway
view vs engine truth","type":"timeseries","gridPos":{"h":8,"w":24,"x":0,"y":18},"datasource":{"type":"prometheus","uid":"prometheus"},"fieldConfig":{"defaults":{"unit":"short"}},"targets":[{"expr":"max(vllm_requests_running)","legendFormat":"gateway:
running"},{"expr":"sum(vllm:num_requests_running)","legendFormat":"engine: running"},{"expr":"max(vllm_kv_usage_perc)","legendFormat":"gateway:
kv (fraction) [same as engine if healthy]"},{"expr":"max(vllm:kv_cache_usage_perc)","legendFormat":"engine:
kv (fraction)"}],"description":"The gateway''s own reading of the engine against
the engine''s self-reported value. A disagreement between a pair is how a stale
observer or a mistuned admission target shows itself, and nothing else in this
dashboard reveals it. The two gateway series (vllm_requests_running, vllm_kv_usage_perc)
ship with homelab-frontend#64 and are absent until it is deployed \u2014 until
then this panel shows the engine''s pair only."}]}]}'
kind: ConfigMap
metadata:
annotations:
grafana_folder: LLM
labels:
grafana_dashboard: '1'
name: llm-observability-dashboard
namespace: logging
-4
View File
@@ -14,14 +14,10 @@ resources:
- alerts/svc-vault-rules.yaml
- alerts/cluster-alerts.yaml
- alerts/api-gateway-alerts.yaml
- alerts/cag-kv-cache-rules.yaml
- servicemonitors/argocd.yaml
- servicemonitors/authentik.yaml
- servicemonitors/forgejo.yaml
- servicemonitors/minio.yaml
- servicemonitors/ingress-nginx.yaml
- servicemonitors/vllm.yaml
- servicemonitors/api-gateway.yaml
- dashboards/cluster-infrastructure.yaml
- dashboards/api-gateway.yaml
- dashboards/llm-observability.yaml
+6 -5
View File
@@ -54,8 +54,8 @@ alertmanager:
# ── Prometheus ────────────────────────────────────────────────────────────────
prometheus:
prometheusSpec:
retention: 30d
retentionSize: "95GB"
retention: 15d
retentionSize: "18GB"
# scrapeTimeout MUST be <= scrapeInterval or the operator refuses to generate
# the Prometheus config ("scrapeTimeout greater than scrapeInterval") and no
@@ -64,9 +64,10 @@ prometheus:
scrapeTimeout: 60s
evaluationInterval: 30s
# Pin to worker-1 for more storage capacity
# Pin to az-a (talos-cp-1) — sole Longhorn node; else the RWO PVC can't
# attach on cp-2/cp-3 (CSINode lacks driver.longhorn.io).
nodeSelector:
kubernetes.io/hostname: worker-1
topology.kubernetes.io/zone: az-a
# Persistent storage — metrics survive node reboots and pod restarts.
# Uses the default `longhorn` StorageClass; nodeSelector above already pins
@@ -78,7 +79,7 @@ prometheus:
accessModes: ["ReadWriteOnce"]
resources:
requests:
storage: 25Gi
storage: 20Gi
resources:
requests:
@@ -1,62 +0,0 @@
# History, recorded so nobody re-derives it the hard way: on 2026-09-29 the
# three latency series below recorded nothing. internal/proxy/llm_metrics.go
# declared a capture wrapper (LLMMetricsCapture) that was never constructed
# anywhere, so the exporter emitted HELP-only stubs and the dashboard panels
# stayed empty.
#
# homelab-frontend#63 fixed exactly that. The wrapper is now
# ResponseWriterWrapper, constructed by NewResponseWriterWrapper
# (internal/proxy/llm_metrics.go:38) and installed on the streaming proxy
# request path. Verified live on 2026-09-29:
# llm_ttft_seconds count=7 sum=598.212s
# llm_itl_seconds count=16116
# llm_tokens_total 3 series
#
# These derived-from-SSE series cover EVERY model including the two Ollama ones
# (ornith:35b, qwen2.5:3b-instruct), which expose no metrics endpoint at all.
# They are proxy-side: TTFT is request-start to first byte and ITL is the gap
# between SSE writes, so both are granular to SSE write boundaries rather than
# to the engine's own token cadence. llm_tokens_total counts `data:` events,
# and the documented assumption in internal/proxy/llm_metrics.go is that these
# upstreams emit one such event per token — so it is a token count only as far
# as that assumption holds. vLLM's own histograms remain authoritative.
#
# Also recorded and working (3 series, one per replica):
# queue_full_requests_total counter backpressure rejects
# warmup_requests_delayed_total counter vLLM slot contention
# vllm_prefix_cache_hit_tokens_total counter prefix-cache hits
#
# NOT working, do not build on it: request_duration_seconds is declared and
# exported but has 0 samples, and its only writer Metrics.RecordRequest has
# zero call sites outside _test.go — verified by ast-grep, not assumed. It is
# the same dead-code shape this branch already corrected for the latency
# series, so it is listed here rather than left to be rediscovered.
#
# Also note the Deployment already carried prometheus.io/scrape annotations,
# but kube-prometheus-stack ignores pod annotations (no additionalScrapeConfigs,
# serviceMonitorSelectorNilUsesHelmValues: false) — so nothing at all was being
# collected before this ServiceMonitor existed.
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: api-gateway
namespace: monitoring
labels:
app.kubernetes.io/name: api-gateway
app.kubernetes.io/part-of: api
spec:
namespaceSelector:
matchNames:
- api
selector:
matchLabels:
app: api-gateway
endpoints:
# api-gateway Service port IS named `http` (unlike the KServe ones), so
# the name form works here.
- port: http
interval: 30s
scrapeTimeout: 10s
path: /metrics
scheme: http
+10 -29
View File
@@ -11,39 +11,20 @@ spec:
matchNames:
- llm-serving
selector:
# Only the three engines that actually serve /metrics.
# ornith-predictor and qwen-cpu are Ollama, which has no Prometheus
# endpoint (/metrics returns 404) — selecting them would add permanently
# DOWN targets. Ollama-model visibility comes from the api-gateway
# ServiceMonitor instead (llm_ttft_seconds / llm_itl_seconds are
# measured at the proxy, so they cover every model including Ollama).
matchExpressions:
- key: app.kubernetes.io/name
operator: In
values:
- llm-reasoning # vLLM 0.11.0 — full engine metrics
- llm-embeddings # TEI 1.8.2 — CPU
- llm-reranker # TEI 1.8.2 — CPU
matchLabels:
app.kubernetes.io/part-of: llm-serving
endpoints:
# targetPort, not port: the KServe-generated Services on llm-serving have
# UNNAMED ports, so `port: <name>` can never match. Naming them would mean
# editing the InferenceServices (predictor restart = full weights reload,
# tens of seconds on the vLLM slot), so scrape the pod port directly.
# prometheus-operator v0.94.1 supports targetPort on ServiceMonitor.
- targetPort: 8080
- port: http
interval: 30s
scrapeTimeout: 10s
path: /metrics
scheme: http
relabelings:
# Prometheus's Kubernetes service discovery already supplies the
# namespace, pod and service labels; the only one that needs deriving
# is `app`, since the TEI panels aggregate by it (by (app)) and SD does
# not promote arbitrary pod labels.
#
# `action: replace` is written explicitly. It is the API server's
# default for relabeling rules, so omitting it leaves the live object
# diverged from this manifest and ArgoCD reports permanent OutOfSync.
- action: replace
sourceLabels: [__meta_kubernetes_pod_label_app_kubernetes_io_name]
- sourceLabels: [__meta_kubernetes_namespace]
targetLabel: namespace
- sourceLabels: [__meta_kubernetes_pod_name]
targetLabel: pod
- sourceLabels: [__meta_kubernetes_service_name]
targetLabel: service
- sourceLabels: [__meta_kubernetes_pod_label_app_kubernetes_io_name]
targetLabel: app
-12
View File
@@ -1,12 +0,0 @@
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
# Poimen infrastructure — CNPG Postgres for memory service.
# Part of the `poimen` ArgoCD Application (multi-source, source 3).
# Sync-wave -1 ensures the DB cluster is healthy before application
# deployments (wave 0) are applied.
resources:
- memory-db.yaml
- poimen-sandbox-namespace.yaml
- poimen-sandbox-quota.yaml
- pi-session-netpol.yaml
- pi-agent-workspace-pv.yaml
-37
View File
@@ -1,37 +0,0 @@
# Dedicated CNPG Postgres for Poimen Memory (GitOps, wave 2).
# Uses default longhorn storage class (3 replicas, dataLocality disabled).
# CNPG generates secret `memory-db-app` + service `memory-db-rw` in ns poimen.
apiVersion: postgresql.cnpg.io/v1
kind: Cluster
metadata:
name: memory-db
namespace: poimen
annotations:
argocd.argoproj.io/sync-wave: "-1"
argocd.argoproj.io/sync-options: SkipDryRunOnMissingResource=true
spec:
instances: 3
imageName: ghcr.io/cloudnative-pg/postgresql:16.2
bootstrap:
initdb:
database: memory
owner: app
encoding: UTF8
localeCollate: C
localeCType: C
postInitApplicationSQL:
- "CREATE EXTENSION vector;"
enableSuperuserAccess: false
resources:
requests: { memory: "512Mi", cpu: "250m" }
limits: { memory: "2Gi", cpu: "1" }
storage:
size: 20Gi
storageClass: longhorn
affinity:
podAntiAffinityType: preferred
topologyKey: kubernetes.io/hostname
tolerations:
- key: node-role.kubernetes.io/control-plane
operator: Exists
effect: NoSchedule
@@ -1,57 +0,0 @@
apiVersion: v1
kind: PersistentVolume
metadata:
finalizers:
- kubernetes.io/pv-protection
labels:
app: pi-coding-agent-sandbox
part-of: poimen-toolkit
name: pi-agent-workspace-pv
annotations:
argocd.argoproj.io/sync-wave: '-1'
spec:
accessModes:
- ReadWriteOnce
capacity:
storage: 10Gi
claimRef:
apiVersion: v1
kind: PersistentVolumeClaim
name: pi-agent-workspace
namespace: poimen-sandbox
hostPath:
path: /var/lib/pi-agent-sandbox
type: DirectoryOrCreate
nodeAffinity:
required:
nodeSelectorTerms:
- matchExpressions:
- key: kubernetes.io/hostname
operator: In
values:
- talos-cp-2
persistentVolumeReclaimPolicy: Retain
volumeMode: Filesystem
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
annotations:
pv.kubernetes.io/bind-completed: 'yes'
argocd.argoproj.io/sync-wave: '-1'
finalizers:
- kubernetes.io/pvc-protection
labels:
app: pi-coding-agent-sandbox
part-of: poimen-toolkit
name: pi-agent-workspace
namespace: poimen-sandbox
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi
storageClassName: ''
volumeMode: Filesystem
volumeName: pi-agent-workspace-pv
-12
View File
@@ -1,12 +0,0 @@
apiVersion: cilium.io/v2
kind: CiliumNetworkPolicy
metadata:
name: pi-session-deny-kube-api
namespace: poimen-sandbox
spec:
endpointSelector:
matchLabels:
app: pi-session
egressDeny:
- toEntities:
- kube-apiserver
@@ -1,9 +0,0 @@
apiVersion: v1
kind: Namespace
metadata:
name: poimen-sandbox
labels:
pod-security.kubernetes.io/enforce: restricted
pod-security.kubernetes.io/enforce-version: latest
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/warn: restricted
@@ -1,12 +0,0 @@
apiVersion: v1
kind: ResourceQuota
metadata:
name: sandbox-quota
namespace: poimen-sandbox
spec:
hard:
pods: "20"
requests.cpu: "10"
requests.memory: 20Gi
limits.cpu: "20"
limits.memory: 40Gi
-1
View File
@@ -16,7 +16,6 @@ resources:
- temporal-operator-role.yaml
- llm-serving-operator-role.yaml
- poimen-memory-operator-role.yaml
- sandbox-observer-role.yaml
# paperless's Role/RoleBinding lives in k8s/apps/paperless/rbac.yaml instead -
# that app already has its own kustomization + namespace, no need to
# duplicate it here. All of these stay inert (grant nothing) until
-23
View File
@@ -1,23 +0,0 @@
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: sandbox-observer
namespace: poimen-sandbox
rules:
- apiGroups: [""]
resources: [pods, pods/log, services]
verbs: [get, list, watch]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: poimen-devs-sandbox
namespace: poimen-sandbox
subjects:
- kind: Group
apiGroup: rbac.authorization.k8s.io
name: "oidc:poimen-devs"
roleRef:
kind: Role
name: sandbox-observer
apiGroup: rbac.authorization.k8s.io
@@ -123,156 +123,6 @@ data:
"custom": {"fillOpacity": 10}
}
}
},
{
"id": 7,
"title": "vLLM Prefix Cache Hit Rate",
"type": "timeseries",
"gridPos": {"h": 8, "w": 12, "x": 0, "y": 36},
"datasource": {"type": "prometheus", "uid": "prometheus"},
"targets": [
{
"expr": "vllm:prefix_cache_hit_rate",
"legendFormat": "prefix cache hit rate"
}
],
"fieldConfig": {
"defaults": {
"unit": "percentunit",
"min": 0,
"max": 1,
"custom": {"fillOpacity": 15},
"thresholds": {
"mode": "absolute",
"steps": [
{"color": "red", "value": 0},
{"color": "yellow", "value": 0.7},
{"color": "green", "value": 0.85}
]
}
}
}
},
{
"id": 8,
"title": "KV Warmup Hit vs Miss",
"type": "timeseries",
"gridPos": {"h": 8, "w": 12, "x": 12, "y": 36},
"datasource": {"type": "prometheus", "uid": "prometheus"},
"targets": [
{
"expr": "rate(memory_kv_cache_warmup_hit_total[5m])",
"legendFormat": "warmup hit"
},
{
"expr": "rate(memory_kv_cache_warmup_miss_total[5m])",
"legendFormat": "warmup miss"
},
{
"expr": "rate(memory_kv_cache_warmup_error_total[5m])",
"legendFormat": "warmup error"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops",
"custom": {"fillOpacity": 10}
}
}
},
{
"id": 9,
"title": "KV Warmup Latency p50/p95 (ms)",
"type": "timeseries",
"gridPos": {"h": 8, "w": 12, "x": 0, "y": 44},
"datasource": {"type": "prometheus", "uid": "prometheus"},
"targets": [
{
"expr": "histogram_quantile(0.50, sum(rate(memory_kv_cache_warmup_latency_ms_bucket[5m])) by (le))",
"legendFormat": "p50 warmup latency"
},
{
"expr": "histogram_quantile(0.95, sum(rate(memory_kv_cache_warmup_latency_ms_bucket[5m])) by (le))",
"legendFormat": "p95 warmup latency"
}
],
"fieldConfig": {
"defaults": {
"unit": "ms",
"custom": {"fillOpacity": 10}
}
}
},
{
"id": 10,
"title": "Standing Context Cache Tier Hits",
"type": "timeseries",
"gridPos": {"h": 8, "w": 12, "x": 12, "y": 44},
"datasource": {"type": "prometheus", "uid": "prometheus"},
"targets": [
{
"expr": "rate(memory_standing_ctx_hit_redis_total[5m])",
"legendFormat": "Redis L1 hit"
},
{
"expr": "rate(memory_standing_ctx_hit_db_total[5m])",
"legendFormat": "DB L2 hit"
},
{
"expr": "rate(memory_standing_ctx_recompute_total[5m])",
"legendFormat": "recompute (L3)"
},
{
"expr": "rate(memory_standing_ctx_304_total[5m])",
"legendFormat": "304 Not Modified"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops",
"custom": {"fillOpacity": 10}
}
}
},
{
"id": 11,
"title": "Standing Context Alert: Stale > 10min post-ingest",
"type": "timeseries",
"description": "Alert if standing context was not refreshed within 10min of an ingest event. Indicates staleness propagation failure.",
"gridPos": {"h": 8, "w": 24, "x": 0, "y": 52},
"datasource": {"type": "prometheus", "uid": "prometheus"},
"targets": [
{
"expr": "rate(memory_standing_ctx_recompute_total[5m]) > 0",
"legendFormat": "recompute rate (non-zero = fresh)"
},
{
"expr": "rate(memory_kv_cache_warmup_miss_total[5m])",
"legendFormat": "warmup miss rate (alert if > 3/5min)"
}
],
"fieldConfig": {
"defaults": {
"unit": "ops",
"custom": {"fillOpacity": 10},
"thresholds": {
"mode": "absolute",
"steps": [
{"color": "green", "value": 0},
{"color": "red", "value": 0.01}
]
}
},
"overrides": [
{
"matcher": {"id": "byName", "options": "warmup miss rate (alert if > 3/5min)"},
"properties": [
{"id": "thresholds", "value": {"mode": "absolute", "steps": [{"color": "green", "value": 0}, {"color": "red", "value": 0.01}]}},
{"id": "custom.thresholdsStyle", "value": {"mode": "area"}}
]
}
]
}
}
]
}
-20
View File
@@ -145,7 +145,6 @@ SERVICE_ACCOUNTS: Dict[str, Dict[str, Any]] = {
SCOPE_MAPPINGS: Dict[str, Dict[str, str]] = {
"roles": {"expression": 'return user.attributes.get("roles", [])'},
"permissions": {"expression": 'return ["*"] if any(user.groups.filter(is_superuser=True)) else list(user.groups.values_list("name", flat=True))'},
"groups": {"expression": 'return {"groups": list(user.groups.values_list("name", flat=True))}'},
"minio_buckets": {"expression": 'return user.attributes.get("minio_buckets", [])'},
"paperless_doctypes": {"expression": 'return user.attributes.get("paperless_doctypes", [])'},
"memory_projects": {"expression": 'return user.attributes.get("memory_projects", [])'},
@@ -247,25 +246,6 @@ for scope_name, scope_spec in SCOPE_MAPPINGS.items():
else:
print(f" {scope_name}: FAILED {status} {res}")
# Fix built-in 'openid' scope to include preferred_username (needed by Grafana, Forgejo, etc.)
# Note: sub MUST be a string, not int, for JSON compatibility with Go struct unmarshaling
if "openid" in existing_scopes:
openid_scope = existing_scopes["openid"]
openid_pk = openid_scope["pk"]
openid_expression = 'return {"sub": str(user.pk), "preferred_username": user.username}'
if openid_expression not in openid_scope.get("expression", ""):
status, res = api("PUT", f"/api/v3/propertymappings/provider/scope/{openid_pk}/", {
"name": openid_scope["name"],
"scope_name": "openid",
"expression": openid_expression,
})
if status in (200, 201):
print(f" openid: updated (sub as string + preferred_username)")
else:
print(f" openid: UPDATE FAILED {status} {res}")
else:
print(f" openid: already correct (sub as string)")
# ===========================================================================
# Phase 4: Get flow UUIDs (needed for providers)
# ===========================================================================
-3
View File
@@ -38,9 +38,6 @@
rewrite name api.riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
rewrite name comfy.riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
rewrite name comfyui.riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
rewrite name gotify.riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
rewrite name pi.riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
rewrite name igotify.riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
rewrite name riotpiao.com ingress-nginx-controller.ingress-nginx.svc.cluster.local
kubernetes cluster.local in-addr.arpa ip6.arpa {