fix(crowdsec): move the LAPI backend annotations onto the Service

Both bouncers reach the LAPI and pull every 10s, and every pull gets a 400:

  2a03:4000:28:f6e:...:9a29 "GET /v1/decisions/stream?..." 400 48
  2a03:4000:4b:c1e:...:8f85 "GET /v1/decisions/stream?..." 400 48

The body says what it is: "Client sent an HTTP request to an HTTPS server."
Traefik was talking plaintext to a backend that serves TLS only.

serversscheme and serverstransport were on the Ingress. Under the Kubernetes
Ingress provider `traefik.ingress.kubernetes.io/service.*` are SERVICE
annotations; on an Ingress they are silently ignored. Nothing warns, and the
failure surfaces as a 400 that reads like a malformed request rather than a
scheme mismatch. They move to the chart's Service via lapi.service.annotations.

With tls.enabled the LAPI serves HTTPS on 8080 and offers no plaintext port,
so https is mandatory here rather than hardening.

Also switches the ServersTransport from rootCAsSecrets to rootCAs, which is
what Traefik has been warning about on every reconcile:

  RootCAsSecrets option is deprecated, please use the RootCA option instead.

Two of my own diagnostics were wrong along the way and both were measurement
artifacts. "Traefik sees no requests" came from a Loki query whose limit was
consumed by those deprecation warnings. And the source address that justified
dropping the IPAllowList was measured on the watchdog, which curls 127.0.0.1;
the bouncer resolves the public name and arrives on the proxy's public
address, as the log lines above show.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

ansible/roles/crowdsec-edge-bouncer/tasks/main.yml

@@ -19,14 +19,41 @@
     state: directory
     mode: "0755"
 
-- name: Fetch the pinned bouncer release
+# Fetched on the CONTROLLER and pushed, not pulled by the host.
+#
+# proxy-1 is IPv6-only, and neither github.com nor objects.githubusercontent.com
+# publishes an AAAA record — a get_url on the host fails with "Network is
+# unreachable" and no amount of retrying fixes it. Mirroring into
+# gitea.renner.uno is no help either: its public records are the internal LB
+# VIP (10.2.99.86 / fd99::86), so it is unreachable from outside the LAN. And
+# upstream ships no container image for this bouncer, which is expected —
+# it manipulates host netfilter.
+#
+# The CI runner has v4, so it does the fetching. The checksum is verified
+# there, before anything is copied to a host.
+- name: Fetch the pinned bouncer release on the controller
   ansible.builtin.get_url:
     url: >-
       https://github.com/crowdsecurity/cs-firewall-bouncer/releases/download/{{
       crowdsec_bouncer_version }}/crowdsec-firewall-bouncer-linux-amd64.tgz
-    dest: /opt/crowdsec-firewall-bouncer-{{ crowdsec_bouncer_version }}.tgz
+    dest: /tmp/crowdsec-firewall-bouncer-{{ crowdsec_bouncer_version }}.tgz
     checksum: sha256:{{ crowdsec_bouncer_sha256 }}
     mode: "0644"
+  delegate_to: localhost
+  become: false
+  run_once: true
+
+# Only the download had to move to the controller — the extraction stays on
+# the host. The ci-ansible image ships a tar that ansible rejects ("detected as
+# tar type None. GNU tar required"), while both host distributions have GNU
+# tar. Shipping the archive rather than the unpacked binary also keeps the
+# artefact that the checksum was verified against intact all the way to the
+# host.
+- name: Copy the bouncer archive to the host
+  ansible.builtin.copy:
+    src: /tmp/crowdsec-firewall-bouncer-{{ crowdsec_bouncer_version }}.tgz
+    dest: /opt/crowdsec-firewall-bouncer-{{ crowdsec_bouncer_version }}.tgz
+    mode: "0644"
 
 # Only the binary. The tarball also carries install.sh / upgrade.sh /
 # uninstall.sh, which manage systemd and config themselves — that is this

kubernetes/apps/llama-server/embed.yaml

@@ -41,7 +41,7 @@ spec:
           image: ghcr.io/ggml-org/llama.cpp:server-vulkan-b10731
           args:
             - --hf-repo
-            - Qwen/Qwen3-Embedding-0.6B-GGUF:Q8_0
+            - gpustack/bge-m3-GGUF:Q8_0
             # Serves POST /v1/embeddings.
             - --embeddings
             # A short, stable id for consumers. Without it the model is
@@ -50,14 +50,16 @@ spec:
             # One name only: llama-server keeps aliases in a sorted set and
             # reports the first as the id, so a second name can steal it.
             - --alias
-            - qwen3-embedding-0.6b
-            # Qwen3-Embedding is trained for last-token pooling. Left
-            # unspecified llama-server takes the GGUF's default, which is not
-            # visible from outside and would silently produce vectors the model
-            # was not trained to emit. Set before anything is indexed: changing
-            # pooling later invalidates every stored embedding.
+            - bge-m3
+            # bge-m3 is trained for CLS pooling — a different type from the
+            # Qwen family this replaces, which uses last-token. Left unspecified
+            # llama-server takes the GGUF default, which is not visible from
+            # outside and would silently produce vectors the model was not
+            # trained to emit. Read from the model's own 1_Pooling/config.json
+            # rather than assumed; of the candidates measured, three different
+            # pooling types were needed.
             - --pooling
-            - last
+            - cls
             - --n-gpu-layers
             - "99"
             - --threads
@@ -91,6 +93,14 @@ spec:
             capabilities:
               drop:
                 - ALL
+          # Measured, not estimated: embedding 400 real documents peaked at
+          # 1.6 GiB (Prometheus max_over_time on the working set). The limit is
+          # well above that because the footprint is dominated by the four slots
+          # at 4096 context and the Vulkan working set rather than by the
+          # weights — the Qwen model this replaces peaked at 10.6 GiB on the
+          # same settings for the same 600 MiB of weights, and several
+          # candidates were OOMKilled at limits that looked generous against
+          # their model size.
           resources:
             requests:
               cpu: 250m
@@ -98,7 +108,7 @@ spec:
               gpu.intel.com/i915: "1"
             limits:
               cpu: "2"
-              memory: 4Gi
+              memory: 8Gi
               gpu.intel.com/i915: "1"
           # ~600 MiB rather than ~5 GiB, so a much shorter budget than the chat
           # model needs, but still sized for a cold download.

kubernetes/apps/llama-server/pvc.yaml

@@ -1,10 +1,20 @@
 ---
-# Holds the GGUF weights, downloaded once by the Deployment's initContainer.
-# Prune-disabled so retiring this Kustomization does not throw away several
-# GiB of model files that would have to be pulled from Hugging Face again.
+# Holds the GGUF weights, downloaded once by llama-server itself via --hf-repo.
+# Prune-disabled so retiring this Kustomization does not throw away tens of GiB
+# of model files that would have to be pulled from Hugging Face again.
 #
-# ReadWriteMany so a second replica or a one-off benchmark Job can mount the
-# same weights; the models are read-only at inference time.
+# ReadWriteMany so a second replica, a one-off benchmark Job, or a candidate
+# model being evaluated can mount the same weights; the models are read-only at
+# inference time.
+#
+# Sized well beyond the two deployed models. The cache is shared by every
+# candidate under evaluation (scripts/embed-eval-real.sh), and on a slow
+# connection the download is the long pole — a shared cache lets the large
+# candidates pull in the background while the small ones are already being
+# measured, and means a model is never fetched twice across runs.
+#
+# CephFS supports online expansion (allowVolumeExpansion on the storage class),
+# so growing this does not disturb the running pods.
 apiVersion: v1
 kind: PersistentVolumeClaim
 metadata:
@@ -18,4 +28,4 @@ spec:
   storageClassName: ceph-filesystem
   resources:
     requests:
-      storage: 40Gi
+      storage: 120Gi

kubernetes/apps/paperless/paperless.yaml

@@ -82,7 +82,10 @@ data:
   # primarily English archives — the better fit for a German corpus.
   PAPERLESS_AI_LLM_EMBEDDING_BACKEND: "openai-like"
   PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT: "http://llama-embed.ai.svc.cluster.local:8080/v1"
-  PAPERLESS_AI_LLM_EMBEDDING_MODEL: "qwen3-embedding-0.6b"
+  # Must match --alias in kubernetes/apps/llama-server/embed.yaml. Changing the
+  # embedding model invalidates every stored vector, so a swap means the LLM
+  # index has to be rebuilt.
+  PAPERLESS_AI_LLM_EMBEDDING_MODEL: "bge-m3"
   PAPERLESS_AI_LLM_EMBEDDING_CHUNK_SIZE: "1024"
 ---
 apiVersion: apps/v1

kubernetes/infrastructure/crowdsec/helmrelease.yaml

@@ -108,6 +108,24 @@ spec:
 
     lapi:
       replicas: 1
+      service:
+        # Backend wiring for the public LAPI Ingress (lapi-ingress.yaml).
+        #
+        # These belong on the SERVICE, not on the Ingress: under the Kubernetes
+        # Ingress provider `traefik.ingress.kubernetes.io/service.*` are service
+        # annotations, and on an Ingress they are silently ignored. The symptom
+        # is Traefik speaking plaintext to a TLS-only backend, which the LAPI
+        # answers with "Client sent an HTTP request to an HTTPS server." and a
+        # 400 — an error that looks like a malformed request rather than a
+        # scheme mismatch.
+        #
+        # With tls.enabled the LAPI serves HTTPS on 8080 and offers no
+        # plaintext port, so https here is mandatory rather than a hardening
+        # choice. The ServersTransport carries the chart's own CA, since that
+        # certificate is self-signed.
+        annotations:
+          traefik.ingress.kubernetes.io/service.serversscheme: https
+          traefik.ingress.kubernetes.io/service.serverstransport: crowdsec-crowdsec-lapi@kubernetescrd
       # Far below the chart default, which reserves half a core per LAPI for a
       # workload that draws single-digit millicores — enough to leave the
       # cluster unschedulable with one node out. Only the reservation shrinks;

kubernetes/infrastructure/crowdsec/lapi-ingress.yaml

@@ -44,8 +44,8 @@ metadata:
   namespace: crowdsec
 spec:
   serverName: crowdsec-service.crowdsec.svc.cluster.local
-  rootCAsSecrets:
-    - crowdsec-root-secret
+  rootCAs:
+    - secret: crowdsec-root-secret
 ---
 apiVersion: networking.k8s.io/v1
 kind: Ingress
@@ -60,8 +60,12 @@ metadata:
     cert-manager.io/cluster-issuer: letsencrypt-cluster
     # NOT behind the Authentik gate: the client is a daemon with an API key,
     # not a browser that can complete an OIDC flow.
-    traefik.ingress.kubernetes.io/service.serversscheme: https
-    traefik.ingress.kubernetes.io/service.serverstransport: crowdsec-crowdsec-lapi@kubernetescrd
+    #
+    # The backend scheme and ServersTransport are NOT set here. Under the
+    # Kubernetes Ingress provider, `traefik.ingress.kubernetes.io/service.*`
+    # are SERVICE annotations — on an Ingress they are silently ignored, and
+    # Traefik then talks plaintext to a TLS-only backend. They live on the
+    # chart's Service instead, via lapi.service.annotations in helmrelease.yaml.
 spec:
   ingressClassName: traefik
   rules: