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Noxus workers execute background tasks — workflow runs, knowledge-base ingestion, and agent conversations. The worker system uses Redis as the default message broker and coordination layer. PostgreSQL can also be used as an alternative broker, but Redis is recommended for production deployments due to lower latency and better support for pub/sub patterns. Workers are configured through environment variables that control task routing, and the Helm chart supports defining multiple pools — each with its own Deployment, Service, autoscaler, and PodDisruptionBudget.

Task Routing

Queue Types (WORKER_SUBSCRIBE)

Each worker pool subscribes to one or more task types via the WORKER_SUBSCRIBE environment variable.
Queue TypeDescription
allProcess all task types
all_but_kbEverything except knowledge-base ingestion
flowWorkflow execution only
chatConversational AI / agent tasks only
kbKnowledge-base ingestion only

Tenant & Workspace Filtering

Workers can be scoped to specific tenants and/or workspaces using comma-separated ID lists:
VariableDescription
WORKER_SUBSCRIBE_TENANTSComma-separated tenant IDs this worker processes (empty = all)
WORKER_SUBSCRIBE_WORKSPACESComma-separated workspace IDs this worker processes (empty = all)
These filters combine with WORKER_SUBSCRIBE — a worker set to workerSubscribe: "flow" with workerSubscribeTenants: "tenant-abc,tenant-xyz" will only process workflow tasks for those two tenants.

Worker Pools

Define multiple pools under worker.pools in your Helm values. Each pool creates an independent Kubernetes Deployment.

Pool Configuration Reference

FieldTypeDefaultDescription
enabledboolEnable or disable this pool
replicaCountint1Static replica count (ignored when autoscaling is enabled)
workerSubscribestring"all_but_kb"Queue type subscription
workerSubscribeTenantsstring""Comma-separated tenant IDs (empty = all)
workerSubscribeWorkspacesstring""Comma-separated workspace IDs (empty = all)
envSecretRefstring""Name of an additional K8s Secret to layer on top of the shared app-env
resourcesobjectCPU/memory requests and limits
autoscalingobjectHPA or KEDA autoscaling config
podDisruptionBudgetobjectPDB settings
affinityobject{}Pod affinity/anti-affinity rules
nodeSelectorobject{}Node selector constraints
tolerationslist[]Node tolerations
topologySpreadConstraintslist[]Topology spread rules

Basic Multi-Pool Example

worker:
  enabled: true
  pools:
    default:
      enabled: true
      workerSubscribe: "all_but_kb"
      resources:
        requests:
          cpu: "2"
          memory: "12Gi"
        limits:
          cpu: "2"
          memory: "12Gi"
      autoscaling:
        enabled: true
        type: "keda"
        minReplicas: 1
        maxReplicas: 10

    kb:
      enabled: true
      workerSubscribe: "kb"
      resources:
        requests:
          cpu: "4"
          memory: "16Gi"
        limits:
          cpu: "4"
          memory: "16Gi"
      autoscaling:
        enabled: true
        type: "hpa"
        minReplicas: 1
        maxReplicas: 5
        targetCPUUtilizationPercentage: 75

    chat:
      enabled: true
      workerSubscribe: "chat"
      resources:
        requests:
          cpu: "4"
          memory: "16Gi"
        limits:
          cpu: "4"
          memory: "16Gi"
      autoscaling:
        enabled: true
        type: "keda"
        minReplicas: 0
        maxReplicas: 5
        keda:
          query: >-
            SELECT COUNT(*) FROM runs
            WHERE status IN ('Queued')
            AND queue_type = 'chat';
          targetQueryValue: "5"

Tenant Isolation

Use workerSubscribeTenants and workerSubscribeWorkspaces to dedicate worker pools to specific tenants or workspaces. This is useful for:
  • Noisy-neighbor isolation — prevent one tenant’s heavy workloads from starving others
  • SLA tiers — dedicated capacity for premium tenants
  • Data residency — pin certain tenants to workers in specific regions or nodes
worker:
  pools:
    # Shared pool for all tenants (catch-all)
    default:
      enabled: true
      workerSubscribe: "all"
      autoscaling:
        enabled: true
        type: "keda"
        minReplicas: 1
        maxReplicas: 10

    # Dedicated pool for a high-volume tenant
    tenant-acme:
      enabled: true
      workerSubscribe: "all"
      workerSubscribeTenants: "tid_acme_corp_123"
      autoscaling:
        enabled: true
        type: "keda"
        minReplicas: 1
        maxReplicas: 8

    # Dedicated KB processing for specific workspaces
    kb-enterprise:
      enabled: true
      workerSubscribe: "kb"
      workerSubscribeWorkspaces: "ws_ent_001,ws_ent_002,ws_ent_003"
      autoscaling:
        enabled: true
        type: "hpa"
        minReplicas: 1
        maxReplicas: 5
        targetCPUUtilizationPercentage: 75

Per-Pool Secrets

By default, all worker pools share the same Kubernetes Secret ({release}-app-env). When different pools need different environment variables — such as separate LLM API keys per tenant, different Redis databases, or pool-specific feature flags — use envSecretRef to layer an additional Secret on top.
worker:
  pools:
    default:
      enabled: true
      workerSubscribe: "all"
      # Uses only the shared app-env secret

    tenant-acme:
      enabled: true
      workerSubscribe: "all"
      workerSubscribeTenants: "tid_acme_corp_123"
      # Env vars in this secret override the shared app-env
      envSecretRef: "acme-worker-env"
Create the per-pool secret separately (or via External Secrets Operator):
apiVersion: v1
kind: Secret
metadata:
  name: acme-worker-env
  namespace: spotflow
type: Opaque
stringData:
  OPENAI_API_KEY: "sk-acme-dedicated-key"
  ANTHROPIC_API_KEY: "sk-ant-acme-key"
The pool-specific secret is mounted after the shared one in envFrom, so its values take precedence for any overlapping keys.

Multi-Namespace Deployment

To run worker groups in different namespaces (e.g., for resource quotas or network policy isolation), deploy separate Helm releases that share the same backend infrastructure.
1

Deploy the primary release

The primary release deploys backend, frontend, beat, and the default worker pool.
# values-primary.yaml
backend:
  enabled: true
frontend:
  enabled: true
beat:
  enabled: true

worker:
  enabled: true
  pools:
    default:
      enabled: true
      workerSubscribe: "all_but_kb"
      autoscaling:
        enabled: true
        type: "keda"
        minReplicas: 1
        maxReplicas: 10
helm upgrade --install noxus ./cdk/helm/noxus-platform \
  --namespace spotflow --create-namespace \
  -f values.yaml -f values-primary.yaml
2

Deploy worker-only releases

For each additional namespace, disable all non-worker components and provide the same database/Redis credentials.
# values-kb-workers.yaml
backend:
  enabled: false
frontend:
  enabled: false
beat:
  enabled: false
relay:
  enabled: false

# Same credentials as the primary release
env:
  DATABASE: "spot"
  REDIS_PORT: "6379"
secrets:
  DATABASE_URL: "postgresql://user:pass@db-host:5432/spot"
  REDIS_URL: "redis-host"
  REDIS_PASSWORD: "redis-pass"

worker:
  enabled: true
  pools:
    kb:
      enabled: true
      workerSubscribe: "kb"
      resources:
        requests:
          cpu: "4"
          memory: "16Gi"
        limits:
          cpu: "4"
          memory: "16Gi"
      autoscaling:
        enabled: true
        type: "hpa"
        minReplicas: 1
        maxReplicas: 5
        targetCPUUtilizationPercentage: 75
      nodeSelector:
        workload-type: kb
helm upgrade --install noxus-kb ./cdk/helm/noxus-platform \
  --namespace spotflow-kb --create-namespace \
  -f values.yaml -f values-kb-workers.yaml
All worker releases must connect to the same PostgreSQL and Redis instances. Redis coordinates task distribution — workers in any namespace pick up tasks from their subscribed queues regardless of where they run.

Cross-Namespace Considerations

  • Secrets: Each namespace gets its own K8s Secret. Use External Secrets Operator or a shared values file to keep credentials in sync.
  • Service Account: Worker-only releases still need a ServiceAccount with IRSA annotations for S3 access.
  • KEDA: ScaledObjects are namespace-scoped. Each release creates its own KEDA resources; the cluster-wide KEDA operator discovers them automatically.
  • Network Policies: Ensure worker namespaces can reach PostgreSQL, Redis, external APIs, and storage endpoints.

Autoscaling

Best for scaling based on actual queue depth. Supports scale-to-zero.KEDA polls PostgreSQL to count queued/running tasks and adjusts replicas to maintain a target ratio.
worker:
  keda:
    postgresConnectionString: "postgresql://user:pass@host:5432/spot"
    pollingInterval: 15
    query: >-
      SELECT COALESCE(COUNT(*), 0) FROM runs
      WHERE status IN ('Queued', 'Running')
      AND created_at > NOW() - '1 hour'::interval;
    targetQueryValue: "10"
    cronTrigger:
      enabled: true
      timezone: "UTC"
      start: "0 9 * * *"
      end: "0 20 * * *"
      desiredReplicas: 1

  pools:
    default:
      autoscaling:
        enabled: true
        type: "keda"
        minReplicas: 1
        maxReplicas: 10
        behavior:
          scaleDown:
            stabilizationWindowSeconds: 300
            policies:
              - type: Percent
                value: 10
                periodSeconds: 60
Individual pools can override the global KEDA query and target:
autoscaling:
  type: "keda"
  keda:
    query: "SELECT COUNT(*) FROM runs WHERE status = 'Queued' AND queue_type = 'chat';"
    targetQueryValue: "5"
    pollingInterval: 10

Verification

After deploying, verify the setup:
# Worker deployments across namespaces
kubectl get deployments -l app=worker --all-namespaces

# Pool labels on pods
kubectl get pods -l app=worker --all-namespaces --show-labels

# KEDA ScaledObjects
kubectl get scaledobjects --all-namespaces

# HPAs
kubectl get hpa --all-namespaces -l app=worker

# PodDisruptionBudgets
kubectl get pdb --all-namespaces -l app=worker

# Verify queue subscription in worker logs
kubectl logs -l app=worker --tail=50 | grep "WORKER_SUBSCRIBE"