Worker services in porter.yaml

Complete field reference for worker services in porter.yaml including health checks, autoscaling, GPU allocation, and resource limits

Worker services are background processing services that don’t expose HTTP endpoints. They’re ideal for queue consumers, background jobs, and long-running processes. This is a complete reference for all fields that can be set for a worker service in porter.yaml.

Field Reference

Field	Type	Required	Description
name	string	Yes	Service identifier (max 31 chars)
type	string	Yes	Must be worker
run	string	Yes	Command to execute
cpuCores	number	Yes	CPU allocation
ramMegabytes	integer	Yes	Memory allocation in MB
instances	integer	No	Number of replicas (default: 1)
autoscaling	object	No	Autoscaling configuration
healthCheck	object	No	Combined health check config
livenessCheck	object	No	Liveness probe config
readinessCheck	object	No	Readiness probe config
startupCheck	object	No	Startup probe config
connections	array	No	External cloud connections
serviceMeshEnabled	boolean	No	Enable service mesh
terminationGracePeriodSeconds	integer	No	Graceful shutdown timeout
gpuCoresNvidia	integer	No	NVIDIA GPU cores
nodeGroup	string	No	Node group UUID

---

Basic Example

services:
  - name: queue-worker
    type: worker
    run: npm run worker
    cpuCores: 0.5
    ramMegabytes: 512
    instances: 3

---

autoscaling

object

Optional

Configure horizontal pod autoscaling based on CPU and memory utilization. See Autoscaling Configuration for full documentation.

---

healthCheck

object

Optional

Configure a combined health check that applies to liveness, readiness, and startup probes. Worker services use command-based health checks since they don’t expose HTTP endpoints.

Field	Type	Description
enabled	boolean	Enable health checks
command	string	Command to run for health check
timeoutSeconds	integer	Command timeout (min: 1)
initialDelaySeconds	integer	Initial delay before checking (min: 0)

healthCheck:
  enabled: true
  command: ./healthcheck.sh
  timeoutSeconds: 5
  initialDelaySeconds: 15

Cannot be used together with livenessCheck, readinessCheck, or startupCheck. Use either the combined healthCheck or the individual checks.

For best practices on combining command-based health checks with graceful shutdown (SIGTERM handling, shutdown markers), see Zero-Downtime Deployments: Workers.

---

Advanced Health Checks

For fine-grained control, configure liveness, readiness, and startup probes separately.

livenessCheck

object

Optional

Determines if the container should be restarted.

livenessCheck:
  enabled: true
  command: ./livez.sh
  timeoutSeconds: 5
  initialDelaySeconds: 15

readinessCheck

object

Optional

Determines if the container is ready to receive work.

readinessCheck:
  enabled: true
  command: ./readyz.sh
  timeoutSeconds: 5
  initialDelaySeconds: 5

startupCheck

object

Optional

Used for slow-starting containers. Other probes are disabled until this passes.

startupCheck:
  enabled: true
  command: ./startupz.sh
  timeoutSeconds: 10
  initialDelaySeconds: 0

---

connections

array

Optional

Connect to external cloud services. See Connections Configuration for full documentation.

---

serviceMeshEnabled

boolean

Optional

Enable service mesh for enhanced inter-service communication with improved performance, reliability, and monitoring.

serviceMeshEnabled: true

Useful for workers that need to communicate with other services in your cluster.

---

terminationGracePeriodSeconds

integer

Optional

Seconds to wait for graceful shutdown before forcefully terminating the container.

terminationGracePeriodSeconds: 120

Set this to a value higher than your longest expected job. This gives workers time to complete in-progress work before shutdown.

---

gpuCoresNvidia

integer

Optional

Allocate NVIDIA GPU cores for ML workloads or GPU-accelerated processing.

gpuCoresNvidia: 1
nodeGroup: gpu-node-group-uuid

Requires a node group with GPU-enabled instances.

---

Complete Example

services:
  - name: queue-processor
    type: worker
    run: npm run worker
    cpuCores: 1
    ramMegabytes: 2048

    # Autoscaling
    autoscaling:
      enabled: true
      minInstances: 2
      maxInstances: 20
      cpuThresholdPercent: 70
      memoryThresholdPercent: 80

    # Health checks
    livenessCheck:
      enabled: true
      command: ./healthcheck.sh
      timeoutSeconds: 5
    readinessCheck:
      enabled: true
      command: ./ready.sh
      timeoutSeconds: 3

    # Cloud connections
    connections:
      - type: awsRole
        role: worker-sqs-access

    # Service mesh
    serviceMeshEnabled: true

    # Graceful shutdown (allow 2 minutes for jobs to complete)
    terminationGracePeriodSeconds: 120

---

Common Use Cases

Queue Consumer

services:
  - name: sqs-consumer
    type: worker
    run: node src/workers/sqs-consumer.js
    cpuCores: 0.5
    ramMegabytes: 512
    instances: 5
    terminationGracePeriodSeconds: 60
    connections:
      - type: awsRole
        role: sqs-consumer-role

Background Job Processor

services:
  - name: job-processor
    type: worker
    run: bundle exec sidekiq
    cpuCores: 1
    ramMegabytes: 1024
    autoscaling:
      enabled: true
      minInstances: 2
      maxInstances: 10
      cpuThresholdPercent: 70
    terminationGracePeriodSeconds: 300

ML Inference Worker

services:
  - name: ml-worker
    type: worker
    run: python worker.py
    cpuCores: 4
    ramMegabytes: 8192
    gpuCoresNvidia: 1
    nodeGroup: gpu-node-group-uuid
    instances: 2