Resource limits

This guide explains how to configure resource limits for Faheem Code Enterprise components. Proper resource configuration ensures stable operation and prevents issues like OOMKills and pod evictions.

Values file structure

All configuration examples in this guide show keys that belong in your site-values.yaml file. The examples show the complete path from the root of the file.

Tip

Create a site-values.yaml file to store your custom configuration. Pass it to Helm with -f site-values.yaml when installing or upgrading.

Understanding Kubernetes resources

Kubernetes uses two key resource settings:

• Requests: The minimum resources guaranteed to a pod. The scheduler uses this to place pods on nodes with sufficient capacity.
• Limits: The maximum resources a pod can use. Exceeding memory limits causes an OOMKill; exceeding CPU limits causes throttling.

Warning

If a pod uses significantly more memory than its request (but below its limit), it becomes a candidate for eviction during node pressure. Set requests close to actual usage for production workloads.

Application server resources

The Faheem Code application server (deployment name: faheemcode) handles the UI, API, and agent orchestration. Configure its resources under the deployment section in your values file.

Default configuration

# site-values.yaml

# ============================================================================
# Application Server (Faheem Code deployment)
# ============================================================================
# Root-level key: deployment
# Controls the main Faheem Code server pod resources
# ============================================================================
deployment:
  replicas: 1
  resources:
    requests:
      memory: 1200Mi
      cpu: 100m
    limits:
      memory: 3Gi

Recommended production configuration

For production workloads, increase memory and add replicas for redundancy:

# site-values.yaml

deployment:                        # Root-level key
  replicas: 2
  resources:
    requests:
      memory: 2560Mi               # 2.5Gi - aligns with typical usage
      cpu: 100m
    limits:
      memory: 4Gi                  # Buffer against OOMKill

When to adjust

Increase resources if you observe:

Symptom	Metric to Check	Action
Pod restarts	RESTARTS column in kubectl get pods	Increase limits.memory
High memory usage	kubectl top pods shows >80% of limit	Increase limits.memory
Evictions during node pressure	Pod events show eviction	Increase requests.memory to match actual usage
Slow response times	Application latency metrics	Add replicas or increase CPU

Horizontal pod autoscaling

For automatic scaling based on load, enable the HorizontalPodAutoscaler:

# site-values.yaml

deployment:                        # Root-level key
  replicas: 2                      # Minimum baseline
  resources:
    requests:
      memory: 2560Mi
      cpu: 200m                    # Increase for HPA to use as scaling signal
    limits:
      memory: 4Gi

autoscaling:                       # Root-level key (separate from deployment)
  enabled: true
  minReplicas: 2
  maxReplicas: 5
  targetCPUUtilizationPercentage: 80
  targetMemoryUtilizationPercentage: 80

Sandbox resources

Sandboxes (also called runtimes) are the isolated containers where agents execute code. Each conversation runs in its own sandbox pod. Configure these via environment variables in the runtime-api.env section.

Available settings

Variable	Default	Description
MEMORY_REQUEST	3072Mi	Minimum memory guaranteed per sandbox
MEMORY_LIMIT	3072Mi	Maximum memory per sandbox
CPU_REQUEST	500m	Minimum CPU guaranteed (500m = 0.5 cores)
CPU_LIMIT	(none)	Maximum CPU per sandbox
EPHEMERAL_STORAGE_SIZE	10Gi	Temporary storage per sandbox

Default configuration

# site-values.yaml

# ============================================================================
# Runtime API (Sandbox Manager)
# ============================================================================
# Root-level key: runtime-api
# This is a subchart that manages sandbox pod lifecycle.
# The env section passes environment variables to the runtime-api container,
# which uses them when creating sandbox pods.
# ============================================================================
runtime-api:
  env:
    MEMORY_REQUEST: "3072Mi"
    MEMORY_LIMIT: "3072Mi"
    CPU_REQUEST: "500m"
    EPHEMERAL_STORAGE_SIZE: "10Gi"

High-resource configuration

For workloads that require more resources (large codebases, memory-intensive builds):

# site-values.yaml

runtime-api:                       # Root-level key (subchart configuration)
  env:
    MEMORY_REQUEST: "8192Mi"
    MEMORY_LIMIT: "8192Mi"
    CPU_REQUEST: "2000m"
    CPU_LIMIT: "4000m"
    EPHEMERAL_STORAGE_SIZE: "50Gi"

Resource format

• Memory: Use Mi suffix (mebibytes). Examples: 1024Mi, 4096Mi, 8192Mi
• CPU: Use millicores. 1000m = 1 CPU core. Examples: 500m, 2000m, 4000m
• Storage: Use Gi suffix (gibibytes). Examples: 10Gi, 50Gi, 100Gi

Warning

Changes to sandbox resources only affect new sandboxes. Existing running sandboxes keep their original limits until stopped and restarted.

Applying changes

1. Update your values file

Edit site-values.yaml with your desired configuration:

# site-values.yaml
#
# This file contains your custom overrides for the Faheem Code Helm chart.
# All keys shown here are root-level keys in the values hierarchy.

# ============================================================================
# Application Server Resources
# ============================================================================
deployment:
  replicas: 2
  resources:
    requests:
      memory: 2560Mi
      cpu: 100m
    limits:
      memory: 4Gi

# ============================================================================
# Sandbox Resources (via Runtime API subchart)
# ============================================================================
runtime-api:
  env:
    MEMORY_REQUEST: "8192Mi"
    MEMORY_LIMIT: "8192Mi"
    CPU_REQUEST: "2000m"
    CPU_LIMIT: "4000m"
    EPHEMERAL_STORAGE_SIZE: "50Gi"

2. Apply with Helm upgrade

helm upgrade faheemcode \
  oci://ghcr.io/alsairy/faheem-code-charts/faheemcode \
  -f site-values.yaml \
  -n faheemcode

Verifying changes

Check application server resources

kubectl get deployment faheemcode -n faheemcode \
  -o jsonpath='{.spec.template.spec.containers[0].resources}' | jq

Check replica count

kubectl get deployment faheemcode -n faheemcode \
  -o jsonpath='{.spec.replicas}'

Check runtime-api environment variables

Verify the sandbox resource settings are configured in the runtime-api deployment:

kubectl get deployment runtime-api -n faheemcode \
  -o jsonpath='{.spec.template.spec.containers[0].env}' | \
  jq '.[] | select(.name | test("MEMORY|CPU|STORAGE"))'

Monitoring resource usage

Current resource consumption

kubectl top pods -n faheemcode

Resource usage over time

For production deployments, we recommend integrating with a monitoring solution (Prometheus/Grafana, Datadog, etc.) to track:

• Memory usage vs. limits (to predict OOMKills)
• Memory usage vs. requests (to predict evictions)
• CPU throttling events
• Pod restart counts

Next steps

Sizing guide

Translate peak concurrent sandboxes into node pools, storage, and database size.

K8s install overview

Return to the Kubernetes installation overview.

Enterprise overview

Learn more about Faheem Code Enterprise features.