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(self-managed-http-load-test)=

Self-Managed NVCF HTTP Load Test

Prerequisites

Self-hosted CLI

You need a working nvcf-cli configured against your self-managed cluster. If you have not set this up yet, follow the {ref}self-hosted-cli guide to install the binary and the {ref}cli-configuration section to point it at your gateway.

Verify the CLI can reach the cluster before continuing:

./nvcf-cli init
./nvcf-cli api-key generate

Deploy the load test function

Use the load_tester_supreme container for load testing. It is purpose-built for high-throughput benchmarking and includes:

  • gRPC + HTTP + SSE endpoints in a single image
  • Tunable repeats, delay, and size fields to shape request/response profiles
  • Built-in OpenTelemetry tracing

The source, build instructions, and registry push examples are in the nv-cloud-function-helpers repository. Build and push the image to whichever container registry your cluster has credentials for:

git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
cd nv-cloud-function-helpers/examples/function_samples/load_tester_supreme

# Build
docker build --platform linux/amd64 -t load_tester_supreme .

# Tag and push (replace with your registry -- NGC, ECR, etc.)
docker tag load_tester_supreme nvcr.io/<your-org>/load_tester_supreme:latest
docker push nvcr.io/<your-org>/load_tester_supreme:latest

:::{tip} To check which registries your cluster recognises, run ./nvcf-cli registry list. :::

Then create the function and deploy it using the CLI:

# Create the function (HTTP)
./nvcf-cli function create \
  --name "load-tester-supreme" \
  --image "nvcr.io/<your-org>/load_tester_supreme:latest" \
  --inference-url "/echo" \
  --inference-port 8000 \
  --health-uri "/health" \
  --health-port 8000 \
  --health-timeout PT30S

# Deploy (adjust GPU type and instance type for your cluster)
./nvcf-cli function deploy create \
  --gpu H100 \
  --instance-type NCP.GPU.H100_1x \
  --min-instances 1 \
  --max-instances 1 \
  --function-id <function id> \
  --version-id <version id>

# Generate an API key for invocations
./nvcf-cli api-key generate

Once deployed, note the following -- you will need them for the run script:

  • Function ID -- the UUID returned by function create
  • Function Version ID -- the UUID of the specific deployed version
  • API key -- from ./nvcf-cli api-key generate (begins with nvapi-)

Obtain the gateway address

Your gateway address is the external address of the Envoy Gateway deployed with the control plane. To retrieve it:

export GATEWAY_ADDR=$(kubectl get gateway nvcf-gateway -n envoy-gateway \
  -o jsonpath='{.status.addresses[0].value}')
echo "Gateway Address: $GATEWAY_ADDR"

On AWS EKS this is an ELB hostname (e.g. a1b2c3d4.us-east-1.elb.amazonaws.com). For a local deployment (Kind, k3d, Docker Desktop) it is typically localhost or 127.0.0.1.

Clone the load test scripts

git clone https://github.com/NVIDIA/nv-cloud-function-helpers.git
cd nv-cloud-function-helpers/examples/load-tests

Install k6

Install k6 if you don't have it:

# macOS
brew install k6
# Linux (Debian/Ubuntu)
sudo gpg -k
sudo gpg --no-default-keyring --keyring /usr/share/keyrings/k6-archive-keyring.gpg \
  --keyserver hkp://keyserver.ubuntu.com:80 \
  --recv-keys C5AD17C747E3415A3642D57D77C6C491D6AC1D69
echo "deb [signed-by=/usr/share/keyrings/k6-archive-keyring.gpg] https://dl.k6.io/deb stable main" \
  | sudo tee /etc/apt/sources.list.d/k6.list
sudo apt-get update && sudo apt-get install k6

Create your run script

The run*.sh scripts are gitignored, so each user creates their own locally. Create run_http_self_managed_test.sh in the load-tests directory:

#!/bin/bash

set -e

export GATEWAY_ADDR=<your-gateway-address>
export TOKEN=<your-nvapi-key>
export FUNCTION_ID=<your-function-id>

# This local/self-managed example uses `http://` because it does not assume TLS
# termination. Use `https://` if your gateway terminates TLS.
# `/echo` matches the inference path configured for the load_tester_supreme
# example. If your function uses a different inference path, replace `/echo`
# with that path in `HTTP_SUPREME_NVCF_URL` and the curl example below.
export HTTP_SUPREME_NVCF_URL="http://${FUNCTION_ID}.invocation.${GATEWAY_ADDR}/echo"
export SENT_MESSAGE_SIZE=32
export RESPONSE_COUNT=1

k6 run functions/supreme_http_test.js \
  --vus 10 --duration 60s \
  -e TOKEN=${TOKEN} \
  -e HTTP_SUPREME_NVCF_URL=${HTTP_SUPREME_NVCF_URL} \
  -e SENT_MESSAGE_SIZE=${SENT_MESSAGE_SIZE} \
  -e RESPONSE_COUNT=${RESPONSE_COUNT}

Make it executable and run:

chmod +x run_http_self_managed_test.sh
./run_http_self_managed_test.sh

Tune the load

Virtual users (VUs)

Each VU simulates a single concurrent HTTP client, sending requests in a loop and holding the invocation connection open while waiting for a response. The number of VUs directly controls the concurrency hitting your endpoint.

VUs Simulates
1--5 Smoke test -- verify the endpoint works under minimal load
10--50 Light load -- a small team or service calling the function
100--500 Moderate load -- multiple services or a rollout with real traffic
1000+ Stress test -- find the breaking point or max throughput

Fixed VUs for a set duration (simplest approach):

# 10 concurrent users for 1 minute
k6 run functions/supreme_http_test.js --vus 10 --duration 60s ...

# 200 concurrent users for 10 minutes
k6 run functions/supreme_http_test.js --vus 200 --duration 10m ...

Ramping VUs with a config file (recommended for real load tests):

Example k6_rampup_config.json:

{
  "cloud": {
    "projectID": 3695020
  },
  "scenarios": {
    "rampup_scenario": {
      "executor": "ramping-vus",
      "startVUs": 0,
      "gracefulRampDown": "30s",
      "gracefulStop": "30s",
      "stages": [
        { "duration": "1m", "target": 5 },
        { "duration": "2m", "target": 5 },
        { "duration": "1m", "target": 25 },
        { "duration": "2m", "target": 25 },
        { "duration": "1m", "target": 100 },
        { "duration": "2m", "target": 100 },
        { "duration": "1m", "target": 500 },
        { "duration": "2m", "target": 500 },
        { "duration": "1m", "target": 1000 },
        { "duration": "2m", "target": 1000 },
        { "duration": "1m", "target": 0 }
      ]
    }
  }
}
k6 run functions/supreme_http_test.js \
  --config k6_rampup_config.json \
  -e TOKEN=${TOKEN} \
  -e HTTP_SUPREME_NVCF_URL=${HTTP_SUPREME_NVCF_URL} \
  -e SENT_MESSAGE_SIZE=${SENT_MESSAGE_SIZE} \
  -e RESPONSE_COUNT=${RESPONSE_COUNT}

Environment variables reference

Variable Purpose
TOKEN Your nvapi-* bearer token from ./nvcf-cli api-key generate
FUNCTION_ID Function ID for invocation routing
HTTP_SUPREME_NVCF_URL Invocation URL for the function inference path: http://<function-id>.invocation.<gateway-addr>/echo
SENT_MESSAGE_SIZE Size of the test payload in bytes
RESPONSE_COUNT Number of responses the server should return

Verifying your endpoint manually

Then verify the endpoint works with curl:

curl -v -X POST \
  "${HTTP_SUPREME_NVCF_URL}" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Nvcf-Poll-Seconds: 5" \
  -d '{"message": "hello", "repeats": 1}'

You should receive a 200 OK response with the Nvcf-Status: fulfilled header.