Vertexa Documentation

A complete guide to getting started with our high-performance computing platform

Introduction

Vertexa is a high-performance computing (HPC) platform that makes cutting-edge compute infrastructure accessible to everyone. With just a few commands you can run CFD simulations, genomic analyses, image processing pipelines and much more.

Simple

Deploy in minutes, not weeks

Scalable

From 1 vCPU to entire clusters

Affordable

Fair, transparent VCU-based pricing

Quick Start

Get up and running with Vertexa in under 5 minutes.

Install the CLI

curl -fsSL https://cli.vertexa.cloud/install.sh | bash

Or via npm: npm install -g @vertexa/cli

Authenticate

vertexa login

You will be redirected to your browser to complete authentication.

Run your first job

vertexa run \
  --env cfd \
  --input simulation.case \
  --output results/

CLI - Command Line Interface

The Vertexa CLI is the fastest way to interact with the platform.

Core Commands

vertexa run

Run a compute job

vertexa status [job-id]

Check the status of a job

vertexa logs [job-id]

Stream logs in real time

vertexa list

List all of your jobs

vertexa cancel [job-id]

Cancel a running job

Advanced Options

vertexa run \
  --env cfd \
  --cpu 64 \
  --memory 256GB \
  --gpu a100 \
  --gpu-count 4 \
  --timeout 24h \
  --input ./data \
  --output ./results \
  --name "CFD Simulation Wing Design"

REST API

Integrate Vertexa directly into your applications using our REST API.

Base URL: https://api.vertexa.cloud/v1

Authentication: Bearer token in the Authorization header

POST /jobs - Create Job

curl -X POST https://api.vertexa.cloud/v1/jobs \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "environment": "cfd",
    "resources": {
      "cpu": 64,
      "memory": "256GB",
      "gpu": "a100",
      "gpuCount": 2
    },
    "input": "s3://bucket/input",
    "output": "s3://bucket/output",
    "timeout": "24h"
  }'

GET /jobs/:id - Job Status

curl https://api.vertexa.cloud/v1/jobs/job_abc123 \
  -H "Authorization: Bearer YOUR_TOKEN"

Response:

{
  "id": "job_abc123",
  "status": "running",
  "progress": 45,
  "vcus_consumed": 1250,
  "created_at": "2025-01-16T10:30:00Z",
  "started_at": "2025-01-16T10:31:00Z"
}

DELETE /jobs/:id - Cancel Job

curl -X DELETE https://api.vertexa.cloud/v1/jobs/job_abc123 \
  -H "Authorization: Bearer YOUR_TOKEN"

Preconfigured Environments

Vertexa ships with environments optimized for different workloads.

CFD (OpenFOAM)

Computational fluid dynamics simulations

--env cfd

Genomics

Genomic analysis and bioinformatics

--env genomics

Satellite

Satellite imagery processing

--env satellite

Machine Learning

GPU-accelerated model training

--env ml

Practical Examples

CFD Simulation of an Aircraft Wing

# Prepare files
mkdir -p input output

# Run the simulation
vertexa run \
  --env cfd \
  --cpu 128 \
  --memory 512GB \
  --input ./input/wing.mesh \
  --output ./output \
  --timeout 12h \
  --name "Wing Analysis v2.1"

# Monitor progress
vertexa logs -f [job-id]

GPU-Accelerated DNA Analysis

vertexa run \
  --env genomics \
  --cpu 64 \
  --memory 256GB \
  --gpu a100 \
  --gpu-count 4 \
  --input ./sequences \
  --output ./results \
  --name "Genome Assembly"

Satellite Imagery Processing

vertexa run \
  --env satellite \
  --cpu 32 \
  --memory 128GB \
  --input s3://my-bucket/sentinel2/ \
  --output s3://my-bucket/processed/ \
  --name "NDVI Analysis 2025"

Security and Best Practices

API Keys

• Never share your API keys
• Rotate keys regularly
• Use environment variables
• Revoke unused keys

Sensitive Data

• Encrypt data at rest
• Use TLS/SSL connections
• Implement access control
• Audit logs regularly

Costs

• Set up VCU alerts
• Always set job timeouts
• Monitor daily consumption
• Right-size allocated resources

Performance

• Pick the right environment
• Allocate adequate resources
• Use caching where possible
• Parallelize your workloads

Need help? Get in touch: support@vertexa.cloud

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