Deployment Guide
This guide covers the step-by-step workflow for deploying AI agents and auditors using the Lucid platform.
Alpha Access Required
Lucid is in private alpha. Request access to get started.
Not sure which deployment mode to use?
See Deployment Modes for a comparison of serverless vs self-hosted options and guidance on choosing the right approach for your use case.
Connect your development tools
After deploying, see the Integration Guide to connect tools like OpenCode and OpenClaw to your agent.
Lucid supports two deployment modes:
| Mode | Command | Best For |
|---|---|---|
| Serverless (Lucid-Managed) | lucid apply --app X --model Y or Observer GUI |
Quick start, instant deployment |
| Self-Hosted | lucid apply -f env.yaml |
Full infrastructure control |
Both modes provide identical TEE security guarantees.
Serverless Deployment (Recommended)
The fastest way to get started. Deploy instantly to Lucid's shared infrastructure with the same TEE security guarantees as self-hosted.
Step 1: Authenticate
Step 2: Browse Available Resources
meta-llama/Llama-3.1-8B Llama 3.1 8B Instruct 128K ✓
meta-llama/Llama-3.1-70B Llama 3.1 70B Instruct 128K ✓
Qwen/Qwen2.5-72B-Instruct Qwen 2.5 72B 128K ✓
microsoft/Phi-3.5-mini Phi 3.5 Mini 128K ✓
lucid catalog auditorsPROFILE AUDITORS RECOMMENDED FOR
coding injection, eval OpenHands, bolt.diy
workflow injection, soc2 Dify, n8n, Langflow
chat injection, toxicity, sovereignty Open WebUI, LobeChat
customer injection, toxicity, pii, soc2 Chatwoot, Botpress
default injection General purpose
Step 3: Deploy Instantly
[+] Environment created: env-abc123def456
Connection URL: https://env-abc123def456.serverless.lucid.ai
App: open-webui
Model: meta-llama/Llama-3.1-8B-Instruct
Auditors: injection, toxicity, sovereignty
Region: us-east-1
[+] Environment ready! No infrastructure provisioning needed.
Step 4: Verify TEE Attestation
[+] Model: https://model-xyz.serverless.lucid.ai (us-east-1) - amd_sev_snp
[+] Auditor: https://auditor-abc.serverless.lucid.ai (us-east-1) - amd_sev_snp
[+] App: https://app-123.serverless.lucid.ai (us-east-1) - amd_sev_snp
[*] 3/3 endpoints have attestation reports
Serverless Options
| Flag | Description |
|---|---|
--app <id> |
App from catalog (e.g., open-webui, dify) |
--model <id> |
Model from catalog (e.g., llama-3.1-8b) |
--profile <name> |
Auditor profile (coding, chat, workflow, customer, default) |
--region <code> |
Data residency (us, eu, apac, any) |
Self-Hosted Deployment
For full control over your infrastructure, use declarative YAML configuration and the lucid apply command.
Step 1: Authenticate
Or use an API key for automation:
Step 2: Create Environment YAML
Create a my-env.yaml file defining your agents:
apiVersion: lucid.io/v1alpha1
kind: LucidEnvironment
metadata:
name: prod-agents
spec:
infrastructure:
provider: gcp
region: us-central1
projectId: my-project
agents:
- name: my-agent
model:
id: meta-llama/Llama-3.3-70B
gpu:
type: H100
memory: 80GB
auditChain:
preRequest:
- auditorId: injection-detector
name: Injection Detector
apps:
- appId: openhands
teeMode: adjacent
Step 3: Preview and Deploy
Infrastructure:
Provider: gcp
Region: us-central1
Agents (1):
- my-agent [enabled]
Model: meta-llama/Llama-3.3-70B
GPU: H100 (80GB)
Auditors: 1
Run 'lucid apply -f <file>' to deploy.
lucid apply -f my-env.yamlCreating agent: my-agent...
Created: agent-abc123
[+] Environment deployed successfully!
Step 4: Monitor and Manage
Agents (1):
NAME STATUS MODEL GPU
my-agent running meta-llama/Llama-3.3-70B H100
lucid logs my-agent[2024-01-15 10:30:00] Agent started
[2024-01-15 10:30:01] Auditors initialized
lucid stop my-agentAgent 'my-agent' stopped.
lucid start my-agentAgent 'my-agent' started.
Step 5: View AI Passports
pass-001 agent-abc123 2024-01-15T10:30:00Z
pass-002 agent-abc123 2024-01-15T10:31:00Z
lucid passport show pass-001Passport ID: pass-001
Hardware Attested: true
TEE Type: AMD SEV-SNP
Auditors: injection, toxicity
Step 6: Configure Passport Display
Choose how end users see the AI Passport. Add to your environment YAML:
spec:
passport:
display:
mode: banner # banner, floating, page_only, browser_extension
position: top # top, bottom (for banner mode)
theme: auto # light, dark, auto
validityDays: 30
minSlsaLevel: 2
| Mode | Description |
|---|---|
banner |
Persistent bar at top/bottom of the page |
floating |
Small badge in corner, expands on click |
page_only |
No in-app UI, users visit /.lucid/passport |
browser_extension |
Users install Lucid Passport Verifier extension |
See AI Passports for full configuration options.
Local Development
For local development, create a local Kind cluster:
✓ Ensuring node image
✓ Preparing nodes
✓ Writing configuration
✓ Starting control-plane
✓ Installing CNI
✓ Installing StorageClass
Set kubectl context to "kind-lucid-dev"
Then deploy a test environment. Create a file called dev-env.yaml:
apiVersion: lucid.io/v1alpha1
kind: LucidEnvironment
metadata:
name: local-test
spec:
infrastructure:
provider: local
agents:
- name: mini-chat
model:
id: mock
gpu:
type: CPU
Apply the configuration:
lucid statusContext: dev
Cluster: lucid-local-k8s
Status: Running
Services:
[OK] verifier-service (1/1)
[OK] observer-ui (1/1)
Agents (1):
NAME STATUS MODEL GPU
mini-chat running mock CPU
Teardown
Deleting cluster 'lucid-local-k8s'...
Cluster deleted.
CLI context reset to production.
Building & Publishing Auditors
Before deploying custom auditors, you must build, verify, and publish them to the Lucid registry.
Build & Verify Auditors
Ensure your Auditor container is compliant with the Lucid Standard.
[+] Compliance probe successful!
[*] Verification complete. Auditor is compliant.
Publish to Registry
To deploy auditors in production, every image must be notarized. This registers the container's cryptographic digest with the Lucid Verifier.
Registering digest with Verifier...
[+] Auditor published and notarized.
Define the Safety Policy
Define your safety guardrails in the auditChain section of your environment YAML:
agents:
- name: my-agent
auditChain:
preRequest:
- auditorId: lucid-guardrails-auditor
name: Injection Detection
env:
INJECTION_THRESHOLD: "0.8"
INJECTION_BLOCK_ON_DETECTION: "true"
response:
- auditorId: lucid-guardrails-auditor
name: Toxicity Filter
See the Policy as Code guide for full schema details.
Using Official Auditor Images
Lucid provides official auditor images to alpha participants:
docker pull us-central1-docker.pkg.dev/lucid-public/lucid-auditors/lucid-guardrails-auditor:latest
Available auditors:
| Auditor | Port | Description |
|---|---|---|
lucid-guardrails-auditor |
8090 | Prompt injection and jailbreak detection |
lucid-guardrails-auditor |
8093 | Multi-label toxicity detection |
lucid-eval-auditor |
8091 | Safety benchmark evaluation |
lucid-pii-compliance-auditor |
8094 | PII detection and compliance |
lucid-sovereignty-auditor |
8095 | Data residency enforcement |
lucid-observability-auditor |
8092 | Telemetry and tracing |
Command Reference
| Command | Description |
|---|---|
lucid apply -f env.yaml |
Deploy environment from YAML |
lucid diff -f env.yaml |
Preview changes before applying |
lucid status |
List all agents |
lucid status <agent-name> |
Show specific agent status |
lucid logs <agent-name> |
View agent logs |
lucid logs <agent-name> -f |
Stream agent logs |
lucid start <agent-name> |
Start a stopped agent |
lucid stop <agent-name> |
Stop a running agent |
lucid teardown |
Delete local Kind cluster |
lucid export <name> -o env.yaml |
Export cluster state to YAML |
What Happens Under the Hood
When you deploy an agent, the Lucid platform:
- Provisions TEE Environment: Creates a secure execution environment with hardware-based isolation
- Injects Sidecars: Adds all auditors defined in your chain to the workload
- Configures Networking: Routes traffic through the auditor sequence
- Enforces Attestation: Ensures all components are cryptographically verified
Cloud Provider Requirements
To use real Hardware Root of Trust, your workloads run on TEE-capable infrastructure managed by Lucid:
| Provider | Hardware |
|---|---|
| GCP | N2DL nodes (AMD SEV-SNP) with Confidential Computing |
| Azure | DCsv3 or ECsv3 nodes (Intel SGX) |
| AWS | Nitro-based instances with Enclaves |
Select your preferred region and hardware in your environment YAML:
spec:
infrastructure:
provider: gcp
region: us-central1
agents:
- name: my-agent
gpu:
type: H100
memory: 80GB