Isolated Crew Runtimes
Run memory-intensive agent crews with dedicated vCPU and RAM allocation.
- Dedicated container compute
Deploy projects built with CrewAI in 60 seconds.
Run multi-agent crews in persistent, isolated container runtimes with Redis task queues, long-running background workers, and automated restarts.
01 / The Workflow
Zero operational glue between prompt and production.
Multi-agent orchestration requires reliable background compute.
Production Control Plane
Built specifically for fast-iterating code.
CrewAI squads delegate tasks across multiple autonomous agents. Running crews in production demands reliable background compute, memory isolation, and automated worker scheduling.
- Persistent background worker containers running 24/7
- Redis queue support for asynchronous task dispatching
- Automatic container health monitoring and crash recovery
Continuous Delivery
Git Push · Automated Containerization · TLS 1.3
1Define your CrewAI agents, tasks, and tools
2Push your repository to GitHub or GitLab
3Deployxa builds a hardened Python runtime image
4Attach Redis or Postgres for queues and memory
02 / Capabilities
Everything you need to ship CrewAI to production.
From automatic framework detection to attached managed databases, Deployxa provides a complete cloud runtime.
Redis Task Queues
Attach managed Redis instances to queue jobs, buffer payloads, and coordinate agent tasks.
- Asynchronous crew execution
Persistent Knowledge Stores
Persist crew output, task artifacts, and knowledge base embeddings across runs.
- Attached PostgreSQL & MySQL
Encrypted LLM Key Vault
Manage API tokens for LLM providers safely without committing secrets to source control.
- Secure credential storage
Live Task Logging
Inspect live agent interactions and tool invocations through the real-time logging dashboard.
- Stream stdout & agent thoughts
Zero-Downtime Updates
Roll out new agent prompts and tool definitions with automatic health validation and instant rollbacks.
- Deploy crew updates safely
03 / Platform Comparison
Why Deployxa is the ideal production cloud.
Compare Deployxa with temporary browser sandboxes and unmanaged manual virtual servers.
| Capability | Deployxa Cloud | Local Sandboxes | Raw VPS / Server |
|---|---|---|---|
| Continuous Git Deployment | Auto-deploy on push | Manual export | Manual git pull & restart |
| Container Isolation & Limits | Hardened Docker sandboxes | Shared browser memory | Manual systemd / Docker |
| Attached Databases | 1-click Postgres & MySQL | Ephemeral storage | Manual setup & patching |
| Automatic HTTPS & Domains | Let’s Encrypt TLS 1.3 | Sandbox subdomains only | Manual Certbot configuration |
| Instant Rollbacks | Sub-second traffic flip | Re-prompt or re-export | Manual git checkout & rebuild |
| MCP Control Plane Integration | Native Streamable HTTP MCP | None | None |
04 / Frequently Asked Questions
Deploying CrewAI on Deployxa.
Can CrewAI run as a background worker on Deployxa?
Yes. Deployxa supports both web-facing HTTP services and headless background worker containers.
How do I pass LLM API keys to my CrewAI agents?
Add OPENAI_API_KEY, ANTHROPIC_API_KEY, or other provider keys in the Deployxa project Environment Variables panel.
What happens if an agent hits an unhandled error?
Deployxa monitors container liveness and restarts failed instances automatically while preserving log records.
Ready when you are
Ready to take your CrewAI application live?
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