Deployment Overview
Welcome to the evoML deployment documentation. evoML supports two main deployment options:
- Kubernetes-based deployment
- Docker-based deployment
Choose the deployment option that best suits your infrastructure needs.
Both deployment methods support:
- Standard installation with internet access
- Air-gapped installation for secure environments
Pre-deployment questions
In order for us to provide you with the best deployment experience, please send us your answers to the following pre-deployment questions. You can send your answers to your dedicated TurinTech contact point, or write to us at support@turintech.ai.
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How many users will be using the platform?
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How many trials will be running concurrently?
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Where will the evoML instance be deployed?
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What level of permissions can be provided?
- Kubernetes cluster access only
- IAM User
- SSH, if bare-metal deployment
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Will evoML/Artemis be deployed in your domain?
- If yes, where is the domain located (e.g. Route 53)?
- Does it need to be restricted to specific IPs or an internal network?
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What kind of data will be used and from which source?
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What is the estimated monthly cost on the cloud of choice for the default proposed deployment?
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Will you be restarting the Kubernetes cluster or the machines used to deploy evoML? If yes, how often will this happen?