Deployment Model

Deployment model definition

A deployment model defines the structure and management of cloud services. It describes how resources are deployed, who manages them, and the relationship between users and the infrastructure.

Key elements

  • Resource Deployment: This explains where and how your cloud resources are located. Are they on-premises, in a public cloud, or a mix?

  • Management Responsibility: Defines whether your team or a third-party manages the infrastructure. This can affect your control and flexibility.

  • User Interaction: Outlines how users will interact with the infrastructure, including access levels and permissions.

Examples of deployment models in use

  • Public Cloud: A startup leverages AWS for its scalability and cost-efficiency. It handles variable traffic loads seamlessly. AWS offers flexibility without significant upfront investment.

  • Private Cloud: A financial institution ensures data security through a private cloud. This model meets regulatory standards effectively. It provides greater control over sensitive information. Learn more about connecting Statsig to your existing tools

  • Hybrid Cloud: A healthcare provider uses a hybrid cloud for patient data. Sensitive data stays on-premises, while less sensitive workloads utilize public cloud resources. This setup balances security and scalability. Understand the different Statsig products

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OpenAI OpenAI
Brex Brex
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Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
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President
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Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
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SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
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Partha Sarathi
Director of Engineering
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