Decision Guide for Private Deployment
For business users considering localized deployments, focus on evaluating the following dimensions:
- hardware requirement: Each concurrent instance is recommended to be configured with 8-core CPU/32GB RAM/NVIDIA T4 graphics card, and the model data requires approximately 500GB of storage space.
- network environment: Gigabit bandwidth should be guaranteed for intranet, and SSL certificate and firewall rules should be configured for extranet access.
- data isolation:: Choice of fully offline mode (regular synchronization of model updates) or hybrid mode (sensitive code handled locally, generic requests go to the cloud)
- Rights ManagementSupports LDAP/Active Directory integration for fine-grained control of code access rights and AI usage rights.
- compliance requirementDeployment solution has passed SOC2 Type II certification and supports the generation of audit logs to meet the compliance requirements of the financial industry.
The implementation process usually includes: contacting the sales team for a deployment package → local environment calibration → model initialization (about 6-8 hours) → stress testing → staff training. It is recommended to try the cloud service first before evaluating the need for privatization.
This answer comes from the articleAI Code Editor: Code Generation and Optimization Tool for Unofficial Claude Code SuitesThe
May not be reproduced without permission:AI productivity tools " What are the key factors that enterprises need to consider when choosing a private deployment?
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