Our team builds Kyva, a private AI workspace that deploys entirely within our customers' AWS environments (for data sovereignty reasons).
We've encountered several interesting technical challenges with this approach:
1. Deployment automation that works with customer IAM policies
2. Monitoring and troubleshooting without direct access
3. Updates and versioning across different customer environments
4. Handling variations in customer AWS configurations
5. Security best practices when you're essentially a "guest" in their cloud
For others who deploy software in customer cloud environments rather than SaaS: What tools, patterns or approaches have you found most effective? Any lessons learned the hard way?
Our team builds Kyva, a private AI workspace that deploys entirely within our customers' AWS environments (for data sovereignty reasons).
We've encountered several interesting technical challenges with this approach:
1. Deployment automation that works with customer IAM policies 2. Monitoring and troubleshooting without direct access 3. Updates and versioning across different customer environments 4. Handling variations in customer AWS configurations 5. Security best practices when you're essentially a "guest" in their cloud
For others who deploy software in customer cloud environments rather than SaaS: What tools, patterns or approaches have you found most effective? Any lessons learned the hard way?