Data Protection Gateway (DPG) protects RESTful web services and microservices without the need for Developers to change code.
No Dev Involvement
- Transparent data protection for JSON payloads
- < 1 minute to close vulnerability gaps for sensitive data
- Keep on top of the latest security without creating major projects
Increase Dev Capacity
- Reduce the drag on the Dev team
- Pass responsibility for data protection to the security team via simplified APIs
Separate Duties
- Devs call data protection
- Data Security admins control the what, the how, and the who via centrally managed policies
Centralized Management
Benefits for each role
With DPG, you can have GOOD + FAST + CHEAP, right now.
- More revenue, due to increased Dev capacity
- More security, due to < 1 minute to close vulnerability gaps
- More innovation, due to not increasing the backlog
Close vulnerability gaps in < minute, Roadmap is respected (because there are no data protection fire drills taking Devs off revenue-generating projects).
Devs can remain focused on revenue-generating projects because they are not involved in updating data protection.
No downtime or fire drills required to update data protection.
Ultra secure (staying on top of your security posture by closing vulnerability gaps in < minute), Roadmap is respected (because there are no data protection fire drills taking Devs off revenue-generating projects).
Visibility into current security posture (single pane of glass, centralized-management, policy-based), No code change to make updates (removes dependency on DevOps for updates).
Reputation is protected, audits are passed, in compliance, does not add to technical debt.
CipherTrust Data Protection Gateway
Operating transparently to all entities on the network, DPG interprets RESTful data and performs protection operations based on profiles defined centrally in CipherTrust Manager. DPG is deployed as a container and is fully compatible with Kubernetes orchestration systems. DPG can also be deployed as a standalone container for development and testing use cases as well as legacy production deployments.