When a production engineering team requests approval for a cloud-based simulation platform, the IT evaluation typically focuses on the same set of concerns: authentication and access control, data residency and isolation, integration with existing systems, compliance with internal security policies, and the operational overhead of supporting another platform. These are the right questions. The challenge is that most cloud engineering vendors answer them with marketing language rather than technical specifics.
This article provides a structured evaluation framework - the specific technical questions that determine whether a cloud engineering platform meets enterprise IT requirements in an oil and gas operating environment.
Authentication and identity management
The baseline requirement is SAML 2.0 or OIDC integration with your identity provider - Azure AD, Okta, OneLogin, or whatever your organization standardizes on. This is non-negotiable for enterprise deployment. Any platform that requires separate credentials or cannot federate authentication with your existing IdP creates a security gap and an administrative burden.
Beyond basic SSO, evaluate whether the platform supports SCIM provisioning for automated user lifecycle management. When an engineer is onboarded or offboarded in your HR system, does the change propagate automatically to the engineering platform? Manual user management in a separate admin console is workable for 10 users. For 50 or 100 users across multiple business units, SCIM provisioning is a practical requirement.
Evaluate the role-based access control model. Does the platform support custom roles with granular permissions, or only predefined admin/user tiers? Can permissions be scoped to organizational units (divisions, regions, groups)? Can a division manager see their division's wells without seeing another division's data? For operators with multiple business units, data scoping aligned with organizational hierarchy is essential.
Enforced SSO - the ability to require that all authentication flows through the IdP with no local password fallback - is a requirement for organizations with strict identity governance policies. Not all cloud platforms support this.
Data architecture and isolation
Understand the multi-tenancy model. Is your organization's data in a shared database with logical isolation, or in a dedicated database instance? Both approaches can meet security requirements, but they have different risk profiles and different implications for data residency, backup, and disaster recovery.
Data encryption should be in place at rest and in transit. At rest, evaluate whether the platform uses disk-level encryption (standard for cloud infrastructure) or application-level encryption with customer-managed keys (higher assurance but more complex). In transit, TLS 1.2 or higher is the minimum standard.
Data residency is a consideration for operators with regulatory requirements or internal policies about where engineering data can be stored geographically. Confirm the platform's hosting regions and whether you can specify the region for your data. For operators with Middle East, European, or Asia-Pacific operations, this can be a compliance-driven requirement.
Evaluate the data export capabilities. If you decide to leave the platform, can you export all your well data, simulation results, and design history in a standard format? Vendor lock-in is a legitimate concern for IT teams, and the answer should be documented before procurement, not discovered after.
API architecture and integration
For engineering platforms that need to connect to existing data infrastructure - SCADA systems, production historians, data lakes, ERP systems - evaluate the API surface. Is there a documented REST API with versioning? Are there webhooks or event streams for real-time data flow? Can the platform push simulation results to Snowflake, Databricks, or your internal data warehouse?
API authentication should follow OAuth 2.0 patterns with scoped API keys or service account credentials. Evaluate rate limiting, pagination, and error handling in the API documentation. A well-documented API with SDKs or client libraries indicates a platform that takes integration seriously. A single undocumented endpoint suggests integration is an afterthought.
For organizations that use WellView, OFM, or other production data management systems, confirm whether the engineering platform can read from and write to these systems. Direct integration is preferable to manual export-import cycles that introduce delay and error.
Audit and compliance
Audit trails should capture who accessed what data, who modified which design parameters, and when. For engineering platforms, the audit trail is not just a security requirement - it is an engineering requirement. When a rod failure occurs and the investigation traces back to a design decision, the ability to reconstruct the decision history from the audit log is operationally valuable.
Evaluate the retention period for audit logs and whether they are exportable. SOX compliance, ISO 27001 certification, and internal audit requirements may dictate minimum retention periods. Confirm that the platform's retention policy meets your requirements or can be configured to do so.
Version history on engineering artifacts - simulation configurations, rod string designs, well parameters - serves a dual purpose. It is both a security control (who changed what) and an engineering tool (what was the design before the last modification). Platforms that treat versioning as an engineering feature rather than just a compliance checkbox provide more value to the end users.
Operational considerations
Cloud platforms eliminate desktop software management - no installations, no patches, no version coordination across workstations. This is a genuine reduction in IT operational overhead. Evaluate this against the overhead of managing another SaaS vendor relationship: license administration, SSO configuration, API key management, user provisioning, and support escalation paths.
Uptime SLAs should be documented. For engineering software that is not on the critical path of production operations (unlike SCADA or safety systems), 99.5% uptime is typically adequate. Higher SLAs (99.9%) may be available at enterprise pricing tiers and are appropriate for organizations where simulation downtime directly delays operational decisions.
Evaluate the vendor's incident response and communication practices. When the platform has an outage or a security incident, how are customers notified? Is there a status page? What are the escalation paths for critical issues?
The evaluation process
A practical evaluation sequence: begin with the security and compliance review (authentication, data isolation, audit trails), then assess the integration architecture (API documentation, existing system connectivity), then validate the operational model (SLA, support, update process). The engineering capabilities - simulation accuracy, feature set, workflow efficiency - should be evaluated by the production engineering team in parallel.
Request a technical architecture document rather than a marketing security overview. The architecture document should describe the hosting infrastructure, the data flow between components, the authentication integration points, and the encryption implementation. If the vendor cannot provide this level of detail, that itself is informative.
PetroBench's platform supports SAML/OIDC SSO, SCIM provisioning, role-based access control with organizational scoping, encrypted data at rest and in transit, audit logging, and a documented REST API. Technical architecture documentation is available on request through petrobench.com/contact.
