The Unified Cloud Platform for Research and Enterprise Innovation
Accelerate research, modernize applications, and deploy secure workloads on industry-leading cloud platforms like AWS, GCP, and UCLA's private cloud. Built for mission-critical enterprise systems, AI/ML, and large-scale data analytics.
$525K
Saved for UCLA in 2025
8x
Growth in Researcher Use
Secure by default | Built for scale | Designed for UCLA
Benefits
For Researchers
Enabled Cloud Platforms: AWS & GCP
GPU-enabled AI/ML experimentation
Large-scale data processing
Scientific computing and simulation
Cloud-native analytics workflows
For IT & APP Teams
Primary Enterprise Platform: AWS
Enterprise-grade AWS environments
Modernization & migration readiness
Secure-by-default landing zones
Standardized identity deployments
Training Resources
A complete training ecosystem for cloud, AI/ML, analytics, and application modernization.
Self-Guided Courses
- Google Cloud Skills Boost
- AWS SkillBuilder
- UCLA Workshop Recordings
Live Workshops (2026)
- Spring: GCP Researcher Enablement
- Summer: AWS Deep Dives for IT Teams
- Fall: AWS Researcher Enablement
Core Capabilities
Secure, governed cloud environments out of the box.
Security
Built-in guardrails, identity controls, and policy frameworks.
Governance
Consistent, lifecycle managed cloud environments.
Optimization
Spend dashboards, discounting, and cost reviews.
Monitoring
Unified logging, metrics, and compliance visibility.
Financial Efficiency
- Enterprise cloud discounts
- Built-in support paths
- Spend analytics and recharge modeling
- Forecasting for grants and budgets
Technical Readiness
- AWS and GCP landing zones
- Automated compliance
- Backup and recovery patterns
- DevOps and CI/CD integration
Workload Placement Options
Determine the right path for your data and workload.
Workload Type Support
| Workload Type | AWS | GCP | Secure Enclaves (Roadmap) |
|---|---|---|---|
| Enterprise Solutions | ✔ | — | — |
| Research Workloads | ✔ | ✔ | — |
| Highly Regulated Research | — | — | ✔ |
Data Classification
| Data Type | AWS | GCP | Secure Enclaves (Roadmap) |
|---|---|---|---|
| Public / Non-Sensitive (P1) | ✔ | ✔ | — |
| UCLA Internal / Moderate (P2) | ✔ | ✔ | — |
| Restricted (P3 - P4) | ✔ | ✔ | — |
| Highly Regulated (CMMC) | — | — | ✔ |
Platform availability reflects UCLA's current operational patterns, compliance posture, and support models; not inherent hyperscaler limitations.
Data classification: P4 data must be handled in consultation with Information Security and implemented in accordance with UCLA security, privacy, and compliance requirements, including appropriate technical controls such as multi-factor authentication, encryption, logging, network restrictions, and data backup and recovery.
Shared responsibility model: BruinCloud operates under a shared responsibility model. Users are responsible for securely configuring their environments in accordance with UCLA policies and applicable regulatory requirements.
Roadmap: 2026 - 2027
- Secure Research Enclaves
- Enhanced Provisioning Automation
- Expanded Cost Management
- Azure Onboarding
*Roadmap items subject to change
