Developing the Enterprise Knowledge Graph Capabilities to Win
Production Deployment and Scaling Strategies
Workshop
Run your knowledge graph in production—fast, secure, and maintainable
Knowledge graphs only become enterprise assets when they perform reliably at scale, stay secure, and evolve under clear governance. This workshop helps teams optimize graph performance, plan scalable.
Leave with a production blueprint—scaling approach, performance priorities, ops plan, and governance model.
The Challenge
Many knowledge graphs reach a proof of concept—but stall when performance, operations, and governance requirements rise in production.
- Performance degrades at scale: Queries slow down as the graph grows, and tuning practices aren’t standardized.
- Scaling strategy is unclear: Teams struggle to design deployment patterns that support high availability and enterprise workloads.
- Operations and governance are underbuilt: Monitoring, maintenance, security, and change control are inconsistent across teams.
Without production discipline, knowledge graphs become fragile—limiting adoption and increasing operational risk.
Our Solution
We guide your team through a practical approach to deploy and scale enterprise knowledge graphs with strong operational and governance foundations.
- Performance Optimization at Scale: Define the tuning practices and priorities required to keep queries fast and predictable.
- Horizontal Scaling and Deployment Patterns: Establish scalable deployment approaches that support availability, resilience, and growth.
- Monitoring and Maintenance Procedures: Define operational practices for monitoring health, managing upgrades, and maintaining performance over time.
- Security for Graph Data and Infrastructure: Identify security and access control requirements to protect sensitive data and system integrity.
- Governance for Graph Evolution: Establish ownership, change management, and standards to govern schema and data evolution responsibly.
Area of Focus
- Optimizing Graph Database Performance at Scale
- Scaling Neo4j Deployments Horizontally
- Implementing Monitoring and Maintenance Procedures
- Securing Knowledge Graph Data and Infrastructure
- Governing the Graph as It Evolves Over Time
Participants Will
- Identify performance bottlenecks and define optimization priorities for scale.
- Define a scaling strategy and deployment patterns that support enterprise availability and growth.
- Establish monitoring and maintenance procedures to keep the graph reliable in production.
- Align on security requirements for data access, infrastructure protection, and operational controls.
- Leave with a governance model to manage graph evolution, upgrades, and ongoing change.
Who Should Attend:
Solution Essentials
Format
Facilitated working session
Duration
4 hours
Skill Level
Intermediate to Advanced
Tools
Slides, workshop templates, key worksheets, checklists, and collaboration tools.