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Duration 21 hours
Course Outline
Introduction to PostgresAI
- Exploring the architecture and key components of PostgresAI
- Core principles: cloning mechanisms, snapshot management, and sandbox environments
- Enterprise adoption strategies and potential Return on Investment (ROI)
PostgresAI Installation and Configuration
- Deploying PostgresAI across Docker and Kubernetes ecosystems
- Establishing integrations with PostgreSQL instances and external storage backends
- Setting up secure authentication and access management protocols
Database Cloning and Experimentation
- Generating instant database clones via thin provisioning techniques
- Safely testing schema modifications within ephemeral environments
- Streamlining CI/CD processes using PostgresAI clones
Monitoring and Observability
- Utilizing PostgresAI dashboards for deep performance insights
- Tracking clone health and analyzing query execution metrics
- Connecting with Grafana, Prometheus, and ELK stack for enhanced observability
AI-Driven Query Optimization
- Applying AI-based recommendations to enhance query efficiency
- Deep-dive analysis of query plans and execution patterns
- Implementing continuous optimization through intelligent feedback loops
Data Governance and Security
- Implementing effective data masking and anonymization strategies
- Ensuring regulatory compliance within cloned environments
- Maintaining audit logs and enforcing role-based access controls
Integrating PostgresAI with Enterprise Workflows
- CI/CD integration via Jenkins, GitLab CI, or GitHub Actions
- Building automated testing pipelines for SQL and schema modifications
- Best practices for team collaboration and environment sharing
Scaling PostgresAI Operations
- Managing large-scale datasets and multi-node cluster configurations
- Enhancing clone provisioning performance and efficiency
- Strategic capacity planning and cost management
Summary and Next Steps
Requirements
- Solid understanding of PostgreSQL database administration principles
- Proficiency in managing Linux server environments
- Experience with containerized or virtualized deployment workflows
Target Audience
- Database Administrators
- DevOps and SRE Engineers
- Data Infrastructure Architects
Testimonials (4)
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Cont - Everymatrix
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Course - PostgreSQL AI for Developers
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