Description

Introduction

Oracle GoldenGate 23ai Microservices is a modern and cloud-ready data replication platform. It enables real-time data integration across systems. Moreover, it supports high performance. In addition, it ensures scalability. The microservices architecture simplifies deployment and management. Furthermore, it provides REST APIs. It also offers a web-based UI. Therefore, users can manage services easily. As a result, it suits real-time analytics and cloud migration. Additionally, it supports zero-downtime data integration.

Learner Prerequisites

• Basic understanding of databases such as Oracle or other RDBMS
• Familiarity with SQL and core database concepts
• Knowledge of Linux or Unix commands
• Understanding of basic networking concepts
• Additionally, exposure to ETL or data integration concepts is helpful

Table of Contents

1. Introduction to GoldenGate 23ai Microservices

1.1 Overview of Oracle GoldenGate and 23ai features
1.2 Microservices vs classic architecture
1.3 Key components and architecture overview
1.4 Common use cases and industry applications
1.5 Benefits of microservices deployment

2. GoldenGate 23ai Architecture Deep Dive

2.1 Core microservices architecture components
2.2 Distribution and receiver services explained
2.3 Administration Server and Service Manager roles
2.4 Extract and Replicat processes overview
2.5 Deployment topologies and design considerations

3. Environment Setup and Prerequisites

3.1 System requirements and supported platforms
3.2 Database configuration for GoldenGate
3.3 Network and port configuration basics
3.4 User privileges and security setup
3.5 Pre-installation checklist

4. Installation of GoldenGate 23ai Microservices

4.1 Downloading and staging the software
4.2 Installation methods such as GUI and silent mode
4.3 Directory structure and file layout
4.4 Initial configuration steps
4.5 Installation verification process

5. Deployment Configuration

5.1 Creating a microservices deployment
5.2 Configuring the Service Manager
5.3 Setting up the Administration Server
5.4 Deployment parameters and best practices
5.5 Managing multiple deployments

6. Configuring Extract Processes

6.1 Types of Extract including classic and integrated
6.2 Creating and registering Extract processes
6.3 Log-based capture configuration
6.4 Parameter files and key settings
6.5 Monitoring Extract performance

7. Configuring Replicat Processes

7.1 Types of Replicat such as integrated and parallel
7.2 Creating Replicat processes
7.3 Mapping and transformation rules
7.4 Error handling and conflict resolution
7.5 Performance tuning basics

8. Trail Files and Data Flow Management

8.1 Understanding trail files
8.2 Local and remote trails
8.3 Data pump configuration
8.4 Managing trail file storage
8.5 Data flow lifecycle

9. Security and Authentication

9.1 User authentication and role management
9.2 SSL and TLS configuration
9.3 Credential store setup
9.4 Data encryption in transit
9.5 Security best practices

10. Monitoring and Management

10.1 Web-based UI overview
10.2 Managing services using REST APIs
10.3 Process monitoring and alerts
10.4 Log files and diagnostics
10.5 Troubleshooting common issues

11. Performance Tuning and Optimization

11.1 Identifying system bottlenecks
11.2 Tuning Extract and Replicat processes
11.3 Improving parallelism and throughput
11.4 Memory and resource management
11.5 Performance testing and benchmarking

12. High Availability and Disaster Recovery

12.1 High availability architecture overview
12.2 Failover and switchover strategies
12.3 Active-active and active-passive setups
12.4 Backup and recovery processes
12.5 Disaster recovery planning

13. Cloud and Container Deployment

13.1 Deployment on cloud platforms like OCI, AWS, and Azure
13.2 Containerization using Docker
13.3 Kubernetes deployment basics
13.4 CI/CD pipeline integration
13.5 Cloud security considerations

14. Real-Time Use Cases and Hands-on Labs

14.1 Setting up real-time data replication
14.2 Zero-downtime migration scenario
14.3 Streaming data to analytics platforms
14.4 Bidirectional replication use case
14.5 Troubleshooting lab exercises

Conclusion

Overall, this training covers GoldenGate 23ai Microservices deployment. Moreover, it explains management clearly. In addition, it builds practical knowledge. Therefore, learners can design scalable solutions. As a result, they can implement secure systems. Furthermore, they can manage real-time data integration effectively.