UsefulLinks
Computer Science
Microservices
Python Microservices
1. Introduction to Microservices Architecture
2. Python Fundamentals for Microservices
3. Designing Python Microservices
4. Inter-Service Communication
5. Data Management Strategies
6. Containerization with Docker
7. Container Orchestration with Kubernetes
8. CI/CD for Microservices
9. Monitoring and Observability
10. Security in Microservices
11. Advanced Patterns and Practices
5.
Data Management Strategies
5.1.
Database Patterns
5.1.1.
Database per Service
5.1.1.1.
Data Isolation
5.1.1.2.
Schema Independence
5.1.1.3.
Technology Diversity
5.1.2.
Shared Database Anti-Pattern
5.1.2.1.
Coupling Issues
5.1.2.2.
Migration Challenges
5.1.2.3.
Scalability Limitations
5.2.
Data Consistency
5.2.1.
ACID Properties
5.2.1.1.
Atomicity
5.2.1.2.
Consistency
5.2.1.3.
Isolation
5.2.1.4.
Durability
5.2.2.
CAP Theorem
5.2.2.1.
Consistency
5.2.2.2.
Availability
5.2.2.3.
Partition Tolerance
5.2.3.
Eventual Consistency
5.2.3.1.
Consistency Models
5.2.3.2.
Conflict Resolution
5.2.3.3.
Convergence Strategies
5.3.
Distributed Transactions
5.3.1.
Two-Phase Commit
5.3.1.1.
Coordinator Role
5.3.1.2.
Participant Role
5.3.1.3.
Failure Scenarios
5.3.2.
Saga Pattern
5.3.2.1.
Choreography-Based Sagas
5.3.2.2.
Orchestration-Based Sagas
5.3.2.3.
Compensating Actions
5.3.3.
Event Sourcing
5.3.3.1.
Event Store
5.3.3.2.
Event Replay
5.3.3.3.
Snapshots
5.4.
Data Synchronization
5.4.1.
Change Data Capture
5.4.1.1.
Database Triggers
5.4.1.2.
Transaction Log Mining
5.4.1.3.
Event Publishing
5.4.2.
Data Replication
5.4.2.1.
Master-Slave Replication
5.4.2.2.
Master-Master Replication
5.4.2.3.
Conflict Resolution
Previous
4. Inter-Service Communication
Go to top
Next
6. Containerization with Docker