What are the benefits and challenges of horizontal scaling in microservices?

Choosing type of scaling is a strategic decision that should align with project, requirements, and long-term goals. Vertical Scaling: Pros: 1. Increased Performance: Enhances system performance efficiently. 2. Simplicity in Management: Managing a single server is simpler. Cons: 1. Limited Scalability: Vertical scaling has an upper limit. 2. Downtime Risk: Involves downtime during upgrades. Horizontal Scaling: Pros: 1. Infinite Scalability: Allows adding more machines for virtually unlimited scalability. 2. Enhanced Redundancy: Distributing load across servers enhances redundancy. Cons: 1. Complex Management: Coordinating multiple servers can be complex. 2. Higher Initial Cost: This may incur higher initial costs due to multiple servers.

Infinite Scalability: Horizontal scaling ensures seamless expansion. In cloud video streaming, as demand surges (e.g., during live sports events), additional servers deploy across regions, ensuring uninterrupted service. While horizontal scaling adapts dynamically to varying workloads, achieving certain quality levels may be challenging compared to vertical scaling. This makes it crucial to carefully evaluate scalability options for services with unpredictable usage patterns.

1. Data Consistency - Ensuring uniform data across nodes. Solution: Implement distributed databases or synchronization mechanisms like the saga pattern for data integrity. 2. Complexity in Implementation - Deploying and managing a distributed system with complex configurations. Solution: Utilize orchestration tools and automation for seamless scaling and deployment. 3. Fault Tolerance - Handling failures and ensuring system availability. Solution: Implement redundancy, failover mechanisms, and robust monitoring for quick issue identification. 4. Testing and Debugging - Identifying and fixing issues in a distributed setup. Solution: Implement thorough testing, utilize logging and monitoring tools, and conduct regular debugging drills.

Unique ID Generator in RDBMS. You cannot use a basic incremental ID generator in the database because two databases could end up with the same ID. For example, you can create a 64-bit number using three parts: timestamp, shard key, and incremental ID. The shard key part could represent a country ID - '01' for id 1, '11' for id 3, etc. The incremental ID part could utilize the auto-increment feature in PostgreSQL, which ensures no conflicts occur because we divide the ID according to the shard key. You would have to divide with remained to keep incremental id in range of that bits part. Alternatively, you can use UUIDs. While there is an extremely low possibility of generating two identical strings, it is not impossible.