Load Balancing Algorithms
Scenario context
Load balancers distribute incoming requests across a pool of healthy backend servers to ensure scalability and reliability.
🎯 System Scenario & Requirements
System Goal
Load balancers distribute incoming requests across a pool of healthy backend servers to ensure scalability and reliability.
Actors & Components
- Application or API tier
- Core service under design
- Operator or SRE observer
Functional Requirements
- Load balancers distribute incoming requests across a pool of healthy backend servers to ensure scalability and reliability.
- Round Robin Distributes requests sequentially in a circular order.
- Best for : Homogeneous servers with equal capacity and short-lived requests.
Constraints & Assumptions
- - IP Hash Hashes the client's IP address to map them consistently to the same backend server.
- - Best for : Stateful applications requiring session persistence ("sticky sessions").
- Production Considerations & Trade-offs - Detection: IP Hash Hashes the client's IP address to map them consistently to the same backend server.
- - User or operator impact: IP Hash Hashes the client's IP address to map them consistently to the same backend server.
⚡ Execution Stages & Decision Trace
Stage 1 — End-to-end outcome
Round Robin Distributes requests sequentially in a circular order.
Round Robin Distributes requests sequentially in a circular order.
Deep Dive
Scenario context
Load balancers distribute incoming requests across a pool of healthy backend servers to ensure scalability and reliability.
1. Round Robin
Distributes requests sequentially in a circular order.
- Best for: Homogeneous servers with equal capacity and short-lived requests.
2. Least Connections
Directs requests to the server with the fewest active sessions.
- Best for: Long-lived connections (like da…
This walkthrough focuses on Scenario context.
Before making a design choice, clarify:
- Load balancers distribute incoming requests across a pool of healthy backend servers to ensure scalability and reliability.
- Round Robin Distributes requests sequentially in a circular order.
- Best for : Homogeneous servers with equal capacity and short-lived requests.
Concepts in play: load-balancing, consistency-replication, database-indexing
Stage 1 — End-to-end outcome
- Round Robin Distributes requests sequentially in a circular order.
Observable outcome: Round Robin Distributes requests sequentially in a circular order.
End-to-end outcome
Load balancers distribute incoming requests across a pool of healthy backend servers to ensure scalability and reliability.
Alternatives considered
Alternatives considered
The source focuses on one primary design.
Failure and degraded modes
Stage 1 — Production Considerations & Trade-offs
- Detection: - IP Hash Hashes the client's IP address to map them consistently to the same backend server.
- User or operator impact: - IP Hash Hashes the client's IP address to map them consistently to the same backend server.
Failure and degraded modes
- Detection: Production Considerations & Trade-offs - Detection: IP Hash Hashes the client's IP address to map them consistently to the same backend server.
- User or operator impact: Production Considerations & Trade-offs - Detection: IP Hash Hashes the client's IP address to map them consistently to the same backend server.
Key learnings
- Round Robin Distributes requests sequentially in a circular order.