Load Balancing
Load balancing is a technique for distributing traffic across multiple servers.
Classification
- ComplexityMedium
- Impact areaTechnical
- Decision typeDesign
- Organizational maturityIntermediate
Technical context
Principles & goals
Use cases & scenarios
Compromises
- Server failures could impact availability.
- Difficulties in diagnosing issues.
- Costs from additional hardware.
- Regularly check server load.
- Monitor traffic patterns.
- Document network topology.
I/O & resources
- Available server resources.
- Traffic patterns.
- Monitoring tools.
- Optimal distribution of traffic.
- Increased server availability.
- Reduced response times.
Description
Load balancing allows for evenly distributing requests across multiple servers, enhancing the availability and scalability of applications. By preventing overload on individual servers, performance is optimized.
✔Benefits
- Increased availability.
- Improved performance.
- Optimal resource utilization.
✖Limitations
- Additional complexity overhead.
- Possible latency from routing.
- Dependence on external services.
Trade-offs
Metrics
- Server Load
Measurement of a server's load.
- Response Time
Time taken to respond to requests.
- Number of Active Connections
Number of users connected at the same time.
Examples & implementations
E-commerce Website
An e-commerce website uses load balancing to manage high user numbers during sales events.
Cloud Services
A cloud service provider uses load balancing to optimize resource allocation.
Streaming Platform
A streaming platform implements load balancing to minimize lag and buffering.
Implementation steps
Evaluate existing server infrastructure.
Choose an appropriate load balancing solution.
Implement and test load balancing.
⚠️ Technical debt & bottlenecks
Technical debt
- Outdated infrastructure.
- Lack of documentation.
- Backend bottlenecks.
Known bottlenecks
Misuse examples
- Overloading a single server.
- Ignoring monitoring data.
- Excessive complexity of the architecture.
Typical traps
- Premature scaling without need.
- Misunderstandings about load balancing techniques.
- Unrealistic expectations of performance.
Required skills
Architectural drivers
Constraints
- • Additional hardware requirements.
- • Network infrastructure for load balancing.
- • Security requirements for data.