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Top 6 Load Balancing Algorithms Every Developer Should Know
تم نشره في 2023/08/17
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Also, it's worth looking for the possibility of positive feedback loops, for instance if certain kinds of errors happening on one particular server (e.g. configuration problem) make processing very fast, and thus make this server even more attractive to the load balancing system.
Error metrics are easily overlooked when computing weights for load balancing. ... 48
DNS supports that. 13
for example should we have a separate copy of the application on each server or there are other ways for doing it?
another consideration is concurrent access to shared resources... how preventing conflicts and data corruption is implemented?
probably another subcategory is distributing the database itself...
i think these can be candidates for separate videos indeed ;) ... 3
1. Round Robin
2. Least Connections
3. Weighted Round Robin
4. Weighted Least Connections
5. IP Hash
6. Least Response Time
Bard responses with a bit different algorithms, Geolocation instead of IP Hash:
1. Round robin.
2. Weighted round robin.
3. Least connections.
4. Least response time.
5. Sticky sessions.
6. Geolocation.
:D ... 2
• If it's a high volume lightweight attack like a Smurfed ping won't the load balancer need to process each packet anyway, even if very briefly?
• Under what circumstances will trivial processing overwhelm the load balancer and is this different between algorithms?
• I'm assuming Sticky Round Robin or IP/URL can just drop all the packets from a user or IP respectively to dodge a denial of service attack. Is this the case?
• How are TCP/IP layers split between the load balancer and the destination machine? Particularly, if an attacker sends massage parts at a rate just under the connection timeout will the load balancer get overwhelmed by excessive open connections or will the destination machine (slow loris attack)? ... 5
🌐 Overview of Load Balancing Algorithms
- Crucial for large-scale web apps.
- Two categories: static and dynamic.
- Goal: Grasp core load balancing for better app architecture.
🔄 Static Load Balancing Algorithms
- Distribute requests without real-time server consideration.
- Examples: Round Robin, Sticky Round Robin, Weighted Round Robin.
- Trade-off: Simplicity vs. Adaptability.
🔍 Hash-Based Algorithms
- Hash functions map requests to servers.
- Challenge: Optimal hash function choice.
- Advantage: Even distribution with a wise function.
🔄 Dynamic Load Balancing Algorithms
- Adapt in real-time based on server conditions.
- Examples: Least Connections, Least Response Time.
- Trade-off: Adaptability vs. Overhead.
⚖️ Trade-offs between Static and Dynamic Algorithms
- Consider trade-offs in load balancing selection.
- Static for stateless apps, dynamic for complex ones.
💬 Viewer Engagement and Conclusion
- Encourage sharing load balancing experiences.
- Highlight simplified "static" and "dynamic" differentiation.
- Promote system design newsletter.
Made with HARPA AI ... 2
If you have enough traffic that you're tracking multiple outstanding requests per server, then you can order each server by whichever is longest: the latency of the last fulfilled request or the elapsed time since the oldest outstanding request. That way, you (practically) don't have any overhead measuring latency. If you don't have enough traffic to accumulate multiple requests per server, then load-balancing shouldn't be a huge problem.
You can add more complex logic to minimize hot-spots and detect server failures, but the gist is still the same. ... 2
*So the Backend is a live streaming application
Also, it's worth looking for the possibility of positive feedback loops, for instance if certain kinds of errors happening on one particular server (e.g. configuration problem) make processing very fast, and thus make this server even more attractive to the load balancing system.
Error metrics are easily overlooked when computing weights for load balancing. ... 48
DNS supports that. 13
for example should we have a separate copy of the application on each server or there are other ways for doing it?
another consideration is concurrent access to shared resources... how preventing conflicts and data corruption is implemented?
probably another subcategory is distributing the database itself...
i think these can be candidates for separate videos indeed ;) ... 3
1. Round Robin
2. Least Connections
3. Weighted Round Robin
4. Weighted Least Connections
5. IP Hash
6. Least Response Time
Bard responses with a bit different algorithms, Geolocation instead of IP Hash:
1. Round robin.
2. Weighted round robin.
3. Least connections.
4. Least response time.
5. Sticky sessions.
6. Geolocation.
:D ... 2
• If it's a high volume lightweight attack like a Smurfed ping won't the load balancer need to process each packet anyway, even if very briefly?
• Under what circumstances will trivial processing overwhelm the load balancer and is this different between algorithms?
• I'm assuming Sticky Round Robin or IP/URL can just drop all the packets from a user or IP respectively to dodge a denial of service attack. Is this the case?
• How are TCP/IP layers split between the load balancer and the destination machine? Particularly, if an attacker sends massage parts at a rate just under the connection timeout will the load balancer get overwhelmed by excessive open connections or will the destination machine (slow loris attack)? ... 5
🌐 Overview of Load Balancing Algorithms
- Crucial for large-scale web apps.
- Two categories: static and dynamic.
- Goal: Grasp core load balancing for better app architecture.
🔄 Static Load Balancing Algorithms
- Distribute requests without real-time server consideration.
- Examples: Round Robin, Sticky Round Robin, Weighted Round Robin.
- Trade-off: Simplicity vs. Adaptability.
🔍 Hash-Based Algorithms
- Hash functions map requests to servers.
- Challenge: Optimal hash function choice.
- Advantage: Even distribution with a wise function.
🔄 Dynamic Load Balancing Algorithms
- Adapt in real-time based on server conditions.
- Examples: Least Connections, Least Response Time.
- Trade-off: Adaptability vs. Overhead.
⚖️ Trade-offs between Static and Dynamic Algorithms
- Consider trade-offs in load balancing selection.
- Static for stateless apps, dynamic for complex ones.
💬 Viewer Engagement and Conclusion
- Encourage sharing load balancing experiences.
- Highlight simplified "static" and "dynamic" differentiation.
- Promote system design newsletter.
Made with HARPA AI ... 2
If you have enough traffic that you're tracking multiple outstanding requests per server, then you can order each server by whichever is longest: the latency of the last fulfilled request or the elapsed time since the oldest outstanding request. That way, you (practically) don't have any overhead measuring latency. If you don't have enough traffic to accumulate multiple requests per server, then load-balancing shouldn't be a huge problem.
You can add more complex logic to minimize hot-spots and detect server failures, but the gist is still the same. ... 2
*So the Backend is a live streaming application