Load Balancing and Performance Optimization Techniques
Load balancing and performance optimization techniques are essential for ensuring optimal performance and scalability. This includes:
- Round Robin: Balance incoming requests among a group of servers by assigning them evenly.
- Least Connection: Sort-out requests to servers with the fewest connections of active hosts to accomplish smoother loads.
- IP Hash: Apply the hash function determined by the customer’s IP address to the pattern of requests, so that incoming requests are always sent to the same server.
- Weighted Round Robin: Give server loads different weights to distribute the load proportionally by means of provision for their capacity.
2. Caching
- Content Caching: Cache static asserts, database queries and API responses in order to lighten a server’s load and boost response times.
- CDNs (Content Delivery Networks): Try CDNs to cache content at user-resident servers and thus reduce the roundtrip latency and lift traffic burden from origin servers.
- Object Caching: Keep freshly used data objects or chunks in memory to fetch them without making too many calls to the database or API and speed up your app.
- Reverse Proxy Caching: Store answers from backend traders to reduce the load on edge servers, and thus, enhancing scalability.
3. Database Optimization
- Query Optimization: Optimize database queries by indexing, using appropriate join techniques, and executing cardinal operations by means of devising queries which would return results with better speeds.
- Connection Pooling: The connection pool be used to maintain database connections and reduce the overhead involved in creating new links.
- Database Sharding: Split database across several instance of databases and selectively choose the instances for better scalability and distribution.
- Replication: Replicate databases to many nodes using NLB technology for high availability and read scaling, facilitating load distribution on the primry databases.
4. Content Compression
- Gzip Compression: Compress responses using Gzip compression for HTTP for efficient delivery and improved network performance.
- Brotli Compression: Use Brotli compression, more efficient than the present one, to further minimize the response size and provide a better performance
- Image Optimization: Enhancements are possible by decreasing image size, compressing, and using latest image formats to speed up the loading speed and thus making use experience better.
Scale From Zero To Million of Users
In startups and businesses, scaling from small beginnings to catering to millions of customers is one thing, but it’s a necessity to both lose and win the game. The path that goes from zero to millions will enable the intersection of innovation, scalability, and adaptability. Nowadays, the pace of change is very fast. The User’s need is changing and the competition is in a tight race. Thus, scaling becomes extremely critical It just isn’t about coping with the growth rate but about making everything from systems and infrastructure to processes able to tackle and level more work.
Important Topics for Scaling from zero to million of users
- Importance of Scaling for Startups and Businesses
- What is Scalability?
- A Roadmap for Scalability
- Factors Influencing Scalability
- Design Principles for Scalable Systems
- Scalable Infrastructure Choices
- Importance of Automation and Monitoring for Scalability
- Scalable Software Development Practices
- Managing Exponential User Growth
- Scaling Databases and Storage Solutions
- Load Balancing and Performance Optimization Techniques
- Example of how to Scale an Application?
- Real-World Example of Successful Scalability
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