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  • Writer's pictureDimit Chadha

Scalability - Best Practices

Scalability

The ability of a system to grow in its capacity to meet the rising demand for its services offered. Scalability enables accommodation of


o More transactions processed per millisecond

o Additional traffic that can be handled

o Number of SQL statements that can be run & results provided simultaneously.

o More storage capacity

o Reducing the adverse impact due to growth on performance, cost and maintainability.


Some Facts

# "Scalability" is not equivalent to "Raw Performance"

# Don't guess the bottleneck, Measure it.

# Do regular capacity planning. Collect usage statistics, predict the growth rate.


Why Need to Scale ?

# Increas in number of customers & concurrent users

# Increase in features of product in scope.

# Increase in Database usage & calls

# Low Performance due to less resources thus increasing response time

# Database’s performance against the multi-transaction batch processing


Basic Techniques To Scale

Scaling Out/Horizontally:

The ability to spread the processing load across more machines. the advantage of being linearly scalable; rather than buying a bigger, more expensive box, we just buy more copies of the same cheap box. With the right architectural design, this approach can scale massively.


Scaling Up/Vertically:

Increasing the power of individual machines. addresses the scalability of a single instance of the service. A simple way to scale most software is simply to run it on a more powerful machine; one with a faster processor or more memory.


Scalable System Architecture - Buildling blocks
  1. Load Balancers - Hardware & Software LBs

  2. Caching Mechnism - In Memory caches, Database caching, cache evictions.

  3. Offline Processing - Messaging, Scheduling, Map-Reduce

  4. Platform Approach - Service Level APIs

  5. Data Partioning

  6. Filtering at Source

  7. Resource Pooling

  8. Content Delivery networks

  9. Session Management

  10. Database Replication


Happy Scaling !

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