How to Scale .NET Apps with Distributed Caching

Discover how to overcome database and storage bottlenecks in .NET applications using distributed caching in this comprehensive conference talk. Explore scalability challenges faced by growing applications and learn how distributed caching can improve response times. Gain insights into identifying suitable use cases for distributed caching in your projects and understand key features to look for in a distributed cache solution. Follow along with hands-on examples demonstrating the implementation of distributed caching techniques. Delve into topics such as runtime data sharing, ASP.NET providers, application data caching, and various caching strategies including read-through, write-through, and write-behind. Learn about cache freshness, partitioning, replication, and advanced features like querying, indexing, and client-side caching to optimize your .NET application's performance and scalability.

Introduction
Scalability
Linear Scalability
Nonlinear Scalability
Which Applications Need Scalability
The Scalability Problem
Distributed Caching
Worst Case Scenario
Use Cases
Runtime Data Sharing
Frameworks
ASPnet Provider
Sanity Testing
No Programming Needed
Application Data Cache
NCache
Application Data caching
Explorations
Sliding Expressions
Cache Dependency
Database Client
Keeping the Caching Fresh
Read Through
Read Through Example
Caching Tier
Readthrough
Readthrough Benefits
RightThrough Benefits
RightBehind Benefits
NCash
Partition Replication
Secular Scalability
Keep Cache Fresh
Cache is a Database
Querying
Linked Query
Grouping
Indexing
Client Cache