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1
Introduction
2
Scalability
3
Linear Scalability
4
Nonlinear Scalability
5
Which Applications Need Scalability
6
The Scalability Problem
7
Distributed Caching
8
Worst Case Scenario
9
Use Cases
10
Runtime Data Sharing
11
Frameworks
12
ASPnet Provider
13
Sanity Testing
14
No Programming Needed
15
Application Data Cache
16
NCache
17
Application Data caching
18
Explorations
19
Sliding Expressions
20
Cache Dependency
21
Database Client
22
Keeping the Caching Fresh
23
Read Through
24
Read Through Example
25
Caching Tier
26
Readthrough
27
Readthrough Benefits
28
RightThrough Benefits
29
RightBehind Benefits
30
NCash
31
Partition Replication
32
Secular Scalability
33
Keep Cache Fresh
34
Cache is a Database
35
Querying
36
Linked Query
37
Grouping
38
Indexing
39
Client Cache
Description:
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.

How to Scale .NET Apps with Distributed Caching

NDC Conferences
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