.Net Distributed Caching

Oct 13, 2014Download as PPTX, PDF1 like2,628 views

Distributed caching improves performance by storing data in multiple locations for faster retrieval. It works by storing copies of data on multiple machines to improve scalability and availability. There are different scopes for caching like application, tenant, user, and session data. The cache key identifies the data and includes the scope and uniqueness. The time to live determines how long cached data remains valid before being refreshed, with lower times improving consistency at the cost of performance. Code examples demonstrate caching patterns for services and tracking statistics across distributed caches.

.Net Distributed Caching
Paul Fryer
Software Architect, Fiserv

cache /kaSH/
verb
–Store away in hiding or
for future use.

Use of phrase “caching” in books, last
200 years

Online search interest for various
cache providers

Cache Scopes
A = Application
T = Tenant
U = User
S = Session

Where to Cache
• Application / Tenant Data = Local Cache
• Session / User Data = Distributed Cache

Cache Key Pattern
{Scope}.{Identity}.{Uniqueness}
A.WebUI.DefaultTheme
A.WebUI.Exchanges.Page1.PageSize10
T.TenantB.MaxHistory
T.TenantC.ContactInformation
U.johnB22.ProfileIcon
U.sallyP1.LastPost
S.2928328387.RequiresSecondFactorAuthentication
S.2050988830.TransactionHistory.Page2.PageSize20

Time to Live
• How critical is the data?
– How current does it have to be?
• Is eventual consistency ok?

TTL Performance Relationship
Time to live
Performance

Consistency
• Events that invalidate cached data should cause
the cached data to update or remove if possible.
• You often only able to capture events within your
application.
• Underlying changes to the source can cause
cached data to be out of sync. Mitigate this with
appropriate TTL.
• Pub/Sub capabilities exist on some distributed
caches.

Code Examples
• Adding a read through cache pattern to a slow
service.
• Consolidating the caching behavior into a
reusable attribute.
• Using a distributed cache to track statistics
about connections, like number or requests
per second.
• Performance testing.

Resources
• CacheSharp – abstraction layer that maps into
multiple cache providers. Useful for establishing
baselines and comparing different providers.
• Redis Session State Provider – ASP.Net web
application session state provider. Useful for web
apps that want to move session state out of
process.
• CacheCow – HTTP Caching framework. Useful for
implementing HTTP caching in web applications.

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.Net Distributed Caching

1. .Net Distributed Caching Paul Fryer Software Architect, Fiserv

2. About Me

6. Portland Hipster

9. WHAT IS CACHE?

12. cache /kaSH/ verb –Store away in hiding or for future use.

13. Use of phrase “caching” in books, last 200 years

14. WHAT IS A DISTRIBUTED CACHE?

15. Horizontal Scale

16. Online search interest for various cache providers

17. HOW TO CACHE

18. Pattern: Read Through Cache

19. Cache Scopes A = Application T = Tenant U = User S = Session

20. Where to Cache • Application / Tenant Data = Local Cache • Session / User Data = Distributed Cache

21. Cache Key Pattern {Scope}.{Identity}.{Uniqueness} A.WebUI.DefaultTheme A.WebUI.Exchanges.Page1.PageSize10 T.TenantB.MaxHistory T.TenantC.ContactInformation U.johnB22.ProfileIcon U.sallyP1.LastPost S.2928328387.RequiresSecondFactorAuthentication S.2050988830.TransactionHistory.Page2.PageSize20

22. Time to Live • How critical is the data? – How current does it have to be? • Is eventual consistency ok?

23. TTL Performance Relationship Time to live Performance

24. Consistency • Events that invalidate cached data should cause the cached data to update or remove if possible. • You often only able to capture events within your application. • Underlying changes to the source can cause cached data to be out of sync. Mitigate this with appropriate TTL. • Pub/Sub capabilities exist on some distributed caches.

25. Code Examples • Adding a read through cache pattern to a slow service. • Consolidating the caching behavior into a reusable attribute. • Using a distributed cache to track statistics about connections, like number or requests per second. • Performance testing.

26. Resources • CacheSharp – abstraction layer that maps into multiple cache providers. Useful for establishing baselines and comparing different providers. • Redis Session State Provider – ASP.Net web application session state provider. Useful for web apps that want to move session state out of process. • CacheCow – HTTP Caching framework. Useful for implementing HTTP caching in web applications.

27. Connect • LinkedIn • My Blog

.Net Distributed Caching

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