Today in this article we will deep dive into Cache Best Practices and Guidelines.
We will cover below aspects for this article,
- What is Cache?
- Where is the Cache data stored?
- Cache – Guidelines and Best Practices
- Understand the data usage pattern
- Define Cache structure
- Define the Data to be Cached
- Do not store compute data in Cache
- Lazy Caching design for data
- Define data expiration in a cache
- Define Eviction policy/strategy for cache
- Concurrency in a Cache
- Connection Resiliency for Cache
- Seeding the data in advance
- Security on Cache’s Data
What is Cache?
Application and its performance are important, specifically the application’s end-user experience by focusing on some very basic applications and its resources delivery techniques.
Implementing and optimizing caching in the application stack is one such technique.
- Cache is a process of accessing the data more quickly to lower the response time from an external
system by a service provider.
- This is an efficient way of getting the data, especially in the case of frequently needed information
accessing.
Where is the Cache data stored?
- The cache is implemented typically, by moving frequently used data to fast storage that is close to the application. So, performance-wise, the Data is very quickly accessible and therefore there is a vast increase in speed in getting the response from the database.
- Because the data is closer to the application instance, it is more efficient to obtain data from a cache rather than the original source.
Cache – Guidelines and Best Practices
We shall go through below a few high-level Cache Best Practices.
Understand the data usage pattern
- Before you consider implementing the cache you must understand the data usage in consideration for the cache.
- Take a note of How frequently your data changes
- Note how frequently the same data is being accessed by the user.
- Take a note of the timings of change in data and user usage mode.
Define Cache structure
- Because caches are basic key-value stores, you may need to cache a data record in numerous formats so that you may access it using various properties.
- Its important to first define the structure of your data that is to be cached.
- Direct Caching a database record will be enough to provide considerable performance benefits but as a good practice though, data should be cached in a format that mixes many records.
Define the Data to be Cached
- Caching is very useful for static data and less useful with continuous changing or dynamic content.
- It’s useful to identify the data that can be cached vs that can be fetched from actual servers.
- Caching continuous changing data may affect the performance of your application losing the real benefits of caching.
Do not store compute data in Cache
- The cache is just a temporary data store that could vanish at any time.
- Depending on the use cases, storing any computed data or modified data in the cache may produce unexpected results. However, this will depend on the use case you are dealing with. Please take the decision as appropriate.
- You basically minimize the chance of losing data.
Lazy Caching design for data
- Seeding the data in advance could not be beneficial if the data is not used by users at all.
- Lazy caching is considered a good caching strategy
- The cache only objects data that the application actually requests, which helps keep cache size in control and lets you manage cache memory effectively.
- Based on cache expiration, you also evict the data keeping the cache size manageable.
Define data expiration in a cache
- Define the expiration period for the cache and the objects after thoroughly understanding the data usage pattern.
- Too short expiration time will make objects expire too quickly reducing the benefits of using the cache.
- Too long expiration can make your data stale giving unexpected behavior to the user using the data…
Define Eviction policy/strategy for cache
- As Cache size is limited. It’s important to define the eviction policy so that the risk of overburdened or exceeding the memory in the cache can be avoided.
- Good eviction policy lets manage the cache memory size based on the data usage pattern.
- LRU (Least Recently Used ) – This policy lets cache removed a few items forcibly based on the least recent usage pattern.
- FIFO(First in First out) – This policy makes items removed from the cache based on their age. Old data is removed first.
- ER(Explicit Removal ) – This is a custom policy defined by you based on some business events.
Concurrency in a Cache
- Caches are generally designed as shared data used by multiple instances of an application.
- Careful consideration of eviction policy chosen for the cache, Concurrency policy design can be considered
- Users can define the Optimistic or Pessimistic approaches for addressing the concurrency issues.
- In the Optimistic approach, updates are performed only if data changes from what originally was retrieved
- In the Pessimistic approach, data is locked for the given updates ( so that no other request updates it)
Connection Resiliency for Cache
- Design for cache connection resiliency.
- Cache being a shared resource is more prone to transient faults etc.
- Set your connection residency policy as per your requirements.
- Set retry, and timeout to the optimum per requirements
Seeding the data in advance
- Seeding the data in advance in the cache can be useful in some use cases.
- Such seeding can be performed when your application starts or bootstraps
- Consider the seeding option after careful analysis and if are aware of the initial data load and effect on the performance.
- The seeding option is considered good only when you know all the data in the cache will be requested by the user else use the Lazy loading pattern as discussed below.
Security on Cache’s Data
- Design Consideration should be for Data at rest in the cache and when data flow in and out from the Cache server.
- Caching Sensitive Data can Lead to serious security issues. Certainly, security is not an afterthought process.
- Sensitive data includes user credentials, PII, and other business-critical information.
- Design your cache as private and accessible to only authorized members.
- Consider implementing SSL.
Other useful references :
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Happy Coding !!
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