Introduction
Cache is one of the most important parts of the backend/frontend. We always use cache to improve latency.
Cache exists in every level of system architecture, from hardware(CPU, Memory, and Disk), OS, Application to User fronted (Browser, app).
A cache is a memory reserved for storing temporary files or data from apps, servers, websites, or browsers to help load faster when requested. It includes images, videos, animation, gifs, scripts, files, etc.
What is Caching?
Caching is a process or method of storing a copy of the continuously asked data in a temporary storage location or cache to be quickly accessed when needed.
Caching helps applications perform dramatically faster and cost significantly less at scale.
In computing, a cache is a high-speed data storage layer which stores a subset of data, typically transient in nature, so that future requests for that data are served up faster than is possible by accessing the data’s primary storage location. Caching allows you to efficiently reuse previously retrieved or computed data.
How does Caching work?
The data in a cache is generally stored in fast access hardware such as RAM (Random-access memory) and may also be used in correlation with a software component. A cache's primary purpose is to increase data retrieval performance by reducing the need to access the underlying slower storage layer.
Trading off capacity for speed, a cache typically stores a subset of data transiently, in contrast to databases whose data is usually complete and durable.
Benefits of Caching
Improve Application Performance. Because memory is orders of magnitude faster than disk (magnetic or SSD), reading data from in-memory cache is extremely fast (sub-millisecond).
Reduce Database Cost. A single cache instance can provide hundreds of thousands of IOPS (Input/output operations per second), potentially replacing a number of database instances, thus driving the total cost down.
Predictable Performance. A common challenge in modern applications is dealing with times of spikes in application usage. Examples include social apps during the Super Bowl or election day, eCommerce websites during Black Friday, etc.
Eliminate Database Hotspots. In many applications, it is likely that a small subset of data, such as a celebrity profile or popular product, will be accessed more frequently than the rest.
Increase Read Throughput (IOPS). In addition to lower latency, in-memory systems also offer much higher request rates (IOPS) relative to a comparable disk-based database.
Types of Caching
Database Caching. The speed and throughput of your database can be the most impactful factor for overall application performance
CDN Caching. CDN reduces load on application origin and improves user experience. Caching web content helps improve upon the responsiveness of your websites by reducing the load on backend resources and network congestion.
Web Caching. Learn about client-side and server-side options for web caching. The caching methodology is based on the HTTP header directives provided by the HTTP response from the origin servers to the browser.
General Cache. Using an in-memory key-value store is a great way to build highly performant applications. Today most key/value stores such as Memcached and Redis can store terabytes worth of data.
Session Management. A centralized session management data store provides consistent user experience, better session durability, and high availability. There are various ways to manage user sessions including storing those sessions locally to the node responding to the HTTP request or designating a layer in your architecture which can store those sessions in a scalable and robust manner.
Best Practices for Cache Management
Effective cache management is crucial for maximizing the benefits of distributed caching. Some best practices include:
1. Cache Eviction: Implement appropriate cache eviction policies, such as Least Recently Used (LRU) or Time to Live (TTL), to ensure that the cache remains updated and relevant.
2. Data Consistency: Ensure that the cache remains consistent with the primary data source, especially in scenarios where data is frequently updated.
3. Monitoring: Regularly monitor cache hit and miss rates to understand cache effectiveness and make necessary adjustments.
- Scalability: Design the cache infrastructure to be scalable, allowing for easy addition of new cache nodes as the application grows.
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