Serverless Caching for Faster Data Serving

Have you ever used Serverless Caching? Most probably you would say NO! Certainly, you might not have used it as it is. But, what if I say you have been using it all the time? Yes, it's true. In this article, let's discuss how that can be true. Firstly, let’s look at what is Serverless Caching and why we need it. Further, we’ll explore cloud providers who facilitate Serverless Cache based cloud services. Finally, let’s dig deep into how you have been using Serverless Caching all the time!


What is Serverless Caching?

Serverless Caching is storing a subset of most critical data in a high-speed data storage layer, hosted in a cloud platform. Typically cached data are transient in nature, which allows faster data serving for future requests than is possible by accessing the original primary storage location. Further, serverless caching allows you to efficiently reuse previously retrieved or computed data.


Why Serverless Caching

We can always use our own local servers for caching, so why do we need serverless caching? Serverless, as the name suggests, involves NO servers. If we have to maintain our own servers for caching, surely it would make our life much harder. In other words, we have to spend resources on planning, building up the network and setting up servers. After that, we have to deal with continuous server maintenance and troubleshooting of network issues. However, with Serverless Caching, we do not need to worry about any of those. Here are some benefits of moving into serverless caching.

  • Fully Managed: Almost all service providers offer fully managed cache services so we no longer need to worry about performing maintenance tasks such as set-up, configuration, monitoring, failure recovery and backups ourselves.
  • High availability and reliability: Serverless cache services have highly available and reliable infrastructure, allowing data backup, snapshots and failure recovery.
  • Better performance: Most cloud providers already have geographically distributed data centers connected by insanely powerful backbone networks, providing sub-second latency. Achieving the same level of performance on a global scale via a custom or in-house deployment would be highly complicated and expensive, if not impossible.
  • High security: All service providers have their own security systems to protect cached data. Eg: AWS Identity and Access Management (IAM). Most cache services support both in-transit and at-rest data encryption to maximize data security.
  • Scalability: Serverless caching is more scalable compared to local cache servers. The scalability of local caching is limited by resource limitations, back-breaking maintenance, and expensiveness. However, with serverless caching, you do not need to worry about those things. Almost all serverless cache services are designed to automatically scale, to handle very large query volumes without any user intervention.
  • Cost-effective: Most of the time, usage of a cloud service for caching is cost-effective than setting up a local server for caching.

Serverless Cache Providers

Great! Looks like flying into Serverless Caching has a lot of gains. To clarify, there are a bunch of cloud service providers offering highly competitive serverless cache-based services. As a result, sometimes it may be challenging to find the best cloud service that satisfies your business requirements. Here is a list of some cloud service providers and their serverless cache-based cloud services.

Amazon Web Service:

  • CloudFront: CloudFront is a CDN service to speed up the distribution of static and dynamic web content to end-users. CloudFront maintains a worldwide network of data centers called Edge Locations that are used to deliver content. When a user requests content, CloudFront redirects the user to the closest edge location, resulting in content delivery with the lowest latency and best possible performance.
  • Route 53: AmazonRoute 53 is a Domain Name Service (DNS) caching service designed to quickly and reliably route end users to Internet applications by translating domain names into their IP addresses.
  • Elasticache: Elasticache is a fully managed, in-memory data store for enterprise-level data-intensive applications. Elasticache can improve the performance of consumer applications, by retrieving data from its in-memory data stores with high throughput and low latency. Above all, AWS Elasticache supports two open-source cache engines, Amazon Elasticache for Redis and Amazon Elasticache for Memcached.
    • Amazon Elasticache for Redis: Remote Dictionary Server, open-source, in-memory key-value data storage which can offer multi-purpose functionalities such as a database, cache, message broker, and queue. Redis delivers sub-millisecond response times enabling millions of requests per second leveraging real-time applications such as online gaming, Financial Services, Healthcare, and IoT. And, Sigma IDE will support Amazon Elasticache for Redis very soon.
    • Amazon Elasticache for Memcached: Memcached is a high-performance, open-source, in-memory data storage, offers a scalable solution for delivering sub-millisecond response times making it useful as a cache or session store. Moreover, Memcached is a popular choice for powering real-time applications such as online gaming, E-Commerce, and IoT.

Redis or Memcached?

Feature Description  Redis  Memcached
Sub-millisecond latency By storing data in-memory, both can read data more quickly than disk-based databases.

Developer ease of use Both Redis and Memcached are syntactically easy to use and require a minimal amount of code to integrate into your application.

Data partitioning Both Redis and Memcached allow distributing data among multiple nodes, facilitating scale-out to better handle more data when demand grows.

Programming language support Supported languages include Java, Python, PHP, C, C++, C#, JavaScript, Node.js, Ruby, Go and many others.

Advanced data structures In addition to strings, Redis supports lists, sets, sorted sets, hashes, bit arrays, and so forth

Multithreading Only Memcached supports for multithreading

Replication Redis allows creating multiple replicas of a Redis primary. As a result, Redis is able to scale up reads and to have highly available clusters.

Snapshots With Redis, you can keep your data on disk with a point in time snapshot which can be used for archiving or recovery.

Source: https://aws.amazon.com/elasticache/redis-vs-memcached/

Google Cloud Platform:

  • Cloud CDN: Cloud CDN is a content delivery network designed by Google to escalate content delivery for applications and websites served out by Google Cloud Platform and Google Compute Engine.
  • Cloud Memorystore: Cloud Memorystore for Redis provides a fully managed in-memory data store service built on scalable, secure and highly available infrastructure managed by Google.
  • Cloud DNS: Cloud DNS is a programmable Domain Name System service running on Google infrastructure. For instance, Cloud DNS can publish and manage millions of DNS zones and records using its user interface, command-line or API

Microsoft Azure:

  • Azure Cache for Redis: Fully managed, open-source–compatible in-memory data store to power fast, scalable applications.

Where do we use Serverless Caching?

In the beginning, I said that you have been using Serverless Caching - even if you did not have any idea about it. Well, Serverless Caching has its contribution to some of the most widely used, important and popular services. Here we summarize a few use cases of serverless caching; if you have ever used at least one of them, you have used Serverless Caching!

  • Content Delivery Networks: CDNs will cache frequently used data on their servers to speed up content delivery speed. Therefore through serverless caching CDNs are able to deliver content much faster than if it had to be delivered all the way from the origin.
  • Database Caching: Relational databases are slow when it comes to working with high volumes of data. As a result of redundancy and the high volume of data, database indexes can start getting slower quite quickly. Database caching allows to dynamically increase throughput and decrease data retrieval latency. In other words, the cache acts as a data access layer to improve read performance.
  • Domain Name System Caching: Domain Name System is the phonebook of the internet. DNS translates domain names into IP addresses so web browsers can connect to internet resources.
  • Serverless API: RESTful APIs (Application Programming Interfaces) expose resources over HTTP, allowing users to interact with them. However, an API does not need to communicate with the backend service or database on every request. In many cases, an API can benefit from a data caching layer to serve requests, where the response remains constant across requests and does not change frequently. Such cached results will deliver much more cost-effective performance, and yield optimal response times.
  • Session store: Session management is the process of securely handling multiple requests to a web-based application or service from a single user or entity. Hence, by its very nature, a Serverless Cache can be used for store session data efficiently.

Conclusion

To sum up, Serverless Caching is becoming the future of the data caching as the world moves towards cloud computing. With the power of Serverless Caching, it has become an indispensable instrument for each and every person in the world. In conclusion, at the end of the day, we all had used - and are still using - Serverless Caching!