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ElastiCache – When speed is everything

Posted on October 25, 2022 by

Categories: AWS


ADVERTORIAL Speed is crucial. According to data gathered in July of this year, more than 63.1% of people worldwide use the internet via smartphones, tablets, or other mobile devices, a rise of 178 million or 3.7% since 2021. With a 98% internet penetration rate, the UK has one of the highest rates in the world, and 90.2% of mobile users there rely on reliable, fast WiFi or cellular connections. Due to the significant increase in real-time applications brought on by the widespread usage of mobile devices, databases are urgently needed to satisfy the need for speedy information delivery. An application may become ultra-fast using in-memory data caches, offering consumers the required immediate reaction time for any application.

As a result, application performance is an essential factor to take into account for both users and system administrators. Site responsiveness is taken into account by search engines like Google when determining rankings since page speed affects the user experience as a whole. According to some statistics, users frequently leave a website after seeing just one page, or they might not even wait for the page to load before leaving. Research by Akamai indicated that a 100-millisecond delay in website load time can decrease conversion rates by 7% and a two-second delay in web page load time raises bounce rate by 103%. This user behavior can, therefore, adversely affect your company’s profitability.

Data retrieval often puts the most pressure on content load times. Solid-state disc (SSD) devices often have content load speeds of milliseconds or more as contrasted to the microsecond latencies possible when directly accessing memory using in-memory data storage. There is a significant speed difference from microseconds to milliseconds (one microsecond is 1/1000 of a millisecond).

Improved data access using in-memory caching.

The quickest storage method to aid with content load speeds is caching regularly accessed, or “hot,” material in memory. In-memory caching enhances the primary database with a high-speed data storage layer for reduced latency. In the cloud, where caching nodes may scale fast to serve applications as compute-intensive workloads and consumption increase, a cache is an efficient approach to speed up data access.

You may independently grow the cache to meet the application’s demands by isolating the caching layer from the application. To achieve the high availability required for essential workloads, applications can also effectively share the same data in the cache. A cache also supports hot data, such as API requests, real-time data, often viewed material, and frequently used but rarely changed computations that consume computer cycles, in addition to supporting database query results.

As opposed to just expanding your database, using an in-memory cache has some crucial advantages. “Scaling down the in-memory caching layer is often less costly than scaling up a database server. Additionally, scaling up a traditional database is likely to result in a lower degree of in-memory performance “The general manager of AWS’s in-memory databases, Itay Maoz, adds.

Another advantage of in-memory caching is its capacity to manage fluctuating workloads by assisting in managing surges in application demand. It can assist buffer such requests without placing undue stress on the core database, for instance, if your online publication site releases a breaking news piece and everyone rushes to read it at once. Having a cache will enable you to provide your clients’ demands even in unforeseen circumstances without forecasting.

A fully managed in-memory caching solution compatible with both the Redis and Memcached open-source engines is available from Amazon Web Services (AWS) called Amazon ElastiCache. By lowering latency to microseconds and providing high throughput, ElastiCache is frequently used by AWS customers to improve the performance of already-existing databases.

Applications with microservices architecture perform better when they have a cache because it reduces network round trips and database hits. ElastiCache expands out hundreds of cache nodes to accommodate high volumes of application queries from multiple servers to fulfill the demands of your most demanding, internet-scale applications. ElastiCache is a remote cache created to accommodate hundreds of millions of operations per second inside a cluster and perform a sub-millisecond.

ElastiCache is wholly managed, making it simple to build, run, and expand an in-memory data store with several advantages over independently managed services. You are not responsible for applying software updates or allocating server resources. Continuous memory management, failure detection and repair, and comprehensive monitoring metrics are all features of ElastiCache. You may instead concentrate on more crucial application development goals by using ElastiCache.

ElastiCache for Redis also provides auto-scaling and data tiering, two fundamental approaches to help cut expenses. By choosing metrics that will initiate scaling, autoscaling enables you to automatically raise or reduce the size of your ElastiCache clusters. Another option to cut expenses is to employ data tiering, which, when memory capacity is exhausted, moves less recently used data transparently and automatically to locally connected NVMe (nonvolatile memory express) SSDs.

ElastiCache functionality was also made available by AWS in 2021 with the release of AWS Controllers for Kubernetes (ACK), allowing users to configure and utilize ElastiCache resources directly from their Kubernetes cluster. This makes it possible for developers to use ElastiCache to support Kubernetes applications without defining ElastiCache resources outside of the cluster or operating and maintaining in-memory caching services inside the cluster.

Two engines for various purposes

Users of ElastiCache have a choice between Memcached and Redis, two fully managed, open-source, in-memory engines, each of which offers a variety of benefits. Both provide easy usage, sub-millisecond latency, excellent performance, and the advantages of managed services, but depending on your needs, there are important distinctions to consider.

Use ElastiCache for Memcached, a Memcached-compatible data store, if you need incredibly high throughput and have a use case for primary object caching. ElastiCache for Memcached was created to handle significant traffic since it is straightforward and can scale up and employ several processor cores to maintain low latency.

ElastiCache for Redis, a Redis-compatible, in-memory data store, is recommended if your use case necessitates the use of more complex data types, such as strings, hashes, lists, sets, sorted sets, or JavaScript Object Notation (JSON) or if you want your cached data to be replicated for high availability across multiple Availability Zones (AZs) or Regions. This wide variety of adaptable Redis data types is supported by ElastiCache for Redis, which also offers new native support for partial JSON document updates and robust searching and filtering using the JSONPath query language.

using ElastiCache to fuel success

Beat, one of Latin America’s fastest-growing ride-hailing companies, experienced hyper growth in 2019 and collaborated with AWS to manage this success using ElastiCache for Redis. Beat, a seasoned user of AWS, combines Amazon Aurora, a fully managed relational database, with ElastiCache for Redis.

Initially, Beat had cluster mode disabled in ElastiCache, limiting it to vertical cluster scaling alone. As its user base increased, Beat had to grow horizontally, changing its setup and turning on cluster mode. By making this adjustment, the firm could evenly distribute the traffic load across all instances, thus lessening the workload on its technical staff. Beat claims that this led to a 90% decrease in computing expenses and a 90% reduction in staff time spent administering the cache layer due to the migration.

What more use cases can in-memory caching technologies like ElastiCache suit well? A cache can assist enhance application performance so that it is predictable and lessen the strain on the backend for any application with a microservices architecture and a compute-intensive analytical workload. Gaming leaderboards are a typical use case since they frequently include many players, a lot of computation, and scores that update every millisecond. The top-scoring players may be returned thanks to ElastiCache for Redis’ support for sorted sets, eliminating the need to retrieve and sort the application’s whole list of players.

The Pokémon Company International (TPCi), which is in charge of ensuring that Pokémon enthusiasts outside of Asia may monitor their accomplishments through fully-featured user profiles in the Pokémon Trainer Club, has found this kind of arrangement to be helpful.

The company transferred user authentication requests to a fully managed AWS solution utilizing Amazon Aurora with PostgreSQL compatibility and user caching to Amazon ElastiCache using Redis and Memcached. ElastiCache for Memcached helps keep tickets active so that existing users’ sessions are not disrupted when new users join.

ElastiCache for Redis queues tasks for new users so they may be requested to perform post-authentication chores. TPCi could make the most of each engine’s advantages by utilizing ElastiCache across both without worrying about doing a time-consuming re-factor of its application.

Putting ElastiCache to use

AWS handles all the configuration necessary for creating and administering a distributed cache environment since ElastiCache is a fully managed service. ElastiCache is a fully managed service, so users don’t need to worry about the configuration required to create and operate a distributed cache environment because AWS takes care of everything. Using AWS CloudFormation templates, ElastiCache resources may be easily created and configured.

It is also an API-accessible service that you can set up using the AWS Management Console, AWS Software Development Kit, or AWS Command Line Interface (AWS CLI) (AWS SDK). Using the ACK for ElastiCache, you may also define and utilize ElastiCache resources directly from your Kubernetes cluster. Downloading the container image and installing it quickly will get developers going.

Customers may utilize ElastiCache as needed and only pay for the time they really use, down to the hour. Those who plan on using the nodes frequently might choose reserved nodes with terms of one or three years. For clients who agree to these terms up front, this offers a sizable discount and lowers costs.

Any relational or non-relational database and any data warehouse, including Amazon Relational Database Service, Amazon Aurora, and Amazon Redshift, may have data cached using ElastiCache. With a relational database with a cache, you may have the blazing-fast speed of an in-memory cache, together with the dependability of data replication and the adaptability of relational data access patterns.

ElastiCache may also be used with non-relational databases like Amazon DynamoDB to help cache read requests for read-intensive or compute-intensive applications, improving performance and reducing costs. ElastiCache can enable Amazon Simple Storage Service (Amazon S3), already known for having industry-leading scalability, data availability, security, and performance, to improve performance even further while simultaneously lowering retrieval and transfer costs.

AWS also provides another fully managed, Redis-compatible service, Amazon MemoryDB, if you wish to streamline your design and avoid using both a cache and a database. Like ElastiCache, this ultra-fast database retains all of its data in memory for microsecond read latency and high throughput. MemoryDB publishes data to a distributed transaction log across various AWS Availability Zones to ensure a quick recovery and restart durability. MemoryDB is advised if you want a long-lasting in-memory database; if not, utilize ElastiCache with your current database for applications requiring sub-millisecond response times.

Using an in-memory cache is the most excellent way to improve the performance of your application while keeping expenses down when speed is critical. Thanks to cloud computing, everyone now has more accessible access to this, even small organizations and teams that want to remain agile and help their clients adopt connected devices more quickly than before.