One of the biggest advantages of opting for software-as-a-service (SaaS) is the easy customization and constant finetuning of features and capabilities to satisfy customer needs. While reducing the total cost of ownership, SaaS also allows customers to add codes specific to their workflows and include rich integrations. This extensibility is crucial for customization and enables prioritization of engineering resources by the SaaS providers.
Another crucial requirement of clients on SaaS platforms is scalability. There may be peaks and troughs in traffic to the application due to expected and unexpected reasons. A seasonal increase in demand, a promotional campaign, sudden trending of a related topic, and so on can see more click-throughs than before. Being able to scale up when the demand peaks and scale down during low-demand periods is another crucial requirement to serve customers cost-effectively.
Extensibility and scalability are an integral part of the business model and therefore requires the SaaS platform to be able to perform under such extraordinary conditions too.
AWS Lambda is one such solution that can help businesses scale based on need, automatically, and allows extensibility.
AWS Lambda Features That Allow Scalability
AWS Lambda, a serverless compute service, helps to manage the compute resources needed to run the code in response to events such as updating the code, changes in the state, and so on. It can also be used for extending other AWS services using custom logic or installing customized backend services requiring scalability, performance, and security. This is made possible by Lambda, which runs the code on computing infrastructure that is highly available. It also manages the administration of the compute resources, such as maintaining the server and the operating system, provisioning capacity and scaling automatically, deploying code and security patches, and monitoring and logging code.
Using Custom Logic to Extend Other AWS Services
As data is ingested and moves through the cloud AWS resources such as Amazon DynamoDB tables and Amazon S3 buckets, the application of custom logic by AWS Lambda enables computing and keeping pace with the incoming requests.
In AWS Lambda, the code is invoked only as per need with automatic scaling to handle the spike in requests without manual intervention and limits. Within a fraction of a second of the event beginning, the code also starts running without compromising performance. Multiple instances of the code can be run due to the code remaining stateless and not needing deployment or configuration.AWS Lambda provides a cost-effective solution for extensibility and scaling as customers pay-per-use.
Provisioned Concurrency is a feature of AWS Lambda that enables it to respond quickly to increased demand by initialing functions and keeping them hyper-ready. This feature can be leveraged to implement interactive services on the web and mobile or to access microservices with latency-sensitivity or synchronous APIs.
Whenever additional workload can be predicted due to an expected increase in traffic, scheduled scaling is also possible. This can be cost-effective by being activated only when required and not at other times. Another option is utilization-based scaling, where provisioned concurrency is increased according to the established utilization metrics. This is useful when demand cannot be predicted.
Customization and Extensibility with AWS Lambda
AWS Lambda’s extensibility and customization capabilities are especially in demand by SaaS customers who have migrated from on-premises solutions. While APIs and integration hooks may address this need, sophisticated customization requires custom code to be integrated with the SaaS workflows for effectiveness.
Therefore, they face challenges such as cost, isolation, and usability. AWS Lambda being serverless, it helps to overcome these challenges by scaling the compute automatically and charging only based on use. It achieves this by abstracting away and simplifying the consumption model. SaaS builders also include controls and features that allow the customization of the execution environments within their own SaaS product. As a result, SaaS owners experience greater flexibility in choosing cost-effective usability and isolation models.
Some of the customers who have successfully enriched their user experience using the extensibility and customization of AWS Lambda for SaaS include Freshworks, Segment Functions, and Netlify Functions.
Read what our AVP of cloud services has to say about the AWS Lambda services: Securing your Serverless Lambda functions
Indium Leveraging AWS Lamba for Scale and Extensibility
Indium Software is a cutting-edge solution provider with a team of AWS specialists who can help businesses migrate/modernize their applications and data on the cloud and
leverage automation to scale. Our team works closely with our customers to understand their needs for scale and extend and develop bespoke solutions to provide cost-effective and scalable solutions. In addition to workload migration and new app development on the cloud, we also help with converting monolithic applications to microservices and leverage containerization and serverless solutions such as AWS Lambda. Be it scheduled scaling or automatic scaling, Indium can tailor the right solution to keep your business agile and responsive, increase customer satisfaction, and break barriers to innovation.