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Cloud computing has generated different services that avoid professionals and companies having to make large investments in software and hardware. For example, you can host and run software from the cloud (SaaS), use an online platform (PaaS), or rent an infrastructure to host the software (IaaS). However, in recent years the concept of “microservice” has been advancing, a model that suggests creating and executing functions separately (FaaS) rather than maintaining a monolithic system. Thus, functions as a service (FaaS) are supported and enhanced by the serverless technology, which means power, accessibility and minimal costs.
What is Amazon Lambda and how does it relate to serverless technology?First, talking about Lambda is talking about the service serverless computing offered by Amazon, one of the most important companies in the cloud computing market. AWS Lambda is a service that allows you to run code or function without having to invest in or manage servers. In other words, you don't have to worry about technical issues, since Amazon (the service provider, in this case) takes care of ensuring that everything works as it should, maintaining their equipment, managing updates, etc. Thus, Lambda executes your code only when needed and allows you to scale automatically, being able to attend from one request per day to thousands per second depending on your needs. The technology AWS serverless It stands out because you don't need to invest in servers, it works on demand and you only pay for what you consume. Specifically, charges apply for every 100 ms of code execution and for the number of times it is activated.
Amazon Lambda Solutions for BusinessNow, Lambda allows you to run any function you need from the cloud. Here you will see some of its basic applications and a couple of real use cases.
Data processingYou can use AWS Serverless technology to run code in response to a trigger, be it user action or changes to the company database. For example, it is possible to use Lamda to:
- Process files when uploading them to the server.
- Process streaming data in real time for tracking.
- Pre-process data for machine learning.