rAWS Lambda Function

AWS Lambda is a computing service that runs your applications in a serverless model, where you can develop without having to worry about servers.

You can use the main languages ​​on the market, such as Java, Python, Node.JS, .NET Core, and Go, and you can expand this list to other languages ​​using a custom Lambda Runtime , even adding support for COBOL !

Also, with Lambda you only pay for what you consume to run your function. You don’t have to pay for idle capacity, and finally you can publish your application more quickly. Let’s understand below how and when to use Lambda can be interesting.

Before we talk about Lambda, let’s clarify what ‘serverless’ means. Many have already heard about this term associating with the thought of running without needing a server.

In fact, serverless is a cloud service model where you don’t have to worry about your application’s infrastructure. This server still exists, however it is fully managed by the cloud provider, allowing you to focus only on your business logic.

A differential of serverless is that you only pay for what your application uses. Unlike a traditional EC2 , you may be charged for idle time on that EC2, at times when your application has no activity.

In addition to Lambda, we have other examples of AWS services that work on the serverless model. Some examples are S3 for file storage, AWS RDS Aurora and DynamoDB for database, and SNS and SQS, services used to manage queues and messaging.

What Services Does PaaS Include?

Although the most common use case of PaaS is web app sending, many other cloud computing services also fall under it.

Database as a Service (DBaaS)

A cloud-hosted database that you manually install on a virtual machine is only an execution of IaaS.

To be considered a PaaS offering, it should be an integrated solution that offers storage, computing power, and relational database capabilities.

An illustration of this is the Azure SQL Database service, which offers a completely managed database with automated updates, scalability, smart threat protection, and AI-powered search.

Cloud service products in this category are also called DBaaS, It is a subcategory of PaaS.

Internet of Things (IoT) Platforms

More items are powered by PCs and connected to the internet than ever before. The new HTTP/3 standard will only speed this up further. Connected devices now include lights, thermostats, ovens, washing machines, locks, and even truck engines.

The bare bones of connectivity to the internet could be considered IaaS, but complex APIs for handling and sharing information across devices and apps fall under PaaS.

Mobile Services (APIs)

Organizations are done agreeing to email while sending notices and showcasing efforts to their clients. They also utilize automated SMS messages at scale.

With SMS APIs, companies can make automated text into their applications.

For example, they can messages customers to:

• Remind them of scheduled calls or meetings.
• Promote a new related product or service.
• Ask for feedback on a recent customer service encounter.
• Recruit customers to join a case study or survey.

These services are sometimes categorized separately as Communications Platform as a Service (CPaaS). It is a PaaS subcategory.

Push Notification APIs

Like SMS text messages, except for browser and mobile push notifications, these APIs power push notifications.

You can use them to:

• • Remind clients to introduce another update for your application.
  • Win back dormant clients who haven’t gotten to your application in weeks.
  • Advertise a relevant limited-time promotion.

Machine Learning

If you genuinely want to take advantage of your data, it’s not enough to just store it in the cloud. The data is still just sitting around, only in another area.

You want to set up calculations to filter through your information and track down significant experiences and noteworthy stages.

With cloud-based machine learning platforms, you can undoubtedly make models (from formats), apply them to your data sets, and scale your registering power depending on the situation.

Hadoop, Spark, & Other Data Processing Frameworks

Apache Hadoop is an open source software framework that makes it possible to deal with big data sets across distributed clusters of virtual machines.

Rather than setting up the environment without preparation, you can use Hadoop as a service from any leading PaaS customer.

• Google offers Hadoop as an integrated part of its Dataproc big data processing service.
• Microsoft offers Hadoop as part of its HDInsight data processing service.
• IBM offers Hadoop as part of BigInsights.
• AWS offers Hadoop and Spark as part of EMR.

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