AWS Lambda Function

AWS Lambda is a serverless computing solution that executes your applications without the need for servers.

A custom Lambda Runtime can provide support for other languages like COBOL as well as the most common ones found on the market today, including Java, Python, Node.JS, and.NET Core.

You just pay for what you use to run your function on Lambda, which is a big advantage. By eliminating the cost of unused capacity, you’ll be able to publish your app faster. Using Lambda can be intriguing, so let’s have a look at how and when.

Before we talk about Lambda, let’s clarify what serverless is. Many people are already familiar with the word “serverless” because of its association with the idea of running without a server.

You don’t have to worry about the infrastructure of your application with a serverless cloud service approach. As long as the cloud provider manages this server, you may concentrate solely on your business logic.

For example, serverless only charges you for what your application consumes, which is a distinct advantage. It’s possible that you’ll be paid even if your application isn’t running, unlike with a standard EC2.

Examples of AWS services that use the serverless approach include Lambda. S3 for file storage, AWS RDS Aurora and DynamoDB for databases, and SNS and SQS for queues and messaging are just a few of the many services available on AWS.

What Services Does PaaS Include?

Many other cloud computing services fall under PaaS, despite the fact that web apps are the most prevalent use case.

Database as a Service (DBaaS)

IaaS can only be used to run a cloud-hosted database on a virtual machine if you manually install it.

To qualify as a PaaS solution, it must include storage, computational power, and relational database capabilities.

An example of this is the Azure SQL Database service, which provides a fully managed database with automated upgrades, scalability, smart threat protection, and AI-powered search.

Because it falls under PaaS, these cloud services are referred to as DBaaS.

Internet of Things (IoT) Platforms

There are now more PCs and internet-connected devices than ever before. The new HTTP/3 standard will only speed things up a little bit more. Lights, thermostats, microwaves, washing machines, locks, and even truck engines are all part of the ever-growing list of connected gadgets.

Connectivity as a service, or IaaS, covers the basics of getting online, but PaaS covers the more advanced APIs for managing and sharing data across multiple devices and applications.

Mobile Services (APIs)

Email is no longer an acceptable method for organizations to communicate with their customers. Automated SMS messages are being used at a large scale by them.

Automated text messages can be added to programs using SMS APIs.

For example, they can message customers to:

• Remind them of scheduled calls or meetings.
• Promote a new related product or service.
• Inquire about previous customer service encounters.
• Invite clients to participate in a case study or a poll.

Communications Platform as a Service (CPaaS) is a subcategory for these services (CPaaS). It falls under the umbrella of PaaS.

Push Notification APIs

Unlike text messages, these APIs power push notifications in the same way that SMS text messages do.

You can use them to:

• • Remind customers that your application is due for another update.
  • Don’t give up on clients who haven’t logged on in weeks.
  • Promote a relevant, time-limited offer.

Machine Learning

It’s not enough to simply put your data in the cloud if you want to make use of it. The data is still sitting around, but in a different location.

Calculations are needed to sort through your data and identify relevant events and phases.

It’s easy to create models (from formats) with cloud-based machine learning systems, apply them to your data sets, and scale your registration capacity according to the circumstances.

Hadoop, Spark, & Other Data Processing Frameworks

Open source software framework Apache Hadoop is able to cope with large data sets across distributed virtual machine clusters.

Use a prominent PaaS customer’s Hadoop service instead of setting up the system from scratch.

• Dataproc, Google’s massive data processing service, includes Hadoop as standard.
• HDInsight, Microsoft’s data processing solution, includes Hadoop.
• BigInsights from IBM includes Hadoop.
• EMR on AWS includes Hadoop and Spark.

Related Articles