Just like A Christmas Carol’s three ghosts, the cloud has three personalities, too—let’s talk about yesterday’s cloud, today’s cloud, and the cloud of the future.

Originally, just the idea of outsourcing your computing to another network was a big deal. That other network’s servers could augment your existing computing resources and enable you to tackle much bigger projects than you could before. This was the very beginning of the cloud. With the Internet in its early days and basic server networks available to help you get a little extra computing help, it had a lot of promise for early software development and operations.

That’s yesterday’s cloud. It had severe limitations, like very limited overall resources. It was about the beginning of SaaS, and data analytics was on the horizon but not quite yet a big If you needed to scale, that might’ve required a discussion with your vendor and some changes onsite at their facilities.

At the end of the day, you were running virtual machines, but you still had to worry about the machines—not their hardware, because someone else was doing the maintenance—but you did have to manage your computing resources closely.

Today, there’s another cloud in town. It’s trying to free us from this close management. Cloud 2.0 has often been described in terms of data. Big data, analytics, and information. With fewer data constraints, companies are free to make the most of the data in new ways.

And tomorrow, the cloud’s continued growth will bring us even more possibilities, making data use more practical for a variety of different industry applications.

Serverless is ideal for applications that have a lot of function-driven events, such as events driven by a mouse click. It’s great for systems that rely on user engagement—and require big bursts of computing power at key moments. It would be hard to have an on-premises infrastructure to meet these needs. It also doesn’t make sense to have to recreate resource management processes and micromanage machine use when you’re creating or operating software that works this way.

From a technical standpoint, it offers benefits such as:

• Supports all major server-side languages/frameworks like Node.js, Python, Java, Scala, and Kotlin.
• Software lifecycle management from a single platform i.e. you can build, deploy, update and delete.
• Safety function for smooth deployment and resource manager
• Minimal configuration required
• Functions optimized for CI/CD workflows
• Supports automation, optimization and best practices of enterprise computing
• 100% extensible functions and frameworks

Making the transition to serverless computing doesn’t have to be too difficult. As long as you start with a viable plan and a willingness to adapt, you shouldn’t have too much trouble.

Here are a few steps to get you started. You’ll be setting up an account with a provider and testing it with your own function. From there, you can quickly start tailoring the service to your needs.

Adapt this test process to your own applications and business needs, but choose something simple so you can play around with your new account:

1. Begin with an application or an idea.
2. Create an account with a serverless computing provider, such as AWS Lambda, Google Cloud, or Microsoft Azure.
3. Prepare to test your new account. To do so, you’ll want to create two buckets. For one of the buckets, you’ll upload photos or another file type you’ll be transforming. The other will receive these files once you’re done.
4. In your management console, you’ll now create a new function using the two buckets you just set up. Specify how the buckets will be used.
5. Name your function and set it aside for later.
6. Create a directory and set up your workspace on your local machine.
7. Write a Javascript file or other code to use files in your new account(Here’s an example using AWS)
8. Upload.
9. Test your function.

Once you’ve tested the process, you can start looking at how existing code (and new, from-scratch code, too) can leverage serverless computing capabilities.