The course is part of this learning path
In this Getting Started with Serverless Computing learning path, we have:
- Learned About Serverless Computing
- Outlined what serverless computing is and how it works
- Reviewed the building blocks of serverless computing
- Outlined common use cases for how people use serverless functions
- Created a RESTful API Using Amazon API Gateway
- Defined a model for the API
- Defined resources for the model
- Added a method for clients to access the resources
- Created our first Serverless Function Using AWS Lambda
- Implemented a serverless function with AWS Lambda
- Connected our Lambda function to our API Gateway
- Explored Using Serverless Functions
- Read values from a Lambda function using an API Gateway endpoint
- Monitored an S3 bucket and triggered a file conversion with a Lambda function
- Used AWS Lambda functions in a restaurant ordering application
- Monitored and debug Lambda functions using AWS CloudWatch
Okay, so that brings us to the end of this Getting Started with Serverless learning path. Let's just go through some of the things that we've covered. So we started off learning about serverless computing. We learned about what serverless computing is and how it works. We reviewed the building blocks of serverless computing, and then we outlined the common use cases for how people are using serverless functions today. Then, we got practical, and we created our first RESTful API using the Amazon API Gateway. We defined a model for the API, and we defined the other resources for that model, and we added a method for clients to access the resources within our API. Then we created our first serverless function using AWS Lambda, and we implemented a serverless function with the AWS Lambda tool, starting from scratch, we built it up. First of all, we presented our AWS Lambda with a series of mock data records, which are provided by the API tool itself, and then we connected our Lambda function to our existing API Gateway. Next, we explored some of the serverless functions and how they can be used in the programming world. We read values from a Lambda function using the API Gateway endpoint. We monitored an S3 bucket and triggered a file conversion with a Lambda function, and converted a .png file to a .zip archive in a new zip archive folder, and we used AWS Lambda functions in our hypothetical restaurant ordering application where we used Lambda functions to first of all strip information from an S3 bucket and post it into DynamoDB. We had our web application take information from the DynamoDB stream and publish it to our ElastiCache cache, and then we had a second function which took our completed order and posted that as done to our hypothetical driver so they could deliver our restaurant order. And then we looked at how we could monitor and debug Lambda functions using AWS CloudWatch and some of the logging functions that we have available to us. So, I'm hoping that you've done the labs as we've been through the courses. The labs are a fantastic way for you to get hands-on experience with using these functions. All right, so thank you very much for your attention during this learning path. So, the next question of course is where to from here. So, the next question is where to from here? Now, if you're interested in learning more about coding applications with serverless functions, then I recommend doing our Getting started with Azure functions course, and look out for the Developing Serverless applications with AWS and the Developing Serverless applications with Azure learning paths, which will go to the next level of detail with how to put applications together, and then we're going to put together some courses that show you know, actual step functions for enterprise-grade applications, and starting to implement business logic using step functions and the Azure equivalent, and then we're also running a series of courses on how to support serverless functions at scale, which I think you'll find very interesting. All right! Thanks for your time. If you have any comments or suggestions for us, please contact us at support@cloudacademy.com.
Andrew is fanatical about helping business teams gain the maximum ROI possible from adopting, using, and optimizing Public Cloud Services. Having built 70+ Cloud Academy courses, Andrew has helped over 50,000 students master cloud computing by sharing the skills and experiences he gained during 20+ years leading digital teams in code and consulting. Before joining Cloud Academy, Andrew worked for AWS and for AWS technology partners Ooyala and Adobe.