Course: AWS Lambdas in Python
duration: 6 hours |
Language: English (US) |
access duration: 90 days |
Details
AWS Lambda is a serverless, event-driven compute service, meaning that it allows you to execute code when a specific event occurs, and abstracts the burden of maintaining infrastructure from you, the developer. Lambda functions are extremely powerful, but generally best-suited for lightweight interactive applications. In this course, you’ll explore serverless computing and the benefits of AWS Lambdas. In addition, you’ll discover how to deploy a lambda function based off a Docker container image and upload it to AWS via the ECR. Finally, you’ll learn to create a lambda function that triggers on a notification from an SNS and write out the contents of that notification to a DynamoDB table.
Result
After completing this course, you’ll be able to use serverless computing in Python with AWS Lamba, and you’ll be able to use AWS Lambda with containers, SES, SNS and DynamoDB.
Prerequisites
No formal prerequisites. However, some prior knowledge about the topic is highly recommended.
Target audience
Software Developer, Web Developer
Content
AWS Lambdas in Python
AWS Lambdas in Python: Serverless Compute in Python with AWS Lambda
AWS Lambda is a serverless, event-driven compute service,
- meaning that it allows you to execute code when a specific event
- occurs, and abstracts the burden of maintaining infrastructure from
- you, the developer. Lambda functions are extremely powerful, but
- generally best-suited for lightweight interactive applications.
- Explore serverless computing and the benefits of AWS Lambdas.
- Discover the AWS Lambda dashboard and deploy a lambda function
- using Python runtime. Practice using blueprints and investigate the
- role of AWS Identity and Access Management in the successful
- outcome of a lambda function. Finally, configure a new REST API
- trigger through the API gateway service and expose that REST API
- using the curl utility. When this course is completed, you will
- recognize the roles and policies required for a lambda to run, and
- be able to create, deploy, and test lambda functions.
AWS Lambdas in Python: Using AWS Lambda with Containers, SES, SNS, & DynamoDB
A major benefit of using AWS Lambda is that you can easily
- integrate with other powerful AWS services like the Elastic
- Container Registry (ECR), AWS Simple Email Service (SES), DynamoDB,
- or Simple Notification Service (SNS). Learn how to deploy a lambda
- function based off a Docker container image and upload it to AWS
- via the ECR. Explore adding functionality to your lambda so that it
- can connect to Twitter. Modify your lambda to write out tweets to
- an S3 bucket and send automated emails. Finally, create a lambda
- function that triggers on a notification from an SNS and write out
- the contents of that notification to a DynamoDB table. Upon
- completion of this course, you will be able to easily deploy lambda
- functions as container images and seamlessly integrate AWS Lambda
- with ECR, SES, DynamoDB, and SNS.
Course options
We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.
Optional practice exam (trial exam)
To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam.
Optional practice lab
To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediately. The lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience.
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