1563522639
The Serverless Framework helps you develop and deploy your AWS Lambda functions, along with the AWS infrastructure resources they require. It’s a CLI that offers structure, automation and best practices out-of-the-box, allowing you to focus on building sophisticated, event-driven, serverless architectures, comprised of Functions and Events.
The Serverless Framework is different from other application frameworks because:
Here are the Framework’s main concepts and how they pertain to AWS and Lambda…
A Function is an AWS Lambda function. It’s an independent unit of deployment, like a microservice. It’s merely code, deployed in the cloud, that is most often written to perform a single job such as:
You can perform multiple jobs in your code, but we don’t recommend doing that without good reason. Separation of concerns is best and the Framework is designed to help you easily develop and deploy Functions, as well as manage lots of them.
Anything that triggers an AWS Lambda Function to execute is regarded by the Framework as an Event. Events are infrastructure events on AWS such as:
When you define an event for your AWS Lambda functions in the Serverless Framework, the Framework will automatically create any infrastructure necessary for that event (e.g., an API Gateway endpoint) and configure your AWS Lambda Functions to listen to it.
Resources are AWS infrastructure components which your Functions use such as:
The Serverless Framework not only deploys your Functions and the Events that trigger them, but it also deploys the AWS infrastructure components your Functions depend upon.
A Service is the Framework’s unit of organization. You can think of it as a project file, though you can have multiple services for a single application. It’s where you define your Functions, the Events that trigger them, and the Resources your Functions use, all in one file entitled serverless.yml
(or serverless.json
or serverless.js
). It looks like this:
# serverless.yml
service: users
functions: # Your "Functions"
usersCreate:
events: # The "Events" that trigger this function
- http: post users/create
usersDelete:
events:
- http: delete users/delete
resources: # The "Resources" your "Functions" use. Raw AWS CloudFormation goes in here.
When you deploy with the Framework by running serverless deploy
, everything in serverless.yml
is deployed at once.
You can overwrite or extend the functionality of the Framework using Plugins. Every serverless.yml
can contain a plugins:
property, which features multiple plugins.
# serverless.yml
plugins:
- serverless-offline
- serverless-secrets
Thanks for reading ❤
If you liked this post, share it with all of your programming buddies!
Follow us on Facebook | Twitter
#aws #microservices #web-service #serverless
1617016800
In this post, I will show you how to use Amazon S3 Object Lambda to resize images on the fly. The Serverless Framework will be used to define the Infrastructure as Code and to simplify the deployment. Sharp will be used to resize the images. Lambda will be written using the Node.js 14x Lambda runtime
One of the most common Lambda patterns is to transform data stored inside Amazon S3. Generally, a lambda function is invoked after a file has been uploaded. Lambda would retrieve that file, apply any needed transformation (e.g. converting type of file) and store the result in S3.
That pattern was working well, however, it would require some work done onto a file despite that being accessed in the future or not.
If you needed to convert a file on the fly you should have created a Lambda function, invoke it via Amazon API GW and wait for the lambda to perform the transformation.
AWS has recently introduced Amazon S3 Object Lambda in a good post by Danilo Poccia. S3 Object Lambda allows creating a Lambda directly connected to the S3 bucket (using S3 Access Points) that is automatically invoked when retrieving the object from S3!
That means that our application needs only to send an S3 Get Object request to retrieve the original or transformed data
Also, a very important peculiarity of using Amazon S3 Object Lambda it’s that the file you want to retrieve doesn’t need to exist on S3! We will make use of this for our scenario
_Note: High-level AWS CLI S3 commands (e.g.
_aws s3 cp_
) don’t currently support S3 Object Lambda, instead we need to use low-level S3 API commands (e.g. __aws s3api get-object)_
In his post, Danilo highlighted the most common use cases for Amazon S3 Object Lambda:
#aws-lambda #serverless #aws-s3 #aws
1617875400
2020 was a difficult year for all of us, and it was no different for engineering teams. Many software releases were postponed, and the industry slowed its development speed quite a bit.
But at least at AWS, some teams released updates out of the door at the end of the year. AWS Lambda received two significant improvements:
With these two new features and Lambda Layers, we now have three ways to add code to Lambda that isn’t directly part of our Lambda function.
The question is now: when should we use what?
In this article, I try to shine some light on the Lambda Layers, Lambda Extensions, and Docker image for Lambda.
First things first. All these Lambda features can be used together. So if you think about where to put your code, at least your decisions aren’t mutually exclusive. You can upload a Docker image and attach a regular Lambda Layer and a Lambda Extension. The same is possible if your Lambda function is based on a ZIP archive.
What does this all mean? Keep reading and find out.
#aws #aws-lambda #serverless #devops #docker #lambda
1625253720
In this Serverless Saturday video, we’ll be going over how to create your first AWS Lambda function!
In the next video, we’ll be covering how to set up CI/CD with your AWS Lambda function so stay tuned and make sure to subscribe!
To get started, log-in to your AWS account here: https://aws.amazon.com/console/
Found this video helpful? Feel free to support this channel here: https://ko-fi.com/jacksonyuan
#node.js #node #lambda #aws #aws lambda #serverless
1598408880
The Basics
AWS KMS is a Key Management Service that let you create Cryptographic keys that you can use to encrypt and decrypt data and also other keys. You can read more about it here.
Important points about Keys
Please note that the customer master keys(CMK) generated can only be used to encrypt small amount of data like passwords, RSA key. You can use AWS KMS CMKs to generate, encrypt, and decrypt data keys. However, AWS KMS does not store, manage, or track your data keys, or perform cryptographic operations with data keys.
You must use and manage data keys outside of AWS KMS. KMS API uses AWS KMS CMK in the encryption operations and they cannot accept more than 4 KB (4096 bytes) of data. To encrypt application data, use the server-side encryption features of an AWS service, or a client-side encryption library, such as the AWS Encryption SDK or the Amazon S3 encryption client.
Scenario
We want to create signup and login forms for a website.
Passwords should be encrypted and stored in DynamoDB database.
What do we need?
Lets Implement it as Serverless Application Model (SAM)!
Lets first create the Key that we will use to encrypt and decrypt password.
KmsKey:
Type: AWS::KMS::Key
Properties:
Description: CMK for encrypting and decrypting
KeyPolicy:
Version: '2012-10-17'
Id: key-default-1
Statement:
- Sid: Enable IAM User Permissions
Effect: Allow
Principal:
AWS: !Sub arn:aws:iam::${AWS::AccountId}:root
Action: kms:*
Resource: '*'
- Sid: Allow administration of the key
Effect: Allow
Principal:
AWS: !Sub arn:aws:iam::${AWS::AccountId}:user/${KeyAdmin}
Action:
- kms:Create*
- kms:Describe*
- kms:Enable*
- kms:List*
- kms:Put*
- kms:Update*
- kms:Revoke*
- kms:Disable*
- kms:Get*
- kms:Delete*
- kms:ScheduleKeyDeletion
- kms:CancelKeyDeletion
Resource: '*'
- Sid: Allow use of the key
Effect: Allow
Principal:
AWS: !Sub arn:aws:iam::${AWS::AccountId}:user/${KeyUser}
Action:
- kms:DescribeKey
- kms:Encrypt
- kms:Decrypt
- kms:ReEncrypt*
- kms:GenerateDataKey
- kms:GenerateDataKeyWithoutPlaintext
Resource: '*'
The important thing in above snippet is the KeyPolicy. KMS requires a Key Administrator and Key User. As a best practice your Key Administrator and Key User should be 2 separate user in your Organisation. We are allowing all permissions to the root users.
So if your key Administrator leaves the organisation, the root user will be able to delete this key. As you can see **KeyAdmin **can manage the key but not use it and KeyUser can only use the key. ${KeyAdmin} and **${KeyUser} **are parameters in the SAM template.
You would be asked to provide values for these parameters during SAM Deploy.
#aws #serverless #aws-sam #aws-key-management-service #aws-certification #aws-api-gateway #tutorial-for-beginners #aws-blogs
1563522639
The Serverless Framework helps you develop and deploy your AWS Lambda functions, along with the AWS infrastructure resources they require. It’s a CLI that offers structure, automation and best practices out-of-the-box, allowing you to focus on building sophisticated, event-driven, serverless architectures, comprised of Functions and Events.
The Serverless Framework is different from other application frameworks because:
Here are the Framework’s main concepts and how they pertain to AWS and Lambda…
A Function is an AWS Lambda function. It’s an independent unit of deployment, like a microservice. It’s merely code, deployed in the cloud, that is most often written to perform a single job such as:
You can perform multiple jobs in your code, but we don’t recommend doing that without good reason. Separation of concerns is best and the Framework is designed to help you easily develop and deploy Functions, as well as manage lots of them.
Anything that triggers an AWS Lambda Function to execute is regarded by the Framework as an Event. Events are infrastructure events on AWS such as:
When you define an event for your AWS Lambda functions in the Serverless Framework, the Framework will automatically create any infrastructure necessary for that event (e.g., an API Gateway endpoint) and configure your AWS Lambda Functions to listen to it.
Resources are AWS infrastructure components which your Functions use such as:
The Serverless Framework not only deploys your Functions and the Events that trigger them, but it also deploys the AWS infrastructure components your Functions depend upon.
A Service is the Framework’s unit of organization. You can think of it as a project file, though you can have multiple services for a single application. It’s where you define your Functions, the Events that trigger them, and the Resources your Functions use, all in one file entitled serverless.yml
(or serverless.json
or serverless.js
). It looks like this:
# serverless.yml
service: users
functions: # Your "Functions"
usersCreate:
events: # The "Events" that trigger this function
- http: post users/create
usersDelete:
events:
- http: delete users/delete
resources: # The "Resources" your "Functions" use. Raw AWS CloudFormation goes in here.
When you deploy with the Framework by running serverless deploy
, everything in serverless.yml
is deployed at once.
You can overwrite or extend the functionality of the Framework using Plugins. Every serverless.yml
can contain a plugins:
property, which features multiple plugins.
# serverless.yml
plugins:
- serverless-offline
- serverless-secrets
Thanks for reading ❤
If you liked this post, share it with all of your programming buddies!
Follow us on Facebook | Twitter
#aws #microservices #web-service #serverless