1597204800
Automating AWS Lambda deployment with Bitbucket Pipelines
In this article, we are talking about AWS lambda functions deployment with Bitbucket Pipelines.
What Is AWS Lambda?
AWS Lambda is a service provided by Amazon. More simply, you have to store your function on to cloud and trigger stored function with events like API calls, database modifications and many more, etc.
The Lambda functions can perform any kind of computing task, from serving web pages and processing streams of data to calling APIs and integrating with other AWS services.
Behind the scene, Amazon manages running servers handling function execution and needed resources to complete function execution.
The Lambda functions can perform any kind of computing task, from serving web pages and processing streams of data to calling APIs and integrating with other AWS services.
Let’s Move on our Demo
Step 1: Create a test function
Create New bitbucket repository
PrashantBhatasana/lambdaFunction
Step 2: Configure AWS credentials
Create an AWS IAM new user with the **AWSLambdaFullAccess **permission.
Create an IAM user.
Attach AWSLambdaFullAccess
Create Acces Key
Download created Access key and secret key
Now Goto bitbucket repository > Settings > Repository variables.
Add the following variables:
AWS_ACCESS_KEY_ID: For AWS access key.
AWS_SECRET_KEY_ID: For AWS secret key.
Step 3: Create our Pipelines file
The bitbucket-pipelines.yml file has 2 sections to it, steps to :
- build and .zip up the Lambda codeAn IAM user with sufficient permissions and access to update the Lambda function
- push the updated code to AWS
In the example below replace the FUNCTION_NAME variable with the name of your function.
Step 4: Executing our deployment
Once we commit anything to bitbucket repository it will trigger our deployment pipeline.
Goto Pipelines section: it will display a new pipeline with In Progress status.
Now you click on that new pipeline it will display your pipeline steps and logs like the above screenshot.
🎊 🎉🤖🎊 🎉 If all goes well, Our lambda function deployed successfully.
Thank you for reading, if you have anything to add please send a response or add a note!
AppGambit
AWS Consulting Partner | Web and Mobile Development Co Based in India
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#lambda #automation #aws #bitbucket #automation-testing
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1597204800
Automating AWS Lambda deployment with Bitbucket Pipelines
In this article, we are talking about AWS lambda functions deployment with Bitbucket Pipelines.
What Is AWS Lambda?
AWS Lambda is a service provided by Amazon. More simply, you have to store your function on to cloud and trigger stored function with events like API calls, database modifications and many more, etc.
The Lambda functions can perform any kind of computing task, from serving web pages and processing streams of data to calling APIs and integrating with other AWS services.
Behind the scene, Amazon manages running servers handling function execution and needed resources to complete function execution.
The Lambda functions can perform any kind of computing task, from serving web pages and processing streams of data to calling APIs and integrating with other AWS services.
Let’s Move on our Demo
Step 1: Create a test function
Create New bitbucket repository
PrashantBhatasana/lambdaFunction
Step 2: Configure AWS credentials
Create an AWS IAM new user with the **AWSLambdaFullAccess **permission.
Create an IAM user.
Attach AWSLambdaFullAccess
Create Acces Key
Download created Access key and secret key
Now Goto bitbucket repository > Settings > Repository variables.
Add the following variables:
AWS_ACCESS_KEY_ID: For AWS access key.
AWS_SECRET_KEY_ID: For AWS secret key.
Step 3: Create our Pipelines file
The bitbucket-pipelines.yml file has 2 sections to it, steps to :
- build and .zip up the Lambda codeAn IAM user with sufficient permissions and access to update the Lambda function
- push the updated code to AWS
In the example below replace the FUNCTION_NAME variable with the name of your function.
Step 4: Executing our deployment
Once we commit anything to bitbucket repository it will trigger our deployment pipeline.
Goto Pipelines section: it will display a new pipeline with In Progress status.
Now you click on that new pipeline it will display your pipeline steps and logs like the above screenshot.
🎊 🎉🤖🎊 🎉 If all goes well, Our lambda function deployed successfully.
Thank you for reading, if you have anything to add please send a response or add a note!
AppGambit
AWS Consulting Partner | Web and Mobile Development Co Based in India
Follow
#lambda #automation #aws #bitbucket #automation-testing
1627088460
Automated Unit Testing in DevOps Pipeline - AWS Lambda using AWS CodeBuild
Learn to automated unit testing in AWS DevOps Pipeline using AWS CodeBuild, including demo in python.
#aws #lambda #aws lambda #pipeline
1621154520
Cross-account access to invoke AWS lambda using AWS CDK
If you are here, you may have a pretty good knowledge of how to use AWS CDK for defining cloud infrastructure in code and provisioning it through AWS. So let’s get started on how to grant permission to your lambda function to access the resources in another AWS account.
Let’s say you have two accounts called Account A and Account B, and you need to give permission to lambda function in Account A (ex: 11111111)to access the resources in Account B(22222222). You can easily do this by assuming an IAM Role in Account B and then uses the returned credentials to invoke AWS resources in Account B.
#acces #account #aws #lambda #aws lambda #aws cdk
1593443976
Automate deployment using AWS CodeDeploy
Reading Time: 6 minutes In the CodeDeploy blog series, we are going to write two blogs the first blog covers the CodeDeploy theory-based and In the second blog, we will cover the full end-to-end automation practical of the application deployment using CodeDeploy and Jenkins. Let’s start aws CodeDeploy is basically a deployment service through which we can easily automate your deployment.
#aws #aws services #devops #deployment #codedeploy #automate
1595837400
Automate Deployment to CloudHub using CloudHub Deployer Plugin Jenkins
Introduction
We live in an age, Where DevOps and automation are becoming more and more necessary and important in projects. So uploading packages manually to servers or platforms is not feasible and salable when you work with architecture like micro-services. So to tackle this problem we need to implement Continuous Delivery and Deployment cycle in our project. In this post I will be showing you how to do exactly that with Mule applications.
After creating a basic Mule App, you might be wondering how to automate the process of deploying a Mule App to CloudHub. In this post, I will be introducing a Jenkins plugin(Github Repository) that I published recently that enables this use case.
How it is compared to other solution/tools available with Jenkins:
Mule-Maven plugin - With this approach you are tight coupling you build and deploy process and most of time its not good. And its hard to scale this approach when you have multi environment deployment and many applications to manage. This approach will not work if you just want to do deployment.
This approach will take time and effort to get working automation that meets your project requirement. The CloudHub Deployer plugin itself is built using same API why re-invent the wheel.
What we will accomplish here:
Jenkins release pipeline using both free style and pipeline script that automates your mule application deployment to CloudHub.
Prerequisites:
- You will need to have Jenkins instance up and running.
- A CloudHub account.
- You need to have a already built package to follow along. Since I am not covering CI(Continuous Integration) for mule apps, there are plenty article on internet for that.
#integration #deployment #jenkins #mulesoft #mule #deployment automation #cloudhub #jenkins pipeline #jenkins automation