1603701565
HashiCorp has recently announced the public preview of the HashiCorp Vault AWS Lambda Extension. The new service is based on the recently launched AWS Lambda Extensions API and allows a serverless application to securely retrieve secrets from HashiCorp Vault without making the Lambda functions Vault-aware.
The extension reads secrets from HashiCorp Vault and writes them to disk before the AWS Lambda function starts. It authenticates using AWS IAM, relying on the same identity the Lambda function is running. As the Runtime API and the Extensions API are independent endpoints, the new approach makes the external security approach transparent to the Lambda function itself.
Source: https://aws.amazon.com/blogs/compute/introducing-aws-lambda-extensions-in-preview
The Vault AWS Lambda Extension can retrieve different secrets from Vault and writes the JSON response from HashiCorp Vault to the configured destination. It is available in the HashiCorp GitHub repo, that includes examples with the Amazon ARN to be referenced in the Lambda function.
“This is going to make a lot of folks’ lives a lot easier” predicts Lucy Davinhart, senior automation engineer at Sky Betting & Gaming. Andrey Devyatkin, DevSecOps consultant, explains the main benefit of the new approach:
This is neat. Before you would have to read secrets via Terraform and pass them via environment variables which didn’t work well with dynamic secrets. I wonder if extension will be able to keep leases renewed.
#serverless #cloud #aws #developer
1616680920
The digitalization drive has become the dominating trend, with computer technologies penetrating all spheres of social and personal life in the modern world. Alongside ushering innumerable benefits, the ubiquitous advent of IT devices has brought serious concerns in its wake. One of the most pressing questions that worries both individuals and organizations is, “How secure is my virtual data?”
Public anxiety is continuously fed by reports of security breaches and data leakages that cost companies a pretty penny. Their financial losses manifest an ever-growing pattern, with businesses having to spend (or waste?) millions of dollars to redress gruesome consequences. For example, Desjardines Group lost over $50 million to cover for the data leakage of their clientele, and Norsk Hydro had to fork out $75 million to eliminate the effects of a cyberattack. Such exorbitant losses are rare, but IBM experts believe that on average, corporate victims of cybercrime have to foot a bill equal to $4 million. Because of such appalling statistics, establishing cybersecurity of their IT environment is prioritized by many organizations. Even the malicious onslaught of the global pandemic didn’t relegate security considerations to a secondary place, with companies reluctant to cut down on the security strategy enforcement expenditures.
#security #aws #serverless #cloud security #aws security
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Serverless M (or Serverless Modular) is a plugin for the serverless framework. This plugins helps you in managing multiple serverless projects with a single serverless.yml file. This plugin gives you a super charged CLI options that you can use to create new features, build them in a single file and deploy them all in parallel
Currently this plugin is tested for the below stack only
Make sure you have the serverless CLI installed
# Install serverless globally
$ npm install serverless -g
To start the serverless modular project locally you can either start with es5 or es6 templates or add it as a plugin
# Step 1. Download the template
$ sls create --template-url https://github.com/aa2kb/serverless-modular/tree/master/template/modular-es6 --path myModularService
# Step 2. Change directory
$ cd myModularService
# Step 3. Create a package.json file
$ npm init
# Step 3. Install dependencies
$ npm i serverless-modular serverless-webpack webpack --save-dev
# Step 1. Download the template
$ sls create --template-url https://github.com/aa2kb/serverless-modular/tree/master/template/modular-es5 --path myModularService
# Step 2. Change directory
$ cd myModularService
# Step 3. Create a package.json file
$ npm init
# Step 3. Install dependencies
$ npm i serverless-modular --save-dev
If you dont want to use the templates above you can just add in your existing project
plugins:
- serverless-modular
Now you are all done to start building your serverless modular functions
The serverless CLI can be accessed by
# Serverless Modular CLI
$ serverless modular
# shorthand
$ sls m
Serverless Modular CLI is based on 4 main commands
sls m init
sls m feature
sls m function
sls m build
sls m deploy
sls m init
The serverless init command helps in creating a basic .gitignore
that is useful for serverless modular.
The basic .gitignore
for serverless modular looks like this
#node_modules
node_modules
#sm main functions
sm.functions.yml
#serverless file generated by build
src/**/serverless.yml
#main serverless directories generated for sls deploy
.serverless
#feature serverless directories generated sls deploy
src/**/.serverless
#serverless logs file generated for main sls deploy
.sm.log
#serverless logs file generated for feature sls deploy
src/**/.sm.log
#Webpack config copied in each feature
src/**/webpack.config.js
The feature command helps in building new features for your project
This command comes with three options
--name: Specify the name you want for your feature
--remove: set value to true if you want to remove the feature
--basePath: Specify the basepath you want for your feature, this base path should be unique for all features. helps in running offline with offline plugin and for API Gateway
options | shortcut | required | values | default value |
---|---|---|---|---|
--name | -n | ✅ | string | N/A |
--remove | -r | ❎ | true, false | false |
--basePath | -p | ❎ | string | same as name |
Creating a basic feature
# Creating a jedi feature
$ sls m feature -n jedi
Creating a feature with different base path
# A feature with different base path
$ sls m feature -n jedi -p tatooine
Deleting a feature
# Anakin is going to delete the jedi feature
$ sls m feature -n jedi -r true
The function command helps in adding new function to a feature
This command comes with four options
--name: Specify the name you want for your function
--feature: Specify the name of the existing feature
--path: Specify the path for HTTP endpoint helps in running offline with offline plugin and for API Gateway
--method: Specify the path for HTTP method helps in running offline with offline plugin and for API Gateway
options | shortcut | required | values | default value |
---|---|---|---|---|
--name | -n | ✅ | string | N/A |
--feature | -f | ✅ | string | N/A |
--path | -p | ❎ | string | same as name |
--method | -m | ❎ | string | 'GET' |
Creating a basic function
# Creating a cloak function for jedi feature
$ sls m function -n cloak -f jedi
Creating a basic function with different path and method
# Creating a cloak function for jedi feature with custom path and HTTP method
$ sls m function -n cloak -f jedi -p powers -m POST
The build command helps in building the project for local or global scope
This command comes with four options
--scope: Specify the scope of the build, use this with "--feature" tag
--feature: Specify the name of the existing feature you want to build
options | shortcut | required | values | default value |
---|---|---|---|---|
--scope | -s | ❎ | string | local |
--feature | -f | ❎ | string | N/A |
Saving build Config in serverless.yml
You can also save config in serverless.yml file
custom:
smConfig:
build:
scope: local
all feature build (local scope)
# Building all local features
$ sls m build
Single feature build (local scope)
# Building a single feature
$ sls m build -f jedi -s local
All features build global scope
# Building all features with global scope
$ sls m build -s global
The deploy command helps in deploying serverless projects to AWS (it uses sls deploy
command)
This command comes with four options
--sm-parallel: Specify if you want to deploy parallel (will only run in parallel when doing multiple deployments)
--sm-scope: Specify if you want to deploy local features or global
--sm-features: Specify the local features you want to deploy (comma separated if multiple)
options | shortcut | required | values | default value |
---|---|---|---|---|
--sm-parallel | ❎ | ❎ | true, false | true |
--sm-scope | ❎ | ❎ | local, global | local |
--sm-features | ❎ | ❎ | string | N/A |
--sm-ignore-build | ❎ | ❎ | string | false |
Saving deploy Config in serverless.yml
You can also save config in serverless.yml file
custom:
smConfig:
deploy:
scope: local
parallel: true
ignoreBuild: true
Deploy all features locally
# deploy all local features
$ sls m deploy
Deploy all features globally
# deploy all global features
$ sls m deploy --sm-scope global
Deploy single feature
# deploy all global features
$ sls m deploy --sm-features jedi
Deploy Multiple features
# deploy all global features
$ sls m deploy --sm-features jedi,sith,dark_side
Deploy Multiple features in sequence
# deploy all global features
$ sls m deploy --sm-features jedi,sith,dark_side --sm-parallel false
Author: aa2kb
Source Code: https://github.com/aa2kb/serverless-modular
License: MIT license
1602964260
Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.
According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.
(State of Kubernetes and Container Security, 2020)
And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.
(State of Kubernetes and Container Security, 2020)
#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml
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
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