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Pierre Chollet for Serverless By Theodo

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sls-mentor: your serverless quality teacher has arrived!

This article is part of a series about sls-mentor, the new open-source tool allowing you to audit your AWS serverless infrastructure.

TL;DR

sls-mentor is an open-source tool allowing you to analyze your AWS Serverless application using the simple command npx sls-mentor. It rates your architecture on the 5 following axes:

🌳 Green IT 🌳 - 🛡 Security 🛡 - 🚀 Speed 🚀 - 💰 IT Costs 💰- 💪 Stability 💪

To do so, sls-mentor assesses your architecture against a set of rules and gives you tips to improve it!

Find sls-mentor on Github ⭐️

The birth of a best-practices encyclopedia

I have been working for Kumo as a fullstack software engineer these last nine months. During this period, I discovered a technology that changed my perception of web development: AWS serverless. Serverless is great but AWS offers so many services, resources and possible configurations that it may sometimes be hard to find best practices.

At Kumo, French developers like me have been using AWS serverless technologies to build applications for the last two years. We decided to create a new open source tool allowing us to organize and share every best practice we discovered during our coding journey. And this is how sls-mentor was born 🐣!

sls-mentor is inspired by a sls-dev-tools feature called Guardian (developed by our friends at Aleios), but our goal is to push the experience much further: we want everyone to be able to know, with a simple command, what can be improved on their app!

Framework agnostic quality checks

To achieve our goal, we decided not to reinvent the wheel: sls-mentor basically works like a big cloud linter, scanning your serverless resources configuration and assessing them against a set of rules. But it is also much more than that!

  • ✅ Instead of parsing some complicated terraform or cloudformation template, we analyze your resources directly from the cloud: we are framework-agnostic.
  • ✅ The set of rules is opinionated, but we bring with each rule the rational behind it, as well as a simple guide to comply with it: we want to share our learnings.
  • ✅ Some frameworks generate resources with hard-to-modify configuration, other pieces of your app have reasons not to comply with every rule: we made it easy to acknowledge warnings while tackling the actual issues.

Enough about features, what about a quick demo instead?

Getting started with sls-mentor

Using sls-mentor is really easy. Just run this command in your terminal:

npx sls-mentor
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It will analyze the resources associated with your default AWS profile. If you want to scan another profile, add the -p <profile> option. If there is no specified region in your credentials config, add the -r <region> option.

Running sls-mentor on an example app

For the purpose of this article, I developed a small service allowing users to write, get and list blog articles. It is composed of three Lambda functions, one S3 bucket and one ApiGateway HttpApi.

Here is a quick architecture schema of the service I built:

Architecture schema

You can find the code behind it here on github. The underlying framework is a Typescript combination of Serverless Framework and CDK. I used the library swarmion to bootstrap the project and have a nice repository ready for deployment, check them out! Anyway, the code and deployment method are not very important here, as sls-mentor is framework agnostic.

Let's run a first analysis! I simply run the command in my terminal:

npx sls-mentor -c sls-mentor-release-core-dev
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Here, the -c parameter allows me to specify the name of one or many cloudformation stacks, in order to target the analysis on my new service. Filtering can also be achieved using tags, using the -t option

sls-mentor level choice

I am instantly prompted with the choice of a level. Levels allow users to fix issues step-by-step, enabling more and more rules as they increase. Let's start easy with level 1.

Passing sls-mentor level 1

The first level of sls-mentor features only four rules, that we consider have high impact on your application while being fairly easy to comply with.

sls-mentor results

This is bad, isn't it? No worries! Level 1 rules can easily be fixed, let's take a look at what went wrong.

  • Rule "No Mono Package" passed for my three Lambda functions: this rule ensures that functions are bundled individually, which was already the case for me (thanks to the Serverless Framework)
  • Rule "Use ARM Architecture" didn't pass for any of my Lambda functions. This rule enforces the use of ARM64 processors instead of x86 ones, as they are faster, cheaper and consume less energy. I will fix this soon!
  • Rule "Server-side encryption enabled" passed for one of my two buckets. It was OK for my serverlessdeployment bucket, but KO for my blog-articles bucket. It is important to enable this rule on buckets to ensure your data's safety.
  • 😴 Rule "use SecurityHeadersPolicy" was skipped as there is no CloudFront distribution in my app yet.

Let's fix my Lambda functions! As I can read it in the documentation specified under every failing resource, I need to switch the processor of my Lambda functions from x86_64 to arm64.

In my case, with the Serverless Framework, it's as easy as changing the value of provider.architecture in the serverless.ts file!

// serverless.ts file (~ serverless.yml)

const serverlessConfiguration = {
  service: 'sls-mentor-release-core',
  // ...
  provider: {
    architecture: 'arm64', // switch to arm64
    // ...
  },
  // ...
};

module.exports = serverlessConfiguration;
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Last task left: fix my blog-articles bucket. I need to enable server-side encryption on my blog-articles bucket. Using the AWS CDK, I must add an encryption method in the CDK definition of the bucket. I chose simple S3_MANAGED encryption to start.

// Using the CDK

const exampleBucket = new Bucket(this, 'BlogArticles', {
  bucketName: 'sls-mentor-blog-articles',
  encryption: BucketEncryption.S3_MANAGED, // Enable encryption
});
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Let's rerun level 1 run of sls-mentor... Everything is green! See, it was not too hard.

sls-mentor results

Level 1 is complete, there are 4 other levels to conquer! To end this article, I will have a quick look at level 2, where I will teach you some advanced sls-mentor tricks...

A look at level 2 + advanced sls-mentor configuration

Let's take a look at the level 2 results:

sls-mentor results

It's not that bad! Level 2 includes level 1 rules so half of the work was already done, plus some rules like "Lambda - Under max memory" are already passing everywhere.

Here, I want to focus on the rule "S3 - Use intelligent tiering". This rule enforces the usage of intelligent tiering in my buckets. It allows infrequently accessed objects to be stored in lower tiers, thus reducing their carbon footprint and cost.

On my application, I use CDK to deploy my bucket, so I will need to add a new lifecycle rule to my bucket definition, transitioning items to IntelligentTiering on their first day.

// Using the CDK

const exampleBucket = new Bucket(this, 'BlogArticles', {
  bucketName: 'sls-mentor-blog-articles',
  encryption: BucketEncryption.S3_MANAGED,
  lifecycleRules: [
    // add a lifecycle rule
    {
      id: 'auto-intelligent-tiering',
      enabled: true,
      transitions: [
        {
          // New objects transition to intelligent tiering on day 0
          storageClass: StorageClass.INTELLIGENT_TIERING,
          transitionAfter: Duration.days(0),
        },
      ],
    },
  ],
});
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But there's a catch, on the dashboard, sls-mentor tells me that 2 buckets failed the check! In fact, the second one is my serverlessdeployment bucket, used during deployment by the Serverless framework. I do not have access to its configuration in my code.

We anticipated this issue: using a simple sls-mentor.json configuration file, I can define resource ARNs that won't be checked. ARNs is the unique identifier of each AWS resource, you can find it in the sls-mentor detailed results or in the AWS console.

In the case of my serverless deployment bucket, I just need to write the following lines in the file:

{
  "rules": {
    "useIntelligentTiering": {
      "ignoredResources": ["^.*serverlessdeployment.*$"]
    }
  }
}
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The ignoredResources fied is an array of regex, so ^.*serverlessdeployment.*$ is enough to avoid checking all resources with ARN containing serverlessdeployment.

sls-mentor results

Everything is alright now! sls-mentor only checked one bucket (my blog-articles bucket), and it passed the check.

Always remember that you should never blindly apply a rule. We are aware that some resources have specific requirements, that sometimes contradict our rules. That's the aim of the configuration file feature (but please use it wisely and do not ignore 100% of your resources 🙏).

Now it's your job to continue the process

I almost completed level 2, but I will stop my journey here. Frustrating, isn't it? Now that you are a sls-mentor professional, it should be easy for you to activate SSL on the blog-articles bucket and finish the job 😉.

There are also levels 3, 4 and 5. Fixing issues in these levels becomes gradually more challenging, but there's nothing impossible! We also plan on adding new rules to sls-mentor, and create new levels of difficulty.

Finally, we encourage you to run periodic checks of sls-mentor in your CI. Use the -l <level> option to target a level and skip the prompt. You can find some CI jobs examples on our website and our repository!

The future of sls-mentor

sls-mentor is currently maintained, we would be glad to receive your contributions! Feel free to create issues or pull requests to implement new rules or improve existing ones.

🎯 We are working on our documentation (the website is still WIP), to make it easier to understand the tool and to share our knowledge.

🎯 We plan on working on integrations like slack bots, to be notified of sls-mentor results.

🎯 And the most important: we want to feature more and more rules, supporting more and more AWS services! (we need you 🫵 !)

Additional content

With the team, we already produced some articles featuring sls-mentor rules or possibilities. Feel free to check them out!

A big thanks to everyone I have been working with developing sls-mentor: Adèle, Juliette, Valentin, Quentin, Vincent, Eloi, Zineb and Alexandre!

Top comments (6)

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mdrijwan profile image
Md Rijwan Razzaq Matin

This is nice. How about the scenarios where we create the AWS resources like S3 via CF template?

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pchol22 profile image
Pierre Chollet

Thanks for the feedback!

sls-mentor is framework agnostic, you can start an analysis no matter how you deployed your S3 Bucket.

In the article I show an example with CDK but it should work the same with a CF template.

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mdrijwan profile image
Md Rijwan Razzaq Matin

That’s great then. I’ll give it a try and see!

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fanycastro profile image
Estefania Castro Vizoso

It works fine the first time I tried it. After that I’ve changed the architecture to arm64, and I run sls-mentor again, however I’m still getting the alert about architecture, any idea why? The change was applied as I’ve checked it in the lambda itself

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pchol22 profile image
Pierre Chollet

Hi, I see 2 possible explanations to your issue :

  • Did you deploy your changes ? (if you are working from an IDE) sls-mentor is based on the online state of your app
  • Otherwise, maybe you only fixed 1 Lambda function ? The score should increase but if other Lambdas aren't ARM64, then the alert will still show up
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fanycastro profile image
Estefania Castro Vizoso

It works fine the first time I tried it. After that I’ve changed the architecture to arm64, and I run sls-mentor again, however I’m still getting the alert about architecture, any idea why?