How To

Every now and then I come across a problem that requires me to scour the Internet and piece together information to find a solution. I typically document my solution so that I never have to go searching again. 🤓 If I think the solution is particularly useful, I’ll post a “how to” to save time for others as well.

If I come across useful tips and tricks for software, apps, APIs, or other packages I typically use, I’ll put together a tutorial on the subject. 💡

Here you’ll find a collection of articles about programming techniques, serverless architecture and applications, server management, cloud technologies, and more. I hope these save you some time and help you learn a few new things as well.

Verifying self-signed JSON Web Tokens (JWTs) with AWS HTTP APIs

Posted in How To & Serverless on March 26, 2020
Last Updated: December 20, 2020

“Trust no one.” Or at least that’s what Fox Mulder told me back in the 90s.

With the recent GA of HTTP APIs for API Gateway, I decided to start evaluating my existing API Gateway REST APIs to see if I could migrate them over to take advantage of the decreased latency and reduced cost of the new HTTP APIs. Several of them were disqualified because they utilize service integrations (a feature that AWS is working to add), but for one of my largest applications, the lack of Custom Authorizers is what brought me to a dead end. Or so I initially thought. 😉

After a bit of research (okay, it was actually several hours because I decided to read through a bunch of specs and blog posts and then run a ton of experiments), it turns out that hosting your own OIDC Conformant “server” to verify self-signed JSON Web Tokens with HTTP APIs is actually quite simple. So as long as you can use JWT for your bearer tokens, you can utilize your existing authentication service (and probably dramatically reduce your latency and cost).

In this post, I’ll show you everything you need to know to set this up yourself. We’ll generate certificates, create our OIDC discovery service, set up our HTTP API authorizers, generate and sign our JWTs, and protect routes with scopes.

How to switch from RDBMS to DynamoDB in 20 easy steps…

Posted in How To & Serverless on June 9, 2019
Last Updated: March 30, 2020

I posted a thread on Twitter with some thoughts on how to how to switch from RDBMS to DynamoDB. Some people have asked me to turn it into a blog post to make it easier to follow. So here it is… with some bonus steps at the end. Enjoy! 😁

I've been spending a lot of time lately with @dynamodb in my #serverless applications, so I thought I'd share my surefire guide to migrating to it from #RDBMS. So here is…

How to switch from RDBMS to #DynamoDB in *20* easy steps… (a thread)

— Jeremy Daly (@jeremy_daly) June 7, 2019

Throttling Third-Party API calls with AWS Lambda

Posted in How To & Serverless on February 2, 2019

In the serverless world, we often get the impression that our applications can scale without limits. With the right design (and enough money), this is theoretically possible. But in reality, many components of our serverless applications DO have limits. Whether these are physical limits, like network throughput or CPU capacity, or soft limits, like AWS Account Limits or third-party API quotas, our serverless applications still need to be able to handle periods of high load. And more importantly, our end users should experience minimal, if any, negative effects when we reach these thresholds.

There are many ways to add resiliency to our serverless applications, but this post is going to focus on dealing specifically with quotas in third-party APIs. We’ll look at how we can use a combination of SQS, CloudWatch Events, and Lambda functions to implement a precisely controlled throttling system. We’ll also discuss how you can implement (almost) guaranteed ordering, state management (for multi-tiered quotas), and how to plan for failure. Let’s get started!

How To: Use SNS and SQS to Distribute and Throttle Events

Posted in How To & Serverless on January 13, 2019

An extremely useful AWS serverless microservice pattern is to distribute an event to one or more SQS queues using SNS. This gives us the ability to use multiple SQS queues to “buffer” events so that we can throttle queue processing to alleviate pressure on downstream resources. For example, if we have an event that needs to write information to a relational database AND trigger another process that needs to call a third-party API, this pattern would be a great fit.

This is a variation of the Distributed Trigger Pattern, but in this example, the SNS topic AND the SQS queues are contained within a single microservice. It is certainly possible to subscribe other microservices to this SNS topic as well, but we’ll stick with intra-service subscriptions for now. The diagram below represents a high-level view of how we might trigger an SNS topic (API Gateway → Lambda → SNS), with SNS then distributing the message to the SQS queues. Let’s call it the Distributed Queue Pattern.

This post assumes you know the basics of setting up a serverless application, and will focus on just the SNS topic subscriptions, permissions, and implementation best practices. Let’s get started!

How To: Add Test Coverage to your Serverless Applications

Posted in How To, Programming & Serverless on July 30, 2018
Last Updated: March 30, 2020

Writing serverless functions brings developers closer and closer to the stack that runs their code. While this gives them a tremendous amount of freedom, it also adds additional responsibility. Serverless applications require developers to think more about security and optimizations, as well as perform other tasks that were traditionally assigned to operations teams. And of course, code quality and proper testing continue to be at the top of the list for production-level applications. In this post, we’ll look at how to add test coverage to our Node.js applications and how we can apply it to our Serverless framework projects. ⚡️

How To: Tag Your Lambda Functions for Smarter Serverless Applications

Posted in How To & Serverless
Last Updated: March 30, 2020

As our serverless applications start to grow in complexity and scope, we often find ourselves publishing dozens if not hundreds of functions to handle our expanding workloads. It’s no secret that serverless development workflows have been a challenge for a lot of organizations. Some best practices are starting to emerge, but many development teams are simply mixing their existing workflows with frameworks like Serverless and AWS SAM to build, test and deploy their serverless applications.

Beyond workflows, another challenge serverless developers encounter as their applications expand, is simply trying to keep all of their functions organized. You may have several functions and resources as part of a microservice contained in their own git repo. Or you might simply put all your functions in a single repository for better common library sharing. Regardless of how code is organized locally, much of that is lost when all your functions end up in a big long list in the AWS Lambda console. In this post we’ll look at how we can use AWS’s resource tagging as a way to apply structure to our deployed functions. This not only give us more insight into our applications, but can be used to apply Cost-Allocation Tags to our billing reports as well. 👍

How To: Optimize the Serverless Optimizer Plugin

Posted in How To & Serverless on June 12, 2018
Last Updated: March 30, 2020

I’m sure you’re already well aware of how awesome the ⚡ Serverless Framework is for managing and deploying your serverless applications. And you’re probably aware that there are several great plugins available that make Serverless even better. But did you know that there was a plugin to optimize your functions and reduce the size of your deployment packages? Or are you already using this plugin to optimize your functions, but hate how it takes too long to optimize locally run functions? In this post I’ll share some quick tips to help you optimize your Serverless Optimizer experience.

How To: Manage Serverless Environment Variables Per Stage

Posted in How To, Serverless & Serverless Stage Manager on May 2, 2018
Last Updated: March 30, 2020

I often find myself creating four separate stages for each ⚡ Serverless Framework project I work on: dev, staging, prod, and local. Obviously the first three are meant to be deployed to the cloud, but the last one, local, is meant to run and test interactions with local resources. It’s also great to have an offline version (like when you’re on a plane ✈ or have terrible wifi somewhere). Plus, development is much faster because you’re not waiting for round trips to the server. 😉

A really great feature of Serverless is the ability to configure ENVIRONMENT variables in the serverless.yml file. This lets us store important global information like database names, service endpoints and more. We can even reference passwords securely using AWS’s Service Manager Parameter Store and decode encrypted secrets on deployment, keeping them safe from developers and source repositories alike. 😬 Just reference the variable with ${ssm:/myapp/my-secure-value~true} in your configuration file.

How To: Stub “.promise()” in AWS-SDK Node.js

Posted in How To & Programming on April 25, 2018

Since AWS released support for Node v8.10 in Lambda, I was able to refactor Lambda API to use async/await instead of Bluebird promises. The code is not only much cleaner now, but I was able to remove a lot of unnecessary overhead as well. As part of the refactoring, I decided to use AWS-SDK’s native promise implementation by appending .promise() to the end of an S3 getObject call. This works perfectly in production and the code is super compact and simple:

let data = await S3.getObject(params).promise()

1	let data = await S3.getObject(params).promise()

The issue came with stubbing the call using Sinon.js. With the old promise method, I was using promisifyAll() to wrap new AWS.S3() and then stubbing the getObjectAsync method. If you’re not familiar with stubbing AWS services, read my post: How To: Stub AWS Services in Lambda Functions using Serverless, Sinon.JS and Promises.

How To: Manage RDS Connections from AWS Lambda Serverless Functions

Posted in How To, Programming & Serverless on April 4, 2018
Last Updated: March 30, 2020

Someone asked a great question on my How To: Reuse Database Connections in AWS Lambda post about how to end the unused connections left over by expired Lambda functions:

I’m playing around with AWS lambda and connections to an RDS database and am finding that for the containers that are not reused the connection remains. I found before that sometimes the connections would just die eventually. I was wondering, is there some way to manage and/or end the connections without needing to wait for them to end on their own? The main issue I’m worried about is that these unused connections would remain for an excessive amount of time and prevent new connections that will actually be used from being made due to the limit on the number of connections.

🧟‍♂️ Zombie RDS connections leftover on container expiration can become a problem when you start to reach a high number of concurrent Lambda executions. My guess is that this is why AWS is launching Aurora Serverless, to deal with relational databases at scale. ~~At the time of this writing it is still in preview mode.~~

Update September 2, 2018: I wrote an NPM module that manages MySQL connections for you in serverless environments. Check it out here.

Update August 9, 2018: Aurora Serverless is now Generally Available!

Overall, I’ve found that Lambda is pretty good about closing database connections when the container expires, but even if it does it reliably, it still doesn’t solve the MAX CONNECTIONS problem. Here are several strategies that I’ve used to deal with this issue.