New Year, New Job, Same Serverless Mission

I took a new job as the GM of Serverless Cloud at Serverless, Inc. I’m really excited about what I’m working on there, and here’s why…

Some Background

When I first discovered AWS Lambda six years ago, I became fascinated with serverless, or rather, I became fascinated with the potential of serverless. Having spent an inordinate amount of time during the first 15 years of my career racking, configuring, patching, maintaining, and (poorly) scaling servers, the notion of abstracting all of that away seemed too good to be true. I had already been using AWS for five years at that point, so even though the cloud had eliminated the need for physical hardware, all the complexity around building high-scale, highly-available, highly-distributed applications was still there. For me, serverless was the way to solve that problem. So I went all in. 

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Aurora Serverless v2: The Good, the Better, and the Possibly Amazing

Three years ago at re:Invent 2017, AWS announced the original Amazon Aurora Serverless preview. I spent quite a bit of time with it, and when it went GA 9 months later, I published my thoughts in a post titled Aurora Serverless: The Good, the Bad and the Scalable.

If you read the post, you’ll see that I was excited and optimistic, even though there were a lot of missing features. And after several months of more experiments, I finally moved some production workloads onto it, and had quite a bit of success. Over the last 18 months, we’ve seen some improvements to the product (including support for PostgreSQL and the Data API), but there were still loads of problems with the scale up/down speeds, failover time, and lack of Aurora provisioned cluster features.

That all changed with the introduction of Amazon Aurora Serverless v2. I finally got access to the preview and spent a few hours trying to break it. My first impression? This thing might just be a silver bullet!

I know that’s a bold statement. 😉 But even though I’ve only been using it for a few hours, I’ve also read through the (minimal) docs, reviewed the pricing, and talked to one of the PMs to understand it the best I could. There clearly must be some caveats, but from what I’ve seen, Aurora Serverless v2 is very, very promising. Let’s take a closer look!

Update December 9, 2020: I’ve updated the post with some more information after having watched the “Amazon Aurora Serverless v2: Instant scaling for demanding workloads” presentation by Murali Brahmadesam (Director of Engineering, Aurora Databases and Storage) and Chayan Biswas (Principle Product Manager, Amazon Aurora). The new images are courtesy of their presentation.

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Jeremy’s Guide to a Very Serverless re:Invent 2020

It’s AWS re:Invent time, and once again, developers, architects, business leaders, and everyone in between are faced with the daunting task of selecting from thousands of hours of re:Invent content. As usual, I will be focusing most of my time on serverless, so I’ve combed through the massive session catalog and picked out the ones that look the most interesting to me. If you’re looking to focus on serverless during this re:Invent, perhaps you’ll find my suggestions useful.

My picks are also available on the Cloud Pegboard re:Invent Tool (Thanks, Ken). Select “Jeremy Daly” from the “AWS Hero Picks” dropdown and you’ll see all my selections with the options to add them to your wishlist and export them to your calendar. I have about 60 sessions on my list, which I’ve categorized below. But I realize that no human is likely going to be able to watch them all, so I’ve also made a list of Sessions you can’t miss!

There are sure to be plenty of announcements throughout the three weeks of re:Invent, so be sure to subscribe to the Off-by-none newsletter for weekly recaps.

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Takeaways from Programming AWS Lambda by Mike Roberts and John Chapin

Recently, Symphonia co-founders Mike Roberts and John Chapin wrote a book called Programming AWS Lambda: Build and Deploy Serverless Applications with Java. I personally abandoned Java long ago, but I knew full well that anything written by Mike and John was sure to be great. So despite the title (and my past war stories of working with Java), I picked up the book and gave it a read. I discovered that it’s not really a book about Java, but a book about building serverless applications with the examples in Java. Sure, there are a few very Java specific things (which every Java developer probably needs to read), but overall, this book offers some great insight into serverless from two experts in the field.

I had the chance to catch up with Mike on a recent episode of Serverless Chats. We discussed the book, how John and Mike got started with serverless (by building Java Lambda functions, of course), and what are some of the best practices people need to think about when building serverless applications. It was a great conversation (which you can watch/listen to here), but it was also jam packed with information, so I thought I’d highlight some of the important takeaways.

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Making the Case for Serverless Use Cases

For quite some time, there was a running joke that “serverless” was just for converting images to thumbnails. That’s still a great use case for serverless, of course, but since AWS released Lambda in 2014, serverless has definitely come a long way. Even still, newcomers to the space often don’t realize just how many use cases there are for serverless. I spoke with Gareth McCumskey, a Solutions Architect at Serverless Inc, on a recent two part episode (part 1 and part 2) of Serverless Chats, and we discussed nine very applicable use cases that I thought I’d share with you here.

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12 Important Lessons from The DynamoDB Book

Fellow serverless advocate, and AWS Data Hero, Alex DeBrie, recently released The DynamoDB Book, which ventures way beyond the basics of DynamoDB, but still offers an approachable and useful resource for developers of any experience level. I had the opportunity to read the book and then speak with Alex about it on Serverless Chats. We discussed several really important lessons from the book that every DynamoDB practitioner needs to know. Here are twelve of my favorites, in no particular order.

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Takeaways from the State of Serverless Report

On a recent episode of Serverless Chats, I spoke with Stephen Pinkerton and Darcy Rayner of Datadog to dig into The State of Serverless report, which was released at the end of February 2020. After frequently fielding customer questions about the topic, Datadog looked at its data and customer use cases, and examined how they were using serverless. Datadog’s report is a way to break it all down, but it’s also an opportunity for its customers (and serverless users alike) to see how other people are using serverless in a data-driven way. I discussed methodology, findings, and key takeaways with Stephen and Darcy, and thought it’d be worthwhile to consolidate and share that insight.

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

“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.

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The Dynamic Composer (an AWS serverless pattern)

I’m a big fan of following the Single Responsibility Principle when creating Lambda functions in my serverless applications. The idea of each function doing “one thing well” allows you to easily separate discrete pieces of business logic into reusable components. In addition, the Lambda concurrency model, along with the ability to add fine-grained IAM permissions per function, gives you a tremendous amount of control over the security, scalability, and cost of each part of your application.

However, there are several drawbacks with this approach that often attract criticism. These include things like increased complexity, higher likelihood of cold starts, separation of log files, and the inability to easily compose functions. I think there is merit to these criticisms, but I have personally found the benefits to far outweigh any of the negatives. A little bit of googling should help you find ways to mitigate many of these concerns, but I want to focus on the one that seems to trip most people up: function composition.

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

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! 😁

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