Among the AWS Lambda announcements at the 2016 re:Invent, Werner Vogels introduced Lambda@Edge (in preview) for running Lambda functions at CloudFront locations. It’s part of the larger movement focused on letting you execute your code wherever you want in your AWS architecture.
I signed up for the preview, and today, I’d like to share my personal experiment with Lambda@Edge for serving dynamically generated, minimized, and compressed HTML pages. We’ll also look at some of the most interesting use cases that Lambda@Edge supports.
Lambda@Edge is still evolving
Although still in preview mode, you can already see the CloudFront trigger showing up in the AWS Lambda Console, as well as a new Edge Node.js 4.3 runtime.
If you are a curious developer, you have probably already tried Lambda@Edge and experienced the strong limitations imposed by this new programming model. For example, your functions can’t run longer than 50 ms, and you can only access or manipulate the upcoming request (i.e. by the client) or the generated response (i.e. by the origin), depending on which event is being handled. While some of these limitations may disappear with general availability, others are not likely to change.
Even if you already have access to the preview, you couldn’t do much with Lambda@Edge other than header manipulation until last week, when Jeff Barr announced a new feature for generating custom HTTP responses.
Jeff Barr also announced another feature: custom logging statements. In fact, Lambda@Edge can now write custom logs directly to Amazon CloudWatch. This functionality will allow you to generate custom reports about your CloudFront distributions. However, in this article, I will mostly focus on content generation and latency optimization. For now, let’s just say that you can write up to 4KB of custom logs per invocation, simply by calling the usual console methods (log, info, error, and warn).
What can you do with Lambda@Edge?
While the set of use cases for Lambda@Edge is relatively small, I think it offers huge potential.
Since you don’t have access to any remote storage or database and you can’t execute an HTTP call, all of the information required by your Lambda Function must be already available at the Edge location, either by inspecting the request or the response (headers and cookies included).
I think the primary use cases can be organized into three categories:
- Request/Response manipulation
- Dynamic content generation
- Pure latency optimization
Let’s see what each category can offer and take a look at the most interesting use cases.
Note: I made up these three categories and you won’t find them on the official AWS documentation.
This category includes all of the use cases where you need to enhance or modify the upcoming request or the generated response with additional headers or content. In this scenario, you will always forward the request to your CloudFront origin (or to the CloudFront cache).
For example, you may want to add custom HTTP headers to an upcoming request to improve your distribution caching layer. You can find a real world scenario by tiny.pictures here. Since the User-Agent header is not white-listed by CloudFront for caching reasons, they have implemented the computing logic to understand whether or not the client supports WebP image format with Lambda@Edge. To achieve this, they inspected the User-Agent header and then added a custom header (which will be white-listed and cached by CloudFront) to the same request before the origin receives it.
Similarly, you may manipulate the response already generated by the origin and implement edge-dependent modifications. For example, you could customize some timezone-related information based on the particular Edge location, or handle special response formatting based on client capabilities, such as converting JSON to XML or vice versa. Note: Serving different data formats based on client capabilities is generally not considered a best practice (i.e. it’s not RESTful at all and SEO experts would discourage it too). Here, I’m considering special scenarios where you need to solve compatibility issues or unexpected corner cases.
Another interesting use case that requires request or response manipulation is A/B testing. You could implement cookie-based A/B testing either by editing the request path or by manipulating the response body. I would recommend the first option, as it makes the chosen variation more explicit at the origin, where you may also take care of creating the initial cookie and tracking events and conversions.
With the very same header-based technique, you can quickly implement URL rewriting, temporary or permanent redirects, or simple cookies initialization. For example, you might alter the request path and convert query string parameters to explicit paths for your origin (i.e. pagination, filtering, navigation, etc.).
Here is a recap of the possible use cases based on request/response manipulation:
- Custom HTTP headers (request)
- Timezone-related information (response)
- Response format adapters (response)
- Cookie-based A/B testing (request)
- URL rewriting (request)
- Temporary redirects (request)
- Cookies initialization (response)
Dynamic content generation
The main advantage of generating content directly at the Edge is that requests will not hit the CloudFront origin at all. It means that you don’t have to worry about distributing your server-side code across multiple regions because each user will only interact with the closest Edge location.
Please note that you can already distribute static content this way with S3 and CloudFront.
Lambda@Edge allows you to achieve the same performance with dynamic content as well. Of course, all of the information must be available at the Edge without any additional network calls (i.e. no databases or 3rd-party integrations), therefore the use cases are quite limited. Server-side rendering at the Edge could be a new way to handle simple cases without messing up client-side rendering, which often adds a considerable amount of assets and dependencies (i.e. more HTTP calls!).
For example, you may generate error pages or login/signup forms on the fly in the case of non-authenticated users. Although this is not a best practice for SEO concerns (without redirects), it may be an interesting solution for optimizing the user experience on certain pages of your website. Given the importance of pages related to user onboarding, customer support, and maintenance windows, Lambda@Edge might optimize the UX by reducing latency to the minimum.
Although these scenarios may sound pretty restricted, I think Lambda@Edge has a very underestimated potential when combined with CloudFront’s caching and server-side rendering.
It’s worth mentioning that Lambda@Edge currently allows you to upload only 1MB of code, dependencies included. This is quite limiting if you need complex libraries to manipulate images or render HTML templates. Also, it currently supports only Node.js 4.3.
Pure latency optimization
This category only aims at optimizing the network latency, and it could include a mix of the previous scenarios. In some use cases, you simply don’t want to hit the origin if not needed.
For example, if your origin is a RESTful API that always requires the Authorization header, why would you need to hit the origin when a request does not contain it? You could generate a 401 Unauthorized response at the edge, and therefore reduce response time and origin load.
With the same technique and goal, you could implement any custom validation logic or transformation at the Edge and optimize special API endpoints. Even if the overall cost might be higher, user experience will improve without increasing your load at the origin. Also, the logic you implement with Lambda@Edge could be completely transparent to the client and the origin—provided that you are already using a CloudFront distribution—so that you won’t need to rewrite URLs around and you can easily remove or improve the Lambda@Edge without impacting the system.
Eventually, if AWS allows you to associate AWS@Edge with your API Gateway distributions you may even end up optimizing costs this way, assuming that invoking Lambda@Edge will be cheaper than invoking API Gateway + Lambda. If the pricing is the same with AWS Lambda, you might spend the same while reducing network latency.
A real-world experiment with server-side rendering and compression
I would need to resolve three issues:
- How to map requests to local resources (i.e. HTML files): I decided to map URLs into local files so that a request to /test.html will be handled by rendering a local test.html file with Plates. Any request to non-existing files will be forwarded to the distribution origin, practically bypassing Lambda@Edge.
- How to shrink everything into 1MB of code: This turned out to be the most challenging step, as my dependencies initially added up to more than 6MB. Sadly, I had to manually hack the html-minifier package and remove a few unused dependencies (i.e. clean-css and uglify-js), even after reducing the node_modules size with modclean. I’m not too proud of this hack, but I will be happy to learn about more robust and elegant solutions.
My Lambda@Edge Function code looks like the following (complete gist and instructions here):
You could make the dynamic rendering arbitrarily complex to cover specific scenarios. Your rendering could involve data stored in cookies or data that depends on the current time or even the specific Edge location. As a simple proof of concept, I’m happy with the result, and I’m looking forward to improving it and using it in real production use cases.
I will be happy to receive your feedback as well, although I don’t expect this experiment to become a reference code base since things might change consistently with general availability.
We have great expectations for Lambda@Edge, as it’s bringing computing capabilities not only out of your virtual machines but also out of data centers and as close as possible to your end users. The preview phase is opening up interesting scenarios for serverless computing at the edge. Or can we say origin-less already?
At the same time, I expect to see even more possibilities coming soon with general availability. For example, I would love to see Lambda@Edge support for Python and native integration with API Gateway distributions. Also, I think many interesting use cases will require more than 1MB of code, and I hope to see it increased to at least 10MB. I can understand why it is a tough tradeoff between propagation efficiency, storage at the edge, and programming flexibility. On the other hand, I think the constrained memory (128MB) and execution time (50ms) will disappear soon, although I don’t feel like they are such an annoying limitation for the most likely use cases.
I can’t wait to see more statistical proofs regarding performance efficiency and to hear about more advanced or unexpected scenarios where Lambda@Edge can make a difference.
Let us know what you think about Lambda@Edge, and feel free to share your experiments and the use cases that we may have missed.
New Content: Azure DP-100 Certification, Alibaba Cloud Certified Associate Prep, 13 Security Labs, and Much More
This past month our Content Team served up a heaping spoonful of new and updated content. Not only did our experts release the brand new Azure DP-100 Certification Learning Path, but they also created 18 new hands-on labs — and so much more! New content on Cloud Academy At any time, y...
AWS Certification Practice Exam: What to Expect from Test Questions
If you’re building applications on the AWS cloud or looking to get started in cloud computing, certification is a way to build deep knowledge in key services unique to the AWS platform. AWS currently offers 12 certifications that cover major cloud roles including Solutions Architect, De...
Overcoming Unprecedented Business Challenges with AWS
From auto-scaling applications with high availability to video conferencing that’s used by everyone, every day — cloud technology has never been more popular or in-demand. But what does this mean for experienced cloud professionals and the challenges they face as they carve out a new p...
Constant Content: Cloud Academy’s Q3 2020 Roadmap
Hello — Andy Larkin here, VP of Content at Cloud Academy. I am pleased to release our roadmap for the next three months of 2020 — August through October. Let me walk you through the content we have planned for you and how this content can help you gain skills, get certified, and...
New Content: Alibaba, Azure AZ-303 and AZ-304, Site Reliability Engineering (SRE) Foundation, Python 3 Programming, 16 Hands-on Labs, and Much More
This month our Content Team did an amazing job at publishing and updating a ton of new content. Not only did our experts release the brand new AZ-303 and AZ-304 Certification Learning Paths, but they also created 16 new hands-on labs — and so much more! New content on Cloud Academy At...
Blog Digest: Which Certifications Should I Get?, The 12 Microsoft Azure Certifications, 6 Ways to Prevent a Data Breach, and More
This month, we were excited to announce that Cloud Academy was recognized in the G2 Summer 2020 reports! These reports highlight the top-rated solutions in the industry, as chosen by the source that matters most: customers. We're grateful to have been nominated as a High Performer in se...
Which Certifications Should I Get?
The old AWS slogan, “Cloud is the new normal” is indeed a reality today. Really, cloud has been the new normal for a while now and getting credentials has become an increasingly effective way to quickly showcase your abilities to recruiters and companies. With all that in mind, the s...
New Content: AWS, Azure, Typescript, Java, Docker, 13 New Labs, and Much More
This month, our Content Team released a whopping 13 new labs in real cloud environments! If you haven't tried out our labs, you might not understand why we think that number is so impressive. Our labs are not “simulated” experiences — they are real cloud environments using accounts on A...
Kickstart Your Tech Training With a Free Week on Cloud Academy
Are you looking to make a jump in your technical career? Want to get trained or certified on AWS, Azure, Google Cloud Platform, DevOps, Kubernetes, Python, or another in-demand skill? Then you'll want to mark your calendar. Starting Monday, June 22 at 12:00 a.m. PDT (3:00 a.m. EDT), ...
New Content: AZ-500 and AZ-400 Updates, 3 Google Professional Exam Preps, Practical ML Learning Path, C# Programming, and More
This month, our Content Team released tons of new content and labs in real cloud environments. Not only that, but we introduced our very first highly interactive "Office Hours" webinar. This webinar, Acing the AWS Solutions Architect Associate Certification, started with a quick overvie...
Azure vs. AWS: Which Certification Provides the Brighter Future?
More and more companies are using cloud services, prompting more and more people to switch their current IT position to something cloud-related. The problem is most people only have that much time after work to learn new technologies, and there are plenty of cloud services that you can ...
Blog Digest: 5 Reasons to Get AWS Certified, OWASP Top 10, Getting Started with VPCs, Top 10 Soft Skills, and More
Thank you for being a valued member of our community! We recently sent out a short survey to understand what type of content you would like us to add to Cloud Academy, and we want to thank everyone who gave us their input. If you would like to complete the survey, it's not too late. It ...