Deploy a Secure Static Site with AWS & Terraform

14. December 2018 2018 0

There are many uses for static websites. A static site is the simplest form of website, though every website consists of delivering HTML, CSS and other resources to a browser. With a static website, initial page content is delivered the same to every user, regardless as to how they’ve interacted with your site previously. There’s no database, authentication or anything else associated with sending the site to the user – just a straight HTTPS connection and some text content. This content can benefit from caching on servers closer to its users for faster delivery; it will generally also be lower cost as the servers to deliver this content to not themselves need to interpret scripting languages or make database connections on behalf of the application.

The static website now has another use, as there are more tools to provide highly interactive in-browser applications based on JavaScript frameworks (such as React, Vue or Angular) which manage client interaction, maintain local data and interact with the web service via small but often frequent API calls. These systems decouple front-end applications from back-end services and allow those back-ends to be written in multiple languages or as small siloed applications, often called microservices. Microservices may take advantage of modern back-end technologies such as containers (via Docker and/or Kubernetes) and “serverless” providers like AWS Lambda.

People deploying static sites fall into these two very different categories – for one the site is the whole of their business, for the other the static site is a very minor part supporting the API. However, each category of static site use still shares similar requirements. In this article we explore deploying a static site with the following attributes:

  • Must work at the root domain of a business, e.g., example.com
  • Must redirect from the common (but unnecessary) www. subdomain to the root domain
  • Must be served via HTTPS (and upgrade HTTP to HTTPS)
  • Must support “pretty” canonical URLs – e.g., example.com/about-us rather than example.com/about-us.html
  • Must not cost anything when not being accessed (except for domain name costs)

AWS Service Offerings

We achieve these requirements through use of the following AWS services:

  • S3
  • CloudFront
  • ACM (Amazon Certificate Manager)
  • Route53
  • Lambda

This may seem like quite a lot of services to host a simple static website; let’s review and summarise why each item is being used:

  • S3 – object storage; allows you to put files in the cloud. Other AWS users or AWS services may be permitted access to these files. They can be made public. S3 supports website hosting, but only via HTTP. For HTTPS you need…
  • CloudFront – content delivery system; can sit in front of an S3 bucket or a website served via any other domain (doesn’t need to be on AWS) and deliver files from servers close to users, caching them if allowed. Allows you to import HTTPS certificates managed by…
  • ACM – generates and stores certificates (you can also upload your own). Will automatically renew certificates which it generates. For generating certificates, your domain must be validated via adding custom CNAME records. This can be done automatically in…
  • Route53 – AWS nameservers and DNS service. R53 replaces your domain provider’s nameservers (at the cost of $0.50 per month per domain) and allows both traditional DNS records (A, CNAME, MX, TXT, etc.) and “alias” records which map to a specific other AWS service – such as S3 websites or CloudFront distributions. Thus an A record on your root domain can link directly to Cloudfront, and your CNAMEs to validate your ACM certificate can also be automatically provisioned
  • Lambda – functions as a service. Lambda lets you run custom code on events, which can come directly or from a variety of other AWS services. Crucially you can put a Lambda function into Cloudfront, manipulating requests or responses as they’re received from or sent to your users. This is how we’ll make our URLs look nice

Hopefully, that gives you some understanding of the services – you could cut out CloudFront and ACM if you didn’t care about HTTPS, but there’s a worldwide push for HTTPS adoption to provide improved security for users and browsers including Chrome are marking pages not served via HTTPS as “insecure” as part of their commitment.

All this is well and good, but whilst AWS is powerful their console leaves much to be desired, and setting up one site can take some time – replicating it for multiple sites is as much an exercise in memory and box ticking as it is in technical prowess. What we need is a way to do this once, or even better have somebody else do this once, and then replicate it as many times as we need.

Enter Terraform from HashiCorp

One of the most powerful parts of AWS isn’t clear when you first start using the console to manage your resources. AWS has a super powerful API that drives pretty much everything. It’s key to so much of their automation, to the entirety of their security model and tools, tools like Terraform.

Terraform from HashiCorp is “Infrastructure-as-Code” or IaC. It lets you define resources on a variety of cloud providers and then run commands to:

  • Check the current state of your environment
  • Make required changes such that your actual environment matches the code you’ve written

In code form, Terraform uses blocks of code called resources:

resource “aws_s3_bucket” “some-internal-reference” {
  bucket = “my-bucket-name”
}

Each resource can include variables (documented on the provider’s website), and these can be text, numbers, true/false, lists (of the above) or maps (basically like subresources with their variables).

Terraform is distributed as pre-built binaries (it’s also open source, written in Go so you can build it yourself) that you can run simply by downloading, making them executable and then executing them. To work with AWS, you need to define a “provider” which is formatted similarly to a resource:

provider “aws” {
}

To run any AWS API (via command line, terraform or a language of your choice) you’ll need to generate an access key and secret key for the account you’d like to use. That’s beyond the scope of this article, but given you should also avoid hardcoding those credentials into Terraform, and given you’d be very well served to have access to it, skip over to the AWS CLI setup instructions and set this up with the correct keys before continuing.

(NB: in this step you’re best provisioning an account with admin rights, or at least full access to IAM, S3, Route53, Cloudfront, ACM & Lambda. However don’t be tempted to create access keys for your root account – AWS recommends against this)

Now that you’ve got your system set up to use AWS programmatically, installed Terraform and been introduced to the basics of its syntax it’s a good time to look at our code on GitHub.

Clone the repository above; you’ll see we have one file in the root (main.tf.example) and then a directory called modules. One of the best parts of Terraform is modules and how they behave. Modules allow one user to define a specific set of infrastructure that may either relate directly to each other or interact by being on the same account. These modules can define variables allowing some aspects (names, domains, tags) to be customised, whilst other items that may be necessary for the module to function (like a certain configuration of a CloudFront distribution) are fixed.

To start off run bash ./setup which will copy the example file to main.tf and also ensure your local Terraform installation has the correct providers (AWS and file archiving) as well as set up the modules. In main.tf then you’ll see a suggested set up using three modules. Of course, you’d be free to just remove main.tf entirely and use each module in its own right, but for this tutorial, it helps to have a complete picture.

At the top of the main.tf file are defined three variables which you’ll need to fill in correctly:

  1. The first is the domain you wish to use – it can be your root domain (example.com) or any sort of subdomain (my-site.example.com).
  2. Second, you’ll need the Zone ID associated with your domain on Route 53. Each Route 53 domain gets a zone ID which relates to AWS’ internal domain mapping system. To find your Zone ID visit the Route53 Hosted Zones page whilst signed in to your AWS account and check the right-hand column next to the root domain you’re interested in using for your static site.
  3. Finally choose a region; if you already use AWS you may have a preferred region, otherwise, choose one from the AWS list nearest to you. As a note, it’s generally best to avoid us-east-1 where possible, as on balance this tends to have more issues arise due to its centrality in various AWS services.

Now for the fun part. Run terraform plan – if your AWS CLI environment is set up the plan should execute and show the creation of a whole list of resources – S3 Buckets, CloudFront distributions, a number of DNS records and even some new IAM roles & policies. If this bit fails entirely, check that the provider entity in main.tf is using the right profile name based on your ~/.aws/credentials file.

Once the plan has run and told you it’s creating resources (it shouldn’t say updating or destroying at this point), you’re ready to go. Run terraform apply – this basically does another plan, but at the end, you can type yes to have Terraform create the resources. This can take a while as Terraform has to call various AWS APIs and some are quicker than others – DNS records can be slightly slower, and ACM generation may wait until it’s verified DNS before returning a positive response. Be patient and eventually it will inform you that it’s finished, or tell you if there have been problems applying.

If the plan or apply options have problems you may need to change some of your variables based on the following possible issues:

  • Names of S3 buckets should be globally unique – so if anyone in the world has a bucket with the name you want, you can’t have it. A good system is to prefix buckets with your company name or suffix them with random characters. By default, the system names your buckets for you, but you can override this.
  • You shouldn’t have an A record for your root or www. domain already in Route53.
  • You shouldn’t have an ACM certificate for your root domain already.

It’s safe (in the case of this code at least) to re-run Terraform if problems have occurred and you’ve tried to fix them – it will only modify or remove resources it has already created, so other resources on the account are safe.

Go into the AWS console and browse S3, CloudFront, Route53 and you should see your various resources created. You can also view the Lambda function and ACM but be aware that for the former you’ll need to be in the specific region you chose to run in, and for the latter, you must select us-east-1 (N. Virginia)

What now?

It’s time to deploy a website. This is the easy part – you can use the S3 console to drag and drop files (remember to use the website bucket and not the logs or www redirect buckets), use awscli to upload yourself (via aws s3 cp or aws s3 sync) or run the example bash script provided in the repo which takes one argument, a directory of all files you want to upload. Be aware – any files uploaded to your bucket will immediately be public on the internet if somebody knows the URL!

If you don’t have a website, check the “example-website” directory – running the bash script above without any arguments will deploy this for you. Once you’ve deployed something, visit your domain and all being well you should see your site. Cloudfront distributions have a variable time to set up so in some cases it might be 15ish minutes before the site works as expected.

Note also that CloudFront is set to cache files for 5 minutes; even a hard refresh won’t reload resource files like CSS or JavaScript as Cloudfront won’t go and fetch them again from your bucket for 5 minutes after first fetching them. During development you may wish to turn this off – you can do this in the CloudFront console, set the TTL values to 0. Once you’re ready to go live, run terraform apply again and it will reconfigure Cloudfront to recommended settings.

Summary

With a minimal amount of work we now have a framework that can deploy a secure static site to any domain we choose in a matter of minutes. We could use this to deploy websites for marketing clients rapidly, publish a blog generated with a static site builder like Jekyll, or use it as the basis for a serverless web application using ReactJS delivered to the client and a back-end provided by AWS Lambda accessed via AWS API Gateway or (newly released) an AWS Application Load Balancer.

About the Author

Mike has been working in web application development for 10 years, including 3 years managing a development team for a property tech startup and before that 4 years building a real time application for managing operations at skydiving centres, as well as some time freelancing. He uses Terraform to manage all the AWS infrastructure for his current work and has dabbled in other custom AWS tools such as an improvement to the CloudWatch logging agent and a deployment tool for S3. You can find him on Twitter @m1ke and GitHub.

About the Editor

Jennifer Davis is a Senior Cloud Advocate at Microsoft. Jennifer is the coauthor of Effective DevOps. Previously, she was a principal site reliability engineer at RealSelf, developed cookbooks to simplify building and managing infrastructure at Chef, and built reliable service platforms at Yahoo. She is a core organizer of devopsdays and organizes the Silicon Valley event. She is the founder of CoffeeOps. She has spoken and written about DevOps, Operations, Monitoring, and Automation.


Just add Code: Fun with Terraform Modules and AWS

06. December 2016 2016 0

Author: Chris Marchesi

Editors: Andrew Langhorn, Anthony Elizondo

This article is going to show you how you can use Terraform, with a little help from Packer and Chef, to deploy a fully-functional sample web application, complete with auto-scaling and load balancing, in under 50 lines of Terraform code.

You will need the sample project to follow along, so make sure you load that up before continuing with reading this article.

The Humble Configuration

Check out the code in the terraform/main.tf file.

It might be hard to think that with this mere smattering of Terraform is setting up:

  • An AWS VPC
  • 2 subnets, each in different availability zones, fully routed
  • An AWS Application Load Balancer
  • A listener for the ALB
  • An AWS Auto Scaling group
  • An ALB target group attached to the ALB
  • Configured security groups for both the ALB and backend instances

So what’s the secret?

Terraform Modules

This example is using a powerful feature of Terraform – the modules feature, providing a semantic and repeatable way to manage AWS infrastructure. The modules hide most of the complexity of setting up a full VPC behind a relatively small set of code, and an even smaller set of changes going forward (generally, to update this application, all that is needed is to update the AMI).

Note that this example is composed entirely of modules – no root module resources exist. That’s not to say that they can’t exist – and in fact one of the secondary examples demonstrates how you can use the outputs of one of the modules to add extra resources on an as-needed basis.

The example is composed of three visible modules, and one module that operates under the hood as a dependency:

  • terraform_aws_vpc, which sets up the VPC and subnets
  • terraform_aws_alb, which sets up the ALB and listener
  • terraform_aws_asg, which configures the Auto Scaling group, and ALB target group for the launched instances
  • terraform_aws_security_group, which is used by the ALB and Auto Scaling modules to set up security groups to restrict traffic flow.

These modules will be explained in detail later in the article.

How Terraform Modules Work

Terraform modules work very similar to basic Terraform configuration. In fact, each Terraform module is a standalone configuration in its own right, and depending on its pre-requisites, can run completely on its own. In fact, a top-level Terraform configuration without any modules being used is still a module – the root module. You sometimes see this mentioned in various parts of the Terraform workflow, such as in things like error messages, and the state file.

Module Sources and Versioning

Terraform supports a wide variety of remote sources for modules, such as simple, generic locations like HTTP, or Git, or well-known locations like GitHub, Bitbucket, or Amazon S3.

You don’t even need to put a module in a remote location. In fact, a good habit to get into is if you need to re-use Terraform code in a local project, put that code in a module – that way you can re-use it several times to create the same kind of resources in either the same, or even better, different, environments.

Declaring a module is simple. Let’s look at the VPC module from the example:

The location of the module is specified with the source parameter. The style of the parameter will dictate what kind of behaviour TF will undertake to get the module.

The rest of the options here are module parameters, which translate to variables within the module. Note that any variable that does not have a default value in the module is a required parameter, and Terraform will not start if these are not supplied.

The last item that should be mentioned is regarding versioning. Most module sources that work off of source control have a versioning parameter you can supply to get a revision or tag – with Git and GitHub sources, this is ref, which can translate to most Git references, be it a branch, or tag.

Versioning is a great way to keep things under control. You might find yourself iterating very fast on certain modules as you learn more about Terraform or your internal infrastructure design patterns change – versioning your modules ensures that you don’t need to constantly refactor otherwise stable stacks.

Module Tips and Tricks

Terraform and HCL is a work in progress, and there may be some things that seem like they may make sense that don’t necessarily work 100% – yet. There are some things that you might want to keep in mind when you are designing your modules that may reduce the complexity that ultimately gets presented to the user:

Use Data Sources

Terraform 0.7+’s data sources feature can go a long way in reducing the amount of data needs to go in to your module.

In this project, data sources are used for things such as obtaining VPC IDs from subnets (aws_subnet) and getting the security groups assigned to an ALB (using the aws_alb_listener and aws_alb data sources chained together). This allows us to create ALBs based off of subnet ID alone, and attach auto-scaling groups to ALBs with knowing only the listener ARN that we need to attach to.

Exploit Zero Values and Defaults

Terraform follows the rules of the language it was created in regarding zero values. Hence, most of the time, supplying an empty parameter is the same as supplying none at all.

This can be advantageous when designing a module to support different kinds of scenarios. For example, the alb module supports TLS via supplying a certificate ARN. Here is the variable declaration:

And here it is referenced in the listener block:

Now, when this module parameter is not supplied, its default value becomes an empty string, which is passed in to aws_alb_listener.alb_listener. This is, most times, exactly the same as if the parameter is not passed in at all. This allows you to not have to worry about this parameter when you just want to use HTTP on this endpoint (the default for the ALB module as a whole).

Pseudo-Conditional Logic

Terraform does not support conditional logic yet, but through creative use of count and interpolation, one can create semi-conditional logic in your resources.

Consider the fact that the terraform_aws_autoscaling module supports the ability to attach the ASG to an ALB, but does not explicit require it. How can you get away with that, though?

To get the answer, check one of the ALB resources in the module:

Here, we make use of the map interpolation function, nested in a lookup function to provide essentially an if/then/else control structure. This is used to control a resource’s instance count, adding an instance if var.enable_albis true, and completely removing the resource from the graph otherwise.

This conditional logic does not necessarily need to be limited to count either. Let’s go back to the aws_alb_listener.alb_listener resource in the ALB module, looking at a different parameter:

Here, we are using this trick to supply the correct SSL policy to the listener if the listener protocol is not HTTP. If it is, we supply the zero value, which as mentioned before, makes it as if the value was never supplied.

Module Limitations

Terraform does have some not-necessarily-obvious limitations that you will want to keep in mind when designing both modules and Terraform code in general. Here are a couple:

Count Cannot be Computed

This is a big one that can really get you when you are writing modules. Consider the following scenario that totally did not happen to me even though I knew of of such things beforehand 😉

  • An ALB listener is created with aws_alb_listener
  • The arn of this resource is passed as an output
  • That output is used as both the ARN to attach an auto-scaling group to, and the pseudo-conditional in the ALB-related resources’ count parameter

What happens? You get this lovely message:

value of 'count' cannot be computed

Actually, it used to be worse (a strconv error was displayed instead), but luckily that changed recently.

Unfortunately, there is no nice way to work around this right now. Extra parameters need to be supplied or you need to structure your modules in way that avoids computed values being passed into count directives in your workflow. (This is pretty much exactly why the terraform_aws_asg module has a enable_alb parameter).

Complex Structures and Zero Values

Complex structures are not necessarily good candidates for zero values, even though it may seem like a good idea. But by defining a complex structure in a resource, you are by nature supplying it a non-zero value, even if most of the fields you supply are empty.

Most resources don’t handle this scenario gracefully, so it’s best to avoid using complex structures in a scenario where you may be designing a module for re-use, and expect that you won’t be using the functionality defined by such a structure often.

The Application in Brief

As our focus in this article is on Terraform modules, and not on other parts of the pattern such as using Packer or Chef to build an AMI, we will only touch up briefly on the non-Terraform parts of this project, so that we can focus on the Terraform code and the AWS resources that it is setting up.

The Gem

The Ruby gem in this project is a small “hello world” application running with Sinatra. This is self-contained within this project and mainly exists to give us an artifact to put on our base AMI to send to the auto-scaling group.

The server prints out the system’s hostname when fetched. This will allow us to see each node in action as we boot things up.

Packer

The built gem is loaded on to an AMI using Packer, for which the code is contained within packer/ami.json. We use chef-solo as a provisioner, which works off a self-contained cookbook named packer_payload in the cookbooks directory. This allows us a bit more of a higher-level workflow than we would have simply with shell scripts, including the ability to better integration test things and also possibly support multiple build targets.

Note that the Packer configuration takes advantage of a new Packer 0.12.0 feature that allows us to fetch an AMI to use as the base right from Packer. This is the source_ami_filter directive. Before Packer 0.12.0, you would have needed to resort to a helper, such as ubuntu_ami.sh, to get the AMI for you.

The Rakefile

The Rakefile is the build runner. It has tasks for Packer (ami), Terraform (infrastructure), and Test Kitchen (kitchen). It also has prerequisite tasks to stage cookbooks (berks_cookbooks), and Terraform modules (tf_modules). It’s necessary to pre-fetch modules when they are being used in Terraform – normally this is handled by terraform get, but the tf_modules task does this for you.

It also handles some parameterization of Terraform commands, which allows us to specify when we want to perform something else other than an apply in Terraform, or use a different configuration.

All of this is in addition to standard Bundler gem tasks like build, etc. Note that install and release tasks have been explicitly disabled so that you don’t install or release the gem by mistake.

The Terraform Modules

Now that we have that out of the way, we can talk about the fun stuff!

As mentioned at the start of the article, This project has 4 different Terraform modules. Also as mentioned, one of them (the Security Group module) is hidden from the end user, as it is consumed by two of the parent modules to create security groups to work with. This exploits the fact that Terraform can, of course, nest modules within each other, allowing for any level of re-usability when designing a module layout.

The AWS VPC Module

The first module, terraform_aws_vpc, creates not only a VPC, but also public subnets as well, complete with route tables and internet gateway attachments.

We’ve already hidden a decent amount of complexity just by doing this, but as an added bonus, redundancy is baked right into the module by distributing any network addresses passed in as subnets to the module across all availability zones available in any particular region via the aws_availability_zones data source. This process does not require previous knowledge of the zones available to the account.

The module passes out pertinent information, such as the VPC ID, the ID of the default network ACL, the created subnet IDs, the availability zones for those subnets as a map, and the ID of the route table created.

The ALB Module

The second module, terraform_aws_alb allows for the creation of AWS Application Load Balancers. If all you need is the defaults, use of this module is extremely simple, creating an ALB that will answer requests on port 80. A default target group is also created that can be used if you don’t have anything else mapped, but we want to use this with our auto-scaling group.

The Auto Scaling Module

The third module, terraform_aws_asg, is arguably the most complex of the three that we see in the sample configuration, but even at that, its required options are very slim.

The beauty of this module is that, thanks to all the aforementioned logic, you can attach more than one ASG to the same ALB with different path patterns (mentioned below), or not attach it to an ALB at all! This allows this same module to be used for a number of scenarios. This is on top of the plethora of options available to you to tune, such as CPU thresholds, health check details, and session stickiness.

Another thing to note is how the AMI for the launch configuration is being fetched from within this module. We work off the tag that we used within Packer, which is supplied as a module variable. This is then searched for within the module via an aws_ami data source. This means that no code or variables need to change when the AMI is updated – the next Terraform run will pick up the most recent AMI with the tag.

Lastly, this module supports the rolling update mechanism laid out by Paul Hinze in this post oh so long ago now. When a new AMI is detected and the auto-scaling group needs to be updated, Terraform will bring up the new ASG, attach it, wait for it to have minimum capacity, and then bring down the old one.

The Security Group Module

The last module to be mentioned, terraform_aws_security_group, is not shown anywhere in our example, but is actually used by the ALB and ASG modules to create Security Groups.

Not only does it create security groups though – it also allows for the creation of 2 kinds of ICMP allow rules. One for all ICMP, if you so choose, but more importantly, allow rules for ICMP type 3 (host unreachable) are always created, as this is how path MTU discovery works. Without this, we might end up with unnecessarily degraded performance.

Give it a Shot

After all this talk about the internals of the project and the Terraform code, you might be eager to bring this up and see it working. Let’s do that now.

Assuming you have the project cloned and AWS credentials set appropriately, do the following:

  • Run bundle install --binstubs --path vendor/bundle to load the project’s Ruby dependencies.
  • Run bundle exec rake ami. This builds the AMI.
  • Run bundle exec rake infrastructure. This will deploy the project.

After this is done, Terraform should return a alb_hostname value to you. You can now load this up in your browser. Load it once, then wait about 1 second, then load it again! Or even better, just run the following in a prompt:

while true; do curl http://ALBHOST/; sleep 1; done

And watch the hostname change between the two hosts.

Tearing it Down

Once you are done, you can destroy the project simply by passing a TF_CMD environment variable in to rake with the destroy command:

TF_CMD=destroy bundle exec rake infrastructure

And that’s it! Note that this does not delete the AMI artifact, you will need to do that yourself.

More Fun

Finally, a few items for the road. These are things that are otherwise important to note or should prove to be helpful in realizing how powerful Terraform modules can be.

Tags

You may have noticed the modules have a project_path parameter that is filled out in the example with the path to the project in GitHub. This is something that I think is important for proper AWS resource management.

Several of our resources have machine-generated names or IDs which make them hard to track on their own. Having a easy-to-reference tag alleviates that. Having the tag reference the project that consumes the resource is even better – I don’t think it gets much clearer than that.

SSL/TLS for the ALB

Try this: create a certificate using Certificate Manager, and change the alb module to the following:

Better yet, see the example here. This can be run with the following command:

And destroyed with:

You now have SSL for your ALB! Of course, you will need to point DNS to the ALB (either via external DNS, CNAME records, or Route 53 alias records – the example includes this), but it’s that easy to change the ALB into an SSL load balancer.

Adding a Second ASG

You can also use the ASG module to create two auto-scaling groups.

There is an example for the above here. Again, run it with:

And destroy it with:

You now have two auto-scaling groups, one handling requests for /foo/*, and one handling requests for /bar/*. Give it a go by reloading each URL and see the unique instances you get for each.

Acknowledgments

I would like to take a moment to thank PayByPhone for allowing me to use their existing Terraform modules as the basis for the publicly available ones at https://github.com/paybyphone. Writing this article would have been a lot more painful without them!

Also thanks to my editors, Anthony Elizondo and Andrew Langhorn for for their feedback and help with this article, and the AWS Advent Team for the chance to stand on their soapbox for my 15 minutes! 🙂

About the Author:

picture of author Chris MarchesiChris Marchesi (@vancluever) is a Systems Engineer working out of Vancouver, BC, Canada. He currently works for PayByPhone, designing tools and patterns to help its engineers and developers work with AWS. He is also a regular contributor to the Terraform project. You can view his work at https://github.com/vancluever, and also his previous articles at https://vancluevertech.com/.

About the Editors:

Andrew Langhorn is a senior consultant at ThoughtWorks. He works with clients large and small on all sorts of infrastructure, security and performance problems. Previously, he was up to no good helping build, manage and operate the infrastructure behind GOV.UK, the simpler, clearer and faster way to access UK Government services and information. He lives in Manchester, England, with his beloved gin collection, blogs at ajlanghorn.com, and is a firm believer that mince pies aren’t to be eaten before December 1st.

Anthony Elizondo is a SRE at Adobe. He enjoys making things, breaking things, and burritos. You can find him at http://twitter.com/complexsplit