AWS is at the forefront of cloud providers. Launched in 2006, with SQS and EC2, Amazon quickly became the biggest IaaS provider. They have the biggest infrastructure and ecosystem, with constant additions of new features and services. In 2018, they passed more than a million active customers. Over the last few years, they have managed to change peoples mindsets about the cloud, and deploying new services to this is now the norm. Using AWS's managed tools and services is a way to drastically improve your productivity and keep your team lean. Amazon continually listens to its customer's feedback and looks at the market trends. Therefore, as the DevOps movement started to get established, Amazon released a number of new services tailored toward implementing some DevOps best practices. In this book, you will see how these services synergize with the DevOps culture.
Amazon services are like Lego pieces. If you can picture your final product, then you can explore the different services and start combining them, in order to build the stack needed to quickly and efficiently build your product. Of course, in this case, the if is a big if, and, unlike Lego, understanding what each piece can do is a lot less visual and colorful. That is why this book is written in a very practical way; throughout the different chapters, we are going to take a web application and deploy it like it's our core product. You will see how to scale the infrastructure supporting it, so that millions of people can use it, and also so that you can make it more secure. And, of course, we will do this following DevOps best practices. By going through that exercise, you will learn how AWS provides a number of managed services and systems to perform a number of common tasks, such as computing, networking, load balancing, storing data, monitoring, programmatically managing infrastructure and deployment, caching, and queuing.
As you saw earlier in this chapter, having a DevOps culture is about rethinking how engineering teams work together, by breaking the development and operations silos and bringing a new set of tools, in order to implement the best practices. AWS helps to accomplish this in many different ways. For some developers, the world of operations can be scary and confusing, but if you want better cooperation between engineers, it is important to expose every aspect of running a service to the entire engineering organization.
As an operations engineer, you can't have a gatekeeper mentality towards developers. Instead, it's better to make them comfortable by accessing production and working on the different components of the platform. A good way to get started with this is in the AWS console, as follows:
While a bit overwhelming, this is still a much better experience for people who are unfamiliar with navigating this web interface, rather than referring to constantly out-of-date documentation, using SSH and random plays in order to discover the topology and configuration of the service. Of course, as your expertise grows and your application becomes more complex, the need to operate it faster increases, and the web interface starts to show some weaknesses. To get around this issue, AWS provides a very DevOps-friendly alternative. An API is accessible through a command-line tool and a number of SDKs (including Java, JavaScript, Python, .NET, PHP, Ruby Go, and C++). These SDKs let you administrate and use the managed services. Finally, as you saw in the previous section, AWS offers a number of services that fit DevOps methodologies and will ultimately allow us to implement complex solutions in no time.
Some of the major services that you will use, at the computing level are Amazon Elastic Compute Cloud (EC2), the service to create virtual servers. Later, as you start to look into how to scale the infrastructure, you will discover Amazon EC2 Auto Scaling, a service that lets you scale pools on EC2 instances, in order to handle traffic spikes and host failures. You will also explore the concept of containers with Docker, through Amazon Elastic ContainerService (ECS). In addition to this, you will create and deploy your application using AWS Elastic Beanstalk, with which you retain full control over the AWS resources powering your application; you can access the underlying resources at any time. Lastly, you will create serverless functions through AWS Lambda, to run custom code without having to host it on our servers. To implement your continuous integration and continuous deployment system, you will rely on the following four services:
- AWS Simple Storage Service (S3): This is the object store service that will allow us to store our artifacts
- AWS CodeBuild: This will let us test our code
- AWS CodeDeploy: This will let us deploy artifacts to our EC2 instances
- AWS CodePipeline: This will let us orchestrate how our code is built, tested, and deployed across environments
To monitor and measure everything, you will rely on AWS CloudWatch, and later, on ElasticSearch/Kibana, to collect, index, and visualize metrics and logs. To stream some of our data to these services, you will rely on AWS Kinesis. To send email and SMS alerts, you will use the Amazon SNS service. For infrastructure management, you will heavily rely on AWS CloudFormation, which provides the ability to create templates of infrastructures. In the end, as you explore ways to better secure our infrastructure, you will encounter Amazon Inspector and AWS Trusted Advisor, and you will explore the IAM and the VPC services in more detail.