The common mistakes involve the development environment, because services are collocated on the same servers, or there isn't the same level of security. As a consequence, services can communicate with one another in development, but not in production.
The development environment may be running a newer version of a service, which has new features that the production doesn't have yet; or it could be simply a question of scale. Perhaps the dataset used in development isn't as big as that of production, and scaling issues will crop up once the new code is out in production. One of the biggest dilemmas in information technology is miscommunication. In other words, the product that you are building reflects the communication of your organization.
A lot of the time, problems don't come from the technology, but from the people and organizations surrounding the technology. If there is dysfunction among your developers and operations team in the organization, this will show. In a DevOps culture, developers and operations have a different mindset.
They help to break down the silos that surround those teams, by sharing responsibilities and adopting similar methodologies to improve productivity. Together, they try to automate whatever is possible not everything, as not everything can be automated in a single go and use metrics to measure their success. As we have noted, a DevOps culture relies on a certain number of principles.
These principles are to source control version control everything, automate whatever is possible, and measure everything. Revision control software has been around for many decades now, but too often, only the product code is checked.
When practicing DevOps, not only is the application code checked, but configurations, tests, documentation, and all of the infrastructure automation needed to deploy the application in all environments, are also checked. Automated software testing predates the history of DevOps, but it is a good starting point. Too often, developers focus on implementing features and forget to add a test to their code. In a DevOps environment, developers are responsible for adding proper testing to their code.
QA teams can still exist; however, similar to other engineering teams, they work on building automation around testing. This topic could fill its own book, but in a nutshell, when developing code, keep in mind that there are four levels of testing automation to focus on, in order to successfully implement DevOps:. In the last few decades, the size of the average infrastructure and the complexity of the stack have skyrocketed.
Managing infrastructure on an ad-hoc basis, as was once possible, is very error-prone. In a DevOps culture, the provisioning and configuration of servers, networks, and services in general, are performed through automation. Configuration management is often what the DevOps movement is known for. However, as you know, this is just a small piece of a big puzzle.
As you now, it is easier to write software in small chunks and deploy the new chunks as soon as possible, to make sure that they are working. To get there, companies practicing DevOps rely on continuous integration and continuous deployment pipelines.
Whenever a new chunk of code is ready, the continuous integration pipeline kicks off. Through an automated testing system, the new code is run through all of the relevant, available tests.
If the new code shows no obvious regression, it is considered valid and can be merged to the main code base. At that point, without further involvement from the developer, a new version of the service or application that includes those new changes will be created and handed off to a system called a continuous deployment system. The continuous deployment system will take the new builds and automatically deploy them to the different environments that are available.
Depending on the complexity of the deployment pipeline, this might include a staging environment, an integration environment, and sometimes, a pre-production environment. Ultimately, if everything goes as planned without any manual intervention , this new build will get deployed to production. One aspect about practicing continuous integration and continuous deployment that often gets misunderstood is that new features don't have to be accessible to users as soon as they are developed. In this paradigm, developers heavily rely on feature flagging and dark launches.
Essentially, whenever you develop new code and want to hide it from the end users, you set a flag in your service configuration to describe who gets access to the new feature, and how. At the engineering level, by dark launching a new feature this way, you can send production traffic to the service, but hide it from the UI, to see the impact it has on your database or on performance, for example. At the product level, you can decide to enable the new feature for only a small percentage of your users, to see if the new feature is working correctly and if the users who have access to the new feature are more engaged than the control group, for example.
Measuring everything is the last major principle that DevOps-driven companies adopt. As Edwards Deming said, you can't improve what you can't measure. DevOps is an ever-evolving process and methodology that feeds off those metrics to assess and improve the overall quality of the product and the team working on it. From a tooling and operating standpoint, the following are some of the metrics most organizations look at:. At the organizational level, it is also interesting to measure the impact of shifting to a DevOps culture.
While this is a lot harder to measure, you can consider the following points:. As you just learned, having a DevOps culture means, first of all, changing the traditional mindset that developers and operations are two separate silos, and making the teams collaborate more, during all phases of the software development life cycle.
In addition to a new mindset, DevOps culture requires a specific set of tools geared toward automation, deployment, and monitoring:. AWS is at the forefront of cloud providers. They have the biggest infrastructure and ecosystem, with constant additions of new features and services. In , 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.
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. 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. If You feel that this book is belong to you and you want to unpublish it, Please Contact us. Download e-Book. Posted on. Page Count. Veselin Kantsev,. Bring the best out of DevOps and build, deploy, and maintain applications on AWS Book Description Knowing how to adopt DevOps in your organization is becoming an increasingly important skill for developers, whether you work for a start-up, an SMB, or an enterprise.
If You feel that this book is belong to you and you want to unpublish it, Please Contact us. Download e-Book. Posted on. Page Count. Yogesh Raheja,. Scale and maintain outstanding performance in your AWS-based infrastructure using DevOps principles Key Features Implement continuous integration and continuous deployment pipelines on AWS Gain insight from an expert who has worked with Silicon Valley's most high-profile companies Implement DevOps principles to take full advantage of the AWS stack and services Book Description The DevOps movement has transformed the way modern tech companies work.
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