Faster Delivery = Happy Users
Automated Process = Fewer Errors
Standards = Cost Reduction
Order Visibility = Confidence
Linking Systems = Efficiency
Achieving rapid application development is not just about tools. In order to adapt existing processes, skillsets and technologies to DevOps, it is necessary to create the right culture.
DevOps won’t work if such silos exist and the only interaction between each team is the creation of a ticket. It is essential, therefore, to break down those barriers to DevOps is to gain ground. Team members have to be willing share what they learn in order to save others from doing duplicate work.
Automation plays an important role in the DevOps movement too. It eliminates much of the manual drudgery to speed deployments and reduce errors. However, automation shouldn’t be done for its own sake. Automation should be aligned to the needs of the development team. Also, its success should be based on the key metrics that matter most.
The Top 3 reasons why you should automate your AWS environment article explains the benefits of automation. But first, let’s focus on how automation is accomplished.
In the DevOps world, this means AWS elements such as web servers can be made once and then that exact configuration can be used every time.
However, the great thing about AWS is that there are multiple ways to accomplish the same result. Sometimes only foundational components of the base Amazon image are taken and the bulk of the application is built from scratch each time.
The manual approach can be used if speed is not of paramount importance. Another approach is to have some major parts pre-prepared while the rest is custom built. Alternatively, the vast majority of the application components can be pre-built with only minor additions to complete the DevOps process. This latter case is the quickest to deploy.
Of course, this demands quite a change in approach. Some IT departments are focused on keeping each physical server up and running, and in the event of an issue, there mentality is to troubleshoot it and get it running again.
But a different mentality is required with DevOps on AWS. Instead of caring about servers, the priority is the end user experience. In that case, the approach is to not try to fix a server, but to replace it and figure out what went wrong after the fact.
By tuning each infrastructure element and turning it into one or more scripts, it becomes possible to reuse and deploy infrastructure the same way every time. All the developer has to do is take various snippets of infrastructure from the application repository, (secure in the knowledge that those represent the very latest iteration) and the infrastructure can deployed the same way every time. AWS facilitates the process via elements such as Elastic Beanstalk, OpsWorks, CodePipeline and Code Deploy.
For example, Beanstalk is a high level service that allows you to abstract out all of the infrastructure requirements on the Amazon platform such as EC2 instances, load balancing, and availability zones. It takes care of all those things, enabling the developer to concentrate purely on custom coding. In essence, BeanStalk is an application management platform that offers plenty of flexibility. It even takes care of capacity planning and health monitoring. It is supported by Amazon OpsWorks, which is a configuration management tool for fine grained control of apps.
At a more granular level, Code Pipeline helps developers build a pipeline to deploy code on AWS. The code is checked then pushed out into another element known as Code Deploy, which rolls out the parts of the application in the right sequence.
For more information, on how you can automate AWS with Softchoice to unlock the value of your infrastructure, visit our Automate AWS landing page to browse Softchoice dashboard and Cloud Formation demos, three case studies, blog articles and discover our Keystone Managed Service for AWS to help you pick the perfect solution for your organization.