As a startup, an organization thrives by breaking rules, challenging the status quo, and standing for all that is against the norm. The same rules don’t apply once the same organization grows, matures, becomes popular, gains a long list of clients, and expands to a global footprint. With scale and growth comes the need for reliability, consistency, being able to deliver the same level of service to all customers, and keeping promises made to customers. At this stage, application patterns become indispensable to an organization’s day-to-day functioning.
Support of the application now and long-term
Mid- to large-size organizations typically deal with numerous internal-only applications and external vendor applications. These applications are changed and updated regularly. To support the applications’ needs, and effectively manage them, organizations need a change management system in place.
A service like AWS Config helps to audit AWS services that power applications so that there’s increased visibility. It tracks changes made by users and applications, and presents a clear picture of how these changes impact AWS resources.
Enabling Shift-left without additional overhead
DevOps bring together Dev, QA, and Ops into smaller, cross-functional teams. The goal is to break down silos between teams, facilitate collaboration, and drive better results faster. Accordingly, shift-left is a tactic used to encourage QA and Ops teams to play a more pivotal role in the initial Dev stages of the pipeline.
The benefits are many. QA brings their experience of testing the application to its limits and informs about what’s feasible to implement. Ops chimes in with concerns and things to watch for once deployed. While shift-left is great from a team standpoint, it can meet with hurdles and can fail if communication patterns are random, and ownership of each step is not clearly defined.
Application patterns encourage systematizing this collaboration between teams. Patterns help to define the type of infrastructure to be used, their configuration, and the kind of tools that fit in with the team’s requirements. Application patterns guide decisions and help to make the right choices, and sometimes compromises, at every step.
Supporting the advancements in Open-Source without fear of tool attrition
There is an explosion of open source tools today. If DevOps teams are attracted to the next shiny new open source tool, they’ll soon find themselves overwhelmed with tools they don’t use and that slow them down.
Open source tools evolve quickly, and their popularity rises and falls with the times. One look at the open source monitoring space will show you that older tools like Nagios and Zabbix are now becoming less relevant, and modern container-aware monitoring tools like Prometheus are taking their place.
AWS supports the use of the top open source tools; for example, Elasticsearch. The AWS Elasticsearch service integrates seamlessly with Kibana for visualization and delivers the ELK stack without the maintenance.
Application patterns enable you to define a strategy for tool adoption. You may find the best open source tool in the world, but what’s the point if you can’t use it in your toolchain, or if it slows down the pace of operations? The popular DevOps mantra of people, processes, and then tools holds true here.
Value Stream Management
Value stream mapping is about visualizing the flow of value from an organization to its customers. In simple words, it’s about taking stock of what you have to offer to customers, and monitoring how your offerings change over time.
Value flows outward to customers, as well as internally between employees and systems. For example, in the context of DevOps, it helps to map the value of Ops to Dev and QA. As these teams are each others’ internal customers, knowing what the value stream is can help remove bottlenecks and drive greater efficiency.
Building a team and culture first
AWS is a great place to build team culture as it is expansive and includes services for pretty much anything you’ll ever need. You can find tools like CodePipeline to quicken development pipelines, to make sure everyone on the team is informed of important changes using CloudWatch and SNS queues, and to automate common tasks with Lambda.
Rather than jumping feet first into AWS and then figuring out how it all works, it pays to first define application patterns and team culture that will govern the way you use AWS. Patterns and culture are closely related. If culture is about the people, application patterns are about the infrastructure and technology stack being used by people.
Whether you’re yet to move to AWS, or are already on board but not getting the most out of it, application patterns help evolve the way you manage applications in AWS. Application patterns help scale applications over the long term, they enable shift-left for DevOps teams without the friction of overhead. Application patterns make it possible to adopt the right open source tools and find success with them. By using application patterns you can visualize the entire process and drive great efficiency, and finally, they support great team culture within DevOps teams.
DevOps teams that run their operations predominantly on AWS need not fly blind. Application patterns bring greater visibility, control, collaboration, and ultimately value.
This post originally appeared on devops.com.