The world of software has been constantly evolving over the years. What it started out to be is not what it currently is. In the beginning, software was built with a different mission. It was optimized for cost and not speed. It wasn’t made with developer experience and innovation in mind. The rise in containerized applications, microservices, and the ilk has completely altered the software ecosystem. The complexities of the modern cloud-native world, even with its self-service capabilities have bought about new challenges that have prompted the need for a shift to platform engineering.
Product vs platform
A product is a consumable piece of software with the primary purpose of enabling users to carry out activities that create value. A platform, on the other hand, is a system that allows products to communicate with each other. It connects multiple user groups and facilitates interactions between them. Platforms decrease engineering friction and help with the distribution of apps.
What is platform engineering?
Platform engineering is a concept that helps bridge the gap between Dev and Ops teams. A platform engineering model, also known as, an internal developer platform (IDP) covers all the operational necessities of the life cycle of an application. It allows platform engineers to build toolchains that combine developer self-service capabilities and abstraction. Platform engineering provides paths of least resistance thus making it easy to complete tasks and deliver products to consumers easily and rapidly.
The concept is unique in that it has the holy trifecta of built-in security practices, recommended tools and preserves developer freedom by enabling them to stray from a path when required. Platform engineering allows developers to do their jobs without being affected by the operations team. It also allows the operations team to ensure the necessary standards are applied and relevant things like backups, scaling, security policies, etc., are in check without burdening the developers.
A platform engineering model helps onboard developers without having to teach them a new skill by allowing them to focus on their code while other systems figure out the complex parts like how the code will be deployed or how to manage configuration across environments.
5 Best practices when transitioning to a platform engineering model
1. Listen to your developers
Your developers are your primary customers. You need to understand what you can do to help improve the developer experience. This means you need to talk to your developers to figure out what challenges they are facing and consider how the platform will help drive productivity. To build a successful platform engineering model, you need to value the feedback you get from your developers and make sure that your platform is solving real problems they face.
2. FOSS is the way to go
A platform should be vendor-agnostic for it to be truly successful and scalable over the longterm. This requires leveraging open source software to build the platform with. Make it a point to always prefer open source. There aren’t many vendor distributions that will fit your exact requirements but there are engineers with in-depth knowledge and understanding that can leverage it to fit into your exact requirements. Therefore, it is easier to create your own cloud management system built on free and open source software. This way when something is broken, or a vendor no longer is a good fit for your organization, you have the option to switch to another vendor.
3. Automation and self service
Developers want to be able to get their code running with a minimal amount of dependency on other people. The more complexity a developer has to deal with in order to get something done, the more mistakes they are likely going to make before they achieve what they want. It is important to have a “you build it, you run it” type of concept in mind when building a platform engineering model in order to allow the developers enough freedom to do things the way and at a speed that facilitates the most productivity.
4. Structure is key
With self-service comes chaos. This is because one way of doing self-service is by giving everyone access to everything and this can be disastrous. Therefore, your model needs to have a standardized way of provisioning and configuring resources. Standardization helps speed things up and achieve the most with the least variation across different services. It ensures that there is uniformity in infrastructure across projects so that teams can easily grasp what is going on without having to relearn a whole stack from the very basics. The platform model allows you to give developers just enough resources to run and manage the applications they build. This reduces the attack surface and builds security into the process.
5. Continuous improvement is a necessity
There is always going to be an eternal construction site for renovations. You need to constantly renew your setup and reinvent core technology by following the latest upstream development. Adding new features in a way that the amount of internal coding time is significantly reduced and quality is significantly increased should be a priority. There needs to be a balance between enterprise requirements for stability and developer need for leading-edge technology.
Conclusion
Transitioning to a platform engineering model helps avoid babysitting your pipeline and each system to ensure things are working the way they are supposed to. It allows you to focus not just on solving the problems of today but try to predict where you are going to be moving in the future. Platform engineering models streamline multiple processes and enable you to focus on what you want to achieve with the system.
If you have questions related to this topic, feel free to book a meeting with one of our solutions experts, mail to sales@amazic.com.
