Modern platform engineering in an AI-led software development era (Part 3)

In part one of our series on modern platform engineering, we examined the changing landscape and key drivers of platform engineering, including a greater focus on cloud platforms, the synergy between them and DevOps, and how the two can help your organization. We also looked at technologies and processes that have consolidated in the industry regarding platform engineering, and we explained how the concept has built upon all the past practices commonly used in the DevOps space to demonstrate a true evolution in design, implementation, and thinking. 

In part two, we explored platform engineering’s role in driving an organization's competitive advantage. We described the four key benefits of future-proofing your software development and operations with a modern platform: Optimizing operational efficiency, agility, scalability, risk reduction, reliability, cost optimization, and resource management. 

In part three (and the conclusion) of the series, we apply our learning to consider the future of platform engineering and DevOps. We discuss the rise in platform maturity and its treatment as a product, as well as how AI-led software development can enhance capabilities.

What is the future of platform engineering and DevOps?

At the current state of our journey in platform engineering, we need to ensure we have a modular platform that allows us to plug in new capabilities quickly. It may not always be a production-grade capability, but we are ready to release it to everyone. Still, we need to be able to collaborate with stream-aligned teams to build new capabilities that support emerging trends and technologies.

If our platform is in a good and modular state, we can even run tests and trials on new or refined capabilities to ensure that we keep supporting our development teams in the best possible way. When we have enough feedback on the current beta capability, which has been tested and tried, it should become the new standard for that capability. It takes time and effort to make the good abstractions needed to reach that level of flexibility, but it will be worth every penny.

When we have a good modular platform, it should be highly available through self-service. This not only frees up time for the platform engineers to build and refine capabilities but also reduces the waiting time for the development teams. We’ve seen multiple cases where we have gone from a manual process that took multiple weeks to self-service that runs within minutes.

A rise in maturity

In general, we’re seeing a rise in maturity when it comes to platforms. While many are still formalising their platform, we’re seeing more and more focus on reaching the self-service level. This grants the teams more flexibility when coming up with new ways to build their products, and in the end, this leaves the whole organization more competitive if the results match their end-users' expectations and needs. While reaching the market is good, we’re seeing higher demands for better utilization of the resources at hand. This comes from the more competitive market, but it comes hand in hand with the wish to be a more sustainable organization.

Whether you are in the stage of formalizing your platform or moving the maturity levels of your platform, we highly encourage you to consider working with the platform as a product if you aren’t already. This means bringing in the mindset of a start-up/scale-up to determine if there is a need in the market for what you are building, and that you have a go-to-market strategy for the next capability you are bringing to the table. Suppose there is no fit in the market. In that case, it doesn’t matter if the capability was fairly fast to build, because when you have released it and onboarded your customers, you are obligated to maintain it until you have a better offering.

Next steps to become AI Native

One of the many natural evolutions we have seen in the industry, for sure, is the rise of artificial intelligence (AI). We’ve already seen many of our clients embrace AI coding assistants for software engineers and infrastructure and platform engineers. Taking your platform to the next level with good abstractions and great modularity is the next step on your journey to success with integrating AI in platforms. Resulting efficiencies free up development teams’ time, allowing for more research projects and integrations. If the platform is set up well, it will ensure you retain all of the good practices that have come to the market in recent years—AI included.

But remember: Figure out where AI will fit your business well. While everything in the market has gotten an AI label, we recommend exploratory phases that can reveal the appropriate places to apply AI in your organization. Hackathons with mixed groups that include software engineers, business representatives, architects, and product owners are a very efficient way to discover some of the shortcomings of existing platforms and identify opportunities to add capabilities. We are firm believers in doing rapid research loops and running AI workloads on your platform, to be able to review results quickly and decide on future investments.

Can platform engineering be modernized?

Since the dawn of large-scale computing, we’ve only seen the pace pick up, and this has been no different in recent years. These days, companies face stronger competition, leading to more pressure on organizations to succeed. Platform engineering may be the key to your organization's success, freeing up more time for core competencies and creative thinking.

For many years, the freedom of choosing your tools and what works for you has been a key message to keep developers happy and focused. Gaining flexibility in the composition of teams or working groups requires less cognitive load on onboarding developers to a potential new business domain. Shifting from a highly explorative period, we’ve seen a big consolidation of tools and practices, which still gives enough headspace for individual teams to adjust to their needs.

Consider this: When looking at your current platform maturity, there are many directions you can choose to go in. Whether you are at the step of formalising a team to build and maintain your platform, if you are ready to build managed offerings for the developers, or you are at a place where you can enable more custom solutions to leverage standard parts of the platform. In the constantly evolving platform sphere, there is no easy day to choose the next step, so it is important to keep treating the platform as a product. Good products make sure there is a market-fit for what is being built, and along with that comes a go-to-market strategy for the new bits and bobs that the world will see.

How we can help

At Eficode, we’re more than happy to help you on your platform engineering journey, whether defining your infrastructure needs, building your platform, integrating AI, or giving you more food for thought. Our experts are ready to help you optimize your DevOps setup and become AI Native in ways appropriate for your organization and your long-term success.