Why 2024 May Be the Breakthrough Year for Platform Engineering

Looking to accelerate the delivery of applications, and the pace at which they generate business value, a growing number are enterprises are turning to platform engineering. When properly deployed, platform engineering improves developer productivity by supplying self-service capabilities within an automated infrastructure.

Platform engineering addresses critical challenges posed by modern hybrid and multi-cloud environments as well as application modernization, says Ken Johnson, vice president of product management at open source software products provider Red Hat in an email interview. "By curating tools and providing policy-based deployment automation for distributed development teams, platform engineers can manage the right balance of control and flexibility needed for their organization’s business objectives."

Growing Interest

Organizations are wrestling with the productivity drag complexity creates. "Application developers spend too much time on context switching and non-development tasks," Johnson observes. "Time pressures can lead to negative impacts on software quality and can create an unmanageable load and risk for operations."

Platform engineering allows teams to choose the tools that best serve their needs and then use them consistently and collaboratively across application development teams and throughout development, deployment and management cycles. "In short, platform engineering has emerged as a pivotal approach to scale DevOps across organizations, simplifying developers' interaction with complex infrastructure, and allowing them to do what they do best: build better code," Johnson says.

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Platform engineering's growing popularity is the result of its ability to drive the convergence of various business lines toward common efficiency and productivity models, says Ignacio Segovia, chief architect, product engineering, with data and digital engineering solutions provider Altimetrik. "This convergence includes elements such as a single source of truth backed by a mature data mesh architecture, sensible AI strategies, modernized software engineering models, faster iteration, and excellent developer experience and tooling," he notes via email.

Organizations adopting platform engineering should ensure that the approach's technology drivers will be supported by existing business-accelerating processes, Segovia says. These elements include programmatic design systems, taxonomy-driven products, rapid prototyping, and pro code solutions, all of which are integral to modern, agile product development processes. "Platform engineering serves as the backbone that supports and enhances these elements."

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An effective run-ahead approach will lead to a successful platform engineering strategy, Segovia says. "This process is designed to ensure that teams are fully prepared to engineer solutions that align with business expectations," he notes. It also should emphasize aligning all elements -- including business requirements, product design, architecture, and engineering solutions -- to deliver immediate business value. A run-ahead approach focuses on manageable, bite-sized outcomes, allowing for a methodical progression that minimizes unexpected deviations in timelines or budgets. "This is an important component for digital businesses seeking effective platform engineering capabilities, improved developer experiences, and productivity."

Facing Challenges

Platform engineering requires evolutions in both design and customization. "It takes time to curate and tailor a critical mass of capabilities that application and ops teams need," Johnson says. "Once initiated, the platform will require ongoing iteration to keep pace with business needs and technological evolution." Internal platforms should be managed like a product, using dedicated teams, feedback loops, and consistent updates to maintain their benefit to the organization. "This last point is really an opportunity more than a drawback, but it does require a new way of thinking for many."

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Every business is a software business, and the need for software engineering is exploding. "Generative AI, and AI overall, are redefining the playing field, fostering a new wave of demand for software and data engineering at scale," says Faruk Muratovic, engineering leader at business advisory firm Deloitte, via email. He notes that most enterprises are now under increasing pressure to transform digitally. "This can be incredibly challenging, as mature enterprises struggle to prioritize their product roadmaps while driving the acceleration of software delivery and meeting their budgetary constraints." These multiple factors contribute to the accumulation of technical debt, as well as inefficiencies and discrepancies in the supply and demand of software delivery capabilities at an unprecedented pace, Muratovic says.

Current business environments require a relentless focus on engineering productivity, which demands a rethinking of legacy engineering organizations from top to bottom, Muratovic says. “Platform adoption can drive a better developer experience, higher velocity via CI/CD, the consistent measurement and visualization of outcomes, and the application of Generative AI-enabled tooling that drives step function improvements in developer productivity."

A Final Thought

Platform engineering should be a top priority for organizations aiming to bring their product development processes in line with modern efficiency and productivity models, Segovia says. "Its role in fostering agile, cohesive self-service, and innovative work environments makes it a key factor in the success of businesses adapting to the rapidly changing technological landscape."