How Are Platform Teams Shaping Future Tech Development?

Platform engineering has emerged as a crucial link between conventional IT operations and advanced development approaches. Findings from a Puppet by Perforce survey show that 43% of enterprises have had platform teams for 3-5 years, signaling their growing importance in tech structures. These teams are situated differently across companies, with over half embedded in DevOps or infrastructure teams, indicating their close association with IT operations. Notably, 40% of platform teams report to distinct leadership, highlighting their distinctive role in the organization.

The core mission of platform teams is to refine development workflows and boost IT productivity. Their position in the company can affect their roles and influence how they assist organizational ambitions, given that they carry various expectations based on the structure they fall under. As platform engineering continues to evolve, it plays a pivotal role in shaping effective development and operational strategies within organizations.

Perceived Importance and Primary Focus

Platform teams are increasingly recognized as the linchpins of IT operations, with 65% of professionals acknowledging their key role. Far from mere support staff, they lead the charge in productivity and automation. These teams focus on lifting the burden of repetitive tasks off developers and ensuring consistency throughout the development pipeline.

With an emphasis on bolstering productivity, 58% of such teams strive to automate routine processes due to the complexities and competitive nature of software delivery, particularly in cloud environments. They are also tasked with proactively incorporating security measures from the very start and accelerating the transition to cloud-native architectures.

Platform engineering therefore serves a crucial, multifaceted role within modern organizations, underpinning their operational effectiveness and strategic development initiatives. This evolution reflects the intricate interplay of technology and process in delivering successful software solutions.

Embracing Cloud-Native Platforms and Security

Although platform teams are focused on advancing their capabilities, they face significant challenges, particularly with the adoption of cloud-native platforms like Kubernetes. Despite its benefits for scalability and resilience, only 22% have implemented it in production, indicating a hesitancy among organizations to fully embrace its potential.

Prioritizing security, 70% of these teams are pioneering the ‘shift left’ approach, embedding security early in the development cycle. This merge of security with a DevOps mindset aims at accelerating deployment while maintaining rigorous security standards. The integration of security from the outset reflects an evolution towards safer, more efficient development practices, blending speed with robust protection. This evolution points to a future where embracing the full scope of cloud-native technology and the early integration of security measures could redefine the standard for software development and deployment.

Developer Empowerment and Process Streamlining

Finding the equilibrium between empowering developers and refining backend processes to enhance productivity, maintain compliance, and fortify security is a prime focus for platform teams. This balance is critical for the evolution of application development and deployment, laying the foundation for a sustainable and innovation-friendly environment.

The challenge platform teams face is significant, to persuade the developer community to adopt and integrate these platform services within their workflow without stifling creativity and innovation. The survey underscores the importance platform engineers place on automating burdensome processes, aiming to liberate developers from the drudgery of repetitive tasks. In doing so, platform teams hope to allow developers to focus their energies on what they do best—building and innovating—and in turn driving the company’s competitive edge forward.

Explore more

Agentic AI Redefines the Software Development Lifecycle

The quiet hum of servers executing tasks once performed by entire teams of developers now underpins the modern software engineering landscape, signaling a fundamental and irreversible shift in how digital products are conceived and built. The emergence of Agentic AI Workflows represents a significant advancement in the software development sector, moving far beyond the simple code-completion tools of the past.

Is AI Creating a Hidden DevOps Crisis?

The sophisticated artificial intelligence that powers real-time recommendations and autonomous systems is placing an unprecedented strain on the very DevOps foundations built to support it, revealing a silent but escalating crisis. As organizations race to deploy increasingly complex AI and machine learning models, they are discovering that the conventional, component-focused practices that served them well in the past are fundamentally

Agentic AI in Banking – Review

The vast majority of a bank’s operational costs are hidden within complex, multi-step workflows that have long resisted traditional automation efforts, a challenge now being met by a new generation of intelligent systems. Agentic and multiagent Artificial Intelligence represent a significant advancement in the banking sector, poised to fundamentally reshape operations. This review will explore the evolution of this technology,

Cooling Job Market Requires a New Talent Strategy

The once-frenzied rhythm of the American job market has slowed to a quiet, steady hum, signaling a profound and lasting transformation that demands an entirely new approach to organizational leadership and talent management. For human resources leaders accustomed to the high-stakes war for talent, the current landscape presents a different, more subtle challenge. The cooldown is not a momentary pause

What If You Hired for Potential, Not Pedigree?

In an increasingly dynamic business landscape, the long-standing practice of using traditional credentials like university degrees and linear career histories as primary hiring benchmarks is proving to be a fundamentally flawed predictor of job success. A more powerful and predictive model is rapidly gaining momentum, one that shifts the focus from a candidate’s past pedigree to their present capabilities and