Platform engineering is rapidly gaining traction in enterprise IT, promising to revolutionize productivity and efficiency. This trend involves maintaining an internal self-service IT infrastructure to support development teams, a practice that has become mainstream due to the scarcity of full-stack developers. However, while the benefits are clear, there are also potential drawbacks that need to be addressed.
The Rise of Platform Engineering
The Need for Internal Developer Platforms
The annual “Accelerate State of DevOps” survey by the Google Cloud DORA team, which gathered insights from 3,000 organizations, highlights the positive impact of platform engineering. Users of internal developer platforms reported a 6% improvement in software delivery and operations performance. These platforms enable faster development cycles and more efficient operations, contributing to overall productivity gains. Enterprises are leveraging these metrics to justify their investments in platform engineering. However, the initial enthusiasm for productivity improvements will need to be tempered by realistic assessments of the ongoing challenges. As these platforms evolve, their effectiveness in handling more complex and larger-scale operations will be critical to maintaining the momentum of productivity gains.
Benefits and Initial Gains
Despite the benefits, the survey also revealed some unexpected downsides. Throughput, defined as the speed of making updates to applications, decreased by 8%. Change stability, which measures the likelihood of updates causing additional work due to failures, dropped by 14%. These decreases suggest that while platform engineering can boost productivity, it may also introduce new challenges. This dual-edged outcome underscores the importance of maintaining a balanced approach when implementing platform engineering practices. Enterprises must prioritize continuous assessment and refinement of their internal platforms to sustain productivity benefits while addressing any negative impacts on throughput and change stability.
Challenges and Drawbacks
Decreased Throughput and Change Stability
Nathen Harvey, DORA lead and developer advocate at Google Cloud, speculated that the introduced platforms might lack sufficient test infrastructure and frameworks, resulting in less quality feedback. Andy Thurai, an analyst at Constellation Research, added that the unequal application of AI automation between software development and platform teams might exacerbate instability. Hyperproductive organizations face compounded problems when code velocity outpaces traditional release engineering, testing, and SRE processes.
Without a robust testing and quality assurance framework, the feedback loop for developers becomes less effective. This can result in a higher likelihood of errors and bugs being introduced during development. Additionally, the discrepancy in AI automation application between development and platform teams may create imbalances in stability. In hyperproductive environments where the push for rapid code deployment is prioritized, traditional processes such as release engineering and site reliability engineering (SRE) struggle to keep pace, further amplifying the instability observed.
Potential Causes of Instability
The DORA report acknowledges that platform engineering introduces a degree of friction due to the added layers that changes must navigate before deployment. However, this potential slowdown is balanced against improved security integrations within infrastructure-as-code (IaC) and GitOps workflows. Automated tools and real-time compliance checks enforce consistent policies, ensuring that security is not overlooked in development. These integrated security measures are crucial for maintaining the integrity of the development process and preventing vulnerabilities from being introduced during rapid development cycles. By embedding security practices directly into the platform engineering framework, organizations can mitigate risks while benefiting from streamlined development processes.
Balancing Speed with Stability
The Role of Security Integrations
Interestingly, the report suggests that some level of instability might be positive, stemming from increased experimentation encouraged by a secure platform environment. This flexibility fosters innovation but may initially lead to more rework and failure. Alternatively, insufficient platform support for quality assurance could necessitate reworking the platform itself. Encouraging experimentation within a secure environment fosters creativity but requires a strong feedback loop and support structure to ensure that any failures or issues that arise can be quickly addressed. Without adequate support, the initial benefits of innovation may be offset by the need for significant rework to maintain stability.
Experimentation and Innovation
In an encouraging pattern noted within the report, platform engineering stages often exhibit initial performance gains, followed by temporary setbacks, and eventually stabilize to bring continued productivity improvements. Businesses must heed developer feedback for sustained success. This trend resonated with Ian Beaver of Verint Systems, who provided a case study reflecting this trajectory. Beaver’s company centralized AI models and frameworks on a standard platform, initially causing disruptions as teams adapted to the new system. However, overcoming these hurdles ultimately led to significant efficiency improvements, reducing time to market for new AI features and simplifying the integration of new AI services.
Case Studies and Real-World Applications
Verint Systems’ Experience
Beaver emphasized the benefits of a centralized platform, allowing the company to solve problems once and reuse solutions across multiple teams. This strategic platform initiative, despite its extensive and challenging rollout, markedly enhanced the quality of life for both research and product teams. The ability to interchange between AI models and cloud providers seamlessly was a significant advantage. The standardized platform provided a unified framework for development and deployment, reducing redundancy and improving collaboration across teams. This facilitated more efficient problem-solving and resource utilization, enabling the company to deliver new features and innovations more rapidly.
Long-Term Benefits
The DORA report highlights the importance of continuous refinement and attentiveness to developer feedback. This trend resonated with many organizations, indicating that platform engineering stages often exhibit initial performance gains, followed by temporary setbacks, and eventually stabilize to bring continued productivity improvements. The iterative nature of platform development means that initial disruptions and challenges are natural, but with the right support and feedback mechanisms in place, these challenges can be overcome, leading to sustained efficiency and productivity gains.
Continuous Improvement and Feedback
The Importance of Developer Feedback
Balanced automation across teams is crucial in fully leveraging platform engineering benefits while mitigating its inherent challenges. Ensuring that both software development and platform teams are equally supported by AI automation can help maintain stability and prevent the issues observed in hyperproductive organizations. By distributing automation tools and resources evenly, organizations can create a more stable and efficient development environment. This balance helps to ensure that all teams can work cohesively towards common goals without creating disparities in capabilities or increasing the likelihood of instability.
Balancing Automation Across Teams
Platform engineering is swiftly becoming a key focus in enterprise IT, promising to transform productivity and efficiency. This approach concentrates on maintaining an internal self-service IT infrastructure that effectively supports development teams, a practice which has emerged as mainstream. The shift is primarily driven by the shortage of full-stack developers, making it a necessity rather than a luxury for organizations looking to stay competitive.
By building and providing a self-service platform, enterprises can empower their development teams to deploy and manage applications more swiftly and efficiently. This lessens the burden on IT operations and allows developers to work with greater autonomy and speed, ultimately fostering innovation and reducing time-to-market.
However, while the advantages of platform engineering are substantial, potential drawbacks need careful consideration. These may include the complexity of managing and maintaining the platform, the need for ongoing investment in infrastructure, and potential security concerns. Proper planning and management are essential to address these challenges and maximize the benefits of platform engineering in the enterprise IT landscape.