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Preparing for the Shift to Platform Engineering

Platform engineering is one of the hottest trends in the software delivery world and is expected to represent the next evolution of DevOps. According to Gartner’s 2023 study of top strategic technology, 80% of software engineering organizations will establish platform teams as internal providers of reusable services, components and tools for application delivery by 2026. What used to happen in one day in the developer world now needs to happen in five minutes. With high pressure for organizations to scale operations quickly, especially in a marketplace clamoring for the benefits of artificial intelligence (AI), automation is increasingly important in platform engineering. It reduces manual errors, streamlines the development process and boosts growth and efficiency. As technology advances rapidly, it becomes more critical for organizations to proactively navigate newly emerging trends within platform engineering to remain competitive. The keys to successful platform engineering include cloud-native architecture, AI and machine learning (ML), and evolving tools that use intuitive interfaces and pre-built components to create functional applications.

Platform Engineering is the Natural Progression of DevOps

Platform engineering expands on the practices of DevOps by moving development out of silos and taking a collaborative, bird’s-eye view of an organization’s technology. Platform engineering is built on a foundational infrastructure that enables self-service capabilities so developers can deploy code faster, more reliably and more securely. While platform engineering represents the next wave of change in DevOps, it’s essential for leaders and developers to understand that it isn’t a singular technology or approach. The shift to platform engineering also represents a cultural shift for developers and leaders to address the needs, challenges and rapid pace of modern software development by optimizing processes, accelerating delivery and reducing the complexity of operations. For platform engineering to succeed, it’s critical to approach it from the perspective of a technology-driven culture that creates solutions with a developer’s perspective in mind. By seeking to improve the developer experience first, enterprises can achieve better results.

Trends Shaping the Landscape

Platform engineering itself is an emerging trend, but several essential ingredients shape how it will impact businesses today and in the future. For organizations to reap its benefits, understanding these essential trends will keep them ahead of the pack.

Cloud-native architecture is fundamental to modern platform engineering by designing and building applications for cloud environments. Infrastructure-as-code (IaC) is a key component, enabling the automated provisioning and management of resources. Cloud-native platforms like Kubernetes, Terraform or Docker facilitate container orchestration and scaling, while serverless computing isolates infrastructure management entirely. This trend ensures that platform engineering is agile, scalable and cost-effective, with minimal downtime and easier maintenance.

Automation is pivotal in platform engineering, reducing manual errors and streamlining deployment workflows. It allows developers to build, test and deploy software more efficiently, leading to faster and more reliable product releases. In fact, 43.2% of early adopters of platform engineering saw faster product delivery. Automation tools like Jenkins, Ansible and Terraform are commonly used to automate infrastructure provisioning, configuration management and deployment pipelines. Machine learning (ML) models can perform automated troubleshooting by analyzing historical data to identify patterns and predict potential issues, proactively addressing problems and minimizing downtime. This also helps with performance optimization. By using AI that can analyze application performance data, automation takes platform engineering to the next level by suggesting optimizations to improve resource utilization and user experience. AI-powered tools assist in generating code or script, which is vital to reducing development time and human error. ML algorithms empower the security side of platform engineering, a top priority for any developer. It’s possible to leverage automated security tests during development and maintenance, even detecting and responding to security threats in real-time. When AI handles routine tasks, developers are less likely to feel overwhelmed or experience burnout. This allows developers to focus on more creative tasks, complex problem-solving and innovation, resulting in more efficient operations to help them achieve higher levels of productivity, security and consistency.

Evolving development tools that create functional applications using intuitive interfaces and pre-built components increasingly simplify application development and deployment. Low-code and no-code platforms allow developers to create applications with minimal coding effort, utilizing visual interfaces and pre-built modules. Serverless frameworks like AWS Lambda and Azure Functions enable developers to focus solely on writing code. An increasing reliance on and advancement of application programming interface (API) gateways provides a simplified way to manage and expose APIs, enhancing application integration and connectivity. Containerization platforms are becoming similarly powerful tools. Platforms like Docker and Kubernetes simplify application deployment across diverse environments by offering standardized containers and orchestration. Adopting a strategic suite of these evolving tools requires a clear understanding of product goals, organizational goals and developmental capabilities.

How Leaders can Support Platform Engineering

It’s projected that 30% of organizations are currently evaluating the adoption of platform engineering practices, and its prevalence will only grow. While platform engineering’s trends are empowered by digital transformation and new technologies, it’s vital to remember that platform engineering represents a shift in DevOps culture. To effectively support the transition, leaders must commit to a culture of platform engineering. Simply adopting technology isn’t enough. It needs to be backed by a thorough strategy that allows developers to truly benefit from the tools and structures of platform engineering. What does this look like? Success requires leaders and developers to encourage collaboration and break down silos between operations and development teams. It’s possible to build a bridge between developers and operations by committing to cloud migration, creating a centralized platform and investing in collaborative tools and the strategy to back it up.

To engage in platform engineering requires dedication to a collaborative culture instigated from the top, empowered by overall strategic decisions and operations. This includes continued learning for developers to stay on top of new languages, trends, challenges and priorities, internally and externally. Teams are more successful when they utilize performance metrics to track workflows that help them conduct effective maintenance and improve on a consistent and ongoing basis.

Embracing Change is Embracing Progress

In the fast-paced and continuously improving world of software development, it’s easy to think that each wave of technology will replace the last. Of course, experts know this isn’t true. Iteration is vital to advancing technologies, and it’s important to embrace the next iteration of progress to stay competitive. Automation and platform engineering are tools that enable developers rather than replace them. It’s important to note that platform engineering doesn’t mark the end of DevOps. Rather, it takes the core foundations that DevOps has built to the next level to empower developers with self-service capabilities, foster collaboration, enhance scalability, accelerate deployment and instigate sustained business growth.

Manish Sharma

Manish Sharma is a lead systems and DevOps engineer with more than 18 years of experience planning and delivering large projects, solving complex problems, and producing technical results under pressure in a hybrid cloud software development environment. He has extensive experience in scripting/tool building, task automation, release management and CI/CD using a broad range of technologies including Jenkins, Chef, Terraform, Powershell, Python, AWS, and SQL Server. Mr. Sharma has a bachelor’s degree in computer science from GNDU University in India. For more information, contact manish.sharma1007@gmail.com.

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