The Role of Platform Engineering in Developing Intelligent Apps​

Intelligent Apps leverage advanced technologies like machine learning (ML), data analytics, and artificial intelligence (AI) to enhance decision-making, content generation, and user experiences. These apps incorporate AI and ML components to process data, derive insights, and adapt to user behavior to boost efficiency and personalization.

Platform engineering is integral to building robust Intelligent Apps. It’s the DevOps-inspired practice of designing, building, and maintaining the infrastructure and systems that underpin software applications. This includes strengthening security, maintaining compliance, controlling costs, and enhancing business value within a governed framework and via an internal developer platform.

Intelligent Apps require careful planning and execution as they necessitate complex processes like data management, model optimization and training, algorithm selection, and development. Fortunately, platform engineering helps with these tasks.

Coupled with Azure services, platform engineering creates a robust foundation for developing, deploying, and maintaining Intelligent Apps. With the help of platform engineering, you’re free to focus on what you do best as a developer. Instead of worrying about the details of infrastructure, ensuring compliance, or navigating the maze of underlying technologies that support modern apps, you can put your efforts toward designing, implementing, and iterating on their Intelligent Apps.

With platform engineering practices, Azure’s scalable infrastructure streamlines the development lifecycle, enabling rapid prototyping and iteration. Azure services—including Azure’s AI portfolio and Azure OpenAI Service—enhance app intelligence. Furthermore, Azure’s DevOps-supporting tools automate deployment and maintenance tasks, ensuring seamless updates and operational efficiency.

Let’s explore how Azure and platform engineering pave the way for the efficient development, deployment, and maintenance of Intelligent Apps.

How Platform Engineering Paves the Way for Intelligent Apps​

The rise of cloud computing and microservices has laid the groundwork for platform engineering techniques.

As applications have become more advanced in their functionality, so too has the underlying ecosystem necessary to deploy, manage, and maintain them. This shift necessitated creating specialized platforms to manage deployment complexities using platform engineering processes. Cloud resources and Infrastructure as Code (IaC) further revolutionized platform engineering by automating infrastructure provisioning and management via code. This streamlined resource deployment, improved scalability, and boosted reliability across environments.

While these technologies provide substantial benefits to developers, they require a careful strategy to be truly effective. This is where platform engineering truly shines. A well-engineered platform supports developer efforts through the concept of self-service with guardrails. It facilitates the autonomy you need in your workflows while simultaneously offering a set of organizational constraints that free you from unnecessary context switching, helping dissolve silos between teams.

Often embracing an “everything as code” philosophy, platform engineering ensures that everything from infrastructure to deployment is easily managed. The “as code” concept allows for infrastructure, policy, security, and all cloud configurations to be maintained like any other form of code using familiar tools and repositories. This approach offers a powerful method for achieving self-service autonomy, enabling you to make changes in a format you’re already familiar with.

Platform engineering supports the entire lifecycle of Intelligent Apps, from conceptualization to deployment and scaling:

• Conceptualization and design—Platform engineering teams collaborate with app developers, data scientists, and stakeholders to grasp Intelligent Apps’ requirements. They offer tech insights, aiding in tech selection and architecture design for scalability, reliability, and performance. Platform engineers help design data architecture, encompassing pipelines, storage, and processing frameworks. They also provide start-right templates that ensure you can start the development process correctly, adhering to policy, following best practices, and utilizing the most relevant technologies.
• Development and testing—Platform engineers configure development environments, giving you tools for efficient coding. They also establish continuous integration and continuous delivery (CI/CD) pipelines for automated processes and offer testing infrastructures. Tools like Azure Pipelines and Azure Test Plans help. By putting the right infrastructure in place—and empowering you with enough self-service autonomy to utilize this infrastructure—platform engineering allows for more focused and consistent development and testing cycles.
• Model training and optimization—Using technologies like distributed computing and GPU acceleration, platform engineers work with data scientists to establish scalable infrastructure for model training. They enhance training efficiency by adjusting hardware setups, refining data pipelines, and employing parallel processing methods. Additionally, they integrate model monitoring tools for performance tracking and retraining.
• Deployment and scaling—Platform engineers create automated deployment pipelines and infrastructure templates for deploying Intelligent Apps across various environments. They guarantee reliable, scalable processes, monitor performance, and use tools like Kubernetes for containerized workloads, ensuring scalability, resilience, and portability.
• Monitoring and maintenance—Platform engineers deploy monitoring and observability tools, like Azure Monitor, for real-time tracking of Intelligent Apps’ health, performance, and usage. They set up alert systems and automated responses, ensuring proactive issue detection and minimizing downtime. Regular performance tuning, capacity planning, and security audits optimize infrastructure efficiency.

Platform engineering ensures scalability, improves reliability through optimized performance, and fosters efficiency by automating workflows—aspects that make for more powerful, performant Intelligent Apps.

Platform Engineering in Action​

To illustrate the impact of platform engineering on developing Intelligent Apps, let’s compare the journey of developing one such app using a traditional software development methodology versus using an Azure-supported platform engineering approach.

The Initial Phase​

In the traditional software development approach, the initial phase typically involves requirements gathering followed by siloed development stages. Comparatively, a platform engineering approach involves embracing integrated planning and development stages. Teams collaborate from the beginning, leveraging Azure’s cloud capabilities for streamlined workflows. Azure services, such as Azure DevOps, facilitate seamless coordination between development, operations, and product teams, ensuring alignment with business objectives.

From the outset, platform engineering supports your development efforts with a templated approach to creating new apps or services. Platform engineers often create start-right templates based on best practices, industry standards, or organizational guidelines to ensure consistency, efficiency, and quality from the project’s conception. These templates may encompass IaC templates, service catalogs, or repositories containing pre-built components and libraries you can use to accelerate development.

Platform engineers help to define the core policies that govern resource provisioning and configuration. These policies might include restrictions on resource types, sizes, or regions, as well as rules for security, compliance, and cost management. With these guardrails in place, you can work without constantly looking over your shoulder to ensure you’re adhering to policy and best practices.

Development and Deployment Phases​

Traditionally, development progresses linearly with limited flexibility for adaptation. Deployment may encounter challenges due to disparate environments, leading to inconsistencies. Moreover, in traditional methods, siloing commonly occurs across design, development, testing, and deployment stages, hampering communication, slowing progress, creating inefficiencies, and hindering collaboration—ultimately resulting in disjointed outcomes.

By empowering you with self-service platforms and powerful automation, a well-engineered platform expedites your development efforts. Self-service interfaces simplify provisioning infrastructure resources such as virtual machines, containers, databases, storage, and networking for use in these phases. You can request and provision the resources you need on-demand without waiting for manual intervention from infrastructure teams.

Leveraging Azure services like Azure Kubernetes Service (AKS) and Azure App Service makes deployment automated and scalable, ensuring consistent performance across environments.

Additionally, Azure’s AI-specific tools—including Azure Machine Learning, Data Science Virtual Machines (DSVMs), and Azure AI Language—make developing and deploying robust Intelligent Apps straightforward.

The Maintenance Phase​

During the maintenance phase, the benefits of platform engineering shine even brighter. Traditional methods often struggle with managing ongoing updates and addressing user feedback promptly. Moreover, post-deployment maintenance using traditional methodology requires dedicated resources for ongoing support and updates.

Platform engineering selects, deploys, and configures infrastructure monitoring tools that provide visibility into the underlying infrastructure components’ health and performance. By letting you access these metrics directly, platform engineering arms you with the information you need to make informed decisions for maintenance and optimization.

Platform engineering enables teams to iterate rapidly based on real-time insights, leveraging Azure’s analytics and monitoring tools to gather actionable data. For instance, Azure Monitor and Application Insights enable proactive monitoring and efficient troubleshooting, minimizing downtime and optimizing performance. Additionally, Azure DevOps facilitates iterative improvements through feature flags and A/B testing, so teams can gather feedback and iterate quickly.

Furthermore, Azure’s AI-powered tools—including AI Anomaly Detector and Azure AI Metrics Advisor—support analytics and anomaly detection, allowing teams to address issues before they impact users.

The Benefits of Platform Engineering​

Let’s review some of the benefits of using platform engineering over traditional development methods for your Intelligent Apps:

• Reduced time to market—Platform engineering accelerates software development through reusable infrastructure components, automation tools, and standardized workflows. This contrasts with traditional methods, which prolong development cycles due to manual processes and lack of automation.
• Improved app quality—Platform engineering ensures consistency, repeatability, and reliability with standardized configurations, security policies, and automated testing. With traditional approaches, quality may suffer due to manual testing, ad-hoc configurations, and inconsistent environments.
• Scalability and resilience—Intelligent Apps designed with platform engineering in mind have resilient infrastructure that supports seamless scalability thanks to automated scaling and fault-tolerant architecture. Traditional, manual development methods can’t compete.
• Enhanced ability to iterate based on user feedback—Traditional methods face the constraints of manual processes and lengthy deployment cycles. Comparatively, platform engineering facilitates rapid iteration and experimentation with flexible platform infrastructure.
• Operational efficiency—Platform engineering improves efficiency through automation, standardized processes, and centralized management. This contrasts with traditional methods, where operational tasks are more manual, leading to inefficiencies and increased costs.

Conclusion​

Azure services and platform engineering have revolutionized the landscape of Intelligent Apps development, offering organizations unprecedented scalability, flexibility, and efficiency. And with Azure’s robust suite of tools, you can deliver intelligent solutions that drive growth and enhance customer experiences.

As we look to the future, the potential of Intelligent Apps to provide substantial business value only continues to grow, promising even greater insights, automation, and competitive advantages. To learn more about the transformative power of Azure, join us at Microsoft Build.