Taming the Complexity of Cloud-Native Development with Internal Developer Platforms

The limitations of monolithic architectures—such as inflexibility and challenges with scalability and agility—have led to the widespread adoption of microservices. In fact, Statista reports that 85% of surveyed organisations currently use microservices.

Breaking a project into smaller, independent services makes it easier to manage and scale each component separately. However, this flexibility comes with its own challenges. Unlike monolithic architectures, where everything exists within a single unit, microservices can be spread across hundreds or even thousands of containers. To illustrate this scale, Google once reported launching approximately 2 billion containers per week.

                                        Image from Krasamo

To manage this complexity, organisations have developed numerous cloud-native tools and solutions that automate various aspects of cloud infrastructure. In the pursuit of efficiency, companies often adopt even more tools—for secrets management, infrastructure provisioning, orchestration, and more. 

While these tools provide powerful capabilities, they also introduce significant challenges. Managing microservices at scale requires complex orchestration, monitoring, and automation, adding operational complexity. Additionally, the growing number of tools can lead to tool sprawl, making maintenance more difficult and increasing the cognitive load on developers.

    Image from Compute Thought

However, these issues are not insolvable. As you’ll see in this piece, they are precisely what led to the creation of Internal Developer Platforms (IDPs)—designed to bring order, automation, and simplicity to cloud-native development.

What are Internal Developer Platforms?

An internal developer platform (IDP) is a self-service layer that sits on top of an organization’s infrastructure and development tools and abstracts many of these cloud native components’ underlying complexity.

It automates many repetitive tasks, such as setting up cloud environments, configuring databases, and handling deployments, making deploying and managing applications easier 

without worrying about the underlying infrastructure. A well-implemented IDP includes:

• Self-service developer portal: An important component of an IDP is an intuitive user interface that makes it easy for developers to self-serve, provision, and manage the resources, infrastructures, and access tools they need with minimal friction.

• Automated workflows: Automation is at the heart of any well-oiled process in the cloud native space, and with IDPs, it's no different. IDPs leverage automation to streamline code testing, building, deployment, and monitoring processes; this approach reduces the likelihood of human-induced errors and ensures consistency.

• Infrastructure management: IDPs should abstract the infrastructure management process for developers, providing them with templates to create high-level definitions of the necessary infrastructures. 

• Environment management and application configuration: IDPs help manage multiple environments (e.g., development, staging, production) by automating the setup and teardown of infrastructure resources. They also allow developers to configure application settings, secrets, and environment variables without deep infrastructure knowledge.

• Observability and monitoring: A well-implemented IDP integrates observability tools to provide real-time insights into application health, performance, and logs. Features like centralized logging, metrics, tracing, and alerting ensure developers can quickly diagnose and resolve issues, improving system reliability.

        Image from LinuxBlog

How IDPs manage complexities in cloud-native development

Recognising what IDPs are, how do they help manage the increasing complexity in cloud-native development environments.

1. Standardisation reduces cognitive load

One of the biggest pain points in cloud-native development is the sheer number of decisions engineers must make daily—choosing the right deployment strategy, configuring Kubernetes YAML files, or managing service dependencies. IDPs provide pre-configured templates, policy-driven automation, and golden paths, allowing teams to focus on building features rather than navigating infrastructure intricacies.

2. Self-Service empowers developers

Without an IDP, developers often rely on DevOps teams to provision environments, troubleshoot CI/CD issues, or configure security policies. This dependency slows down development cycles and creates bottlenecks. IDPs enable self-service capabilities, allowing engineers to spin up environments, deploy applications, and manage configurations independently, accelerating development velocity.

3. Enhanced security and compliance

Security is a constant concern in cloud-native environments, with misconfigurations and vulnerabilities leading to breaches. IDPs enforce built-in guardrails—from role-based access control (RBAC) to automated security scans—ensuring compliance with industry standards and internal policies without manual intervention.

4. Accelerating onboarding and reducing time-to-value

For organisations hiring new engineers, ramp-up time is critical. With an IDP, newcomers no longer need to learn the intricacies of the cloud provider’s API, the company’s Kubernetes setup, or complex CI/CD workflows. A unified developer experience reduces onboarding time from weeks to days, helping teams ship faster.

5. Unifying the Developer Experience

IDPs unify developer workflows by standardising tools, automating best practices, and providing a single pane of glass for managing deployments, security, and observability. This holistic approach reduces cognitive overhead and fosters seamless collaboration across teams. Brian Leatham of Netflix at the PlatformCon 2022 explained that Netflix microservices architecture was becoming too fragmented and as thus the team had to turn to IDPs to unify developer experiences across the company’s Software Development Life Cycle (SDLC).

The bottom line

As revolutionary as it is, the microservices approach to development introduces a lot of complexity. Unlike a monolith, where everything is contained in a single unit and can be easily traced, microservices applications are spread across multiple containers, often running on different cloud platforms. Managing such a system requires a more strategic and efficient approach.

To keep everything running smoothly, you need CI/CD pipelines to automate testing and deployment—because manually deploying each service is inefficient and error-prone. You also need orchestration tools like Kubernetes to manage containers, Infrastructure as Code (IaC) tools to handle provisioning, and secrets management to store credentials and access keys securely.

As the list of necessary tools grows, you may spend more time managing infrastructure and operations than writing code. This is where platform engineering comes in.

Platform engineering abstracts the complexity of managing cloud-native applications by providing self-service, automation, and standardisation for developers. It ensures developers can focus on building features rather than wrestling with infrastructure. With Internal Developer Platforms (IDPs), teams can streamline deployments, improve security, and maintain best practices—all while reducing operational overhead.

In essence, platform engineering bridges the gap between developer experience and operational efficiency, making modern software development faster, safer, and more scalable.