What Is Platform Engineering? A Guide for the Low-Budget Platform Engineer

Platform engineering bridges gaps between traditional software development and operations, creating scalable, flexible platforms that enhance developer productivity and operational efficiency.

Platform engineers abstract away the complexities of underlying infrastructure and middleware, allowing developers to focus on writing code and developing features without worrying about the intricacies of the deployment environment. This discipline consolidates various technology aspects, from cloud GUIs to infrastructure to security, into platforms that standardize development workflows and (arguably) accelerate product lifecycles.

In this article:

• Key Areas of Platform Engineering
• Platform Engineering vs. DevOps vs. SRE
• Platform Engineering Benefits 
• Platform Engineering Challenges
• Technologies Used in Platform Engineering
• Platform Engineering Best Practices

Key Areas of Platform Engineering

Building Internal Developer Platforms

An internal developer platform (IDP) centralizes tools and processes for software development, deployment, and management. It standardizes environments, streamlining workflows and reducing friction in the software development lifecycle. IDPs offer self-service capabilities, empowering developers to manage resources and deploy applications with minimal operational dependencies.

By consolidating tools and automating workflows, IDPs enhance developer experience and productivity. They reduce the cognitive load on developers, enabling them to focus on coding and improving code quality, while automation reduces errors in repetitive tasks like deployment and configuration.

Standardizing Software Delivery Processes

Standardizing delivery processes ensures consistent and efficient software development, deployment, and operation. It includes defining best practices, tools, and guidelines to streamline development workflows. This standardization minimizes variability in output and simplifies troubleshooting and maintenance.

Security is integral to standardizing delivery processes. Incorporating security practices from the start, like implementing automated security testing and enforcing access controls, mitigates risks and ensures compliance. Securing delivery processes is an effective way to protect applications and the sensitive data they hold from vulnerabilities.

Setting and Maintaining Service Level Agreements

Internal Service Level Agreements (SLAs) define the expected performance and availability of services offered by the platform team. Setting clear SLAs ensures transparency and sets realistic expectations between platform engineers and their internal customers, typically the software developers and product teams.

Maintaining these SLAs involves continuous monitoring, reporting, and adjusting of services to meet agreed standards. It fosters accountability and trust, encouraging a culture of continuous improvement. SLAs guide decisions on capacity planning and prioritization of platform enhancements, ensuring services evolve to meet users’ needs.

Setting and Maintaining Policies and Guardrails

Platforms must be opinionated about things that matter most: Resource efficiency, security and compliance. This can be achieved by setting “start right” templates using the everything-as-code (EaC) approach, and “stay right” guardrails of automated governance, scanning, and policy configuration. Many platform vendors, like Backstage and Cortex, developed a scoring mechanism for custom workflows. This shows the developer-customer just how aligned their workflow is with organizational policies. 

Monitoring Team Performance Metrics

Team performance metrics are critical for assessing the effectiveness of platform engineering efforts. Key performance indicators (KPIs) include deployment frequency, change lead time, change failure rate, and mean time to recovery. These metrics provide insights into the development and operational health of the platform.

Regularly reviewing these metrics helps identify bottlenecks, inefficiencies, and improvement opportunities. It enables teams to make data-driven decisions, optimizing processes and tools to improve throughput, stability, and reliability. Continuous improvement based on performance metrics ensures platforms meet the evolving needs of developers and business requirements.

Platform Engineering vs. DevOps vs. SRE

Platform engineering, DevOps, and Site Reliability Engineering (SRE) share common goals of improving software delivery and operational efficiency, but differ in focus and approach: 

• DevOps emphasizes the cultural and process aspects of collaboration between development and operations teams. It focuses on continuous integration and delivery (CI/CD), automation, and fostering a culture of shared responsibility.
• SRE, originated by Google, focuses on applying software engineering principles to operational problems to achieve high availability and reliability. It involves creating scalable and highly reliable software systems. 
• Platform engineering encompasses elements from both DevOps and SRE but focuses on building and managing the platform that supports these practices. It targets the underlying infrastructure, creating tools, and automating workflows to empower developers and operations teams.

Learn more in our detailed guides to:

• Platform engineering vs DevOps (coming soon)
• Platform engineering vs SRE (coming soon)

Platform Engineering Benefits

Here are some of the key benefits of platform engineering for a development organization:

Improved Project Quality

Platform engineering enhances project quality by standardizing development environments and automating key processes. This uniformity reduces discrepancies between development, testing, and production, lowering the chance of bugs and issues. Automated testing and deployment ensure consistency and speed up the delivery of high-quality software.

By abstracting complexities and minimizing manual interventions, platform engineering reduces human error, further enhancing project quality. Developers can focus on code and feature development, relying on the platform to ensure that best practices and quality checks are automatically applied throughout the software development lifecycle.

Improved Development Consistency

Consistency in development practices is crucial for scalable and maintainable software projects. Platform engineering establishes standardized processes and tools across the development lifecycle, minimizing variations and enhancing predictability. This consistency simplifies onboarding, collaboration, and knowledge sharing among developers, regardless of project or team.

A consistent development environment reduces friction and inefficiencies, enabling developers to focus on innovation rather than resolving environmental discrepancies. Streamlined workflows and automated toolchains not only improve developer productivity but also lead to more reliable and predictable release schedules.

Improved Software Reliability

Platform engineering significantly improves software reliability by creating a stable and controlled development environment. By automating deployments and integrating continuous testing and monitoring, platform engineering ensures that applications are always in a deployable state and that issues are detected and addressed early in the development cycle. 

Furthermore, platform engineering practices, such as implementing fault-tolerant systems and automated recovery processes, ensure that applications are resilient to failures. By designing systems that can automatically recover from crashes, network issues, or other unexpected problems, platform engineering minimizes downtime and ensures that services remain available to users.

Platform Engineering Challenges

While platform engineering has important benefits, it also comes with its own set of challenges.

Costs

The only certain outcome of a platform initiative is the required investment of funds and engineering time. This often makes organizational leadership hesitate about giving the mandate in the first place. The community is already engaged in discussions on how to make this project cost-effective, and how it can repay itself by demonstrating financial impact. 

Related: Learn how and why platform engineers should prioritize infrastructure optimization 

Greater Complexity

Adopting platform engineering introduces complexity due to the integration of various tools, technologies, and processes. There is often a need for specialized skills and extensive knowledge to design, implement, and manage the platform effectively. Balancing flexibility with standardization is challenging, ensuring the platform meets diverse needs without becoming unwieldy.

Compatibility with Technologies and Frameworks

Organizations often rely on a diverse set of tools and technologies for their operations, and a development platform must be designed to integrate seamlessly with these systems. This includes not only technical compatibility in terms of APIs, data formats, and protocols but also supporting various development methodologies and workflows already in place. 

This challenge is compounded by the fast pace of technological change, requiring platform engineers to continuously adapt and update the platform to keep it compatible with new tools and technologies as they emerge.

Larger Staff

Implementing and maintaining a platform engineering approach requires a larger, more specialized staff. Recruiting and retaining skilled professionals in platform engineering, DevOps, and SRE can be challenging due to the high demand for these skills. The need for continuous training and development to keep up with evolving technologies adds to the challenge.

Technologies Used in Platform Engineering

Here are some of the main technologies used to build development platforms:

Infrastructure as Code (IaC) Tools

Infrastructure as Code (IaC) tools automate the provisioning and management of infrastructure through code. This approach ensures consistency, repeatability, and speed in deploying infrastructure resources. Tools like Terraform, Ansible, and CloudFormation enable developers to define infrastructure specifications in code, version control it, and apply it across environments.

By treating infrastructure as code, organizations can apply software development best practices, such as version control, code review, and continuous integration, to infrastructure management. This not only improves productivity and reduces errors but also enhances collaboration between development and operations teams.

Containerization and Orchestration

Containerization packages applications and their dependencies into containers, providing a consistent and isolated environment across development, testing, and production. Docker is a prominent containerization technology, simplifying application packaging and deployment. Container orchestration tools like Kubernetes manage the lifecycle of containers, ensuring they run efficiently and scale based on demand.

This combination enhances application portability, scalability, and efficiency. Developers can focus on building applications without worrying about the underlying infrastructure. Orchestration tools automate deployment, scaling, and management of containerized applications, enabling more resilient and scalable applications.

CI/CD Tools

Continuous Integration (CI) and Continuous Delivery (CD) tools automate the software release process from code commit to production deployment. Tools such as Ocean CD enable automated testing and deployment, ensuring code changes are integrated and delivered quickly and reliably.

CI/CD practices reduce manual errors, accelerate feedback loops, and increase deployment frequency. By automating the build, test, and deployment processes, these tools help maintain high-quality codebases and facilitate rapid iteration, response to changes, and quicker time-to-market.

Service Mesh Tools

Service mesh tools manage communication between microservices, providing capabilities like service discovery, load balancing, fault tolerance, and encryption. Tools like Istio, Linkerd, and Consul implement a service mesh layer that abstracts complexity and ensures reliable, secure inter-service communication.

By decoupling application logic from networking concerns, service mesh tools facilitate easier scaling, maintenance, and management of microservices architectures. They offer detailed monitoring and tracing for better observability and troubleshooting, enhancing the resilience and performance of distributed applications.

Cloud Management Platforms

Cloud management platforms (CMPs) enable centralized management of cloud environments, streamlining operations across multiple cloud providers and services. Tools like OpenShift and Cloud Foundry offer abstraction layers over diverse cloud infrastructures, simplifying deployment, scaling, and management.

CMPs provide unified interfaces for provisioning, monitoring, and managing cloud resources, ensuring cost-effectiveness, and compliance. They empower teams to leverage cloud resources efficiently, maximizing the benefits of cloud computing while minimizing complexity and risk.

Related content: Read our guide to platform engineering tools

Platform Engineering Best Practices

Be business-specific 

No two platforms are identical; as an internal product, the platform should address the organization’s particular strategic challenges and objectives. Therefore, its planning phase should include internal research, answering questions like: Which KPIs do we need to improve to increase competitiveness and profit? Which recurring activities require the most clicking around from my developers? Which compliance frameworks are we subject to?  

Treat it as a full-on product 

In larger organizations, the platforms are owned by a dedicated product team, which operates according to product management best practices. This includes internal needs research, defining an MVP and a roadmap thereafter, and monitoring user adoption and behavior in order to optimize the platform as it matures. 

CNCF’s platform engineering maturity model explains the challenges organizations face and the opportunities they should aim for as they mature their platform teams. 

Prioritize the Developer Experience 

A well-designed platform offers an intuitive and seamless environment, where developers have easy access to tools, resources, and documentation. By minimizing the complexity and friction in the development lifecycle, engineers can focus more on creating and less on administrative or operational tasks. This not only boosts productivity but also enhances job satisfaction and retention among the development team.

Enhancing the developer experience involves continuous feedback loops with the users of the platform — the developers themselves. Gathering and acting upon feedback ensures the platform evolves in alignment with the developers’ needs, addressing pain points and introducing relevant improvements. Incorporating modern UX/UI principles into tooling interfaces and ensuring comprehensive, accessible documentation are important steps towards making the platform developer-friendly.

Leverage Self-Service and Automation Capabilities 

Incorporating self-service capabilities and automation into the platform is key to empowering developers and streamlining workflows. Self-service portals and APIs allow developers to provision resources, access services, and manage deployments independently, without waiting for manual approvals or interventions.

The focus on automation extends beyond simplifying developer tasks to encompass the entire platform’s operational aspect. Automated scaling, healing, and optimization mechanisms ensure that the platform not only supports development activities efficiently but also maintains high performance and availability with minimal manual oversight.

Ensure Platform Resources Are Used Efficiently and Optimize Costs

Efficient resource utilization and cost optimization are crucial in managing cloud and platform resources. Implementing policies for right-sizing, auto-scaling, and shutdown schedules ensures resources align with actual usage, avoiding wastage and reducing costs.

Tools for cost management and optimization, like Eco from Spot by NetApp, provide insights into resource usage and cost trends. By monitoring, analyzing, and optimizing resource deployment, organizations can achieve a balance between performance and cost, maximizing the return on their technology investments.

Platform Engineering for Kubernetes with Spot by NetApp

Spot by NetApp’s optimization portfolio provides resource optimization solutions that can help make your IDP more impactful. Here are some examples of automated actions our users enjoy on their K8s, EKS, ECS, AKS and GKE infrastructure: 

• Autoscaling: This single word encompasses multiple procedures: knowing when to scale up or down, determining what types of instances to spin up, and keeping those instances available for as long as the workload requires. EC2 ASG’s are an example for rigid, rule-based autoscaling. You might want to get acquainted with additional K8s autoscaling methods like HPA or event-driven autoscaling. 
• Automated rightsizing: Recommendations based on actual memory and CPU usage can be automatically applied to certain clusters or workloads 
• Default shutdown scheduling: Requested resources can be eliminated after regular office hours, unless the developer opts out a specific cluster. 
• Automated bin packing: Instead of having nine servers 10% utilized, gather those small workloads in one server. Bin packing can be user-specific or not, according to your security policies. 
• Dynamic storage volume: Your IDP should regularly remove idle storage. It’s also recommended to align attached volume and IOPS with node size to avoid overprovisioning in smaller nodes. 
• AI-based predictive rebalancing replaces spot machines before they’re evicted involuntarily due to unavailability. 
• Data, network, and application persistence for stateful workloads, either by reattachment or frequent snapshots. 
• Dynamic resource blending aware of existing commitments (RIs, SPs) which must be used before purchasing any spot or on-demand machines. 
• “Roly-poly” fallback moves your workload to on-demand or existing commitments if there is no spot availability. When spots are once again available, you want to hop back onto them. 

To discover what key optimization capabilities your platform can enable in container infrastructures, read our blog post or visit the product page.