How to Track Platform Engineering: Metrics & KPIs

Platform engineering is the art of automating day-to-day software delivery processes in a way that benefits developers. Platform engineers build custom internal tools tailored to meet developer needs. For instance, an internal portal could allow developers to spin up new staging environments or retrieve production logs with a single click.

Platform engineering metrics are quantitative indicators used to measure the effectiveness, reliability, and adoption of internal developer platforms (IDPs) and the overall platform engineering function.

Monitoring platform metrics enables you to understand how your systems benefit your organization. Metrics such as environment provisioning times, deployment counts, and developer onboarding duration provide data that lets you prove developer productivity is improving. 

In turn, you can accurately assess the business value generated by platform engineering to calculate your return on investment (ROI).

Metrics should be designed so they align with your own KPIs (key performance indicators). For instance, if you want developers to be able to self-serve 95% of their infrastructure requirements, then tracking the number of developer-triggered IaC runs could be a straightforward way to measure compliance.

Let’s examine some key metrics to include in a platform engineering monitoring strategy. The following metrics and categories capture all aspects of an IDP’s operations. We’re also listing common KPIs applicable to each category, which can serve as inspiration when setting your own objectives.

1. Developer experience metrics

Platform engineering exists to serve developer needs. An improvement in developer experience metrics is therefore a basic requirement for any IDP implementation.

Metrics to collect in this category include:

• The time taken to provision a new environment
• The time required to collect feedback on new changes
• The number of different tools developers must use to ship a change
• Developer self-service rates (how many tasks can be completed without involving other team members)
• Developer onboarding time (how long it takes for new developers to become productive)
• Developer satisfaction scores, based on surveys and feedback

These metrics indicate whether the platform is actually helping developers to achieve their day-to-day tasks. They naturally map to KPIs such as achieving a self-service rate above 90% or ensuring new developers can be onboarded within a week.

2. Adoption and usage metrics

Internal platforms must be widely adopted to be successful. It sounds simple, but unless developers use the platform, you won’t see a good return on investment.

Platforms can go underutilized for many different reasons. For instance, developers may not be aware that the platform is available, be uncertain about how to use its tools, or revert to existing processes due to ingrained habits.

The following metrics can help you gauge platform adoption:

• Deployment frequency
• The number of pipelines being run through the platform
• The number of developers engaging with the platform daily
• The number of apps, tools, and services accessible through the platform
• The proportion of services that have full documentation available
• The increase in MRs opened or infrastructure resources deployed after these processes are moved into the platform

KPIs in this category should reflect your expectation for platform adoption. For instance, you might aim for 95% of developers being able to use the platform to achieve all their day-to-day tasks. More frequent platform use is also a good general indicator of success; therefore, a relevant target might be to have 95% of developers active on the platform each day.

3. Reliability and performance metrics

Monitoring the reliability and performance of the tools created by platform engineers highlights problems and inefficiencies. Try instrumenting your platform so it exposes the following metrics:

• Resource consumption statistics (e.g., CPU and memory usage)
• Platform uptime and availability
• Average request duration
• Request latency
• Time taken to complete key processes, such as provisioning a new development environment
• Number of incidents experienced

These metrics align with KPIs such as maintaining 99.9% platform availability during business hours or being able to start new environments in under 15 minutes.

Slow and unreliable platforms add friction to developer workflows. They can actually hinder productivity if developers are kept waiting for unreliable processes to complete. Regularly reviewing performance metrics helps identify these issues, allowing you to make targeted improvements to address them.

4. Business value metrics

Although platform engineering primarily serves developers, it should ultimately generate business-level value too. Optimizing DevEx leads to productivity and throughput improvements, reducing change lead times for faster go-to-market times. This cycle creates a positive feedback loop where investment in platform engineering also enhances business outcomes.

Measuring the business value generated by platform engineering depends on all the metrics discussed above. Reliable, widely-adopted platforms that are actively improving daily DevEx are the most likely to positively impact your organization. Layering in the following additional metrics then lets you calculate the monetary ROI of platform engineering:

• Time spent implementing internal platforms
• Cost of platform implementation (salaries and new tool licenses)
• Reduction in average change lead times
• Reduction in production incidents experienced
• Reduction in the number of overall tools used
• Code quality and test failure rates
• Change in infrastructure costs before/after platform implementation
• Infrastructure utilization efficiency (e.g., if platform engineering enables greater sharing of resources between different services)
• Per-developer costs (costs of hiring, onboarding, and supporting each developer, before and after platform implementation)

These metrics illustrate the broader impacts of platform engineering. They allow you to measure compliance with business-level KPIs, such as reducing infrastructure spending by 10% or cutting change failure rates to under 1%. This helps you design platforms that go beyond serving developer needs to also support business and customer-facing priorities.

As we’ve outlined above, metrics are best analyzed in the context of your own KPIs. Success looks different for each team, so it’s important to set your own targets that reflect the unique parts of your operations.

Nonetheless, platform engineering is designed to improve the developer experience. Increasing software delivery productivity and efficiency is a secondary, implicit objective. Therefore, your KPIs will usually align around these themes.

At the highest level, platform engineering KPIs need to reflect the four categories of metrics discussed in this article: developer experience, platform adoption, platform reliability, and business-level benefits. For example, you may want to cut developer onboarding times to two days, reduce your spending on developer tools and infrastructure to 20% of its current level, or accelerate change lead times by an average of one day.

Once you’ve set your KPIs, you can select the metrics that’ll allow you to detect success. Use the suggestions we’ve provided above as a starting point, while ensuring each metric directly contributes to one of your KPIs. Metrics should be as precise, relevant, and actionable as possible; values that don’t support your KPIs will create unhelpful noise.

Platform metrics scorecard

To make platform engineering metrics actionable, it’s useful to organize them in a clear, structured format. The platform metrics scorecard below provides a practical example of how to track key metrics, align them with business goals, and monitor platform performance over time.

We’ve now covered the key metrics and KPIs to include in your platform engineering monitoring strategy. Let’s wrap up with a quick summary of some best practices to follow as you measure your platform’s success.

1. Set KPIs based on desired platform engineering outcomes

Your KPIs should represent the outcomes you want platform engineering to produce. Whether it’s quicker lead times, reduced infrastructure spending, or improved code quality, setting clear KPIs early on makes it likelier that your efforts will succeed.

2. Measure metrics that give actionable information about KPIs

Each metric you track should provide actionable information about one or more of your KPIs. This ensures the data you collect is actually relevant to your aims and operations. 

Filtering out metrics that aren’t aligned with KPIs allows you to cut through the noise and more easily identify significant trends.

3. Holistically analyze platform engineering outcomes across all KPIs

Metrics don’t exist in silos. You need to consider how metrics and KPIs interact to reveal the true extent of trends. Investing in platform engineering may initially increase infrastructure costs, for instance, but the expenditure could be offset by improvements in developer productivity that enable you to reach the market faster. 

The full picture is only revealed when you examine all your metrics and KPIs holistically.

4. Regularly iterate upon your metrics and KPIs

Regularly reviewing your metrics and KPIs ensures you’re still collecting the most suitable data as your platform matures. Your KPIs may change as your platform engineering experience matures, requiring adjustments to the metrics you collect. You may also find you need more data to combat visibility blind spots.

5. Focus on developer outcomes first and foremost

Improving the developer experience should be your primary goal in platform engineering. Monitoring developer outcomes using metrics such as onboarding time and developer satisfaction scores enables you to understand whether your platform is fulfilling its main purpose. 

Even if platform engineering doesn’t improve your business-level KPIs, enhancing DevEx will boost developer motivation and morale. This creates long-term benefits for your business.

6. Understand lagging and leading metrics

Finally, it’s important to distinguish between lagging and leading metrics. A leading metric quickly responds to new changes, whereas lagging metrics take time to update. 

Easily measured values, such as developer satisfaction and infrastructure costs, can be used as leading indicators. In contrast, higher-level statistics, including delivery throughput and average change lead time, are lagging indicators that require long-term data to establish a trend. 

Because platform engineering targets sustained improvements, it’s likely your KPIs will depend on leading metrics that may not always accurately reflect recent changes.

Spacelift is an IaC orchestration platform that serves as a great base for platform engineering. It enables you to build safe self-service infrastructure workflows that you can configure and govern using a single centralized solution.

Spacelift manages your IaC workflows, supporting Terraform, OpenTofu, Pulumi, CloudFormation, and more. You can trigger workflows either manually or based on automated events, such as a Git push. Blueprints allow you to create reusable stack templates that developers can launch on demand, without needing locally configured IaC tools or cloud credentials. 

The platform also supports Prometheus and Datadog integration, allowing you to collect detailed metrics and analyze developer activity.

Spacelift supports precise RBAC-based access management, policy-driven compliance controls, and direct integrations with your source repositories and cloud accounts. Our solution gives you a platform engineering head start by enabling scalable and secure infrastructure management. 

Spacelift lets platform teams centrally manage infrastructure workflows, while empowering developers to self-serve the resources they need.

If you want a product that greatly enhances the lives of your platform engineering team members, create a free account with Spacelift today, or book a demo with one of our engineers.

Platform engineering improves software delivery efficiency by focusing on DevEx enhancements. However, simply building new tools and processes doesn’t automatically guarantee success. You need to set clear KPIs and regularly monitor platform-level metrics to check you’re on track.

The metrics, KPIs, and best practices discussed above should help you get started building successful internal platforms. Remember to be realistic in your expectations and regularly iterate on the metrics you capture. You can then gradually refine your systems so they match developer needs more closely.