3 Measuring your way to platform engineering success

 

This chapter covers

  • Using data and measurements to determine success
  • Assessing engineering practice and quality over the entire end-to-end delivery lifecycle
  • Acting on platform product key performance indicators and developer experience effects
  • Planning for maturing capabilities

So far in our journey at Epetech, we have established a vision and strategy based on the business need for building an engineering platform, and we have put together the foundational engineering practices to create it. We have also looked at software-­defined platforms and the cloud-native approach, which simplifies the process. Now it’s time for the last critical element of our planning process: measuring what we will build. This chapter will round out all the pieces required to ensure we are setting up the platform engineering journey to succeed—not just in the short term but for scaling.

3.1 Organizational aspects of platform engineering success

3.1.1 Changes needed for an organization to prepare for platform engineering

3.1.2 Prerequisites for the change

3.1.3 Implementing organizational changes

3.1.4 Building platforms in organizations

3.2 Path-to-production and platform value metrics

3.2.1 How do you identify the scope of your engineering platform?

3.2.2 Platform value modeling and metrics

3.3 Cognitive load and mechanical sympathy for developers and platform engineers

3.3.1 What is cognitive load for developers, and how do we measure it?

3.3.2 Why reduce cognitive load?

3.3.3 Techniques for reducing cognitive load

3.3.4 The need for mechanical sympathy

3.4 Common platform performance metrics

3.4.1 Adoption

3.4.2 Developer sentiment

3.4.3 Effectiveness

3.5 Evolving measures

3.5.1 Cost planning

3.5.2 Risk assessment

Summary