10 Crucial Engineering Metrics Must Follow In 2024

Software engineers use performance metrics to make informed decisions about their products, features, processes, and even their dev teams. In addition, measuring lets you know if you’re on track to meet your engineering goals.

With so many tasks, data, and other information to monitor, how do you choose the right metrics to track? We’ll share that and more in this guide.

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Engineering Metrics Vs. Engineering KPIs: What’s The Difference?

DevOps engineers, IT professionals, and management use the terms interchangeably. Yet, metrics and KPIs do not mean the same thing.

All KPIs are metrics. But not all metrics are “key” performance indicators in software engineering.

What are engineering metrics?

Metrics show the status of various aspects of engineering. They include progress or performance data. Today, you can measure plenty of software engineering metrics. They fall into three categories:

Most modern software development tools offer rich dashboards that display a variety of metrics. The different metrics do not contribute equally to improving software quality or engineering workflows. Metrics that correlate with specific organizational objectives are the ones to measure. This is where KPIs come in.

What is an engineering KPI?

An engineering KPI (Key Performance Indicator) is a quantifiable metric that an engineering team uses to gauge its success over time — and whether or not they’re meeting set strategic goals. Engineering KPIs can be performance, security, or cost related.

The following are four examples of engineering goals you may be working on:

Each of these goals will require a metric or set of metrics to measure your progress towards achieving the goal. What KPIs should you measure for each goal? How do you measure the right engineering KPIs for each purpose?

trics show the status of various aspects of engineering. They include progress or performance data. Today, you can measure plenty of software engineering metrics. They fall into three categories:

Most modern software development tools offer rich dashboards that display a variety of metrics. The different metrics do not contribute equally to improving software quality or engineering workflows. Metrics that correlate with specific organizational objectives are the ones to measure. This is where KPIs come in.

What is an engineering KPI?

An engineering KPI (Key Performance Indicator) is a quantifiable metric that an engineering team uses to gauge its success over time — and whether or not they’re meeting set strategic goals. Engineering KPIs can be performance, security, or cost related.

The following are four examples of engineering goals you may be working on:

Each of these goals will require a metric or set of metrics to measure your progress towards achieving the goal. What KPIs should you measure for each goal? How do you measure the right engineering KPIs for each purpose?

How To Measure The Right Engineering Metrics And KPIs

A lot of engineers feel metrics are unfair. “Software development cannot be quantified”, they might say. However, often they really mean using metrics like “business value”, “story points”, “tickets”, and “lines of code” to judge software engineers’ productivity is neither accurate nor fair.

The following seven characteristics will help you find the right metrics to track and measure.

So, are the benefits of measuring, tracking, and tweaking your engineering metrics worth all the effort?

Consider the following.

What Are The Benefits Of Tracking Engineering Metrics?

Engineering metrics deliver both qualitative and quantitative benefits that include the following.

With these benefits in mind, what are the top software engineering KPIs you’ll want to track, monitor, and measure for your organization?

10 Core KPIs That Ensure Software Engineering Success

Each organization sets its own KPIs based on its targets, so the following ten won’t make an exhaustive list. However, the following engineering KPIs do span various types of metrics in software engineering, from people and process metrics to project, internal, and external metrics. They include:

Now let’s look at a few of the top KPIs for engineering teams.

1. Velocity

Engineers or teams use velocity to measure how much work they accomplish in a sprint. It is a performance KPI that is different for every engineer or team.

Using velocity, you can predict how much time an engineer or team will need to complete a backlog. You can measure velocity in hours or story points. An average velocity of four to seven sprints may be an excellent way to measure it.

When commits do not match actual work completed, issues are likely present in product throughput, active days, efficiency (percentage of quality code), and commitment size.

2. Cycle time

Cycle time is a vital engineering KPI because it measures how much time a task took to complete. It could be a bug fix or adding new code. It also includes each time you reopen work and complete it again.

You can use cycle times to identify what work takes especially long to complete — and identify bottlenecks that slow down projects. Plus, you can estimate the length of future projects.

To measure cycle time, take the time needed to complete a task minus the start time. The cycle time can be in hours, days, weeks, or sprints. Low values are better. It is usual for cycle time to vary from project to project. However, projects with similar story points should have a consistent average cycle time.

3. Cumulative flow

Cumulative flow is a progress engineering KPI that shows how tasks are distributed across various stages so you can identify bottlenecks and ensure consistent workflows.

You measure cumulative flow using a visual chart to show how tickets shift from one status to another over time. For example:

The x-axis represents time and the y-axis represents tasks. The colors indicate the task’s status, with red denoting tasks that are awaiting delivery and green showing tasks that have been completed.

When the bands progress in parallel, the throughput is stable. This indicates that tasks are entering and leaving your workflow in equal numbers.

A rapidly widening band means you have fewer tasks completed than cards are coming in. But a rapidly narrowing band shows that you have more capacity than you need. So you can relocate elsewhere.

4. Sprint burndown

A sprint burndown measures how much work is left to do before a sprint is over. The KPI indicates progress towards a specific goal rather than showing only completed tasks. The sprint burndown chart allows engineers to track the rate at which they must burn down story points to complete a sprint on time.

The black line below represents that rate:

The blue line shows how many story points engineers burned down over 10 days. Notice how they couldn’t keep up between days three to six but exceeded the target after that.

This KPI can also help you discover unplanned tasks when you find your work keeps increasing or is stagnant instead of reducing. You can also use it to quickly diagnose and resolve performance problems.

5. Release burndown

Software engineers use release burndown as a KPI to determine how much work they need to complete before releasing a product.

It is a powerful metric for estimating releases in real-time. Each time you make a change to the code, it will help you keep track of how it affects the release date. Then, you can predict by how many sprints the release deadline can be shifted.

It’s like creating a sprint burndown chart, except release burndown measures the entire project’s remaining work, whether it’s hours, days, weeks, or sprints.

6. Code churn

Code churn is both an effectiveness and code quality KPI that shows the number of code changes (rewrites or deletions) your developers make within 21 days of writing the first code.

Code churn charts might look this:

A high churn rate during the initial stages of development is healthy, but it should level off towards the release stage. You may have unstable code throughout the various software engineering phases if you have a high churn near release.

7. Mean time to repair (MTTR)

MTTR can be a production or security KPI, depending on the context you use it.

As a production metric, it measures the amount of time engineers take to repair a problem or recover fully. As a software security KPI, it shows the time it takes engineers to deploy a working solution from the time they discover a security breach.

Calculate MTTR by dividing the total amount of time you spent on repairs over a period of time. A lower number is better.

MTTR shows how long users must wait before re-using the software in both scenarios. It is what many users refer to as technical support. As a result, it impacts customer experience and how likely a customer will be to recommend your service to others.

8. Mean time between failures (MTBF)

Engineers and customers use MTBF to gauge software quality and reliability. In actual use, it reflects how long the product lasts without causing any disruptions. The longer the time before repairs, the better.

Divide the total operational time for a given period by the total number of failures to get the mean.

9. Supporting each other

When you focus on helping customers, you are on the right track. However, collaboration begins closer to home, whether within a team, department, or an entire organization. Teamwork, continuous improvement, and getting team members unstuck are all collaboration KPIs for engineers.

Metrics you can use to foster a willingness to help each other include:

10. Cost

Cost estimation is a key part of resource planning for engineering projects. You can use cost metrics to help you understand your engineers’ costs for building and running your products.

There are several ways in which cost insight can help you. Here’s how:

Consider cloud costs, for instance. If you use a cloud service provider like AWS, it can be nearly impossible to see how line items on your AWS bill translate to real business value by simply looking at how much you spent that month.

The next thing is to align your engineering metrics with your company-wide goals to see how your technical decisions affect your entire organization.

How To Align Engineering Metrics With Your Company-Wide Goals

Here’s the thing. Engineering metrics by themselves aren’t helpful if they are not linked to specific business dimensions. For them to be resourceful, the metrics need to mean something in the context of your business. How?

Mapping engineering metrics to specific features, customers, dev teams, and products can help transform them from mere metrics to KPIs. Here’s an example.

You can track cost per feature to see how much your engineers are spending to support a specific product feature. They can also track its usage. By doing this, you can learn how popular the feature is among your customers and how much it costs to support each month.

Then you can move the feature to a higher pricing plan if demand is high enough to justify charging more for it. Alternatively, if it is not popular and you need to reduce waste, you can refactor it or decommission it altogether.

Yet, few cloud cost tools can help you map your engineering metrics to your business goals.

CloudZero can help

With a comprehensive cloud cost optimization platform, like CloudZero, you can accurately link your engineering metrics to your business goals in terms of costs — without losing your mind.

For example, CloudZero helps you to capture, understand, and take immediate action on granular cost insights for engineers, such as cost per deployment, per product feature, per migration, per service, per team, per project, and more.

By shifting cloud cost optimization left, you can empower your engineers to understand how their technical decisions impact your organization’s finances.

With CloudZero, your engineers can track engineering costs almost in real-time, with hourly reports, and context-rich cost anomaly alerts, enabling them to see what specific actions lead to overspending and which ones do not.

With time, they will learn what decisions to avoid at the architectural level in order to build cost-effective solutions. The solutions can help you not only avoid overspending in the short term, but also improve your margins over time.

With the savings, you can further improve your services, or add more in-demand features without much external financing. You can also leverage the savings to lower your product prices and attract and retain customers.

CloudZero was designed for engineers. It is intuitive and self-serve. You’ll be able to investigate engineering cost issues and debug them in minutes. From AWS to Kubernetes to Datadog, CloudZero will be your single pane of glass for all your cloud costs.

Yet, reading about CloudZero is nothing like experiencing it for yourself. to experience CloudZero in action.

Frequently Asked Questions About Engineering Metrics And KPIs

Here are answers to some burning engineering metrics FAQs.

How do you measure productivity in software engineering?

Each organization measures productivity differently. But the most common method is to calculate the amount of output for a specific timeframe, such as user stories or line of code.

What is the most useful metric to measure for an engineering team?

Engineering cycle time is one of the most critical metrics to track since it gives you an idea of how efficient your processes are.

What are the KPIs for engineering maintenance?

Consider mean time between failure, unscheduled downtime, maintenance costs, and work order cycle time.

What is the difference between lead time to changes and cycle time in engineering metrics?

A software engineer’s lead time to change refers to the time it takes from receiving a feature request from a project stakeholder to fulfilling it.

Meanwhile, cycle time refers to the time committed to developing a feature up until it is ready to ship.

This metric demonstrates a development process’s velocity. It indicates how quickly engineering can deliver a product to the customer, from start to finish.