9 Metrics Database DevOps Teams Should be Tracking

In a world where users expect timely and responsive updates, speed and agility are essential to survival. To deliver this speed and innovation to users, organizations have turned to database DevOps.

While there are countless best-practices guides, organizational coaches, executive courses, and more on the topic of DevOps for the database, organizations often fail to recognize when and where problems can actually be helped by DevOps. By focusing on this essential set of 9 DevOps metrics, organizations can ensure that their efforts are moving in the right direction.

1. Deployment Frequency 

This metric should trend up or remain stable from week to week. While this metric doesn’t tell the full story, it’s one of the most important markers of speed and agility. A very low deployment frequency means that your business isn’t in a position to adapt to changing market conditions well.

If you are releasing only once or twice a year, you risk disruption from competitors who have found ways to speed up their software releases. You also risk angering users who are still waiting for you to address their feedback with new capabilities and innovation. The goal is to move towards smaller, more frequent releases. Smaller releases are less risky, which allows your organization to better respond to the market 

2. Change Volume 

Measuring and tracking change volume helps you temper the effects of solely pushing your team towards a high deployment frequency.

It’s easy to have a large deployment frequency by rapidly releasing trivial changes that are inconsequential to the user experience and to market needs. By tracking change volume and ensuring that net output over time (change volume times deployment frequency) is not suffering, you can have confidence that you are delivering new capabilities and enhancements in a smaller and more agile manner. 

3. Lead Time 

Lead time is the amount of time it takes for code to get from development all the way through to production.

A long lead time should be a big warning sign. This could show that any changes to product direction or strategy to respond to market conditions will take a long time to deliver. The goal is to get shorter lead times so that your business is nimble and can quickly adapt – or even capitalize – on new or emerging market conditions. 

4. Percentage of Failed Deployments 

Tracking the percentage of failed deployments charts releases that:

  • Caused outages of service
  • Degraded end-user performance or experience
  • Failed to meet end user needs

In attempting to quickly deliver new capabilities and enhancements, it’s important not to sacrifice quality or performance. Tracking failed deployments can ensure that the increase in agility is not coming at the expense of quality. 

5. Mean Time to Recovery (MTTR)

It’s an inevitability that something will go wrong, and it’s important to plan for failure and recovery. By tracking how long it takes the team to recover from a failure, you can ensure that team collaboration, transparency, product architecture, technical debt, and more are in balance – and that your team, product, and process are robust enough to bounce back quickly from failure. When mean time to recovery starts to creep up from your average mean time, it’s a sign that either the team, product, or process is in need of attention. 

6. Customer Ticket Volume 

This is a great indicator of customer satisfaction and an insightful metric to track. For instance, if you’re looking to deploy more without causing outages, you can track tickets post deployment. The number of tickets generated by users is a good indicator of how well a team is doing in achieving their goals. 

7. % Change in User Volume 

A change in user volume can show the number of new users signing up, the amount of traffic generated, and how they are interacting with the service of your team. Tracking this metric can help ensure that your infrastructure is able to meet demand. 

8. Availability 

Were any SLAs violated, and what is the overall uptime for the product or service? If you can maintain healthy uptime even given fluctuations in user volume, you’re tracking pretty well. 

9. Performance (Response Time)    

Response time and performance should remain stable, even after an increase in user volume or a new deployment. Performance metrics indicates that the product or service is operating within predetermined thresholds.   

These database DevOps metrics are a great start for any organization. Companies that adopt database DevOps can deliver applications faster — going from what was once measured in weeks or months, to days or even hours. This means delivering value to your customers in ways that your competitors can’t. 

But, by using DevOps tools to properly measure and improve these core metrics, you can get rid of inefficiencies, remain competitive, and ensure long-term survival in the marketplace.

Seeing is believing.