DevOps measurement: Monitoring systems to inform business decisions

Monitoring is the process of collecting, analyzing, and using information to track applications and infrastructure in order to guide business decisions. Monitoring is a key capability because it gives you insight into your systems and your work. Properly implemented, monitoring also gives you rapid feedback so that you can quickly find and fix problems early in the software development lifecycle.

Monitoring also helps you communicate information about your systems to people in other areas of the software development and delivery pipeline, and to other parts of the business. Knowledge acquired downstream in operations might get integrated into upstream teams, such as development and product management. For example, the knowledge gained from operating a highly scalable application that uses a NoSQL database as a data store can be valuable information for developers as they build a similar application.

This knowledge transfer allows teams to quickly identify learnings, whether they stem from a production issue, a deployment error, or your customer usage patterns. You can then share these learnings across your organization to help people and systems improve.

How to implement monitoring

The following elements are key to effective monitoring:

  • Collecting data from key areas throughout the value chain, including application performance and infrastructure.
  • Using the collected data to make business decisions.

Collecting data

To collect data more effectively, you should implement monitoring solutions, either as homegrown services or managed services, that give visibility into development work, testing, QA, and IT operations. Make sure that you choose metrics that are appropriate for function and for your business. For a discussion of metrics and measurement in DevOps, see the white paper (PDF) from the 2015 DevOps Enterprise Forum.

Using data to make business decisions

When you transform and visualize the collected data, you make it accessible to different audiences and help them make decisions. For example, you might want to share operations data upstream.You can also integrate this data as appropriate into reports and briefings, and use it in meetings to make informed business decisions. In this case, appropriate means relevant, timely, accurate, and easy to understand.

In these meetings, be sure to also provide context, to help those who might not be familiar with the data understand how it pertains to the discussion and how it can inform the decisions to be made. For example, you might want to know how to answer the following questions:

  • Are these values relatively high or low?
  • Are they expected?
  • Do you anticipate changes?
  • How is this data different from historical reports?
  • Has your technology or infrastructure impacted the numbers in interesting or non-obvious ways?

Common pitfalls in monitoring

The following pitfalls are common when monitoring systems:

  • Monitoring reactively. For example, only getting alerted when the system goes down, but not using monitoring data to help alert when the system approaches critical thresholds.

  • Monitoring too small a scope. For example, monitoring one or two areas rather than the full software development and delivery pipeline. This pitfall highlights metrics, focusing only on the areas that are measured, which might not be the optimal areas to monitor.

  • Focusing on local optimizations. For example, focusing on reducing the response time for one service's storage needs without evaluating whether the broader infrastructure could also benefit from the same improvement.

  • Monitoring everything. By collecting data and reporting on everything your system, you run the risk of over-alerting or drowning in data. Taking a thoughtful approach to monitoring can help draw attention to key areas.

Ways to improve monitoring

To improve your monitoring effectiveness, we recommend that you focus your efforts on two main areas:

  1. Collecting data from key areas throughout the value chain.

    By analyzing the data that you collect and doing a gap analysis, you can help ensure that you collect the right data for your organization.

  2. Using the collected data to make business decisions.

    The data that you collect should drive value across the organization, and the metrics that you select must be meaningful to your organization. Meaningful data can be used by many teams, from DevOps to Finance.

    It's also important to find the right medium to display the monitoring information. Different uses for the information demand different presentation choices. Real-time dashboards might be most useful to the DevOps team, while regularly generated business reports might be useful for metrics measured over a longer period.

    The most important thing is to ensure the data is available, shared, and used to guide decisions. If the best you can do to kick things off is a shared spreadsheet, use that. Then graduate to fancy dashboards later. Don't let perfect be the enemy of good enough.

Ways to measure monitoring

Effective monitoring helps drive performance improvements in software development and delivery. However, measuring the effectiveness of monitoring can be difficult to instrument in systems. Although you might be able to automatically measure how much data is being collected from your systems and the types of that data, it's more difficult to know if or where that data is being used.

To help you gauge the effectiveness of monitoring in your organization, consider the extent to which people agree or disagree with the following statements:

  • Data from application performance monitoring tools is used to make business decisions.
  • Data from infrastructure monitoring tools is used to make business decisions.

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