DevOps is the combination of practices and philosophies that increases a business’s ability to deliver applications and services at a much faster pace than those organizations that use traditional software development and processes. This momentum allows businesses to serve their customers in a better way and improve their footprint in the market.
However, how do organizations know that DevOps is working? Are their customers satisfied? Where is the delivery speed slowing down? These are all very important questions and there is a method to figure out their answers. This method requires appropriate measurement and monitoring systems to make informed business decisions.
Measuring the Right Things
Monitoring is the set of procedures and processes performed to collect, analyze, and use the information to track applications and infrastructure to make smart and effective business decisions. Here are the main goals of monitoring:
- It gives you a deep insight into the systems. When performance issues arise, monitoring, if done right, feeds diagnostic data back to development teams.
- Monitoring allows you to communicate system information to software development areas and other parts of the business. This allows the DevOps team to identify the root problem, whether the issue is a production or deployment one, or customer usage patterns, and use the data to mitigate the issues.
- Another monitoring goal is to determine the impact of change. If the outcome is positive, the team can double down on it. If it is negative, the team will work on remediation so that they do not recur.
How to Implement and Improve Monitoring
Collecting Data: To collect data from key value chain areas, like application performance and infrastructure, businesses need to implement monitoring solutions, either as in-house or managed services, which provides transparency into application development, testing, quality assurance, and IT operations. Here are some key metrics that businesses can start with when making data-driven decisions.
Mean Time Between Failure (MTBF): This refers to the average time between when a problem has been identified and when it is fixed. This shows your company’s ability to detect and solve issues.
Lead Time: The average time between conceptualization and the implementation phase. This is an effective KPI to assess workflow, efficiency, and productivity.
Defect Escape Rate: The frequency at which errors are discovered and fixed during the pre-production process rather than during production. This determines the quality of your software releases and the ability of the software development team to innovate.
Apdex: The measure of how much your customers/clients are satisfied with the response of web applications. The response time starts when the customer makes a request and ends when that request has been completed or resolved.
Change Lead Time: Also known as Mean Time to Change, this refers to the time it takes for a new update, bug fix, or any other change to go from the concept to production. This determines the efficiency of the development process. By performing a gap analysis on this data, you can ensure that you have collected relevant data for your organization. Businesses can represent and make this data available via different charts and reports. By making sure your team has a greater understanding of their value and impact, you can identify the areas you need to identify your future investments. Equipped with this information, your organization can make data-oriented decisions.
Using Data for Informed Decision-Making
By interpreting the collected data, businesses can make it accessible to different departments and help them in their decision-making processes. This data may be integrated to create relevant, timely, and easy to understand reports. Businesses should also provide some context so that all audiences can understand how the data pertains to the discussion and how it can result in informed business decisions. Some questions that may require answers include:
- How high and low the values are?
- Are these values expected?
- How is the data different from historical reports?
- Has your technology impacted the numbers in significant ways?
Whatever data you collect, it should have the potential to drive value across the entire organization. This type of meaningful data is useful for many different teams, from DevOps to Marketing to Finance to Customer Support. It is also important that businesses find the right medium to display the key metrics and data since different usage demands different data presentation options. For DevOps teams, a real-time dashboard might be a better choice while routine reports might be a good option if you want to see historical metric data over longer periods of time. The most important thing to keep in mind is that this data is appropriately accessible to various teams and is used to create informed business decisions.
Pitfalls When Monitoring Systems
Here are some pitfalls that DevOps should avoid when monitoring systems:
- Not monitoring proactively: The team may only get alerted and start remediation when a system issue causes a breakdown, instead of being alerted when a system approaches critical levels.
- Monitoring on a very limited scope: Businesses should make it a habit to monitor their entire software development and delivery pipeline on a regular business, rather than just monitor one or two areas they think should be measured.
These few areas may not be the best places to monitor.
- Optimizing locally: Focusing on a single area without considering its impact on the broader infrastructure is one of the most common mistakes businesses make. In many cases, the overall infrastructure may benefit from the same remediation efforts.
- Monitoring everything: If you try to measure each and every metric, you risk drowning in data. Instead, businesses need to take a smart approach and figure out which key metrics need to be measured that can result in optimal outcomes.
If your monitoring is done well, it can help increase software development and delivery speed and performance. Although businesses may be able to measure the data and the types of data being collected from their systems, they have more difficulty understanding whether the data is being used in order to make informed business decisions. To help figure out the effectiveness of monitoring in your business, you need to consider whether people think that data from application performance and infrastructure monitoring tools should be used to make business decisions. Source: https://cloud.google.com/architecture/devops/devops-measurement-monitoring-systems