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What are the risks of relying too heavily on continuous integration metrics?

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Continuous integration (CI) is a practice of merging code changes frequently and automatically testing them for errors. CI metrics are indicators of the quality, speed, and efficiency of the CI process. They can help system architects identify and resolve issues, improve performance, and deliver value to customers. However, relying too heavily on CI metrics can also pose some risks that may compromise the system architecture and the business goals. Here are some of the risks and how to avoid them.

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1 Risk 1: Focusing on quantity over quality

One of the common risks of relying too heavily on CI metrics is focusing on quantity over quality. For example, you may be tempted to measure the success of your CI process by the number of builds, commits, tests, or deployments per day or week. However, this may not reflect the actual quality of your code, the functionality of your features, or the satisfaction of your users. You may end up with a lot of code changes that are poorly tested, buggy, or irrelevant to the customer needs. To avoid this risk, you should balance your CI metrics with other quality metrics, such as code coverage, defect rate, user feedback, or business value.

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Edwin Harris II

Senior Software Developer @ Florida DCF | Azure Developer Associate
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Avoid tunnel vision on certain metrics: high code coverage doesn't mean you have effective tests that provide value. Prioritize metrics that provide value to the enterprise, process, solution, out customer. Don't focus so much on those that do neither but make a neat statistic to impress your manager. Balancing quantity and quality in CI metrics is vital for achieving the primary goals of CI: maintaining high code quality and meeting user and business needs. This balance requires a comprehensive approach that integrates various metrics, from code coverage to user feedback, ensuring that the focus remains on delivering value rather than merely tracking numerical progress. Value, value, value!

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2 Risk 2: Ignoring the context and the trade-offs

Another risk of relying too heavily on CI metrics is ignoring the context and the trade-offs of your system architecture. For example, you may be obsessed with achieving a high level of automation, speed, and reliability in your CI process. However, this may come at the cost of flexibility, scalability, or security in your system architecture. You may end up with a rigid, complex, or vulnerable system that cannot adapt to changing requirements, environments, or threats. To avoid this risk, you should consider the context and the trade-offs of your system architecture and align your CI metrics with your architectural principles, goals, and constraints.

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Edwin Harris II

Senior Software Developer @ Florida DCF | Azure Developer Associate
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Always align CI metrics with overarching architectural goals. For instance, include performance and security reviews as part of the CI process. Quality architectural features often require more resources. Balance the need for speed with the necessity of thoroughness. And finally, system requirements change. Ensure that CI processes and metrics are flexible enough to adapt to these changes. Balancing CI metrics with the broader context of system architecture is crucial. It involves understanding and managing trade-offs between various desirable qualities like speed, scalability, flexibility, and security. This balance ensures that the CI process supports a robust and adaptable system architecture.

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3 Risk 3: Misinterpreting or manipulating the data

A third risk of relying too heavily on CI metrics is misinterpreting or manipulating the data. For example, you may be influenced by cognitive biases, such as confirmation bias, anchoring bias, or survivorship bias, when analyzing your CI metrics. You may only look for data that supports your assumptions, opinions, or preferences, and ignore or discard data that contradicts them. You may also be tempted to manipulate the data to make it look better, such as cherry-picking, smoothing, or falsifying the data. This may lead to inaccurate, incomplete, or misleading insights that may harm your system architecture and your business decisions. To avoid this risk, you should use objective, reliable, and transparent data sources, methods, and tools for your CI metrics, and verify, validate, and communicate your data clearly and honestly.

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4 Risk 4: Creating a culture of blame and pressure

A fourth risk of relying too heavily on CI metrics is creating a culture of blame and pressure. For example, you may use your CI metrics as a way of judging, rewarding, or punishing your team members or stakeholders. You may blame them for failing to meet your CI metrics, or pressure them to achieve unrealistic or unreasonable targets. This may create a toxic and stressful environment that may lower the morale, motivation, and collaboration of your team and stakeholders. It may also discourage them from taking risks, experimenting, or learning from failures. To avoid this risk, you should use your CI metrics as a way of supporting, empowering, and improving your team and stakeholders. You should celebrate their successes, acknowledge their challenges, and provide them with constructive feedback, guidance, and resources.

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5 Risk 5: Missing the big picture and the purpose

A fifth risk of relying too heavily on CI metrics is missing the big picture and the purpose of your system architecture and your business. For example, you may be so focused on optimizing your CI metrics that you lose sight of the overall vision, mission, and strategy of your system architecture and your business. You may forget why you are building the system, who you are building it for, and what value you are delivering to them. You may also neglect other aspects of your system architecture and your business, such as innovation, customer experience, or social responsibility. To avoid this risk, you should always remember the big picture and the purpose of your system architecture and your business, and align your CI metrics with them. You should also review and revise your CI metrics regularly to ensure that they are relevant, meaningful, and impactful.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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What are the risks of relying too heavily on continuous integration metrics?

1

2

3

4

5

6

1 Risk 1: Focusing on quantity over quality

2 Risk 2: Ignoring the context and the trade-offs

3 Risk 3: Misinterpreting or manipulating the data

4 Risk 4: Creating a culture of blame and pressure

5 Risk 5: Missing the big picture and the purpose

6 Here’s what else to consider

System Architecture

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What are the risks of relying too heavily on continuous integration metrics?

1

2

3

4

5

6

1 Risk 1: Focusing on quantity over quality

2 Risk 2: Ignoring the context and the trade-offs

3 Risk 3: Misinterpreting or manipulating the data

4 Risk 4: Creating a culture of blame and pressure

5 Risk 5: Missing the big picture and the purpose

6 Here’s what else to consider

System Architecture

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