How can you test and monitor a system during continuous delivery?

1 Choose the right testing strategy

Testing is essential to verify that your system meets the functional and non-functional requirements, as well as the user expectations. However, testing can be time-consuming, complex, and costly; thus, selecting the right testing strategy for your system architecture and delivery pipeline is key. Common testing strategies include unit testing, integration testing, system testing, acceptance testing, performance testing, and security testing. Depending on your system architecture, you may need to use different levels and types of testing; for instance, if you have a microservices-based system, more integration testing may be necessary while a monolithic system would require more system testing. Additionally, it is important to prioritize the most critical and risky features and scenarios for testing, as well as utilizing test automation tools and frameworks to expedite the process.

2 Implement continuous feedback loops

Feedback is essential to identifying and solving issues, enhancing quality, and optimizing performance. To achieve this, you should implement continuous feedback loops throughout your delivery pipeline from development to deployment to operation. This includes code reviews for ensuring coding standards and best practices are met, static analysis for evaluating code quality and detecting potential errors or vulnerabilities, dynamic analysis for analyzing runtime behavior and performance, test results to analyze test coverage, defects, and failures, deployment logs to monitor deployment status and history, monitoring metrics for assessing system health and performance indicators such as availability, response time, throughput, error rate etc., alerting systems to notify relevant stakeholders when the system exceeds a predefined threshold or experiences an anomaly, and feedback surveys for collecting user or customer feedback and satisfaction ratings. In order to benefit from these feedback loops, you should use tools and platforms that enable data collection, visualization, and analysis in real time. Additionally, it is important to communicate feedback with team members and other stakeholders so that necessary adjustments can be made to improve your system.

3 Design for observability and resilience

Observability and resilience are two key characteristics of a system that can handle changes and failures gracefully. Observability allows you to monitor and understand the internal state and behavior of your system from the external outputs, while resilience enables your system to recover and continue to function despite errors, faults, or disruptions. To design for these two characteristics, you should define and collect meaningful metrics that reflect the system performance, reliability, and user experience. Additionally, logging and tracing tools should be used to capture and correlate the system events and activities. Health checks and probes should be implemented to monitor the status and readiness of system components or services. Circuit breakers and fallbacks should be used to prevent cascading failures while providing alternative responses. Retries and timeouts should be used to handle transient errors, while load balancers and autoscaling should be employed to distribute the workload and resources. Finally, backups and disaster recovery plans should be in place to restore the system data and functionality. By designing for observability and resilience, you can enhance your system quality and availability while reducing the risks associated with failures.

4 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?