What is it?
Observability allows one to observe and understand what is happening during test execution. It means that we can see the inner workings of a test and examine, analyze, look at data inputs, review intermediate states, and also the output results.
People who use observability are seen to be 2.1 times more likely to detect any issues. Another benefit is that it has been reported that there is a 69% improvement in the meantime to repair (MTTR), which is how quickly an organization can respond to unplanned breakdowns and repair them.
Observability is great as it allows us to see what is happening in a test rather than wait for the final output.
With the push to the cloud, there are more changes and dynamism around changes. This means that it is difficult to deal with unknown things, for that reason observability is a lifesaver as it allows us to tackle the complexity.
This is a critical component of effective testing, DevSecOps, and software development. Teams can then use this data to build better, more secure, and more resilient applications.
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Why does observability matter?
If we want to ship new features faster and resolve issues before customers are impacted it is key that we have a strategy in place around observability.
It decreases our development time as we can diagnose issues more quickly.
We can increase our testing coverage, thus resulting in fewer escaped defects — which in turn means better quality software.
Better quality software means that our customers will be happier — which in turn means a positive business impact.
It has been shown that those who focus on observability have a competitive advantage.
Allows developers and testers to diagnose issues during testing. This means fixes can be understood more easily and they can be resolved.
Without observability, it is hard to determine the cause of the failure, so it is harder to fix and it can slow down the development process.
Lack of observability is a massive risk. Take for instance we have a production issue, without observability in place it would be very difficult to troubleshoot the issue and in most cases, it will take 3 times the time to find a root cause if that is even possible.
On top of this, the brand reputation can be damaged, developers will be frustrated and issues with your product will sit unresolved.
How can you add observability to your testing process?
Ultimately it can be used by anyone in a software development life cycle including developers, testers, and DevOps.
For instance, you can look into:
Using logging — will help you to track what is happening before and after any operations in your code.
Using debugging tools — you can add breakpoints and steps through the code to identify issues during testing. This is great for reproducing difficult issues and from experience, this was a lifesaver for me when I was a developer.
Use monitoring tools — these are real-time insights into the performance of your applications, report usage, and error rate. Monitoring tools are a key aid and it would be difficult to find these in testing.
Test automation — allows you to run your tests more quickly, at any instance of the life cycle.
My advice would be to start small and then use that confidence to move forward. It is also key that business benefit is taken with some ‘quick wins’. Look into your user logging and debugging tools as a starting point as these are not complex tasks.
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Testing in production
Observability facilitates testing in production by providing detailed information about the production environment and the infrastructure. As per my experience, testing is an educated approach to validate a system’s correctness, though it does not predict some edge cases or possible issues that may occur in production.
For that reason testing in production allows us to test code changes on live user traffic, catch bugs early and improve customer satisfaction.
There are two ways to conduct testing in production environments:
A/B testing — analyze if changes lead to a better user experience, with observability it is easier to see the impact.
Continuous monitoring — with this you can discover issues with the software.
What observability tools exist in the market?
a. Logging frameworks — these generate logs and capture relevant information during test execution.
b. Debuggers — tools that allow you to step through the code and examine values of variables at runtime.
c. Monitoring tools — provide real-time visibility into the performance of the application during test execution.
d. Test Automation frameworks — these allow you to automate manual test cases and collect data.
e. Profilers — measure the performance of the application during test execution.
f. APM tools — application performance monitoring to track the performance of your application during test execution.
The above tools are useful, though from experience the tool selected depends on your technical stack and also the architecture of your system.
For instance, when selecting your automation framework it depends on many factors such as:
Which framework is best for collaboration between developers and testers?
What is the language of the application being tested?
Does the architecture of the system lead itself more to one framework than another?
How long will it take to implement test observability in my organization?
This depends on the complexity of the system in question, the testing framework, and the level of observability required. Basic features like logging and debugging are easy to do and can be added quickly — in hours or days.
More advanced features like monitoring tools or profiling can take a lot longer. In these instances, proof of concept is key where course corrections are implemented if you are going down the wrong avenue.
In our DevSecOps team, the types of questions that we asked ourselves initially were:
Do we have any logs for the end-to-end customer journey?
Do we need any dashboards for capturing business metrics?
Do we need any alerts when this feature is due to go live?
Are we solely focusing on metrics when we should be looking at observability AND metrics?
What are possible challenges when implementing test observability?
Data silos — it is key that we understand our data and how it connects.
Volume, velocity, variety, and complexity — it’s always good to start small, keep learning, and then keep adding more data.
Manual instrumentation and configuration.
Lack of pre-production.
Wasting time troubleshooting
The area in which we struggled was that of data silos, by understanding our architecture better we could start to piece together how different data components were linked together. This was a time-consuming task, though it added a lot of value.
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Where is observability heading in the future?
Consolidation of tools — Right now many companies are having to use two or more tools to meet their observability needs. Having one tool will allow companies to save time, be more efficient, and also lower their costs.
Culture of collaboration — observability allows collaboration on code within the developer environment. This means that the collaboration and feedback loop between teams will be enhanced. The result will be better monitoring and fewer escaped defects in production.
On-demand tooling — modern observability tools are moving away from subscription structures that limit visibility and are moving to usage-based models. Usage-based models allow organizations to only pay for what they use.
In summary
Observability should be a natural ally to all testers. Remember testers ask questions and observability does the same, but aims to uncover answers.
We are more alike than we think! Working together can accelerate successful delivery. Ultimately, it is a win for customer experience.
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