Shift left in testing has always been important.
However, shift right in testing has become increasingly important.
The methods by which we gather data out of production monitoring tools like Data Dog and AppDynamics and turn it into meaningful consumption for testing in automation, performance, functional, integration, end-to-end, and others carry high significance.
Gaining access to production data is a boon these days, as it provides a delta of what we are testing and what’s being tested in production by real users. This data ultimately helps testing teams be more proactive, efficient, and effective.
I am a tester and can build my test infrastructure and environments.
Repeated complaints from testing teams are that they have to wait for days or even months to get a test environment, and this becomes a hurdle when they must test something to meet deadlines, even if they depend on external teams for the testing. We transitioned and built a testing team that could build their infrastructure and environments for all testing activities, and were able to make the entire process automated based on their requirements.
DevPerfOps–Performance Testing & Engineering in the DevOps World
Performance testing in DevOps is still a pain today with a lot of challenges. In response, we automated and built an end-to-end performance testing system and integrated it into the pipeline with auto-monitoring and an advanced level of auto analysis that enables the test team to understand:
(a) How auto analysis could be the future, and how people need to adopt it.
(b) The challenges, best practices, and plans and where they should focus.
Why and how to Build Your Test Results Data Gold Mine?
Companies need to focus on testing data. We have been trying to push all of our testing results data (unit, integration, performance, security, accessibility, and other types) to a centralized database (NoSQL database). Once we do this, we can build various kinds of dashboards and metrics, and radiate them across the company and its teams. We can also start building AI/ML on top of this to perform predictive analysis and more. This will eventually help open up a lot of avenues to tap into once we have this data.
Performance Testing and Engineering on Cloud/AWS
It’s an ocean, and it takes a lot of effort and fine planning to reap the benefits of cloud and AWS. We have been conducting performance testing and engineering on AWS for many years and are quite familiar with the challenges, best practices, and services that must be leveraged in order to carry out performance testing on AWS.
How to Build the Mountain-Testing Database
We can use this database for a variety of testing requirements, and it is of utmost importance for organizations to build and manage these truly golden databases. We have a large volume of performance testing databases and we’re proud of the effort, planning, and time our team has spent to build it over the years. We continue to build it as our product develops and we have a robust process on how we manage, maintain, deploy, and replicate it across multiple environments.