The introduction of cloud technology was one of the most significant technological shifts that have happened over the past two decades. Cloud engineering has not only enabled ISVs to reduce the costs involved with infrastructure but has shown a whole new perspective to scale the business technology reforms.
From the shortening of time to market with the software, infrastructure, or industry-leading platforms, cloud testing services have helped companies to deal with unpredictable spikes in demand for innovation.
Growth Statistics & Risks
As per the statistics shared by findstack,
- 81 percent of enterprises have laid out a multi-cloud strategy or are either in progress
- 67 percent of all enterprise infrastructure would be on the cloud by the end of 2021
- 82 percent of the workload is likely to reside on the cloud in the near future
- AWS owns the largest market share for cloud computing at 32 percent.
And with all such scope for expansion and growth, cloud computing is likely to be the base of future IT infrastructure. Nevertheless, despite having so many advantages, cloud computing or cloud engineering is a risk-ridden process. From regulatory guidelines to compliance issues, legal instructions, security, system uptime, and all the expense made on upgrade and migration, cloud demand some serious quality assurance.
Therefore, the idea of preventing any kind of pitfalls on the way to cloud migration or adopting cloud-based services, the organizations need to involve some quality benchmarks and strong testing practices with their existing engineering operations. In other words, the need to support the high-demand delivery models of cloud testing needs immediate attention when it comes to quality.
Like any other software, the implementation of cloud-based services also demands short release cycles that too along with hotfixes and feature enhancements that can help meet end-user goals. Besides, the success parameters for a cloud-based service can be defined as availability, performance, and scalability potential delivered over a stable internet connection.
Besides, meeting all these parameters demands a QA process that can meet the highest benchmarks of product architecture. Moreover, the implementation of the cloud demands higher maintainability from the service provider in order to overcome the high cost of ownership.
Cloud Testing Best Practices
Since the only way to achieve such goals with cloud engineering is to stick with some of the most significant cloud engineering testing best practices that can help yield success with cloud migration key elements integrated to the business models. Let us quickly jump on understanding the most important practices that make it to a successful cloud engineering business model.
An Iterative Approach
The first step to achieve a great cloud engineering project is opting for an iterative approach as you plan to build a project. Though you may consider taking on a big-bang approach that involves hundreds of parameters and quality aspects to meet at the earliest stages of the project, an iterative approach could help you keep things simplified. Moreover, an iterative approach is usually fostered with respect to agile methodologies, which means greater scope for practicing new techniques, rapid check on errors, and even faster error removal with the ease of working on any failed agendas.
Plan Early Data Migration
When your business operations rely on cloud technology, your migration requirements for scalability or any system updates should never come into the way of the customer operations. Therefore, the immediate step that you need to follow after planning the process is to jump on the data migration. This might need you to gather all the team of engineers, developers, testers, and technical stakeholders to intervene and develop a strategy that could help with customer data migration early in the development lifecycle.
Measure Cloud Infrastructure
Once you are done shaping your cloud data migration strategy as per the iterative approach and agile practices, you need to jump on evaluating the existing cloud infrastructure. It will help you learn the suitability of the existing system for rationalizing the development goals and understand the need for scalability on the existing technical framework to create the required test infrastructure. Some of the most significant benefits of measuring your cloud infrastructure include saving on resources, better resource utilization, and overall improvement on time to market.
Decide The Test Plans
When working on a cloud project that needs to align with the futuristic business requirements of the customers, it is vital that everything must be tested well in time. Once you are done working on the idea of measuring cloud infrastructure scalability requirements, make sure you start working on integrating test cycles into your project. As it needs you to accommodate functionality, availability, performance, reliability, & security, make sure you have sufficient bandwidth to manage all the test cycles.
Establish Delivery Control
Since testing needs to be done in a controlled environment, establishing control on delivery operations is even more crucial with cloud engineering. This might need you to foster integrations like the use of project life cycle management tools that can help have the advantage to trace the project. The traceability and visibility requirements allow you to have all the command you need to check the project under test for optimum delivery.
Cloud testing services are mission-critical when you need to establish a stable, secure, and performance-oriented cloud engineering project. Therefore, the right approach to testing should involve running smoke tests on every daily build that on success should be moved to regression. On top of that, your test teams should focus on running a CI/CD (Continuous Integration/Continuous Development) Pipeline to ensure that all the parts of the project should align with each other. Moreover, continuous integration into the cloud testing process allows you to attain the highest quality benchmarks overcoming any potential flaws.
Automation Is A Must
Things have changed a lot with time. Earlier, there was no such struggle with the launch of technical solutions as only a few major brands were there to embrace the requirements of the business enthusiasts. However, the modern business environment is highly dependent on cloud technology, and for no surprise, most business organizations these days have their own team of engineers to take on development, testing, and deployment.
Cutting it short, the modern business environment needs faster solutions that come from quick scalability and faster launches. Since testing every single component for efficiency in the cloud can be tricky, automating the QA infrastructure setup could help prevent all the extra provisioning time while collaborating with the right cloud testing services provider can help prevent all the downtime.
Regression Test Suite Automation
Last but not least, you need to ensure that all the regression test suites must be automated to their full capacity. This would help your team to focus on the most significant issues with the development process while you can automate regression test suites to work on all the repetitive tasks. Moreover, you can hire testers for cloud testing to help you with the automation of regression test suites while reducing all the unwanted delays to the release cycle.
Concluding it all…
Cloud engineering is one of the most complex technical operations to foster, and it gets even more complicated when testing comes into the picture. The right balance of automation and manual testing on the way to define cloud migration key elements could turn to be a pain for the developers when not done with the right approach.
However, having all the essential knowledge on the best practices could help execute the entire process seamlessly. In the above article, we tried discussing some of the most important testings best practices that are user-friendly and could help you yield success with your cloud engineering ventures.
All The Best!