Cloud computing has brought about a profound change in the way businesses function today. Whether it is business expansion, service offerings, security infrastructure, or product management, cloud services have helped organizations improve upon every business segment.
Cloud adoption continues to grow globally across the industry spectrum. A recent Gartner report shows that spending on public cloud services will reach $482 billion in 2022. In addition, Gartner has also predicted that public cloud spending for all enterprises will increase from just 17% in 2021 to 45% of their IT spending by 2026.
Even though cloud migration and adoption are all-pervasive, organizations find it challenging to adopt the cloud effectively. As a result, to embrace the cloud with confidence, organizations must adopt non-traditional quality engineering (QE) practices.
Here are the five quality principles for a successful cloud migration and adoption:
When organizations plan to migrate their existing applications to the cloud, they face multiple challenges during the cloud integration phase. Most of these barriers are related to access, performance and security. Moreover, these challenges are further intensified in hybrid cloud infrastructure, where application is partially hosted on the cloud and partially on on-premises data center.
Traditional quality assurance methods are not enough to tackle such complexities of the hybrid cloud systems. They tend to slow down the transaction process and inadvertently become a bottleneck. In such situations, an automated parallel testing framework comes to the rescue. These frameworks perform an application benchmark on the existing infra and compare against the migrated environment. The benchmarking is generally not restricted to the functionality, however, it would also cover single user performance, URL validation through crawlers and access validation. With such bespoke test strategies migration, decision-making can be quick and scalable.
Organizations migrate to the cloud or build a cloud-native application with the sole objective to gain agility and improve deployment velocity. Every cloud-based application is run as a code, i.e., automated, and zero manual intervention is required. However, when it comes to cloud assurance, such end-to-end automation is missing, thereby defeating overall cloud’s purpose.
Organizations seeking to take complete advantage of the cloud need to embrace a culture of automate first, automate everything for their cloud assurance process. This contemporary automation approach not only focusses on in-sprint automation, but also tries to automate the entire automation pipeline, from test data to infrastructure to quality gates. Such zero touch automation approaches serve as a potential enabler for fostering cloud adoption effectively.
The technology world has come a long way from monolithic to modular software architecture. Moreover, the advent of microservices and cloud infrastructure has led to even greater modularity in the software. Now, each microservice is capable of being deployed independently in production to achieve time to market advantage.
To take advantage of these capabilities and at the same time not compromise on quality, it is not sufficient to shift-left testing activities. Rather, it has to be shifted further left and extreme shift-left testing has to be adopted.
Enterprises can also achieve extreme shift-left through contract testing in a microservice infrastructure. Consumer-driven contract testing verifies integration between two microservices independently and reduces the feedback time pertaining to integration issues. When your organization starts testing contracts from day one, you reduce the chances of potential service misalignments in your microservice infrastructure.
Another critical capability of Cloud infrastructure and cloud native architecture is the resilience. Cloud services are inherently resilient and are hosted on robust infrastructure; nonetheless, problems occur. To achieve a good resilient application, your business can simultaneously focus on infrastructure availability/site reliability and also application resilience.
Different processes such as SLOs (Service Level Objectives), SLIs (Service Level Indicators) and SLAs (Service Level Agreements) facilitate organizations in ensuring the resilience of the infrastructure. Along with these processes to monitor the infra, enterprises have to deploy chaos engineering techniques. In chaos engineering, testing is based on the concept of Testing in Production (TiP). Here organizations use testing methods like monkey testing to check the resilience of individual components of the cloud-native applications while in production.
With horizontal scaling of infrastructure, cloud provides the ability to dial workloads up and down on-demand. However, auto-scalability also runs the risk of taking up more capacity than needed, thereby stretching the budget over a period. So, to avoid such a budget increase, your business needs to adopt governance and testing of infra code.
Both container monitoring and Iac testing are integral to the Quality Engineering frameworks that enable your business to fine-tune the usage of resources and deliver the best possible performance without putting extra load on your testing budget.
With cloud-based infrastructure and cloud native architecture becoming the face of new Digital development initiatives, it has become imperative for organizations to adopt a modern Quality Engineering strategy to embrace cloud technology with confidence and to reap the maximum benefit out of this massive opportunity.
