When it comes to computer services, cloud computing is the distribution of on-demand computing resources — from apps to storage and processing power — that are often delivered through the internet and on a pay-per-use basis.
Companies may rent access to everything from apps to storage from a cloud service provider rather than investing in their computer equipment or data centers. As a result, cloud services are becoming more popular. Using cloud computing services allows businesses to forego the high upfront costs and complexity of building and maintaining their own IT infrastructure and instead pay only for the resources used when they are needed. As a result, cloud computing service providers may realize considerable cost savings by providing the same services to many consumers, increasing their profitability.
A wide variety of alternatives are now available via cloud computing services, ranging from the fundamentals of storage, networking, and processing power to more advanced applications such as natural language processing and artificial intelligence, in addition to typical office applications. Now, almost any service that does not need you to be physically present in front of the computer gear you are using may be supplied over the cloud.
Cloud computing is the foundation for a plethora of services. The cloud encompasses everything from consumer services such as Gmail and the cloud backup of images on your smartphone to commercial services that enable giant corporations to store all of their data and operate their apps in the cloud. For example, NetFlix depends on cloud computing services to manage its video streaming service and its other business processes, as do many other organizations, like Google, Amazon, and Microsoft.
When it comes to many applications, cloud sharing computing is becoming the de-facto standard: software providers are increasingly selling their apps as services through the internet rather than as separate products as they attempt to transition to a subscription-based business model. However, there is a possible drawback to cloud computing, which is that it might result in increased expenses and risks for businesses that use cloud computing services.
The location of the service and many other variables such as the hardware or operating system on which it is running are essentially irrelevant to the user, which is a crucial idea in cloud computing. The cloud metaphor was derived from ancient telecommunications network designs. For example, the public telephone network (and subsequently the internet) was sometimes portrayed as a cloud to signify that the network itself didn’t seem necessary — it was merely a smattering of information. But, of course, this is an oversimplification; for many consumers, the location of their services and data remains a critical concern.
Even while cloud computing has been present since the early 2000s, the notion of computing-as-a-service has been there for much longer — as far back as the 1960s, when computer bureaus would enable firms to rent time on a mainframe rather than having to own a mainframe of their own. These ‘time-sharing’ services were mainly supplanted by the introduction of the personal computer, which made owning a computer much cheaper. In turn, the development of corporate data centers allowed businesses to store massive quantities of information.
However, the notion of renting access to computing power has resurrected time and time again, most notably in the late 1990s and early 2000s with the rise of application service providers, utility computing, and grid computing. This was followed by the rise of cloud computing, which gained significant traction with the introduction of software as a service and the establishment of hyper-scale cloud computing providers such as Amazon Web Services.
According to statistics from IDC, the cost of constructing the infrastructure necessary to enable cloud computing currently accounts for more than a third of all IT investment globally. As computer workloads migrate to the cloud, expenditure on conventional in-house IT continues to decline as more and more workloads are moved to public cloud services supplied by vendors or private clouds established by organizations themselves. According to 451 Research, approximately one-third of enterprise IT spending will be spent on hosting and cloud services this year, “indicating a growing reliance on external sources of infrastructure, application, management, and security services.” 451 Research also predicts that approximately one-third of enterprise IT spending will be spent on cloud services this year. In addition, according to Gartner, by 2021, half of all global organizations utilizing the cloud will have made the switch to a fully managed cloud environment.
The research firm Gartner predicts that worldwide expenditure on cloud services will reach $260 billion this year, increasing from $219.6 billion in 2012. The company’s revenue is also growing quicker than experts anticipated. However, the exact proportion of demand coming from organizations that genuinely want to go to the cloud vs. the balance produced by suppliers who now exclusively provide cloud-based versions of their products is not known (often because they are keen to move away from selling one-off licenses to selling potentially more lucrative and predictable cloud subscriptions).
While much of the testing has been focused on “cloud-based” or “cloud-enabled” application testing, it is becoming necessary for the Quality engineering community to understand and identify the testing needs for “cloud native” apps, which are becoming more popular. Designing, architecting, and building distributed software applications in such a way that they can take full advantage of the underlying PaaS (Platform-as-a-Service) and IaaS (Infrastructure-as-a-Service) service models offered by cloud service providers are referred to as creating Cloud-Native applications (CNA). These applications are developed as a collection of discrete Microservices most of the time. (See public domain definition for more information.)
As a result, we must reframe our approach to testing for “Cloud Native” applications. The following are some of the most important considerations to bear in mind while developing a plan for such testing. Unit, integration, and end-to-end testing should be performed using a microservices testing strategy. Given the possibility of a high number of tests due to many combinations and permutations, optimize the number of tests by using a risk-based approach to testing. The essential thing to have is the correct strategy and insights about the readiness of services to minimize waste due to lack of preparedness or flakiness in testing due to lack of availability.
As a conventional strategy in Microservices testing, automation of such contract tests in conjunction with an integration pipeline will allow the discovery of faults in the earliest stages. Non-functional testing, in particular, Failure mode and effect testing (also known as chaos engineering) The need to guarantee that software fulfills non-functional needs such as scalability, adaptability, and resilience is just as critical as ensuring that the product meets its business requirements. Compared to old-fashioned monolithic apps, identifying probable failure modes in a microservices architecture is more difficult due to the very nature of the design. Chaos engineering is beneficial because it injects modestly planned failures into a system, allowing for their detection and analysis and the implementation of remedial steps. It is vital to remember that this should not always be done in a staging environment but rather in a live environment where you might run the danger of intentionally crashing the server. If the system is designed correctly, another server will take over. However, it is critical to comprehend the entire ramifications and to develop your test method properly in this case.
The monitoring logs and metrics analysis may provide information on the status, behavior, and interaction between the services in a production environment. In addition, these may provide valuable insights for evaluating and debugging any difficulties as fast as possible. A well-balanced mix of observability and monitoring tools will benefit both parties. Aspects of testing that are version controlled. Given that we are dealing with technologies such as Kubernetes, which can dynamically update the versions of containers, we must address the problems associated with rollbacks. If you are testing a multi-version scenario, you must maintain track of the changes from one version to another.
Because there are so many underlying components in cloud-native app development, it is more difficult and vital to take a whole new approach to security. Everything is a code, and scanning through code, configuration, and integrations are all critical components of the plan, and they are all significant aspects of the strategy. The increasing need for Infrastructure as Code and the difficulties in scanning the same and building connections between code, infrastructure, and settings are all factors to consider.
It is essential to recognize that even though we may prepare for rigorous functional and non-functional testing to increase the quality of cloud-native apps, end-users may still have problems. Therefore, our plan should allow us to decrease the likelihood of failures, and in the case of a loss, it should enable us to promptly analyze and repair the problems, therefore avoiding them in future releases.
My name is Mukesh Jakhar and I am a Web Application Developer and Software Developer, currently living in Jaipur, India. I have a Master of Computer Application in Computer Science from JNU Jaipur University. I loves to write on technology and programming topics. Apart from this, I love to travel and enjoy the beauty of nature.