Welcome!

Machine Learning Authors: Pat Romanski, Yeshim Deniz, Liz McMillan, Elizabeth White, Zakia Bouachraoui

Related Topics: Containers Expo Blog, @CloudExpo, SDN Journal

Containers Expo Blog: Article

API Virtualization: A Strategy for Uniting Teams | @CloudExpo #API #Cloud #Virtualization

API virtualization is increasingly becoming another avenue that allows software development teams to collaborate more

API Virtualization: A Strategy for Uniting Teams
By Harsh Upreti

Recently an analysis was completed by SmartBear to gauge the sense of what software professionals believe is the core value provided by API virtualization. It was concluded that software professionals, including developers, testers, managers and architects believe that the biggest benefit of virtualization is that it brings teams together by allowing them to collaborate. In total, 18% more respondents indicated that virtualization has more value in uniting teams than it has in adding speed to delivery or reducing costs.

Background
We ran our test via email to a broad sample of our customer base - about 36,000 email addresses in total. This involved randomly sending one of three different subject lines to each address. The topics of these subject lines positioned API virtualization as a strategy for doing one of the following:

  1. Uniting dev and test teams
  2. Delivering APIs faster
  3. Reducing delivery costs

We measured the interest of the email recipients by tracking which people opened these emails. From there, we dug into the results by job role and job title - bringing us to the conclusions below.

What team members think about virtualization
API virtualization is increasingly becoming another avenue that allows software development teams to collaborate more.

The results were enlightening. We found that the majority of the respondents engaged more with content around uniting teams rather than reducing costs or saving time. 81% of the developers indicated that they find virtualization valuable in uniting teams. Only 15% thought that virtualization helps in delivering APIs faster.

Dev Scrn

Results from our base of managers and senior managers was a bit different, many of these managers are senior executives. Many managers indicate that costs and speed are important, 20% and 35% respectively, but interestingly the majority (i.e. 45%) still indicate that virtualization provides excellent value in uniting teams.

SeniorManScrn

We also sent this study to Software Architects, architects almost unanimously thought that uniting teams was the best value virtualization could offer, 81% engaged more with the content that indicated virtualization unites teams, the remaining 18% indicated making API delivery faster was a good value that can be derived from virtualization.

SofrArcScrn

API Virtualization and software delivery
The results of these tests strongly suggest that, in software delivery, there is an increasing pressure on teams to work in close collaboration. Developers, testers and managers are not just concerned about time and money but also in the way their teams work closely and cooperate.

Service virtualization enables team members to share their work with one another. This is what that process might look like:

  1. A developer creates a set of API calls that mimics the actual APIs that are still under development.
  2. A tester can now test off of the virtual API.
  3. Now, the developer and tester can code and test in parallel. Virtualization also enables sharing of services across geographies.

For example: A subject matter expert in OFX (a protocol used in financial APIs), who is located on Wall Street, can ideate, and quickly prototype a virtual service and share it with a development team in India through service virtualization over internet. Proprietary, sandboxed and firewalled environments now can be made accessible across the world with just a few clicks.

API Virtualization and costs
Besides tying teams together, virtualization makes it easy to work with services which are not under your control. Services and APIs that cost money to access can be replaced with virtual services. Thus for testing and development purposes there is no need to connect to the live service, teams can finish development and testing with just virtual services.

For example: Imagine you are using Google maps API for your software and you need to load test. You can record and virtualize the maps API and replay it for the load testing. Specially in this scenario, you should isolate your software and load test, you should not inadvertently load test the Google maps API. Sophisticated virtualization allows you to create real world scenarios through throttling and limiting the virtualized Google maps API. Thus enabling developers and testers to test against real world situations and error scenarios.

A good virtualization solution should provide capabilities to fully simulate the actual service, and provide hassle free switching between virtual and the actual environment. ServiceV Pro is a virtualization solution from SmartBear that provides all of the above, it also allows you to share your virtual services and control your virtual environment to generate realistic scenarios. The tool is a part of the ReadyAPI suite of applications and allows you to very quick capture and create a virtual service from a single user interface. Teams can get up and running with ServiceV Pro in minutes, create sophisticated virtual services and start coding and testing against them.

More Stories By SmartBear Blog

As the leader in software quality tools for the connected world, SmartBear supports more than two million software professionals and over 25,000 organizations in 90 countries that use its products to build and deliver the world’s greatest applications. With today’s applications deploying on mobile, Web, desktop, Internet of Things (IoT) or even embedded computing platforms, the connected nature of these applications through public and private APIs presents a unique set of challenges for developers, testers and operations teams. SmartBear's software quality tools assist with code review, functional and load testing, API readiness as well as performance monitoring of these modern applications.

CloudEXPO Stories
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
The deluge of IoT sensor data collected from connected devices and the powerful AI required to make that data actionable are giving rise to a hybrid ecosystem in which cloud, on-prem and edge processes become interweaved. Attendees will learn how emerging composable infrastructure solutions deliver the adaptive architecture needed to manage this new data reality. Machine learning algorithms can better anticipate data storms and automate resources to support surges, including fully scalable GPU-centric compute for the most data-intensive applications. Hyperconverged systems already in place can be revitalized with vendor-agnostic, PCIe-deployed, disaggregated approach to composable, maximizing the value of previous investments.
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed how this same philosophy can be applied to highly scaled applications, and can dramatically increase your resilience to failure.
Machine learning has taken residence at our cities' cores and now we can finally have "smart cities." Cities are a collection of buildings made to provide the structure and safety necessary for people to function, create and survive. Buildings are a pool of ever-changing performance data from large automated systems such as heating and cooling to the people that live and work within them. Through machine learning, buildings can optimize performance, reduce costs, and improve occupant comfort by sharing information within the building and with outside city infrastructure via real time shared cloud capabilities.
As Cybric's Chief Technology Officer, Mike D. Kail is responsible for the strategic vision and technical direction of the platform. Prior to founding Cybric, Mike was Yahoo's CIO and SVP of Infrastructure, where he led the IT and Data Center functions for the company. He has more than 24 years of IT Operations experience with a focus on highly-scalable architectures.