SOGETI UK BLOG

Hands up if you’ve ever experienced deployment issues where the root cause turned out to be environmental? Solution delivery requires a process for getting from a development environment to a production environment, usually with multiple other environments along the way. Organisations want this process to be as seamless and automatic as possible. They put in place what they consider to be a robust configuration and change management process; but they still experience issues post deployment to any new environment, usually down to known and unknown differences between environments.

This was challenging enough when limited to physical environments, but then along came the Cloud.

Applications started to move towards a cloud model as they became more pervasively available through the web, required more data processing, and spanned the boundaries of multiple devices. Cloud computing services allowed an enterprise to expand its infrastructure, add capacity on demand, or outsource the whole infrastructure. This resulted in greater flexibility, a wider choice of computing resources and often significant cost savings. The bottom line for IT directors is still the need to manage their internal computing environments, whilst learning how to secure, manage and monitor the growing range of external resources residing in the cloud.

Organisations are looking to continuously deliver at faster rates than ever, and modern IT architectures (and trends), like hybrid cloud, as well as containers, micro services and Interoperability Testing, are making IT environments increasingly more complex. In turn, this combination is overwhelming the ability of IT operations to successfully deliver support to the business.

Hybrid cloud deployments are currently fairly low, but aspirations are high. Technology analyst Gartner predicts that nearly half of large enterprises will be likely to have hybrid cloud deployments by the end of 2017.

A hybrid cloud brings together the best of a public cloud provider (such as Amazon Web Services, Google Cloud, or Microsoft Azure) with a private cloud platform, designed for use by a single organisation. It incorporates, not just bridges between, public and private clouds; enabling businesses and their IT organisations unprecedented flexibility. The public cloud aspect provides access to a wide array of low criticality applications and services, with private clouds offering reliable performance and security for critical business applications. Hybrid clouds also increase business agility; the flexibility to use a variety of services, the scalability to keep pace with business volume, the efficiency to keep costs to a minimum, and, of course, the ability to protect data and other technology assets.

Of course, hybrid clouds bring new challenges; the functionality that makes them so attractive also renders them difficult to administer and a number of concerns emerge. Incident response becomes a great deal more complex due to lack of visibility into the cloud, plus greater complexity in the application layer, interdependence between heterogeneous environments, and limited configuration standardisation.

As enterprises prepare to entrust more and more of their IT infrastructures to hybrid clouds, IT staff must see into these clouds, understand the dynamics of their resources and workflows, and manage them as they do traditional data centre environments. Resources tend to be pooled, shared, and dynamically allocated and moved in virtualized cloud environments, but devices require elastic infrastructures as they appear, expand, contract, and vanish according to user demands. Their myriad configurations continually change.

Emerging IT operations analytics solutions can help, especially with the emergence of DevOps. One of the key challenges is the integration between different platforms, which can be addressed by monitoring and analysing configuration as systems transition to cloud entities, enabling application and data portability. Using innovative analytics and an integrated approach to performance, capacity, and configuration management, IT operations analytics solutions provide the intelligence and visibility needed to proactively ensure service levels, operational efficiency, and continuous compliance in dynamic hybrid cloud environments. By extending analysis into the hybrid cloud, these analytics solutions enable intelligent automation, proactive management and comprehensive visibility, delivering the deepest insight into the performance, availability, and security of business systems. This is regardless of where the systems reside. This streamlines hybrid cloud adoption, and in the process, accelerates the transition to the hybrid cloud by providing visibility into legacy environments and validating applications transitioning to new environments.

Our Solution

Sogeti has recently launched OneShare, a rich cloud platform and toolset that allows organisations to manage and monitor application development environments, test environments and infrastructure resources in a systematic way. OneShare delivers a flexible and continuous platform and toolset on top of Microsoft Azure, giving users the ability to load, use, manage and monitor their environments. Users have the ability with OneShare to copy and deploy test infrastructures or move applications between development and test environments in one click of a button.

OneShare offers tangible benefits and value in addition to enabling and enhancing cloud transformation. The platform’s capabilities include:

–          A self-service, one-stop shop solution, including an environment, tools and services for testers that also leverage Sogeti’s best in class TMap® testing methodology. This combination of resources aligned with OneShare generates lower testing costs and offers a move to a Pay-Per-Use model, improving the efficiency and availability of test environments.

–          A dashboard with comprehensive analytics, showing usage uptime/downtime/efficiency etc.

–          A fully functional Microsoft Azure public cloud combined with team integration activities and management of Software deployment in Cloud environments with desired state configuration capabilities.

–          Continuous integration including versioning software deployment in a Cloud environment using configuration database templates and desired state configuration.

For more information visit www.uk.sogeti.com/oneshare

AUTHOR:
Michael Lagdon is a Managing Consultant at Sogeti UK.

Posted in: Azure, Business Intelligence, Cloud, Developers, DevOps, Infrastructure, Microsoft      
Comments: 0
Tags: , , , , , , , , , , ,

 

Testing is an essential, but time and resource consuming, activity in the software development process. Generating a short, but effective, test suite typically requires a lot of effort allied to expert knowledge. In a model-based process, among other subtasks, test construction and test execution can be partially automated. Model-based testing is defined as follows in the ISTQB Glossary (v2.4. July 2014):

Testing based on a model of the component or system under test, e.g. reliability growth models, usage models such as operational profiles or behavioural models such as decision table or state transition diagram.

So, model-based testing is based on creating test cases derived from a behavioural model of the test object – the (test) model. This model describes the expected behaviour of the test object. These test cases are then, where possible, automatically generated from the test object. The challenge with this approach lies creating a formal behaviour model in which the operation of (part of) the application is represented.

Functional requirements, for instance derived from use cases, can serve as a starting point for the creation of the model. The model used for developing the application or a separate test model can be used. A test modeller creates a test by hand and may utilise a tool that will create test cases that can read this model. A lot of tools use an UML (Unified Modelling Language) model; the tools can also improve the process of designing the model.

The basic idea is that from a formal or semi-formal model, complete test cases (input and expected output pairs) can be generated.

There is extensive research in this field, and the technology has now matured sufficiently enough that there are a number of commercial tools and industrial applications available to assist with developing tests. Details of some of the available open source tools can be found here.

Benefits and Advantages of Model-Based Testing

Model-based testing has several advantages when compared to conventional software test production:

  • – Test cost reduction – Perhaps one of the most important reasons for using model-based testing is that its improved efficiency and cost savings improve the quality of the software, while also reducing overall effort. Defects are also detected earlier in the testing life cycle.
  • – Easy to achieve better test coverage – The use of model-based testing allows engineers to achieve better test coverage, analysis and planning. Based on well-defined models, the system requirement test coverage can be easily measured while a tool is provided to support scenario analysis and prioritisation.
  • – Good documentation – Model-based testing requires the production of detailed documents which can be used as a training tool for new testers in a team.
  • – Reusability of assets – This is another advantage in model-based testing because the model-based test assets can be reused and reproduced easily in regression testing. Whenever software changes are introduced, the model(s) can be easily modified to accommodate these changes.
  • – Better understanding – Creating models increases overall understanding of the system.  Inaccuracies, omissions, inconsistencies or ambiguity in the specifications and requirement documentation may cause problems or additional costs during testing.  The creation of a model by testers serves to highlight such issues earlier in the test process and to detect bugs at an early stage in the development process.

Issues with Model-Based Software Testing

However, there are some issues relating to model-based software testing:

  • – Model quality and standardisation – In order for model-based testing to achieve its full potential, care needs to be taken when developing the models. Test engineers need to have domain experience in order to effectively create appropriate models.
  • – Choosing the right model – There are situations that fit one model better than another and care is required when selecting which model to use. In particular, some models require considerable effort to develop depending upon the level of detail required and the complexity of the domain.
  • – Model complexity – In large projects, trying to model an entire system using finite state machines becomes unfeasible, given the inherent complexity of the problem at hand. State-explosion refers to the huge number of states that will be generated when trying to model a real system at a fairly detailed level.
  • – Automated mechanisms that evaluate test results (called oracles) are crucial to model-based testing. Without them a major value of model-based testing, automation, is almost voided. But on the automation front, the possibilities offered by model-based testing techniques do not offer a solution to the oracle problem. In fact, automation reportedly makes the oracle problem even more difficult.
  • – Model-based testing demands a high level of skills from the test engineers. They not only need to have domain-specific knowledge, but they should also be familiar with the theory behind the models and need experience and / or training in the use of the various automated tools available. Furthermore, quality modelling and the analysis of products depend on engineers’ good understanding of products and having the experience to write the model and choose the test selection criteria.
  • – Model-based testing cannot be used to test all of the quality attributes required for a complete test suite – MBT covers only functionality and some aspects of suitability.  Other techniques will be required to adequately cover other aspects of the test project

Conclusion

Model-based testing is certainly worth consideration for small to medium sized projects, especially where repetition of testing is a considerable factor (e.g. regression testing).

Sogeti includes MBT in its testing solutions

Sogeti provides clients with high quality, cost effective testing solutions, using MBT, automation and other methods.

At the end of 2012, we launched PointZERO – a framework that delivers parallel step-by-step improvement based on an array of measures, methods and tools, leading to business solutions that are fit for purpose and right the first time.

In 2014, we launched the market-leading Sogeti Studio, which provides our clients with an on demand service that can enable them to create websites, and mobile applications, and to test those across a wide range of regularly refreshed browsers, devices and application configurations. Within the Studio we also carry out a number of tool evaluations and our consultants are skilled in a range of testing methods.

Sogeti continue to make significant investment to further develop our reputation as a global testing services thought leader, and we are currently developing model-based testing capability to extend our service offerings.

AUTHOR:
Michael Lagdon is a Managing Consultant at Sogeti UK.

Posted in: Automation Testing, Behaviour Driven Development, functional testing, Sogeti Studio, Transitioning      
Comments: 0
Tags: , , , , , , , , ,

 

What is Omni-Channel?

Omni-channel retailing is an evolution of multi-channel retailing, but concentrated more on providing a seamless consumer experience across all available shopping channels, i.e. mobile internet devices, computers, brick-and-mortar, television, radio, direct mail, catalogue etc. Customers now expect this type of experience and have to meet these demands by deploying specialised supply chain strategy software, updating their testing strategy, and tracking customers across all channels.

The Evolution of Omni-Channel

Way back in time (or so it feels), when companies created their first websites, they created their first digital relationships with their customers. Businesses have a voracious appetite for establishing a market presence that was no longer constrained by bricks and mortar and limited opening hours.

Just a few years later Yahoo and Google enabled a second digital layer – Search – and a multi-billion dollar search industry was born, and companies realized they needed their websites to be ‘found’.

Around 2007, ‘chat rooms’ evolved into social networks, quickly becoming a preferred way for consumers to communicate and discover new products and services – whether reviews were good or bad. There was a social network explosion that brought with it a host of new advertising, commerce and service options.

At the same time, mobile began to pick up steam and so the greatest new commerce channel since shopping centres was born. Combined with social media, mobile presented an unprecedented opportunity to provide the consumer, whenever and wherever they were, with relevant and helpful content. Fast forward a few years and consumers have quickly come to expect a 24/7 buying and service experience.

The Challenges

Many retailers had spent their entire lives thinking about how to build an engaging experience in one channel, usually a store. Now, with web and mobile almost a commodity, retailers have to understand how to connect with their customers, the way those customers want to connect.  Increasingly complex layers of digital connection between companies and their customers are being created. Understanding and mastering these layers, and integrating traditional advertising through a uniform and consistent communication strategy represents new challenges for marketing and retailing. Yet, now, every major retailer needs an omni-channel marketing strategy to survive. Those retailers that keep pace with the latest mobile technologies, and evolve their marketing strategies to embrace them soonest, will be the only ones to maintain and grow their market share.

In order to achieve success in omni-channel, retailers and marketers must look through the eyes of the consumer, optimising their experience across all the channels so that it is seamless, integrated and consistent. Omni-channel anticipates that customers may start in one channel and move to another as they progress to a conclusion i.e. sale. For example, they may see an advert on television, go online to research products, use their tablet to start purchase or add to basket, then use a smart phone to complete the purchase.

Standing out from the crowd in this increasingly complex and cluttered world, across all of these channels is not easy. If the customer experience in each channel is not uniquely helpful, they will become annoyed by repetitive ubiquity. There needs to be a different yet consistent brand approach for each channel.

In addition, marketing is undergoing rapid and major changes. It is shifting away from mass ‘push’-based marketing towards more personalised communication with consumers, through the many channels and on the many devices they use.

Consumers leave a data trail on every level. The companies that can best mine this stream of information will gain a powerful competitive advantage. Analytics is the new key to the kingdom and for many retailers, good data analysis may be the only competitive advantage in a world of instant price comparisons, multiple review sources, and ‘buy it now’ buttons. This data can be used to tailor the consumer experience across all channels. This will drive increased customer loyalty, and with that comes increased sales!

As if developing effective omni-channel marketing solutions wasn’t tough enough, keeping pace with the underlying technologies increases the complexity twofold. Companies need their omni-channel marketing solutions to provide a high quality experience across channels, which means testing across a large number of devices, operating systems etc. In addition, the new technology must integrate fully with their legacy and back office systems.

For marketers and retailers, they not only need to test email subject lines, social channels, content, landing pages etc. Testing the customer experience and technology aspects before going to market requires an ever-evolving set of technical testing skills and resources, and few companies can justify the investment required to provide for themselves in house.

How Sogeti Can Help

Sogeti is perfectly placed to help companies deliver omni-channel marketing with a fully integrated testing solution.

Not only can we provide a core front-end testing capability for Mobile Functional Testing, Mobile Usability Testing, Mobile Performance Testing, Mobile Security Testing and Web Accessibility Testing, we can support end-to-end omni-channel marketing scenarios with user experience research, plus mobile payments using the latest NFC (Near Field Communication) and HCE (Host Card Emulation) technology.

Sogeti Studio – our UK based web and mobile testing lab provides services on demand, and gives you access to all of the the devices and resources you need to test thoroughly, without significant investment. Out of the Studio we also offer Content Management System (CMS) testing, tool evaluations and more. Find details and case studies here.

Sogeti can also support mobile strategy, development and portfolio management, as well as all of your Big Data and analytics and Smart Commerce needs. Mobile details here. Big Data and Analytics here. Smart Commerce here.

To find out more, please email us: enquiries.uk@sogeti.com, or call us today: +44 (0) 20 7014 8900

Follow Sogeti at:

facebook.com/SogetiUK   
twitter.com/uk_sogeti

AUTHOR:
Michael Lagdon is a Managing Consultant at Sogeti UK.

Posted in: Business Intelligence, communication, Digital, Digital strategy, e-Commerce, Marketing, mobile applications, mobile testing, Mobility, Omnichannel, Rapid Application Development, REWARD, Security, Social media, Social media analytics, Software Development, Software testing, Sogeti Studio, User Experience      
Comments: 0
Tags: , , , , , , , , , , , , , , , , , , , , , , , ,