Published By: Dell EMC
Published Date: Nov 04, 2016
With the 'EMC Mission Control' center in Portsmouth, UK and a second at the America’s Cup venue in Bermuda, plus a mobile center travelling worldwide to the preliminary events, Land Rover BAR will have all its data continuously replicated. The team in Portsmouth can analyze race and testing data immediately, as well as identify and make improvements right up to and through the finals in June 2017. This allows the design team and the crew to adapt much faster. With the introduction of the VCE VxRail Appliance powered by Intel® Xeon® processors, Land Rover BAR will be able to flexibly and rapidly scale, irrespective of location, ensuring a seamless experience for the team. To learn more about the impact of the Dell EMC VCE VxRail Appliance, read this brief infographic.
As the application economy drives companies to roll out applications more quickly, companies are seeing testing in a new light. Once considered a speed bump on the DevOps fast track, new tools and testing methodologies are emerging to bring testing up to speed.
In this ebook, we’ll explore some of the challenges on the road to continuous testing, along with new approaches that will help you adopt next-gen testing practices that offer the ability to test early, often and automatically.
Continuous testing is the practice of testing across every activity in the SDLC to uncover and fix unexpected behaviors as soon as they are injected. Continuous testing is the embedding of testing as a fundamental and ongoing aspect of every activity through the application lifecycle, from requirements through production, to ensure the business value is being achieved as expected.
As the pace of business continues to quicken, companies are starting to recognize that to stay competitive the process of developing and releasing software needs to change. Release cadence has greatly accelerated. There is no occasion anymore for a six- to 18-month find-and-fix turnaround in which the customer will find the delay acceptable. Things need to move faster, and they need to be ready and perfect faster.
Download this whitepaper to find out how CA Technologies can help with your Continuous Testing.
Business applications have become the battleground for customer loyalty. To compete, IT organizations are under pressure to deliver applications faster and with higher quality. Continuous Delivery (CD) of code offers a solution. CD may be paired with DevOps, Agile and other methodologies. However, QA and testing can be an obstacle to CD’s rapid development and deployment of high quality code. Testers and developers must engage in Continuous Testing, continuously testing software for performance, quality and user experience as it’s being developed.
Continuous Testing is not a push button process, though. It requires a comprehensive approach. This paper outlines the common challenges to Continuous Testing and highlights results from real users who have used technology to get to succeed with the Continuous Testing process.
With the application economy in full swing, more organizations are turning to Continuous Testing and DevOps development practices in order to quickly roll out applications that reflect the ever-changing needs of tech-savvy, experience-driven consumers.
Rigorous data they need, in the right formats. This forces teams to postpone their testing until the next sprint. As a result, organizations like yours are increasingly looking for ways to overcome the challenges of poor quality data and slow, manual data provisioning. They are also concerned about compliance and data privacy when using sensitive information for testing. CA Test Data Manager can help you mitigate all these concerns, so you’re positioned to achieve real cost savings.
To compete successfully in today’s economy, companies from all industries require the ability to deliver software faster, with higher quality, and reduced risk and costs. This is only possible with a modern software factory that can deliver quality software continuously. Yet for most enterprises, testing has not kept pace with modern development methodologies. A new approach to software testing is required: Continuous Testing.
In the first session in a series, join product management leadership to gain in-depth insights on how by shifting testing left, and automating all aspects of test case generation and execution, continuous testing, it enables you to deliver quality software faster than ever.
Recorded Feb 5 2018 49 mins
Steve Feloney, VP Product Management CA Technologies
If you’re relying on manual processes for testing applications, artificial and automated intelligence (AI) and machine learning (ML) can help you build more efficient continuous frameworks for quality delivery.
In this on-demand webinar, “Continuous Intelligent Testing: Applying AI and ML to Your Testing Practices,” you’ll learn how to:
Use AI and ML as the new, necessary approach for testing intelligent applications.
Strategically apply AI and ML to your testing practices.
Identify the tangible benefits of continuous intelligent testing.
Reduce risk while driving test efficiency and improvement.
This webinar offers practical steps to applying AI and ML to your app testing.
The speaker, Jeff Scheaffer, is senior vice president and general manager of the Continuous Delivery Business Unit at CA Technologies. His specialties include DevOps, Mobility, Software as a Service (SaaS) and Continuous Delivery (CDCI).
Companies struggle to find the right test data when testing applications which leads to bottlenecks, defects and constant delays. There is a better way and we want to show you how:
Join us for this webcast to learn:
- How Test Data Manager finds, builds, protects and delivers test data fast!
- How to get your testing teams moving towards self sufficiency with test data
Get your questions answered. Come away happy!
Recorded Aug 20 2018 60 mins
Prashant Pandey, CA Technologies
Published By: Dynatrace
Published Date: May 20, 2016
The Art of DevOps: Embark on a mission to continuously deliver assets to the operational battlegrounds safely, securely, and quickly.
This eBook gives you, a veteran of application development wars, recommendations that will put you at strategic advantage to win today's war:
- Supplement manual tests with automated testing
- Add advanced performance monitoring technology to your arsenal to prevent problems from infiltrating your code after check-in
- Leverage best-in-class communications and advanced performance monitoring to quickly identify and prevent casualties resulting from poor performance
Pour dynamiser le marché ou rester compétitives, les entreprises doivent livrer leurs produits logiciels plus rapidement que jamais. Les méthodes traditionnelles d’assurance qualité ne sont cependant pas en mesure de supporter cette cadence soutenue. Bien qu’ils aient aidé les organisations à améliorer la qualité du code, les mécanismes d’intégration continue ne prennent pas en charge les tests de bout en bout à l’échelle du cycle de vie du code.
Dans les organisations agiles d’aujourd’hui, les équipes de production se trouvent face à un défi de taille : déployer en production les nouvelles versions immédiatement après les phases de développement et de test. Pour assurer la réussite d’un tel déploiement, il est nécessaire de mettre en œuvre un processus automatique et transparent. ce processus, nous l’avons baptisé Zero Touch Deployment™.
cet article examine deux approches du Zero Touch Deployment : une solution basée sur les scripts et une plate-forme d’automatisation de la mise en production. Il indique comment chacune de ces approches peut résoudre les principaux défis technologiques et organisationnels face auxquels se trouvent les organisations agiles lorsqu’elles décident d’implémenter un système de déploiement automatique.
cet article commence par retracer le contexte commercial et technologique qui pousse les organisations agiles à se tourner vers des solutions d’automatisation du déploiement.
Pour pouvoir réellement mettre en œuvre une approche de livraison continue, les organisations doivent entièrement repenser la façon de mener leur processus d’assurance qualité (QA). Cela passe notamment par redéfinir le rôle que les professionnels d’assurance qualité jouent au sein de l’organisation, automatiser le plus possible à chaque niveau et revoir entièrement les structures de test, pour prendre en charge des versions logicielles plus légères et plus rapides.
Faites passer rapidement vos idées du stade de la conception au stade du développement, sans sacrifier la qualité, grâce à un écosystème de livraison continue de bout en bout capable de mettre en œuvre des tests rigoureux selon la fonctionnalité utilisateur souhaitée.
Dans une série d’articles, Paul Gerrard, consultant et spécialiste des tests, aborde diverses questions sur ces derniers. Les modèles de test sont essentiels pour les tests et, dans cet article, Paul Gerrard évoque l’art de créer et d’utiliser ces modèles. Si les testeurs interviennent de plus en plus tôt, de pair avec les développeurs ou du moins plus étroitement, les testeurs (et les développeurs) doivent être capables de créer des modèles, de savoir comment les articuler et les partager, ainsi que d’encourager une meilleure collaboration.
Générez des données virtuelles riches qui couvrent tous les scénarios possibles et fournissent un accès illimité aux environnements nécessaires pour livrer des applications testées avec soin, dans les délais et le budget impartis. Modélisez les données des systèmes réels complexes et appliquez des algorithmes d’apprentissage automatisé de règles pour éliminer la dette technique et permettre une compréhension approfondie des applications composites. Mettez en outre à la disposition des équipes distribuées des données virtuelles à la demande et évitez les goulots d’étranglement au niveau des tests.
If you’re managing an IT team, you may be turning to DevOps as the path to faster delivery of software.
DevOps can help your team become more efficient — and your organization more competitive — but you’ll need to be able to communicate to your team why things are changing, and how their usual working practices are likely to alter.
Download this guide to explore:
• How to align DevOps with your organization’s goals.
• What change might look like — for operations, development and the organization at large.
• Why security is a great icebreaker.
• The importance of focusing on the team over individual DevOps specialists.
• How to embrace agile ways of working, along with infrastructure as code, code review, continuous integration and unit testing.
Over the last several years CA Technologies has acquired a number of companies and their respective products, to augment its continuous delivery suite and, especially, its DevTest portfolio. In particular, it has recently acquired Grid-Tools and Rally Software. Bloor Research has been asked to explore how Grid Tools’ products – now known as CA Test Data Manager (formerly Datamaker and CA Datafinder) and CA Agile Requirements Designer (formerly Agile Designer) expand and augment the capabilities provided by CA Service Virtualization (previously iTKO’s LISA) and CA Agile Central (formerly Rally), making the whole greater than the sum of the parts.
CA’s portfolio is designed to drive efficiency from planning through production. A core component of our continuous delivery portfolio is CA Release Automation, a market-leading application release automation solution that delivers full application deployment automation and release coordination across stages, environments and teams. The solution’s analytic capabilities enable DevOps teams to plan, manage, analyze and optimize the continuous delivery pipeline from a single control point. In addition, the portfolio includes CA Agile Central, CA Agile Requirements Designer, CA Service Virtualization and CA Test Data Manager. We continue to invest in and enhance the portfolio, most recently via the acquisition of BlazeMeter, an innovative, SaaS-based performance and load-testing solution.
Software delivery processes and systems, and the people involved with them, are under increasing pressure. Sometimes it’s digital transformation, other times it’s simply the challenge of keeping up with the demands created by ever more dynamic markets and an escalating pace of change. None of this is news, but is does provide an important backdrop to the discussion of how software delivery needs to evolve, especially given that traditional methods and approaches were never designed to deal with the fastmoving and unpredictable environment you are probably working in today.
One way to shift testing practices earlier in your software lifecycle is by using multi-layered visual models to specify requirements in a way where all ambiguity is inherently removed. With unambiguous and complete requirements, developers introduce less defects into their code and manual test cases, automated test scripts and required test data can be automatically generated based on the requirement, without manual intervention.
Take an idea from design to deployment at pace— without compromising quality—using an end-to-end, continuous delivery ecosystem that’s capable of driving rigorous testing from the desired user functionality.
Ubiquitous connectivity and mobile devices have changed everything, opening up markets to millions of new consumers across the globe. Within the past few years, nimble upstarts have created mobile apps that have converted banking customers, cab riders and hotel guests at unprecedented rates. Large, established brands are scrambling to transform their businesses in order to maintain market share. To compete in this application economy, you must adapt or be left behind.
In a series of articles Paul Gerrard, a testing guru and consultant, discusses a range of testing topics. Test models are fundamental to testing and, in this article, Paul talks about the art of creating and using models. If testers are “shifting left,” pairing with developers or at least working more closely with developers, testers (and developers) need to be able to create models, learn how to articulate and share them, and support better collaboration.
Generate rich virtual data that covers the full range of possible scenarios and provide the unconstrained access to environments needed to deliver rigorously tested applications on time and within budget. Model complex live system data and apply automated rule-learning algorithms to pay off technical debt and uncover in depth understanding of composite applications, while exposing virtual data to distributed teams on demand and avoiding testing bottlenecks.