When To Choose Edge Computing?
Edge computing will continue to improve with advanced tech enhancements like 5G connectivity, artificial intelligence (AI), and satellite mesh in the foreseeable future.
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Atmecs-Blog
Why is Graph Technology a Critical Enabler For Future Innovation?
Graph technologies are expected to be extremely promising in the upcoming decade. They are considered one of the significant strides needed for advancement in technology. Different sectors, like health, business, banking, agriculture, logistics, utilities etc., are looking for its applications in their respective fields.
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Investing In Metaverse – Is This For You?
Metaverse – All the technology giants are having exciting conversations about the metaverse.
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Smart Spaces – The Phygital World
A smart space is a physical or virtual environment; it provides an increasingly open, linked, integrated, and cognitive ecosystem where humans and technology-enabled systems interact in a smart area
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Employee Health and Wellbeing at the Workplace
A company’s success is strongly correlated with the contribution of its employees and their wellbeing. It is critical to prioritise employee well-being and establish a positive work culture to achieve and safeguard success.
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Engineering change to accelerate digital transformation
Engineering Change – Accelerating Digital Transformation ATMECS – Content Team Industry 4.0 offers several possibilities to today’s modern society. It promises valuable data, lower waste, and higher visibility into the comprehensive value stream for change leaders. New tools and sources of information are available to make processes efficient and profitable. Research and Markets estimate that the digital transformation market will increase by 23% to $3.3 trillion by 2025 (CAGR). However, implementing a digital transformation needs consensus across all levels. Though change leaders are open to new technology engineering, they may have to face a lot of resistance, albeit justified, along the way. For change leaders, efficiently implementing a digital transformation requires exhibiting value and building harmony throughout the hierarchy. The process from identifying a technological need for solving a business problem to efficient deployment is long. Change leaders convert it into a reality when they state their position effectively. Future Themes for Digital Transformation Based on industry data, Gartner research and our experience enabling deep tech solutions and services for our clients, here are some common themes of the best digital transformations that will shape the future. Process Automation and Virtualization A big part of the workforce, across all industry verticals, is seeing a rise in the use of technology to enable process efficiency and promote automation. With better process automation and virtualization, companies are gearing up for the next wave of transformation in their enterprise. AI-based, self-learning robots using assisted technologies like IoT etc., present development opportunities for humans to communicate better by adding granular information. With enhanced simulations and 4D printing, development processes have sped up while improving safety and operational practices. The proliferation of emerging technologies has helped companies navigate tricky labour-related issues and redefine their work methods. Total Experience – Breaking through silo thinking Understanding the voice of the customer is a critical success factor for any business. However, the role of “customer” has expanded to include every individual a company or a brand interacts with. Total experience refers to a blend of customer experience, employee experience, and user experience to state all possibilities and experiences for both customers and employees. With customers and employees going digital, “listening” to the total experience is the next big thing to enhance and improve the sustainability of transformational initiatives. Data Fabric to Enhance Decision Intelligence Companies notice a rising requirement for deeper insights and analytics through data generated by three sources – people, machines, and organizations. Decision Intelligence and Data Fabric are two significant trends that enhance data use effectiveness while easing human-driven data handling jobs. Data fabric integrates data across platforms and users and develops a central source that allows data accessibility anywhere needed. Decision Intelligence, on the other hand, enhances organizational decision-making by implementing Artificial Intelligence and Data Analytics to develop an intelligent platform that automates and enhances AI-based decision-making. Software 2.0 With improved hardware, businesses require programs using AI structures and automation to unravel better use cases such as machine-supported simulations and autonomous vehicles to do more without needing manual interference. Software 2.0 replaces programmers with neural networks that use ML to develop software and will remain on trend as its popularity is consistently rising. No-code or low-code setups are already seeing citizen developers take on roles that sophisticated developers once held. Modularized, repurpose-able product features’ engineering will enable companies to achieve greater speed to market. Distributed Enterprise Post pandemic, most organizations have adopted a hybrid approach, making them pivot business models to meet consumer and behavioural changes through remote working. Distributed enterprises allow a distant framework to virtualize consumer touchpoints and enhance relevant technologies. A recent Gartner study states that 75% of companies that use distributed enterprises will grow better than their contemporaries by 2023. Verticals Using Cloud-Native Platforms With the rise in digitalization, companies are moving their legacy applications and work to the Cloud through ‘lift and shift’ approaches. However, that approach does not work for all and typically hits roadblocks on scaling or elasticity. Businesses are adopting cloud-native platforms instead to automate their workloads and tasks and concentrate on competitive differentiation. Technology engineering is becoming increasingly important to help companies grow, develop and reshape the world. “Every company is a technology company” – is the new paradigm for business leaders. Often, however, leaders are left wondering about the gap between innovation and adoption. This is where change leadership comes in. Change leaders with a ‘Product/Service Management’ mindset tend to envision a strategic roadmap grounded in customer centricity and undertake implementations with a ‘no-compromise’ process orientation. These change leaders are champions of industry. Here are some considerations when you, as a change leader, want to implement your next large-scale digital transformation project. Change Leader Caveats Getting Buy-In from Key Stakeholders Digital transformations don’t yield sustainable results when businesses are not aligned on processes and outcomes. Indeed, most CIOs acknowledge improper focus, inefficient executive sponsorship, and resistance to change as major hindrances to successful transformation initiatives. Change leaders articulate the vision for digital transformation in a business structure and the glue for success in transformational initiatives. From acknowledging the employee’s efforts to tracking results, they work between business processes and outcomes. A critical responsibility of change leaders is to achieve stakeholder consensus across different levels of the organization. Change leaders must understand every role in the process chain above and below the surface level. Employees will always be anxious about new technologies causing disruption and making existing processes complex. It is the job of a change leader to build trust and awareness, reduce employee workload, gain consensus, enhance efficiency and effectiveness of daily work. They draft the vision for a digital transformation and support throughout the implementation such that it gets more efficient in the long run. Sponsoring Tools and Technologies that Enable Doing More with Less Digital transformations fall short of expectations when done in a piecemeal approach. Improper or ill-timed process modifications exacerbate the problem of data silos and lead to integration issues downstream. To derive best results, change leaders should promote
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Sports’ Tryst With NFTs
Sports’ Tryst With NFTs ATMECS – Content Team The sports industry is growing rapidly. It is not just about competition in physical sport anymore but also in the digital space. The accelerated growth of partnership between sports and digital technologies over the last few years has spawned changes to the market landscape and sports tech ecosystem that were once thought unfathomable. With the proliferation of e-gaming, betting, and the rise of online broadcasting/streaming (OTT), two major trends are currently emerging in the sports industry: Non-Fungible Tokens (NFTs), which according to Gartner Hype Cycle 2021 is at the Peak of Inflated Expectations, and Blockchain in Sports. A 2022 Sports Industry Outlook Report from Deloitte is optimistic about how blockchain technology will change the way fans interact with their favourite sports and hopes that new types of “collectibles” will lead to new markets for the industry. In this blog, we would like to take you on a journey of how blockchain is redefining the sports industry especially with respect to Fan Engagement and what it means for the future. A Quick Overview Of NFTs Blockchain technology is now widely popular in the sports industry. Most of the time, it is associated with the Initial Coin Offering (ICO), which is a way to encourage transparency and trust in fundraising. But what are NFTs or non-fungible tokens? The basic idea behind an NFT is that a token is used to represent ownership of unique items. The token, in other words, is a non-interchangeable unit of data stored on a blockchain, think of this as a digital ledger which retains history of ownership and value, that can be sold and traded. The NFT data units may be associated with digital files of art, photos, games, videos, and audio. While the Quantum NFT created by digital artist Kevin McCoy in 2014 is credited as the first NFT to be minted as a “monetized graphic”, the CryptoKitties, a blockchain based virtual game, NFTs created the first use case for wider adoption. It allowed people to trade and breed digital cats stored on smart contracts in the Ethereum blockchain. Much of Cryptokitties success is attributed with their ability to conform to the ERC-721 standard, explicitly developed for non-fungible tokens from the start. It allows users to store unique and identifiable data about any item that can be traded or sold in digital space, so ownership and movements are tracked through one smart contract. The Rise Of Fan Tokens The recent rise of fan tokens in the sports industry has also become a new trend as more teams and clubs adopt blockchain technology as a mainstream method for payment or transactions with fans. For example, a few European Soccer Clubs use fan tokens to reward their fans using blockchain technology and cryptocurrencies. Unlike the Non Fungible Token, Fan Tokens are fungible or interchangeable. Owners of Fan tokens can exchange them for services provided by a sports team or club. Fan tokens are digital assets that can interact with club ecosystems, including voting on fan polls and earning rewards. You can also use them off-platform to buy merchandise, match tickets, and other club-related content. Fan tokens are at times referred to as sports cryptocurrencies or utility tokens. Fan tokenization gives sports teams a way to monetize their vast global fan bases while creating a more direct relationship with fans than they’ve ever had before. Current Marketplaces Of NFT In the Sports Industry Now that you’re familiar with the NFT landscape, it’s time to dive right into its heart: marketplaces. These marketplaces are where the majority of NFT transactions happen. They’re one of the most critical puzzle pieces because they’re where all the action happens. When considering buying your first NFT, you should research each marketplace to determine which one is best. Here’s a list of a few top NFT marketplaces: OpenSea.io It features CryptoPunks, Decentraland items, Cryptovoxels assets, Axie Infinity items, etc. OpenSea offers a variety of non-fungible tokens—from art to censorship-resistant domains to virtual worlds to collectibles. It supports ERC721 and ERC1155 assets. Rarible.com This community-owned NFT marketplace rewards users who sell or buy unique digital assets on the market by distributing 75,000 RARI every week to active users. Foundation Foundation is a platform built to help digital artists and crypto-collectors connect and share ideas. It is a place where you can buy and sell artwork from top artists. SuperRare SuperRare is an online marketplace for people to buy and sell authentically created digital artworks, the ownership of which is recorded on the blockchain. It focuses on digital art pieces made by artists they personally select. AsyncArt Asynchronous Art is a way to purchase digital art that evolves. Buyers get to choose how the art is transformed through an app that updates the piece. KnownOrigin A curated gallery of exclusive Digital Artworks ranging from limited collectible editions to open prints and artist editions on blockchain technology using Ethereum smart contracts and ERC721 tokens. Currently, it features work from over 100 artists, including Joe Hargreaves, Quibe, and Ben Giles. Nifty Gateway Nifty Gateway is an NFT marketplace that sells artworks from digital artists, brands, and celebrities. It is a sister company of Gemini (a licensed Cryptocurrency exchange and custodian). NBA Top Shot The National Basketball Association (NBA) in collaboration with Dapper Labs created NBA Top Shot, a blockchain-based platform that allows fans to buy, sell and trade numbered versions of specific, officially-licensed video highlights. The platform allows users to transact with cryptocurrency and conventional credit based payments. Dapper Labs has also forged a partnership with the National Football Association (NFL) to launch a similar platform for NFL content called NFL ALL DAY. Advantage Of Sport NFT Marketplaces Unlike traditional sports memorabilia, digital collectibles are not subject to physical wear and tear. You can store and exchange safely in crypto wallets. The digital nature of NFTs also makes them easier and cheaper to trade. NFTs are unique digital collectibles. They are authenticated on a blockchain, making them effectively impossible
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A Blog Article and A White Paper – What’s The Difference?
A Blog Article and A White Paper – What’s The Difference? ATMECS – Content Team [read_meter] According to the American Marketing Association, “Marketing is the activity, set of institutions, and processes for creating, communicating, delivering, and exchanging offerings that have value for customers, clients, partners, and society at large.” Marketing is the most significant element of every branding and advertising. As the world is continuously transforming and evolving, marketing has been a constant need of B2B enterprises, multinational companies, B2C companies etc., to make people aware of their products and services. And, sometimes, the way a company markets itself helps differentiate itself from its competitors. However, the techniques of marketing, especially digital marketing, evolve rapidly. Companies across the globe are constantly finding new and innovative ways to reach and serve their target audience via online content marketing. Petabytes of fresh online content gets created each day worldwide and this content could be in the form of video, short form and long form editorial or op-ed content, text brochures, blog posts, white papers, etc. Each type of content has its own pros and cons to it. In this article, we will brief you on two types of content – white papers & blogs – to help you understand what they are and how they can be used effectively as part of a digital marketing strategy. White papers – A brief introduction When it comes to B2B marketing, white papers are a widely used content marketing tool. Whitepapers highlight the usage and solutions that a company, or an enterprise, plans to offer to its customer via its products and services. White papers are authoritative publications to educate people about an issue, brand, cause, solution, etc. In most cases, white papers are the best tools for lead generation and product purchase guides. Approximately 64% of B2B enterprises, according to a Content Marketing Institute Research Study, use white papers for marketing their product. Since white papers are widely used in online content marketing and influencing consideration or conversion are always important objectives, it is critical to pay attention not just to the content but also to the product or service itself. As a business, you want to convert readers into purchasers, which you may achieve by discussing how the product or service can directly benefit them. The readers need to know why they require it, how it will assist them, what issues it will solve, and other pertinent details. Some people believe that white papers are basically product or service pitches. This is not true. However, it may easily come off as a sales pitch if you are not careful about managing the tone & messaging intensity. Sometimes, even blog posts tend to be perceived as selling an idea, product, or service. Therefore, it is crucial therefore to strike the correct balance between convincing and informing your audience while authoring either types of content. Blog posts – A brief overview A blog post is a technique of reaching out to target audiences directly and individually. It appears on the website briefing the customers about the product or service in approximately 350-800 words. More than 90% of content marketers use blog posts for marketing their products, according to SEMRush. A blog post is a collection of data, topics, or sentiments maintained in a log. It is clearly the priority of many B2B enterprises. Empirical studies show, companies see 55% more readers on the website when they make blog posts their priority. Mostly, every blog includes some visually appealing photographs to attract more readers. They have a shorter length and are easy to post. Blogs are an excellent method to grab the attention of your target audience. Therefore, they end up generating approximately 67% leads per month for a brand. Blog articles assist organizations in establishing relationships with their internet users and consumers. One of the most significant advantages is that they may improve your SEO with certain keywords. Let’s tabulate the differences between white papers and blog posts! A blog post and a white paper differ in many aspects. A blog post carries a practical perspective to the topic, whereas a white paper is an attempt to educate and promote a specific brand/idea/premise. Both the concepts are based on different core factors. Some extra points about white papers Most good white papers should have the following: The material of a white paper is often in the form of a downloadable PDF. It may also be necessary to provide an email address to download. This facilitates a continuation in the interaction between the company and the audience. The white paper’s beginning, particularly the first paragraph, should pique the reader’s interest. Consider it the elevator pitch for any content of your white paper. This is what makes it unique. Tips to combine white papers with blog posts: An excellent white paper will provide enough material for numerous blog entries. In reality, the following is the ideal technique for combining the two: Create a powerful white paper. Take one major idea from the white paper and write a blog post about it. Point to the landing page for the complete white paper at the conclusion of the blog. Repeat steps 2–3 until you’ve covered all of the white paper’s main points. This method makes use of your blog’s SEO strength to increase visibility and downloads for your white paper. The white paper is the main topic, while the blog articles are just the side projects presented as smaller pieces that link back to the main information.
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Software Defined Networking (SDN)
Software Defined Networking (SDN) Anupam Jagdish Bhoutkar Software Defined Networking (SDN) What is SDN? Software-Defined Networking, or SDN, is a strategy that removes control and configuration from each individual network device and places that responsibility on a controller. When done correctly, a controller-based approach yields the following benefits: Automation Configuration consistency Enhanced software/firmware upgrades (easier, quicker, less downtime) Increased visibility into network events Cost reduction Increased performance Real-time remediation of network outages without human intervention Over the past decade, virtualization has been one of the biggest changes for organizations have ever seen. It has brought about real change in server provisioning by automating and streamlining the technology. However, it is a major setback that network/storage infrastructure was not modernized to keep up with the next wave business challenges like that of cloud computing. While virtualization completely focused on computer/server workloads, it was less concerned about the storage and network domain. Thus, fully deployed, and functional VMs did not change the traditional networking and storage strategies. SDN will bring about that flexibility and economy of software to hardware data centers which traditional networking failed to deliver. Traditional Network: Networks are getting too big and too complex to manage manually, one device at a time. The average network now has thousands of endpoints connected to countless routers, switches, firewalls, APs, load balancers, and optimizers. Scale alone dictates we cannot continue our current strategy. Businesses today demand that networking adopts a more agile methodology to keep up with organizational requirements and modern frameworks like AppDev. Any downtime is now frowned upon, even when planned. By now, SDN sounds like an ideal solution for today’s organizations, but it is important to understand the architecture, benefits, misconceptions, and limitations of it as well. Businesses today demand that networking adopts a more agile methodology to keep up with organizational requirements and modern frameworks like AppDev. Any downtime is now frowned upon, even when planned. Architecture of Software Defined Networking (SDN): SDN architecture separates the network into three distinguishable layers Application layer: Applications communicate with the control layer using northbound API and control layer communicates with data plane using southbound APIs. The SDN application layer, not surprisingly, contains the typical network applications or functions like intrusion detection systems, load balancing or firewalls. Control layer: The control layer is considered as the brain of SDN. The intelligence to this layer is provided by centralized SDN controller software. This controller resides on a server and manages policies and the flow of traffic throughout the network. Infrastructure layer: The physical switches in the network constitute the infrastructure layer. A traditional network uses a specialized appliance, such as a firewall or load balancer, whereas a software-defined network replaces the appliance with an application that uses the controller to manage the data plane behaviour. How it works? Before we define how SDN works, let us briefly touch upon what a switch is made of. A switch is a network device that consists of two components – the control plane and the forwarding plane. The forwarding plane is that piece of hardware other than the CPU that ensures packets are routed across the network. And now, how does this forwarding plane function? There comes the role of the control plane where the routing protocols reside and perform their work whose results control the forwarding plane tables and determine how packets are routed. Thus, in simple terms, SDN is a software that deploys control on the forwarding plane by a writing software that will expand or replace portions of the control plane on the switch provided by vendors like Cisco, Juniper etc. For example, protocols like OpenFlow will help in the evolution of SDN that is not actually tied to any vendor. We hope this explains how SDN has become an emerging architecture that is designed to manage and support virtual machines and the dynamic nature of today’s applications independent of the physical network. Different models of Software Defined Networking and Vendors Open SDN uses open protocols to control the virtual and physical devices responsible for routing the data packets. API SDN uses programming interfaces, often called southbound APIs, to control the flow of data to and from each device. Overlay Model SDN creates a virtual network above existing hardware, providing tunnels containing channels to data centers. This model then allocates bandwidth in each channel and assigns devices to each channel. Hybrid Model SDN combines SDN and traditional networking, allowing the optimal protocol to be assigned for each type of traffic. Hybrid SDN is often used as a phase-in approach to SDN. According to Gartner Critical Capabilities for Data Center and Cloud Networking 2020, listed below are some of top vendors of the industry who provides reliable, scalable and robust SDN solutions. Business Drivers and Challenges Reduced CAPEX: Centralized intelligence and implementation of logic in switches eliminate the deployment of thousands of switches. Thus, the total cost allocated for maintenance of switches is reduced as well as the total cost of network equipment. A huge chunk of organizations would want to revamp their traditional IT setup and upgrade to SDN for this major reason. Reduced OPEX: Now, when the network has been centralized, it leaves with just a few points of management. Thus, it will take only very few engineers to manage our new modern network. Moreover, it does give room for better utilization of existing hardware while decreasing the need for more expensive and high-end network equipment. Centrally Managed: SDN consolidates network intelligence, which provides a holistic view of the network configuration and activity. Programmable: The ability to directly program network features and configure network resources quickly and easily through automated SDN services. Deliver Agility and Flexibility: As business and application needs change, administrators can adjust network configuration as needed. Enable Innovation – Open Connectivity: SDN is based on and implemented via open standards. As a result, SDN streamlines network design and provides consistent networking in a vendor-neutral architecture. Common Misconception SDN is a significant architectural change over traditional networking infrastructure. However,
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Optimizing Performance of Your Testing Team
Optimizing Performance of Your Testing Team Velmurugan Kothandapani & ATMECS Content Team We live in a time where yesterday’s imagination has become today’s reality. Digital innovation, smart applications and machine intelligence are advancing at such a rapid pace, one may wonder: what happens between technological innovation, production/development and mass adoption of any new product? You may be surprised to know there is a tireless team of engineers who perform rigorous tests during any technology product development and deployment cycle to ensure innovation goes from labs to market swiftly. They are the Quality Assurance (QA) Team. Leaders of QA teams face a number of challenges implementing Test Automation “the right way” when the pace of innovation is so fast. Here are a few we have experienced first hand: Asking the right questions – early! The foundational paradigm of every testing team is to “Ask Better Questions” early on in the Software Development Life-Cycle (SDLC). A single flaw, albeit identified, late in the process could result in a higher cost. Needless to say, not catching a defect and, inadvertently, allowing it into production could result in a significant financial loss, company credibility and a loss of customer trust. Effective use of Artificial Intelligence The question is no longer whether or not to use AI but where AI should be deployed to get the best use out of it. As computing power, advancements in AI and debates on what a machine and man can or should do, grow everyday, it is important to demarcate roles and responsibilities of AI and people resources so that each one performs at their optimum for the advancement of human society. Here’s where business and IT leaders need to question whether liberating human testers from monotonous duties and allocating them to spend more time on exploratory testing is in the best interests of a company’s IT organization. After all, “The Art of Questioning” is what distinguishes humans from machines. Organizational Asynchronicity From sales and marketing to R&D, from development to testing, functional departments, more often than not, have their own KPIs and ways of functioning. This lends itself to teams working in silos following their own departmental SOPs. QA & Testing, while being the conscious keeper of any new product innovation, are often under prioritized. As a result, this leads to long product test life cycles, delayed product development, and delayed time to market. Challenges due to today’s global, digital world While the growth of digital technologies has enabled every company to make their product or service ubiquitous through global reach, it has also added a few headaches to Testing teams. Deploying test environments, on cloud vs on-prem and infrastructure challenges due to multiple customer touch points – platforms, devices, browsers – are all questions that keep testing teams up at night. Not to mention scalability issues when the volume of test modules, and test suites grow. Cumbersome Testing Framework Development Developing a Testing Framework while on-boarding an automation project is both time consuming, cost and resource intensive. It requires nuanced programming skill sets and versatile developers to be part of the framework development cycle. Absence of Right Tools Given the plethora of current and future challenges faced by a business in the post-pandemic era, it is imperative for IT leaders to “empower” its testers by providing them with the “best in class” tools and technologies. More often than not the “Testing” function is likened to a “Black Box”. This is so because there is a lack of proper reporting solutions to enable visibility into test coverage and executive intervention/decision making Introducing ATMECS FALCON – A Test Automation Platform, Testers and Team Leaders Love to Use ATMECS engineers have studied the testing landscape in depth and have developed an out of the box unified continuous testing platform to support testing of and quickly automate Web UI, Web Services, Restful Services, Mobile in one elegant platform. Falcon – an AI powered, intelligent and automated testing platform – has made testing and automation both effective, efficient and enjoyable for testing resources and team leaders. With parallel execution enabled for large test suite runs and centralized reporting to monitor and analyze all project test results in an intuitive user interface, once dreaded activities are now seamless, easy to complete and pleasurable for testers both in-house and at our client deployments. Additionally, what used to take over a week to accomplish now takes less than 15 minutes with Falcon. With timely quality reporting, dashboards and alerts, Falcon helps key IT stakeholders informed and in control of their testing process while setting up engineering teams for successful completion and deployments. Since Falcon works seamlessly with cloud technologies, on demand and at scale, our clients have testified that with Falcon, quality is no longer a serial activity after engineering builds but a parallel activity that agile teams can depend on through the build cycles. Sneak peek at Falcon – Highlights One Tool for Web, Mobile Native Apps, Web Services (Restful, SOAP) AI powered Smart Locator Generator that generates locators automagically for the UI elements of both web, native mobile apps. AI powered self-healing test scripts to automatically fix and adjust to changes in UI AI powered PDF files comparison Test Data Support in XML, Excel, JSON, DB (relational, document based) Built-in integration with Jira, Continuous Integration tool (Jenkins). Built-in integration with SauceCloud, BrowserStack (Cloud based platform for automated testing) AI integration for speed and accuracy The suite also provides a Lean version (without integration with above tools) with all key features of the framework Supported browsers are IE, Chrome, Firefox, Opera & Safari, while supported operating systems are Windows, Mac, Linux (thanks to the flexibility of Selenium) Integrated Centralized Report Dashboard for leadership team Manual testers can also use this framework to automate, with minimal training and without an in-depth understanding of the tool / framework / programming Contact Us to Know More!
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