For more than a decade now, Siemens has been pursuing a growth strategy that combines acquisitions with organic R&D. With technologies from each in place, Siemens is now combining some of its software products into a single portfolio to provide users with easier access to many of its different software capabilities.
An example of this can be seen in Siemens’ launch of Opcenter, which integrates the company’s Manufacturing Operations Management (MOM) capabilities such as scheduling, manufacturing execution, manufacturing intelligence, and quality management into a single cloud-ready portfolio. These capabilities come from a combination of Siemens in-house products, as well as those acquired from companies like Camstar and Preactor.
According to Siemens,integrating these capabilities and making them available via the cloud makes Opcenter easier to deploy and minimizes the amount of user training typically required. It should also ease the typically lengthy software implementation process while giving companies greater access to their production lines.
Opcenter can be launched on-site, remotely, or both simultaneously. All software systems and applications can operate on a variety of smart devices.
“Siemens Opcenter is the next logical step, given our extensive technological innovation and MOM portfolio evolution,” said Rene Wolf, senior vice president, Manufacturing Operations Management Software at Siemens Digital Industries.
Along with the launch of Opcenter, Siemens announced a new version of its Manufacturing Execution System (MES) software. The newest features in this version are focused on smart device integration, mobility, and capabilities that enhance availability and data flow.
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Volkswagen has opened its new information technologydevelopment centre in Dresden that will work to create industrial cloud to connect all its production facilities.
Around 80 IT specialists will work in the facility to develop the Volkswagen industrial cloud that is being built in association with Amazon Web Services.
The industrial cloud will bring together data from Volkswagen’s all the factories and enable smart real-time control, simultaneously in different factories. The goal of this industrial cloud system is to amalgamate all data and digitalize the production and logistics.
The automakers is also putting 5,000 digital experts into a new unit called “Car.Software” by 2025, as the German car manufacturer aims to develop at least 60% of its software in-house by then, up from less than 10% currently.
Volkswagen also said all of its new vehicles would use the same software platform – consisting of its vehicle operating system known as “vw.os” and the Volkswagen Automotive Cloud – by 2025.
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The global tech talent pool has never looked more attractive, especially as the demand for software developers continues its dramatic rise. In fact, according to the U.S. Bureau of Labor Statistics, “Employment of software developers is projected to grow 24% from 2016 to 2026, much faster than the average for all occupations.”
If you’re not technical yourself, it can be hard to tell when you’ve found a reliable software developer or a team worth contracting. So how do you approach hiring software engineers when you’re a nontechnical business owner?
As the CEO of a software design and development agency, I always give my potential clients and friends who are searching for outsourced development work the same essential tips I would give to a family member.
Step 1: Reach Out To A Tech-Savvy Friend For Support
Before you think about starting your search, reach out to your most technical friend, even if they’re happily employed. Maybe it’s the guy who was the go-to computer science whiz in high school or the woman who wrote the software at your previous job. Bottom line: Make it someone that you trust and who you feel comfortable enough saying something technically “dumb” to without worrying about their reaction.
Start by explaining to them what your software idea is and how you imagine it looking and working for a user. Then, ask them if they’ll help you write a brief technical description of your project and your needs — nothing fancy, and maybe a couple of paragraphs. They’ll likely know how to put together a quick technical summary so that another engineer will understand it and, this can make your first communication with an unfamiliar technical person that much easier.
Step 2: Locate Candidates
After you’ve nailed down a formalized version of your idea, ask your friend to help you locate five to ten freelancers or software development agencies whose skills are a good fit for your project. Platforms like Clutch, Upwork and GoodFirms are great places to find engineers and agencies.I’ve personally found it most effective to connect with at least five different freelancers or agencies that I know I’ll be able to work with.
Step 3: Set Up Interviews
With your list of potential candidates, you can start setting up the first round of interviews. If you like a specific freelancer or firm, then you may want to ask your technical friend to perform a second, more technical interview.
Pro tip: Offer your friend a $250 Amazon gift card or cash as a reward for helping vet your candidates, and make them take it. Their enormously helpful assistance will be of more value than you can imagine. Plus, that seemingly small investment upfront can often save you a ton of money, time, disappointment and stress down the line.
Step 4: Vet, Vet, Vet
This vetting process is where you can really rely on your trusted technical friend to ask the technical questions you may not understand the answers to. They can help you conduct an in-depth evaluation of a candidate’s technical expertise and experience working with similar clients. This may serve you much better than a simple cost analysis.
When vetting, ask candidates important questions such as:
• Do you have similar projects to mine in your portfolio?
• How do you charge for your time and expertise?
• What happens if the scope of my project changes?
Also, have them describe how they work with nontechnical people to make sure you know what you’re getting.
Step 5: Talk To Their References
Ask your top three candidates to put you in touch with three business owners they worked with who had projects similar to yours or around the same size. Ask them how technical that business owner was and how they might compare to you and your project. If there are similarities, then when you speak to that business owner, you’ll likely be able to gauge how easy the freelancer or agency was to work with for someone with your level of technical skill.
Any hesitation or excuses on the part of the freelancer or agency to share that information may serve only as a minor red flag because let’s face it: Not all clients are the easiest to work with. A good freelancer or agency, however, can likely provide you with four to five references at the drop of a dime.
Don’t Make This Common Mistake
It’s common for a nontechnical person who’s so engaged and excited about their project to want to hit the ground running and focus their engineer search on cost. One of the biggest mistakes you can make, however, is comparing freelancers or agencies based solely on their fixed project price quote or what they charge per hour.
If you lack a deep technical background and haven’t sought help from a tech-savvy friend, you may not have provided enough details for a freelancer or an agency to adequately estimate your project’s cost. Your candidates may be missing a key understanding of what you’re looking to build. Comparing candidates based on estimates from incomplete project scopes and ultimately picking someone because they’re the cheapest often results in unique challenges. Inevitably, that path can end up costing you more in time, money and headaches.
When considering a freelancer or agency, it’s always important to check out any reviews you can find online and/or talk to their references. You also want to understand their project management style and how responsive and communicative they are at the start. Ask to interview the lead project manager and lead engineer who will be working on your project.
When in doubt, take a cue from the Beatles, and get by with a little help from your friends. Don’t have a super technical buddy? Well, considering there are over 4.5 million IT workers in the U.S., ask your social network. Ask the people you trust most to connect you with someone who can help you. A decision like this that could make or break your project — and ultimately, your business — is worth the wait and the small fee you pay a friend.
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Just what we need–yet another “framework” for improving software security.
We’ve already got the PCI DSS (Payment Card Industry Data Security Standard), the BSIMM (Building Security In Maturity Model), the OWASP(Open Web Application Security Project), the SAMM (Software Assurance Maturity Model), the ISO (International Organization for Standardization), the SAFECode (Software Assurance Forum for Excellence in Code—the list goes on.
And it’s about to go on some more. The framework in the works—a white paper draft at the moment—from the National Institute of Standards and Technology (NIST), is called SSDF, as in, “Mitigating the Risk of Software Vulnerabilities by Adopting a Secure Software Development Framework (SSDF).” It went public June 11 and the comment window is open through August 5.
The framework recommends 19 practices, organized into four groups:
Prepare the organization.
Protect the software.
Produce well-secured software.
Respond to vulnerability reports.
Following the practices, the paper says, “should help software producers reduce the number of vulnerabilities in released software, mitigate the potential impact of the exploitation of undetected or unaddressed vulnerabilities, and address the root causes of vulnerabilities to prevent future recurrences. Software consumers can reuse and adapt the practices in their software acquisition processes.”
Recommendations, not mandates
All good. A more-than-worthy goal. Who wouldn’t want to mitigate the risks of software vulnerabilities? It’s just that it sounds a bit like issuing a framework for controlling the speed of vehicles on public ways when there have been dozens of laws on the books for decades designed to do the same thing.
Beyond that, whatever the specifics of the final version of the framework, they will be recommendations, not mandates. NIST is a federal agency, under the Department of Commerce, but is not a regulatory agency and therefore has no leverage to force compliance with the framework.
And yet … perhaps it will fill a void. The goal of the proposed framework seems to be less about trying to reinvent the wheel and more about bringing various types of high-quality wheels together in one place so people who need wheels can decide what fits their needs.
Indeed, the practices refer heavily to the multiple frameworks listed above, indicating that this is a consolidation of existing best-practice recommendations.
As one of the co-authors, Murugiah Souppaya, of the computer security division of the Information Technology Laboratory (within NIST), put it, “The paper facilitates communications about secure software development practices among groups across different business sectors around the world by providing a common language that points back to the existing industry sectors specific practices.”
He added that this “common language” is meant to help them describe their current practices. “This will allow them to set their desired baseline and identify areas for improvement,” he said.
Of course, none of the existing frameworks has transformed software security so far. There are headlines daily about breaches enabled by vulnerabilities—sometimes rampant—in applications or devices controlled by software.
So even if this is the best one yet, if organizations aren’t persuaded to invest the time and money to follow the recommendations, it is unlikely to generate even incremental, never mind transformational, improvements in software security.
Taking the long view
What are its chances of breaking that precedent? Not high—at least not in the short term—in the view of Sammy Migues.
Migues, principal scientist at Synopsys and a co-author of the BSIMM, said this doesn’t mean the proposed framework has no potential value. “Yes, following it would help,” he said. “But who is going to follow it? Only those for whom it is mandated, and only if they’re audited.”
And the number of those is likely to be small indeed. Migues noted that NIST “doesn’t make law or set policy. It’s an innovation organization for cheerleading and awareness. So unless some other organization that has the imprimatur of authority holds people to it, it’s unlikely that it will be followed,” he said.
The marketplace—both public and private—could exert some leverage, he said, if entities putting jobs out to bid made a security framework like this one part of the RFP (request for proposals). “They could say, ‘This is one of the things you have to comply with to get the contract,’” he said.
But given the number of frameworks/standards already in existence, it is difficult to see how “one more arrow in the quiver” would be the one that suddenly disrupts the marketplace like that.
Part of the problem, he said, is that it’s hard to change people who are set in their ways, even in an industry that is evolving as rapidly as IT.
“There are a couple of things I really like [in the proposal]—one of them is to implement a supporting toolchain. They’ve actually put thought into it—they’re saying you can’t just download free stuff. And putting these in as actual tasks, along with who should think about them, is useful,” he said.
“But every development manager has his or her way of doing things. Do you think any of them are going to look at this and say, ‘Wow. I’ve been doing this for 20 years and have been doing it wrong all that time! I need to start doing it completely differently’? Not a chance.”
Incremental change
Still, if a framework like this makes its way into the education system, it could yield incremental changes that would become transformative over time, he said.
“It can’t come from a vendor, but from neutral third parties,” he said. “If it makes its way into textbooks, college courses and RFPs, then it might gain some traction with regulatory bodies.”
NIST is hopeful that the framework’s “high-level” approach will make it more palatable to an “audience” of organizations with vast diversity in size and industry verticals. “The most important thing is implementing the practices and not the mechanisms used to do so. For example, one organization might automate a particular step, while another might use manual processes,” the paper says.
To that, Souppaya adds that the intent is for the SSDF to be “customized by different sectors and individual organizations to best suit their risks, situations, and needs as organizations will have different software development methodologies, different programming languages, different toolchains, etc.”
Migues agrees that flexibility is important—that getting the job done is more important than how the job gets done. But he said many organizations might not know the options for the “how.”
“What’s missing is workshops—something like a session at RSA with CISOs—that would guide people through how to do it based on their needs,” he said. “Just because I buy a Julia Child cookbook doesn’t mean I can do the recipes if I don’t know how to cook.”
Something along that line may be in the works. The authors of the white paper call it “a starting point” that they intend to expand to cover topics such as “how an SSDF may apply to and vary for different software development methodologies.”
That future work, they said, “will primarily take the form of use cases so the insights will be more readily applicable to certain types of development environments.”
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Robotic process automation, or RPA, has emerged as a potent productivity-enhancement innovation that is being embraced globally by virtually all industry sectors. This is hardly surprising since a software robot (also known as a bot) can work around the clock at a fraction of an employee’s cost.
Is RPA delivering to its promise of having digital labour seamlessly replace humans? The evidence is mixed. Many companies are experiencing significant productivity gains, but research suggests that 30-50% of RPA projects fail, unleashing risks.
A telecom company had deployed bots for managing its complaints process. Coding errors led to many grievances being diverted to an incorrect queue, resulting in a backlog of complaints. A global conglomerate deployed bots in its finance and accounts function to automate the accruals process. Its auditors, however, noticed that the accruals had been materially under-reported for a quarter. Unfortunately, incorrect rule-set definitions in the bots had led to the problem. Information security is also at risk: There have been reports of malicious employees launching cyberattacks on bots to access sensitive company data.
While critics blame the underlying technology, this is seldom the case. Usually, the root cause lies in the inattention to risk and internal control considerations in the bot-development life cycle and the re-designed, bot-enabled processes. There are five simple design principles to increase confidence in RPA implementations.
First, the less risky processes should be prioritized for automation. Sensitive processes, such as those related to finance and compliance should come later. An additional layer of monitoring controls should be considered for all mission-critical processes. Second, RPA practitioners should adopt a “what-cannot-go-wrong?” mindset. For instance, if bots are posting transactions to an enterprise’s core technology platform, users and administrators with access to these bots should not have the ability to execute conflicting transactions, such as placing an order and approving the payment. Third, bots need to undergo robust risk-based functional testing. This, however, is sometimes not adhered to during the software development life cycle. An investment bank discovered that a bot emailing end-of-day trade confirmations to customers was “dangling” because fields that were supposed to contain email addresses were empty. Fourth, watertight processes around bot security are critical. Similar to humans, bots too have user-names and passwords. Ensuring that these are encrypted and accessed by employees according to their assigned privileges is key to preventing unauthorized access and potential misuse, including fraud. Finally, implementing robust change-control processes is critical. RPA teams need to be made aware of changes to system interfaces so they can make timely updates.
As companies expand automation efforts, risk management functions need to step up and serve as critical lines of defence in the governance of these programs. Risk managers can identify pitfalls related to automating specific processes, pressure-test redesigned processes before they go live, and implement early warning systems that can predict, and ultimately, prevent bot failures. Leading risk functions, for instance, are deploying “supervisory bots” that monitor critical tasks performed by other bots and proactively raise alarm bells if they suspect performance issues.
Indeed, a healthy dose of risk management can allow software robots to become trusted enablers in an organization’s digital transformation journey.
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Founded in Bengaluru and now headquartered in San Francisco, Postman’s Series B round of fundraise will further accelerate its growth in the API ecosystem.
Postman, a collaboration platform for API development, announced its Series B round of fund raise of $50 million led by San Francisco-based early-stage investor CRV. Its existing investor Nexus Venture Partners also participated in the funding round.
CRV’s general partner Devdutt Yellurkar has joined Postman’s board of directors, the company said in a statement.
Headquartered in San Francisco, Postman builds platforms for the development and management of APIs (application programming interface), the language by which different software talk to one another. It’s target audience are the world’s 20 million-odd software developers.
“Over the past couple of years, Postman has emerged as a true API development and testing platform and a very fast growing developer community,” said Yellurkar. “CRV is deeply involved in the API and microservices space, and we have been tracking Postman from its early days in Bengaluru.”
In 2014, Abhinav Asthana, Ankit Sobti and Abhijit Kane, co-founded Postman in Bengaluru. Within a year the startup had 2.5 million users. At present, its collaboration platform for API development is used by more than 7 million developers and 300,000 plus companies worldwide.
“We are looking forward to working with Abhinav, Anki, Abhijit and the rest of the team at Postman as they build a foundational software company,” added Yellurkar.
Postman plans to use the new funding to accelerate its product roadmap, expand its commitment to helping companies leverage Postman across the enterprise, and increase customer support and success throughout the Postman community.
“As software development moves from a code-first to an API-first approach, Postman is evolving as the must-have companion for every developer,” said Jishnu Bhattacharjee, managing director, Nexus Venture Partners, which led Postman’s October 2015 seed and Series A funding round, which totaled $7 million. “It has been a real pleasure to have backed Postman from day one. We are super excited about the journey ahead,” added Bhattacharjee, who is also on the Postman board.
Postman CEO and co-founder Abhinav Asthana said, “APIs are the building blocks of effective software – so while software might be eating the world, we know that APIs are eating software. Innovation in APIs will drive the future of software development, and this funding will further accelerate Postman’s growth in the API ecosystem.”
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Java has a robust and lively ecosystem of support features. How can developers sort through the dizzying number of options to find the perfect tool for their project? Kayla Matthews explains how developers can find exactly what they are looking for.
Anyone with any amount of experience in the Java ecosystem — even just a little — knows it has a wealth of support features. There are two broad segments of this support: a robust selection of developer tools and software and just as many third-party libraries or frameworks.
Libraries, like frameworks, compile a vast selection of conventional programming and development functions into a single package. Generally, they are open-source and readily available for free. Essentially, they exist to eliminate a lot of the tedium and repetition that occurs in application and software development.
A library consists of a robust selection of class definitions or pre-written code that other developers have created. Instead of defining each class, operation, or function in every application from scratch, you can include a library which allows you to reference the existing code chunks. It’s much like going to a physical library and borrowing a book; only with programming, you’re going into a digital library and borrowing classes or functions.
Basics aside, the Java community is almost overflowing with libraries you can use. There are so many it can be challenging to narrow down your options. Where do you start? How do you know you’re making the best choice?
Assess your needs
Before doing anything, you first need to assess the current scope of the project and consider what you’ll need from the libraries you incorporate. More commonly, developers end up needing a specific type of library over something generic. To name a few, there are libraries for logging, JSON parsing, unit testing, HTTP, XML, database connection pools, and messaging.
There are also general-purpose or generic libraries like Apache Commons or Google Guava. They work to simplify a variety of tasks as opposed to something more specific. General-purpose libraries do offer a lot of help, but if you need something specific, it’s much more helpful to decide what to use up front. If you don’t, you’ll be writing the necessary code yourself, which can take quite some time.
Grade the library
As you might expect, not all libraries are equal. Some offer a healthy selection of classes and functions, yet they may have become deprecated. This means they no longer have support from a development standpoint. Alternatively, they might still be in active development, but the documentation is lacking or nonexistent, which makes using them incredibly difficult.
Whatever the case, you’ll want to grade the library before you include it in your next project. Consider how well-documented it is, as well as how active the support community is. Are there developer forums where you can get help from others? Is there bare-bones API documentation, or are there tutorials, guides, and samples too?
Generally, you can assess or measure the grade of a library by comparing it to others. If it’s lacking, you know to stay away. If it offers a healthy supply of support options, you’re good to go.
Check stable/unstable/testing status
Is the library in active development? If the answer is no, that’s OK. It’s not necessarily a deal-breaker as long as the library is well-documented, has some kind of active community behind it, and is relatively problem-free.
If it is active, you’ll want to consider its current status. Is it stable or in its early testing phase? A stable release is often streamlined and free of bugs and common issues, even though some might still appear. An unstable release, on the other hand, is “bleeding-edge,” which means the latest version probably hasn’t been through the wringer yet.
Of course, these things affect your project considerably, so decide based on what you need and prefer.
Is it popular?
With popular libraries and frameworks, you get a lot more bang for your buck. They often have a bustling community behind them of like-minded developers who are actively using the library in their projects. Also, many experienced and knowledgeable developers have worked with the library in the past. That is going to help you significantly when you need advice or guidance, or even when you need to hire someone who knows what they’re doing.
Sometimes, you might like one library more than another, but find it more beneficial to go with the more popular one because it has more support and is more widely used.
Do you like the API?
This last point is tricky because it involves using the library and its content, at least for a period. An API, or application programming interface, is what expressly allows you to tap into the integrated content of the library. It’s primarily a matter of personal preference, but it affects the overall experience. If you don’t enjoy using the API or working with it directly, you’re going to have a rough go of it.
You learn more in the doing
Finally, keep in mind you’ll learn a lot more about a particular library when you start to call upon it. Working with the API is one excellent example. But you might also find the library doesn’t help you as much as you thought, maybe because it lacks the necessary classes or modules you need. Furthermore, it’s also possible active development changes the experience. You might start with one library, but through the course of several updates, it becomes less reliable or causes a host of issues for your project.
The best way to deal with this is to incorporate a library review period into your regular development to consider the direct value it is offering you. It’s better to decide early on that you need to swap libraries than toward the end of a project. Not only will it save you a headache — it will save you time and money, too .
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Businesses spent over a trillion dollars on enterprise software and IT services last year, with a healthy forecasted growth fueling an otherwise flat IT market.
You might expect this investment would be producing better and better software, but every day you probably experience the reverse. Cryptic error messages, confusing flows and plain old software crashes seem as inevitable as death and taxes.
But they don’t need to be. The difference between disappointment and software people love to use boils down to just five golden rules.
In previous posts, I discussed the fundamentals of understanding your userand creating a consistent and performant experience. In this final post, we wrap up balancing the needs of the head (pragmatic security) with the heart (user delight).
Rule No. 4: Be Secure (Yet Practical)
Data is digital, and digital data is vulnerable. Personal data, corporate secrets — it’s all fair game for cybercriminals. It doesn’t matter how performant or user-centric your software is if it exposes sensitive information for pilfering.
That said, you need to strike a balance. Security is not a yes-no question; rather, it’s a compromise between risk and return. All security creates inconvenience. The question is whether the value of what you’re trying to protect justifies the trouble. If you’re designing a banking site, you can justify almost any amount of security: strong passwords, captchas, two-factor authentication. But should you ask the user to enter a two-factor code to check their gas bill? That’s harder to say.
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Where digital transformation continues to ripple across all the industries; from banking to retail, businesses turn up to mass adoption of digital technologies for innovation and survival in the long run. The business ecosystem is giving a thrust to the C-suite gems to fuel revenue growth with dynamic business models, which entice the customers with innovative services, and top-class experiences. This may sound a plausible idea at prima facie, but the challenge is real when it comes to draw a pliant business model and devising a customer-centric operational plan to make it work. Technologically advanced tools, and software can set a go-get plan in motion, for which, CIOs and business leaders must learn, how digital innovation should be harnessed if improving value chain is in their heads and hearts. However, digital innovation and transformation is different for every business, yet are based on the commonly shared principle of customer-centricity. True, companies do not usually turn up to customer-centric projects, and expensive digital transformation, unless they lag behind the competition, nearing to their downfall. Therefore, chasing efficiency and agility, business leaders are in the pursuit of digital products and services that combine their strategy with the technology to achieve success. These applications or software enable the businesses to connect with their customers or seamlessly, upgrade the performance of their employees, and digitize their internal business operations.
As most of the companies are now aggressively shifting toward digital transformation, the compatibility of the applications or software with different networks and channels in a specific condition remains a big concern. All thanks to Digital Quality Assurance, which makes the business, take a step forward towards digital transformation; the integrated testing of multiple embedded software and devices is now possible and easy to execute.
Switching to digital quality assurance
ShepHyken, an American customer service expert, said: “A brand is defined by the customer’s experience. The experience is delivered by the employees.” It is the founding principle of Digital Quality Assurance, which aims to deliver customers an impeccable customer experience. In the traditional landscape, Quality Assurance (QA) stood for keeping a check on time, costs, and quality throughout the software development life cycle.
Always considered sluggish, and redundant due to the waterfall model, the traditional QA replaced by the Digital Quality Assurance—a breakthrough in digital testing which saves time, repetitive efforts, customer experience for the companies. These are the end-goals of almost every business’ digital transformation strategy, which digital assurance fulfils. In digital assurance, the speed of the product development is optimized from the initial stages, and the quality of the product is tracked throughout the development stages. Costs and development efforts are significantly reduced because of a concentrated focus on building a viable product in the first attempt only using the customer-data and various automation technologies.
Pump it up with data and analytics
To develop an application that drives customer engagement, having precise customer and behavioral data before or at the time of development in hand is the key. Earlier, QA testers used to rely on reported defects, surveyed shortcomings, reviews, and feedbacks of the customers. In this new age of testing, the teams can directly access the customer’s data through Big Data- and AI-powered systems and test the software for a better-quality insight. With Agile/DevOps, digital QA testing teams can reduce the errors and shorten up the development cycle by drawing inferences from data sourced through Facebook, Twitter, web portals, digital assets, and web analytics, etc.
Achieve higher customer satisfaction levels
A customer starts looking for an alternative, as soon as his application is bogged down by the technical glitches. In the wake of agile development, business leaders strive to align the development of the product with the needs and requirements of the customers for winning customer loyalty and trust. For this, Digital Quality Assurance yields early visibility of the product across production stages as well as accelerate the process through a context-driven testing approach.
Improving the understanding of the context, in which customers engage with the application, it empowers the QA teams to impart the customer expectations to the developers, reducing the risks of errors from the ideation stage. The timely customer feedback and experiences from previous development cycles serve as the inputs for testers and developers to collaboratively work to deliver a quality application.
Get improved organizational efficiency
Destined to facilitate continual collaboration, and communication between development and operations teams, DevOps is widely adopted by businesses to achieve organizational efficiency as well as effectiveness. But, utilization of the old strategy for testing is defeating the purpose of DevOps in most organizations.
In today’s world, with need to deliver at rapid pace, where development teams have adopted rapid development techniques, it’s the need of the hour for quality assurance teams to move away from traditionally pre-defined smoke/sanity/functional/regression test suites to the ones created dynamically using machine learning to identify high probability point of failures.
Automated machines and human QA testers
QA testing has always remained imperative to the development of reliable and quality software. In this new age of Digital Assurance role of functional manual testers will be redefined because of automated testing tools backed up by AI and ML.
Looking at the pace of innovation in the field, the days are not far enough when the machines, trained by humans, will write and implement test codes. We are already seeing the advent of self-healing automation scripts, automated test data generators, test scenario, documentation and analysis, to performance load model generations using ML and AI.
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On Monday at the Cisco Live event in San Diego, Cisco’s developer program DevNet announced an update to its professional certification program. The update joins software developers with network professionals under a new community-based developer center, with the hopes of accelerating the progress of network automation in organizations, according to a press release.
“Networking technology has evolved significantly over the last five years and the new network can accelerate business, catalyze new applications, and bring DevOps practices to networks,” Susie Wee, senior vice president, CTO, and founder of Cisco DevNet, said in a press release. “We are bringing software skills to the networking industry with new Cisco DevNet certifications. In addition, we are bringing software, practices to networking by having a community of networkers and developers work together to solve tough network automation problems through shared code repositories. This will allow the industry to take full advantage of the capabilities of the new network to accelerate business.”
Network automation is one of the biggest challenges for IT, a Cisco report found. However, organizations can combat this by creating a network based on the Walk-Run-Fly method: Walk through the networks to gain insight or visibility on success and failures; run activation policies and implement them across domains; and fly by managing applications and devices with DevOps workflows.
The new certifications include the DevNet certifications to validate software professionals, streamlined certifications to validate engineering professionals, and training to help entry level professionals in both the network and software industries.
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