{"id":11483,"date":"2019-09-30T09:20:35","date_gmt":"2019-09-30T09:20:35","guid":{"rendered":"http:\/\/abstracta.us\/blog\/?p=11483"},"modified":"2025-05-05T21:23:13","modified_gmt":"2025-05-05T21:23:13","slug":"releasing-software-at-speed-without-losing-quality","status":"publish","type":"post","link":"https:\/\/abstracta.us\/blog\/testing-strategy\/releasing-software-at-speed-without-losing-quality\/","title":{"rendered":"3 Essentials for Releasing Software at Speed Without Losing Quality"},"content":{"rendered":"

How to reduce time to market while maintaining quality?\u00a0<\/span><\/h1>\n

How long does it take at your company, from the time someone in sales or marketing comes up with an idea, to the time that it\u2019s making money and adding value to your users? Let\u2019s say it\u2019s a simple change to your software or an added functionality in which everyone agrees that it would be an improvement. And, let’s say that the change would have to be able to support 100,000 users in a 100-minute window. You want to avoid any risk and also design and ship it so that it provides a great user experience. How long would it take to make that a reality? If you think it\u2019s five days, for example, how much time could you possibly shave off that? A few hours? A day? Two days?<\/span><\/p>\n

With any digital transformation, it\u2019s essential to attain “quality at speed” to be able to provide quick solutions with a reduced time to market, but without sacrificing quality. In this hyper-competitive world, the difference is not in who has the best idea, but in who can implement it and bring it to market in the shortest time, in the best way, with appropriate quality.\u00a0<\/span><\/p>\n

How can companies achieve quality digital products at speed? Over ten years since founding Abstracta, my colleagues and I have noticed three team capabilities that play a pivotal role: the ability to leverage AI, to automate the build pipeline, and to cultivate a strong team culture that leans heavily towards Agile and DevOps. Here\u2019s why!\u00a0<\/span><\/p>\n

<\/span>1. Leverage Artificial Intelligence<\/b><\/span><\/strong><\/span><\/h2>\n

According to the <\/span>World Quality Report 2018-2019<\/span><\/a> by Capgemini and Sogeti, an average of 22% of IT budgets goes to AI projects<\/span>\u2014and it\u2019s even higher <\/span>in the high tech industry; 25%. Fortunately, today there are many AI-based tools from which developers can choose such the <\/span>IBM cloud console<\/span><\/a>, which allows you to enable voice recognition, image processing, and more very easily. Similar platforms have also been built by <\/span>Google<\/span><\/a>, <\/span>Amazon<\/span><\/a>, and <\/span>Microsoft<\/span><\/a>.<\/span><\/p>\n

<\/span>The Importance of Data Science Skills<\/b><\/span><\/strong><\/span><\/h3>\n

Okay, maybe not just <\/span>anyone<\/span><\/i> can set up these tools quickly and it\u2019ll be a challenge to actually create something<\/span> of value <\/span><\/i>with these AI tools. But, companies are realizing the ways in which they can solve problems and streamline processes.<\/span><\/p>\n

In this regard, we\u2019ve found at Abstracta that <\/span>incorporating a data scientist is key<\/b>, since this role is imperative for handling the use of today\u2019s machine learning and artificial intelligence tools. I know that hiring a data scientist sounds intimidating, but we\u2019ve found a practical, cost-effective way to do so.<\/span><\/p>\n

A year ago, we realized we could benefit from creating an AI tool that would streamline aspects of our operations so that we could focus more of our energy on delivering better software testing services (instead of getting caught up in paperwork). At the time, we didn\u2019t have anyone specifically trained in machine learning in-house, but one of our team members, Rodrigo Quintana<\/a>,\u00a0being\u00a0highly mathematically-oriented, jumped at the opportunity for us to enroll him in the <\/span>Coursera course<\/span><\/a>, Data Science Specialization, by John Hopkins University.\u00a0<\/span>Today, Rodrigo\u00a0<\/strong>is already collaborating in the research and development of our own tools and even contributing to the development of one of our most important client\u2019s testing products.\u00a0<\/strong><\/p>\n

\"coursera<\/p>\n

With all of the online courses available today, it\u2019s easier than you\u2019d think to develop someone\u2019s data science skills in-house<\/strong>, you just have to find someone who is motivated and give them the time and space to dive in.<\/p>\n

According to this <\/span>Sogeti<\/span><\/a> article reflecting on the World Quality Report, Abstracta is not unique in incorporating this role, <\/span><\/p>\n

\u201cAs AI in Testing and QA matures, three new roles will distinctly emerge: AI QA strategists, data scientists, and AI test experts.\u201d<\/p><\/blockquote>\n

<\/span>AI-Based Testing Tools<\/b><\/span><\/strong><\/span><\/h3>\n

When it comes to AI specifically applied to software testing, it\u2019s the newest generation of test automation tools that embraces AI the most, making tests even more powerful and robust, like <\/span>mabl<\/span><\/a>, <\/span>Testim<\/span><\/a>, and a visual regression testing tool developed by one of our own at Abstracta called <\/span>Oculow.<\/span><\/a> The AI aspect of these tools helps to facilitate test maintenance and speed up execution times even more than traditional test automation tools can. Read more about test automation and AI in <\/span>this post<\/span><\/a>.\u00a0<\/span><\/p>\n

To sum it up, using AI to enhance your operations and your testing toolkit will allow your team to focus on quality, move faster, and still detect major errors before go-live.\u00a0<\/span><\/p>\n

<\/span>2. Set Up an Automated CI\/CD Pipeline<\/b><\/span><\/strong><\/span><\/h2>\n

It should come as no surprise that to facilitate agility and velocity, <\/span>teams should adopt DevOps and set up a Continuous Integration\/Continuous Delivery (CI\/CD) pipeline for building products.<\/b>\u00a0<\/span><\/p>\n

Ultimately, a scheme needs to be in place wherein whenever a developer makes a change, he or she receives an almost immediate notification about whether the change was approved or not, thus increasing productivity through continuous feedback and helping to detect errors nearly instantly, when they\u2019re easier to fix.<\/span><\/p>\n

\"CI\/CD<\/p>\n

In the graphic above, you can see this pipeline is built on top of an integration server. The most popular one in the open source world is <\/span>Jenkins<\/span><\/a>, but there are dozens to choose from.\u00a0<\/span><\/p>\n

So, what types of processes can be automated in a CI\/CD pipeline? Actually, quite a lot!\u00a0<\/span><\/p>\n

<\/span>Automated Regression Testing<\/b><\/span><\/strong><\/span><\/h3>\n

One of the first things to consider are regression tests, first of all at the level of unitary code, then at the integration level, and finally at the UI level, a.k.a. end-to-end tests. As mentioned earlier, there are dozens of great tools meant for this type of test automation, some of which are enhanced with AI.\u00a0<\/span><\/p>\n

After setting up functional test automation, these tests can be enhanced with the help of the cloud, for example, testing in a device cloud, like <\/span>AWS Device Farm<\/span><\/a> which is great to scale or <\/span>Saucelabs<\/span><\/a> for executing on devices with different browsers and operating systems, thus achieving cross browser testing.\u00a0<\/span><\/p>\n

<\/span>Performance Testing<\/b><\/span><\/strong><\/span><\/h3>\n

It\u2019s well known that performance is another relevant aspect of software quality as users have less and less tolerance for long page load times. They want systems that are not only updated often, but have a great user experience.\u00a0<\/span><\/p>\n

With one client of ours, Shutterfly, we helped its performance engineering team to automate performance testing in its CI\/CD pipeline which enabled its devs to know instantly and automatically when a new line of code caused Shutterfly.com\u2019s performance to worsen. Read more about how exactly these tests were set up <\/span>here<\/span><\/a>.\u00a0<\/span><\/p>\n

<\/span>Other Automatic Checks to Consider<\/b><\/span><\/strong><\/span><\/h3>\n

It\u2019s even possible to add automatic <\/span>code quality<\/span><\/a>, <\/span>security<\/span><\/a>, <\/span>accessibility<\/span><\/a> and <\/span>usability<\/span><\/a> checks. As you can see, there are a lot of aspects of software that can be checked automatically.\u00a0<\/span><\/p>\n

Undoubtedly, this does not mean testers are unnecessary, but if teams decide to do everything by hand and not empower themselves with the right tools, they can hardly achieve the competitive difference that comes from releasing high quality software at speed.<\/span><\/p>\n

<\/span>3. Build a Strong Team with an Agile and DevOps Culture<\/b><\/span><\/strong><\/span><\/h2>\n

\"abstracta<\/p>\n

Having the right capabilities and technology stack is important, but in order to truly achieve quality at speed, <\/span>it\u2019s essential to have a team that is highly Agile and engaged.<\/b><\/p>\n

<\/span>Don’t Do Agile, Be Agile<\/b><\/span><\/strong><\/span><\/h3>\n

It may go without saying that in order to receive feedback and deliver value continuously, it\u2019s absolutely necessary to follow agile practices combined with a <\/span>DevOps culture<\/span><\/a>. It\u2019s also important not to just work in such a way on paper, but on the ground (which is much <\/span>easier said than done<\/span><\/a>).\u00a0<\/span><\/p>\n

If teams don\u2019t fully embrace the values of the Agile manifesto, then applying methodologies like Scrum will be doomed to fail. Teams who are \u201cbeing agile\u201d embrace change, innovation, and learning and creating value as soon as possible.\u00a0<\/span><\/p>\n

<\/span>Keep Team Members Engaged<\/b><\/span><\/strong><\/span><\/h3>\n

To achieve your development and business goals, it\u2019s essential that everyone on the team find meaning in what they do and feel connected with the company\u2019s broader objectives. Without this, a high employee attrition rate may result, which will inevitably slow down development and negatively affect morale.<\/span><\/p>\n

To boost engagement, we\u2019ve been helping<\/span> each of our employees to create a roadmap<\/b>\u2014<\/b>a strategic plan<\/b>\u2014<\/b>to achieve both their personal and professional goals<\/b>. This transformative practice has given us the tools to gain greater insight into our employees\u2019 desires, doubts, and concerns they may have about their position. Thereby, we\u2019ve found new avenues to accommodate them and adapt to their needs, accompanying them every step along the way.\u00a0<\/span><\/p>\n

In the last year, we\u2019ve seen greater overall levels of employee satisfaction and, as a byproduct, a 75% decrease in turnover<\/strong> from the previous year. With less employee churn, we\u2019ve been able to improve the continuity of our testing services and better serve our clients, helping them release better quality software, faster.\u00a0<\/span><\/p>\n

<\/span>Achieve Quality at Speed<\/b><\/span><\/strong><\/span><\/h2>\n

Looking back to my question at the beginning of this post, in order to release a highly performant, reliable, and robust new product feature in less time than it normally would, what should teams do?\u00a0<\/span><\/p>\n

We\u2019ve found from our experiences that teams need to be empowered in three ways: by leveraging AI, implementing an efficient, automated CI\/CD pipeline, and building a great team with a strong culture around Agile and DevOps.\u00a0<\/span><\/p>\n

What are some other essential keys, in your opinion, to releasing the best software possible in ever shorter timespans?\u00a0<\/span><\/p>\n

\n

\"guide<\/a><\/p>\n

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<\/span>Recommended for You<\/span><\/span><\/h2>\n

White Paper: 8 Mistakes Companies Make When Transitioning to CI\/CD<\/a>
\nTesting as the Driver Towards a DevOps Culture<\/a><\/p>\n