Real test practitioners will show how test automation solved many of their quality issues when the Automated Software Testing and Quality one-day virtual event returns on May 16. Produced by software testing company Parasoft, among the topics to be discussed are metrics, how automation can significantly cut test time, shifting testing left, the use (or not) of generative AI, the synergy between automation and service virtualization, and more.

“We’ve worked really hard to make sure that most of the sessions are coming from the practitioner community,” said Arthur Hicken, chief evangelist at Parasoft. “So people are telling you how they solved their problem – what metrics they use to solve the problems, what the main challenge was, what kind of results they saw, you know what pitfalls they’ve hit.”

As for AI in testing, Hicken said Parasoft has created AI augmentations at every aspect of the testing pyramid, which he acknowledged is getting “kind of long in the tooth,” before adding that it still is useful, helpful advice. “Whether it’s static analysis, unit test, API testing, functional testing, performance testing, UX testing, we’ll talk about how these different things will help you in your day-to-day job.”

He went on to say that he doesn’t believe the things he’s talking about are job killers. “I think they’re just ways to help. I haven’t met any software engineer that says, I don’t have enough to do, I’ve got to pad my work with something. I think just being able to get their job done will make their life better.”

On the subject of generative AI, Hicken says it can be quite smart about some things but struggles with others. So, the more clearly you can draw the boundaries of what you expect it to be able to do, and the more narrow you can scope it down, AI just does a better job.

This, he said, is true of testing in general. “Service virtualization helps you decouple from real-world things that you can’t really control or can’t afford to play with,” he said. “Most people don’t have a spare mainframe. Some people interact with real-world objects. We see that in the healthcare space, where faxes are part of a normal workflow. And so testing becomes very, very difficult.”

Further, he said, “As we use AI to start to increase the amount of testing, we’re doing the permutations, we run into a data problem, we just don’t have enough real data. So it starts synthesizing virtual data. So the service virtualization is a way to synthesize data to get broader coverage. And because of that, there’s always a temptation to use real-world data as your starting point. But in many jurisdictions, real-world data is a pretty big no-no. GDPR doesn’t allow it.”

So, in the end, the question remains: How do you know it was worth it? What did you do to measure? Hicken said, “I don’t believe there’s a universal quality measure or ROI measure; I believe there are lots of fascinating different things that you can look at that might be interesting for you. So I would say look for that.”

Hicken also noted, humorously, that if test automation did not deliver value, the speakers he sought out for ASTQ would not have returned his calls. 

There is still time to register to learn more about automated software testing and Parasoft.

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Because of that, before you can even begin to measure how your team is performing, it’s critically important to understand your organization’s approach to development and how the teams are structured to maximize that effort.

“Finding good metrics, like flow metrics, end up being a balance between … do you treat what developers are doing as a manufacturing process? Or do you treat it more as a creative process?” said Jeremy Freeman, co-founder and CTO at Allstacks, providers of value stream intelligence software.  

Freeman referred back to the “Iron Triangle” approach to software development quality, which states that you can either develop things quickly, cheaply or at high quality, and everything between them is a tradeoff. 

This approach, he said, can also apply to flow metrics. 

Organizations can optimize more toward speed and predictability, or they can optimize toward data science and problem-solving. “These types of tradeoffs actually permeate all of your business decisions as technology leaders,” he said. “Do you focus on fixing quality? Or do you focus on fixing or shipping new features? And the flow metrics that are now a core component of the SAFe Framework end up having their own sorts of these ‘Flow Triangles.’ There’s your velocity, cycle time and team load. You always want to have really high-velocity routines. And that is intimately linked to how long it takes you to do things, and how many things are being worked on at once?”

Many high-functioning organizations have different teams working at different speeds, using different processes and tools, so coordinating that work is critical. “Thinking about flow metrics as a way to help make sure teams are working together is really important,” Freeman said. “If you imagine a team working on delivering a sprint goal, then you take a step back and think about how the collection of teams is working against shipping a major feature. You have to think about how fast things are getting delivered, and how that impacts your ship time. Are the levers you have to play with as a leader right? So these metrics are really helpful, and flow is really apt.”

Freeman recommends that organizations first figure out where their problems are, with the development team and all stakeholders. Then you can start measuring some coarse things around outcomes, and as you start identifying potential solutions, then you can get tighter and tighter with what you’re measuring. 

He noted that in talking to development teams, it seems like their biggest bottleneck is getting pull requests across the line. “There’s a high cycle time, no one will review my pull request, and that’s preventing us from actually shifting work,” he said. “In the pull request example,” he said, “maybe we’ll go from measuring your request cycle time to measuring how long it takes to get your first review, to know how long it takes you to actually complete any review cycle. And as you build those metrics up, you’ll actually get better information and start to pinpoint and solve problems.” 

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The company has mined 20 years of data on how software, operations and business teams plan, track and deliver work to give Atlassian Intelligence a “unique understanding of teamwork,” according to a company blog announcing the new tool. It is that understanding upon which a teamwork graph is built around both service-based work and project-based work.

Atlassian Intelligence constructs this teamwork graph that shows the types of work being done and the relationship between them – enriched with additional context and data from the third-party apps teams use, according to the blog. 

“Our mission is to unleash the potential in every team. I think with the emergence of artificial intelligence and generative AI technologies, this is a huge part of helping us accelerate teamwork. We think teamwork is going to continue to change drastically,” Sherif Mansour, head of product for Atlassian Intelligence, told SD Times in an interview. 

Atlassian Intelligence is a part of the Atlassian platform, and on the service side of things, integrates with Jira Service Management to help users resolve issues more quickly, by using large language models to gain context about and intent of each request. An acquisition last year of percept.ai, along with a partnership with OpenAI, has helped Atlassian power up its virtual agents with greater understanding by combining the company’s internal models with OpenAI models.

Mansour gave the example of a worker needing access to a particular system. “In this case, [the agent] says, ‘I think you need account access.’ But it also knows related information. So, in this example, people who request access to Figma also request access to Adobe Creative Suite. It knows this because the customer has modeled in their system that they have two request types – one for Figma and one for the Creative Suite. In that example, the user will say, ‘Just Figma, please.’ “

A capability built into Jira Service Management called intents enables the virtual agent to take the request further. “In this case, the intent is for account access. And once [the user] defines an intent, they can define specific steps for that intent. We need to know what role they’re going to need access to, an edit role or view role, and with the power of cross-product automation, and scripting, the customer has automatically allowed the AI to grant access to the system, because that’s the set of rules they have defined in this example.”

On the project side, Atlassian Intelligence can help resolve issues across all Jira Cloud products, such as requesting to see which mobile features are blocking an upcoming launch, by translating a natural language query to Jira Query Language. The results of that query, pulled from Atlassian and third-party tools, can be visualized and analyzed by the newly GA Atlassian Analytics BI reporting tool to provide insights into the progress of work.

The complete blog post can be read here.

New features in Confluence

Also at its Atlassian Team ’23 event today, the company announced updates to its Confluence knowledge base, introducing whiteboards and databases. Both are nearing beta release.

Noting that every product starts with an idea, Atlassian has created whiteboards in Confluence to enable teams to turn those ideas into actionable plans in Jira. Users can use sticky notes, a pen, or stamps and timers in a whiteboard, then convert those notes into Jira Cloud issues, the company explained in its announcement. Users can view relationships between issues, such as if one piece of work is blocking another, and assign out all Jira issues to engineers.

To join the waitlist for the beta, click here.

Confluence databases are built upon the acquisition of K15t to bring structured tables in which organizations can organize things like Jira tasks, Confluence pages, statuses and due dates into one table. “Imagine an HR team tracking multiple candidates throughout the interview process, marketing teams managing complex ad campaigns, sales leveraging the latest competitive intelligence, and IT coordinating employee equipment,” the company wrote in a blog post.

To join the waitlist for the beta, click here.

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People who converted to virtual interactions with their customers did well, and those who didn’t suffered. But to do so, and keep up with those virtual competitors, often meant exposing things before they were ready, or even fully thought out. That led to a lot of technical debt, yet still didn’t calm the need for speed.

If you look to the Facebook-type models of extremely rapid releases, you’d need a highly scalable infrastructure with a rigorous testing environment – which on its face seems anathema to digital transformation –  to give you the ability to rapidly stand things up to test, and to perform those tests.

So, with your business online and on the line, it’s almost impossible to keep testing at a pace the business needs to adhere to without employing automation.

So said Arthur Hicken, evangelist at test solutions provider Parasoft, in a discussion we had leading up to this week’s Improve: Testing conference – at which Hicken will be presenting a session.

“You have to do things right now, you’re testing, and you’ve got to have a high degree of automation,” Hicken told SD Times. “You’ve got to have a high degree of confidence in that automation. And you’ve got to make sure that you can do everything you can not just to find bugs, but you’ve got to stop creating so many bugs in the first place.”

Parasoft has supported rigorous testing efforts for years, in medical devices and other areas where safety is critical – what Hicken likes to call “planes, trains and automobiles.” And in that space, he said, organizations are kind of slow to adopt new practices.

“It’s interesting because what happens is that we see the enterprise market looking more at the rigor because they need that mission-critical reliability,” Hicken said. “And we see the safety-critical market where the volume of code is exploding, we see them adopting. I mean, agile is becoming the norm. It’s not the disruptors, it’s the market leaders. DevOps, containerization, lightweight tools, CI/CD have all become the norm.”

Parasoft this year has been positioned among the leaders in the Forrester Wave for Continuous Automation Testing platforms, showing both a strong product offering and a strong strategy. Hicken said Parasoft has been hyper-focused on AI augmentation – not looking to build an AI “silver bullet,” but looking at real problems people have with test creation, test execution and test maintenance. He calls these, “all the ways to reduce the effort on developers, especially tedious efforts. And to give them guidance for things that might not be obvious.”

It also involves “the ability to do self-healing, and the test impact analysis so that when you do make a change, and you’re worried about is this change that I made going to break my online infrastructure, that we can give you the exact correct set of tests that make sure that that functionality is working properly, no more, no less,” he explained.

At the end of the day, Hicken said, “when you’re looking for continuous testing tools, you’re looking for something that can solve an actual problem you have. You’re not looking for, say, a service virtualization tool; you’re looking for a tool that can help you test before other components are ready. You’re not looking for a UI automation tool; you’re looking to make sure that your tool isn’t going to break down when you release it.” 

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At its first DevOps-focused event – Unleash – today in Berlin, the company unveiled Jira Product Discovery. The company also announced the free integration of its Jira Work Management tool into Jira Software, and a new slant on its Jira Worfklow Templates – now designed by customers. According to Atlassian’s Agile solutions head of product Megan Cook, the integrations with the Jira Software suite helps organizations ideate, prioritize and jumpstart their efforts to deliver software that will make a real impact on the software’s users.

Jira Product Discovery, which is available today in a open beta for which customers can sign up today, was created to help organizations identify which new product features to build, based on research, customer feedback and internal prioritization. Cook pointed out that this traditionally has been an unstructured effort. “Software teams have efficient processes in place for building the software and managing it once it’s out there, and dealing with incidents,” she said. “But when it comes to discovery, that’s often been a bit of a black box.”

So decisions on what to build often are made in a vacuum, or driven by what Cook called “the loudest voice in the room,” rather than being about the outcomes the company needs to drive.

The interested parties – developers, product managers, marketers, executives – come into the room with their spreadsheets, backlogs, mental notes and emails, and debate and discuss and prioritize features together. 

But Atlassian believes it’s critical for all these teams to get aligned before any code gets written, to help ensure what will be built will achieve the organization’s goals.

Jira Product Discovery provides a dashboard into which all the ideas for a product can be viewed, and each idea is matched to a business outcome. It also can help with prioritization, based on data such as strategic value, user impact and more. “You can define anything that’s important to the team.. and the team can actually see which goal this [feature] is supposed to hit, how much impact to the users, and what does it rank in terms of advancing as a strategy?,” Cook explained. 

Because Jira Product Discovery brings transparency to the decision-making, all the roles around development can contribute to the product, each with their own diverse ideas. This, Cook noted, connects what was invisible about product development to the rest of the business, giving all stakeholders a view of all the ideas as well as the ability to rank the value of each, which leads to better decisions and better outcomes for the company. “So product managers can gather their team, they can set the impact and effort scores for each idea to see what will drive impact for the customer and the business,” she said.

When a product plan is agreed upon, this can all be connected back into the epics, projects and boards of Jira Software, so teams can build sprints or launch plans to achieve the goals they want to reach, Cook said.

Expected to be generally available within three months, Jira Product Discovery will be free for up to three creators, and above that it’ll be USD$10 a month per creator. 

Jira Work Management, a tool Cook described as “a project management tool for business users,” is now integrated into Jira Software, and is free for those customers until March 2024. The tool, which became generally available in April 2021, empowers organizations to plan, track and manage their work across the business and technical teams. 

According to the company’s announcement, “by utilizing both Jira Software and Jira Work Management, collaboration is streamlined, so businesses can ship features and market them while always staying in sync. Teams can visualize collaboration across development and business teams with cross-project dashboards and reporting or connect disparate tools together through first- and third-party integrations in the Atlassian ecosystem.”

Finally, released in Jira Workflow Templates today are custom workflows that, the company said, “take industry-leading best practices and turn them into templates, making it easy to swipe their playbooks, for free.” Jira templates are free for the entire Jira suite. “Every team can quickly get started managing their projects with Atlassian’s cloud products and partner integrations — many of which are built natively into our templates,” the company wrote.

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They were wrong.

The remainder of 2020 and 2021 were spent trying to figure out how to get an entire workforce to work remotely, while still being able to collaborate and innovate. Sales of cloud solutions soared. Much of the new software companies invested in required training just to get up to speed.

But training in the form of in-person conferences ceased to exist, and organizers sought to digitalize the live experience to closely resemble those conferences.

Fast forward to 2023. The software and infrastructure organizations have put in place enabled them to continue to work, albeit not necessarily at peak performance. Most companies today have figured out the ‘what’ of remote work, and some have advanced to the ‘how.’

But this move to a digital transformation has provided organizations with tools that can help them work even more efficiently than they could when tethered to an on-premises data center, and are only now just starting to reap the benefits. 

Thus, the editors of SD Times have determined that 2023 will be “The Year of Continuous Improvement.” It will, though, extend beyond 2023.

Bob Walker, technical director at continuous delivery company Octopus Deploy, said, “The way I kind of look at that is that you have a revolution, where everyone’s bought all these new tools and they’re starting to implement everything. Then you have this evolution of, we just adopted this brand new CI tool, or this brand new CD tool, whatever the case may be. And then you have this evolution where you have to learn through it, and everything takes time.”

Development managers, or a team of software engineers, or QA, have to worry about making sure they’re delivering on goals and OKRs, to ensure the software they deliver has value. So, Walker noted, “it’s a balance between ‘what can we do right now’ versus ‘what can we do in a few month’s time’? What do we have right now that is ‘good enough’ to get us through the next couple of weeks or the next couple months, and then start looking at how we can make small changes to these other improvements? It can be a massive time investment.”

Show me the metrics

Continuous improvement begins with an understanding of what’s happening in your product and processes. There are DevOps and workflow metrics that teams can leverage to find weaknesses or hurdles that slow production or are wasteful time sucks, such as waiting on a pull request. 

Mik Kersten, who wrote the book “Project to Product” on optimizing flow, holds the view that continuous improvement needs to be driven by data. “You need to be able to measure, you need to understand how you’re driving business outcomes, or failing to drive business outcomes,” he said. “But it’s not just at the team level, or at the level of the Scrum team, or the Agile team, but the level of the organization.”

Yet, like Agile development and DevOps adoption, there’s no prescription for success. Some organizations do daily Scrum stand-ups but still deliver software in a “waterfall” fashion. Some will adopt automated testing and note that it’s an improvement. So, this begs the question: Isn’t incremental improvement good? Does it have to be an overarching goal?

Chris Gardner, VP and research director at Forrester, said data bears out the need for organization-wide improvement efforts, so that as they adopt things like automated testing, or value stream management, they can begin to move down the road in a more unified way, as opposed to simply being better at testing, or better at security.

“When we ask folks if they’re leveraging DevOps or SRE, or platform methodologies, the numbers are usually pretty high in terms of people saying they’re doing it,” Gardner said. “But then we ask them, the second question is, are you doing it across your organization? Is every application being supported this way? And the answer is inevitably no, it’s not scaled out. So I believe that continuous improvement also means scaling out success, and not just having it in pockets.”

For Gardner, continuous improvement is not just implementing new methodologies, but scaling the ones you have within your organization that are successful, and perhaps scaling down the ones that are not. “Not every approach is going to be a winner,” he said. 

Eat more lean

Agile programming, DevOps and now value stream management are seen as the best-practice approaches to continuous improvement. These are based on lean manufacturing principles that advanced organizations use to eliminate process bottlenecks and repetitive tasks.

Value stream management, particularly, has become a new driver for continuous improvement.

According to Lance Knight, president and COO of VSM platform provider ConnectALL, value stream management is a human endeavor performed with a mindset of being more efficient. “When you think about the Lean principles that are around value stream management, it’s about looking at how to remove non-value-added activities, maybe automate some of your value-added activities and remove costs and overhead inside your value stream.”

Value stream management, he noted, is a driver of continuous improvement. “You’re continually looking at how you’re doing things, you’re continually looking at what can be removed to be more efficient,” he said.

Knight went on to make the point that you can’t simply deploy value stream management and be done. “It’s a human endeavor, people keep looking at it, managing it, facilitating it to remove waste,” he said. So, to have a successful implementation, he advised: “Learn lean, implement, map your value stream, understand systems thinking, consistently look for places to improve, either by changing human processes or by using software to automate, to drive that efficiency and create predictability in your software value stream.”

At software tools provider Atlassian, they’re working to move software teams to mastery by offering coaching. “Coach teams help [IT teams] get feedback about their previous processes and then allow for continuous improvement,” said Suzie Prince, head of product, DevOps, at Atlassian. In Compass, Atlassian’s developer portal that provides a real-time representation of the engineering output, they’ve created CheckOps, which Prince described as akin to a retrospective. “You’re going to look at your components that are in production, and look at the health of them every day. And this will give you insights into what that health looks like and allow you again to continuously improve on keeping them to the certain bar that you expect.”

Another driver of continuous improvement, she said, is the current economic uncertainty. With conditions being as they are, she said, “We know that people will be thinking about waste and efficiency. And so we also will be able to provide insights into things like this continuous flow of work and reducing the waste of where people are waiting for things and the handoffs that are a long time. We want to use automation to reduce that as well. All which I think fits in the same set of continuously improving.”

Key to it all is automation

Automation and continuous improvement are inexorably tied together, heard in many conversations SD Times has had with practitioners of the course of the year. It is essential to freeing up high-level engineers from having to perform repetitive, mundane tasks as well as adding reliability to work processes.

So whether it’s automation for creating and executing test scripts, or for triggering events when a change to a code base is made, or implementing tighter restrictions on data access, automation can make organizations more efficient and their processes more reliable.

When starting to use automation, according to John Laffey, product strategy lead at configuration management company Puppet (now a Perforce company), you should first find the things that interrupt your day. “IT and DevOps staffs tend to be really, really interrupt- driven, when I got out and talk to them,” he said. “I hear anything from 30% to 50% of some people’s time is spent doing things they had no intention of doing when they logged on in the morning. That is the stuff you should automate.” 

By automating repetitive little things that are easy fixes, that’s going to start freeing up time to be more productive and innovative, Laffey said. On the other hand, he said there’s not point in automating things that you’re going to do once a month, “I once had a boss that spent days and days writing a script to automate something we did like once a quarter that took 15 minutes. There’s no return on investment on that. Automate the things that you can do and that others can use.”

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According to Greg Brown, VP of global marketing at Melissa, ““Data quality touches every aspect of business, making it one of the most successful areas to shave dollars off the cost of customer outreach. Yhe deeper customer insight powered by smarter data not only helps marketers target their audience in more powerful ways, but also ensures that correct, standardized, and validated information provides the most cost-effective foundation to all outreach and campaigns.”

Melissa has created an ROI calculator that shows how data quality can save organizations money. An example is organizations mailing to 50,000 targets, but finding that 6,500 are undeliverable. In the physical world, using address verification to remove bad addresses can save a company $23,000 on postage and material costs. In the digital world, using an email provider such as Hubspot or MailChimp and email verification, companies can cut costs by reducing the number of mailings contracted for, and avoid getting a reputation as a spammer due to undeliverables and bounces.These steps can eliminate waste and lost opportunities from incorrect mailing.

Another example assumes an online shop sends 278 packages per day or nearly 100,000 parcels per year, with an average of 9% typically undeliverable. With address validation, mailers reduce undeliverable packages by 2/3. Return shipment costs are reduced by $40,000 annually, saving more than $570,000 in sales per year.

Further, Melissa said, matching and deduplication tools help establish a single, high-quality customer record linking all customer touchpoints for al 360-degree view of each customer. 

“All these benefits and cost savings are a direct result of data quality investments,” added Brown.

For more information on how to improve marketing costs through proactive, seamless data quality, click here to download Melissa’s Solutions Catalog. To connect with members of Melissa’s global intelligence team, visit https://www.melissa.com or call 1-800-MELISSA.

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Recent laws such as the General Data Protection Regulation (GDPR) instituted in Europe, and the California Consumer Privacy Act in the United States have put limits on collecting and sharing data without the person’s consent. And while enforcement at first was lax, more companies have been hit with fines for not following the regulation.

“The idea of GDPR is good, because the idea is to protect everybody’s personalized data, because you and me, you want to know where your data is used and why it’s used, where it’s coming from and what is recorded about you,” explained Cagdas Gandar, the managing director at the Germany office of data company Melissa. “Before, people had the liberty to just take that data and do whatever they want with your information.”

That, he added, is why there is GDPR. “It became the normal way of life for marketing companies, and for some companies, it meant also that they are not in business anymore – especially companies who collected data without any permission, or consent, and were selling this data,” Gandar said.

He did acknowledge that these regulations have been burdensome on a lot of companies, “and it has hurt them.” But the need for rules about how to collect and work with data overrode the need for marketers.

There seems to be a cat-and-mouse game between marketers and the public, in that marketers want to capture names, while most people just want to get the content without providing any information about themselves. One way to game the system is to input an incorrect name, such as “Mickey Mouse.” Another is to sign up for a disposable email address, which is only valid for 10 minutes or so – giving the person time to get the information they want without any way for the company to follow up with them. 

Part of this is due to the huge volumes of emails people get each day. With these restrictions on data collection and use, one would expect a decrease in the amount of emails people receive from marketers. And Gandar said he is seeing that in Europe.”Maybe you just want to read news or a whitepaper because you’re interested in a topic, but you want to decide by yourself when you want to get in touch with that company to get more information, so that the ball is in your court and you don’t get triggered from everywhere…Everybody calls, but it’s certainly a lot less.”

One way around this is through the use of a data minimization strategy. The idea is to collect just enough personal information to satisfy a request, and to keep the data only as long as it takes to fulfill that request. Beyond that, using personalization marketers can ensure that the people in their database are only receiving emails that align with the person’s expressed areas of interest. 

Unfortunately for many marketers, this will reduce the number of names they can put in their funnels – but the upside is that these are real people with real interests in the subject. Gandar said, “At the end of the day, if you ask for my perfect personal preference, I’d prefer 30 good leads to 270 that are not good. We have to just change our mindset a little bit, that it’s not about quantity anymore. It’s just about quality. It’s also more economical just working on 30, than working on 270 requests, prospects, or leads.”

The key to successful data utilization for marketing? Visibility and transparency, according to Gandar, who related this story. “There was this media house, where they also have different products, different magazines, where you can subscribe. And I thought, it’s really interesting, so I signed up for all of them. And I received a lot of emails, and then at one point, I couldn’t handle it anymore. And this is the problem of all the people, I think you’re getting just too many emails, you don’t have time to read it, and your mailbox gets too big. Then I went through to their website, logged in and clicked the opt-in option. And I could see all my subscriptions, which was really nice. And then I could decide what I want to still receive, and which ones I can unsubscribe from. So more visibility and more transparency was a really nice solution presented there.”

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Forrester research director for software development Chris Gardner spoke with SD Times editor-in-chief David Rubinstein to talk about what they’re seeing for 2023. This is a transcript of that conversation, edited for length and clarity.

SD Times: We’re here to kind of get a sense of what you folks are seeing coming up in 2023 for software development.

Gardner: There’s a couple different things that we’re expecting. We’re predicting five different things happening. The first prediction is that, since the development’s taken off in a huge way, we’re getting a tremendous number of questions around low code and no code, particularly from folks that are building applications for the first time. We are seeing a significant number of traditional developers also use low code, no code, and they’re running into their own challenges.

[Non-traditional developers] within organizations are given the access to the tools they need in order to do that development. And they are traditionally not given too much governance or too many constraints as to what they can use. What ends up happening is we’re seeing a number of folks that are building applications and aren’t really thinking about the security ramifications of them. They don’t really talk with their security team; they don’t really ask questions around application security or secure coding or data sensitivity. And what we’re seeing is the potential for a breach. So our prediction is that there will be a headline security breach coming out of citizen development in 2023. Most likely, it’ll be sensitive data that gets out that’s not supposed to get out. And to try to battle this, security teams need to set proper guardrails and review roles instead of proper governance. Those pieces will prevent them from necessarily having that breach. 

SD Times: Yes, that certainly mirrors what we’ve been reporting. So, what’s the second prediction?

Gardner: The second prediction is, API strategies traditionally have been brought about by IT. And that’s not going to stop. IT is big on building out API’s for connecting things like infrastructure and applications to one another. But what we’re seeing is increased interest in this from business leaders, specifically from folks at the C-level. Over 40% of API strategy is coming from the CEO, as opposed to coming from the CIO, possibly coming from boards of directors saying that they need business agility, they need to be able to manufacture, they need to be able to create connections between manufacturing systems, retail systems, automotive systems, so that ecosystem will be required to be created, or will be requested to be created by the C-level folks that are not necessarily in IT. And we’re expecting 40% of strategies will be led by those folks. So those are the people who are actually going to be working to set up the policies, run API’s, and they’ll be building out the ecosystems involved with them. So they’ll go back to the developers and say, here’s what I’m trying to do and trying to connect in terms of my workforce or in terms of my manufacturing, what I’m trying to build out. But it won’t be a situation where it comes up with these API’s on their own.

SD Times: There’s been a lot of talk about API’s now becoming the most vulnerable attack area for bad actors. 

Gardner: And that’s all the more reason why security needs to be involved in this conversation as well. Whenever we talk about API’s and to API taxonomies, and Forrester, we always bring the security and risk management folks into the conversation because it’s critical for them to own that and to shift that process of making sure the API’s are secured as far left as possible.

SD Times: And the third prediction?

Gardner: The third prediction is around the metaverse. So metaverse isn’t here yet, but everyone thinks it’s going to be here eventually. But there’s a lot of precursors, and there’s a metaverse standards forum that was started up this year that includes members across a wide variety of companies. However, they’re not necessarily in the business of implementing standards, they’re in the business of letting their member organizations come up with standards that the group itself can adopt. So what we predict is there’s going to be a number of competing API standards for the metaverse next year to connect between different worlds, almost as akin to how hyperlinks work to connect you around the web. But there will not be one standard. 

SD Times: Interesting. All right. And number four.

Gardner: Number four is value stream management. So we’ve found that since we started looking at this space around 2020, that value stream management has started to explode. There’s been a number of platforms and players that have come into fruition that are allowing folks to look at the entire software delivery life cycle from beginning to end and find places to remove bottlenecks and improve flow, and identify areas that would be great at contributing to business value. We’re expecting that 20% of enterprises will purchase a VSM solution in 2023. The enterprises that do adopt it, we expected to see a 50% improvement in release cadence and better alignment, delivering on core business goals. 

But it’s one of those things that up until recently, value stream management has been thought of mostly at the kind of strategy level; it’s not really been thought of at the developer level. And we’re seeing more and more folks adopted as a critical component of the developer life cycle and getting the most value out of it.

SD Times: And finally, number five.

Gardner: The final prediction is around WebAssembly. And WebAssembly is traditionally thought of to be used in web applications, like BBC’s iPlayer. And libraries like TensorFlow use WebAssembly for high speeds in the browser. What we’re going to find is WebAssembly is going to move to the edge in a big way, we’re already starting to see folks leverage WebAssembly to avoid runtime parsing that bogs down JavaScript at the edge. And at the edge, speed matters. Edge computing requires microseconds, not milliseconds. So we’re expecting that 30% of folks will use WebAssembly at the edge as opposed to web components. And of the compilers that are leveraged for it, which Rust is probably the strongest, it’s going to bring non-JavaScript developers to the edge. Rust itself is going to grow about 10%, in part because of its use of the edge. So edge is going to push development of WebAssembly and Rust in a big way in 2023.

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Part of the struggle is an outgrowth of the “shift left” strategy advocated in the DevOps space, leaving developers overwhelmed by tasks such as testing and security that they haven’t been trained for. This has led to a growing sense of developer dissatisfaction as they have less time to write the code for innovative solutions they love to create.

Further, with the rise of cloud native computing, developers in many cases are having to create infrastructure environments for testing, staging and pre-production, which further erodes the time they have to be creative.

When DevOps first came into being, it was thought that these practices could bring developers and operations teams together. In many ways, though, organizations simply shifted a lot of operations functions onto developers. Today, we’re seeing what D2iQ’s VP of Product Dan Ciruli called a “recentralization of control,” as the recently named platform engineering teams (which used to be called infrastructure teams) work to make developers more productive by standing up and running infrastructure for them.

Another trend seen in DevOps this year was around automation. Companies began implementing automation in their CI/CD pipelines, in testing and in identifying and remediating issues throughout the development life cycle. 

On the security side of things, a big trend in 2022 saw organizations creating software bills of materials (SBOMs). These help organizations understand what’s going into the software they’re creating, whether it’s code written in-house or an open-source or third-party component.

DevOps news items making headlines this year include the CD Foundation announcing CDEvents, a vendor-neutral specification for defining the format of event data; the partnership of Opsera and Octopus Deploy to create a no-code DevOps orchestration layer, and a Tasktop-Broadcom partnership to enable companies to better measure their business value.

Also, in March, Codefresh launched its Software Delivery Platform that brings the Argo toolset into a single platform, which the company described as “enterprise-class tooling for Argo, built on GitOps best practices.”

In July, Broadcom announced its plan to acquire VMware for $61 billion, though the deal had yet to be finalized as of late November. And in June, GitLab 15.0 was released with capabilities for  container scanning and speeding up workflows in the WYSIWYG Markdown editor for wikis. 

In the fall, the DevOps Institute, under the direction of Jayne Groll, announced SKILup IT Learning, a subscription-based online education website. The top tier subscription comes with certification preparation video training courses.

Also this year, SD Times published a four-part series from EPAM consultant Jack Maher and V.S. Optima co-founder Pavel Azaletsky explaining DevOps feedback loops. The first, which examines delayed feedback, and the rest of the series can be read here. 

Increasing interest in VSM

This year also saw the increase in both interest and offerings around value stream management.

Value stream management is being touted as a solution above Agile and DevOps that will finally bring the IT side and the business side together, working toward the same goals of delivering value to customers while continuously improving their operations.

According to a Forrester report earlier this year, the number of vendors offering products in this space has about quadrupled from its first report in 2017, when few people had heard of VSM. Now we’re seeing companies entering the space such as Broadcom, ServiceNow and Atlassian creating solutions, to go along with early players ConnectALL, digital.ai, HCL and Plutora.

In July of this year, portfolio management company Planview acquired early leader Tasktop to implement its Flow Framework into its products.

Also this year, SD Times produced its fourth {virtual} VSMcon event. One of the highlights was this talk – using events from the film “Ferris Bueller’s Day Off” –  titled, “If you don’t stop to secure DevOps as part of your VSM, you could miss it.”

And, in September, the OASIS open-source standards consortium created a Value Stream Management Interoperability (VSMI) Technical Committee to develop standards for how tools within the DevOps organization can share data between them, allowing for better insights and decisions.

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