devopsy.kinsta.cloud

Tag: Productivity

Nerd/Noir Allies With DX to Improve Developer Productivity

Nerd/Noir today announced it has partnered with DX, a provider of a platform for measuring developer experience, to identify areas where organizations can improve developer experiences in less than six weeks.

The consulting firm plans to leverage the DevEx 360 platform created by DX to survey developers before recommending a plan.

Nerd/Noir CEO David Laribee said that approach will make it simpler for DevOps teams to pinpoint where changes to workflows will have the most impact on 25 different key performance indicators (KPIs).

In addition, DevOps teams will be able to compare their results against more than 120,000 anonymized data samples collected across multiple industries and sectors.

There’s a lot of focus on developer productivity these days, largely because more organizations realize the extent to which they have become dependent on software to drive revenue and improve profitability. The challenge is organizations can’t afford to hire an unlimited number of developers, so many are now embracing platform engineering as a methodology for managing DevOps workflows at scale.

Most DevOps teams track metrics, but they are generally focused on software engineering issues rather than actual developer productivity. Measuring developer productivity tends to be a less exact science. Once upon a time, an organization might have tracked the lines of code being written, but the total number of lines of code written may not be especially good. In more recent times, metrics have been developed that, among other things, keep track of how much time developers spend actually coding versus maintaining their software development environment.

The issue that organizations are contending with is that more responsibility for managing everything from development environments to provisioning and securing cloud infrastructure has shifted, and the cognitive load that each developer is required to carry has increased. Every minute developers spend on these tasks, however, is, in theory, one less minute developers are potentially spending writing the business logic that drives an application.

Of course, there’s no way developers are going to write business logic for eight hours straight every day, so there are maintenance windows. However, application development is as much art as it is science. No one knows for sure when inspiration might strike, but if developers are busy maintaining code that they created to provision infrastructure, the less probable it becomes for some flash of brilliant insight into how an application might be made better is likely to occur.

DevOps teams need to strike a delicate balance. Developers like to be able to experiment with new tools and platforms, so any approach to platform engineering that smacks of totalitarianism will be resisted, and IT leaders need to proceed with caution. If talented developers start heading for the exits, IT leaders will find it difficult to replace them because great developers, even in an economic downturn, are still difficult to hire and retain. The challenge and the opportunity are to convince developers to embrace changes to workflows based on their input versus imposing one that benefits the DevOps teams more than the developers those teams are supposed to support.

January 9, 2024
The Ultimate Measure of Software Development Effectiveness

There is a famous quote by Peter Drucker that states, “You can’t manage what you can’t measure.” In our industry, measuring how quickly we can get working software into the hands of our customers has become a mantra for agile development teams, and it’s even being talked about in the boardrooms.

Customers measure the value of software by how quickly it can solve their problems. Customer needs change constantly. Just like us, they are responding to the needs of their own customers. Reacting quickly to customer feedback and turning that feedback into working features is key to customer satisfaction and retention.

Having these directives in mind, it’s no wonder our teams are being asked to deliver working software sooner. Often, the main roadblock in achieving this goal lies not in developing the features but in getting them deployed.

Let’s focus on three areas that determine your team’s deployment performance, which, in turn, directly impacts your software development effectiveness.

1. Frequency of Deployments

When I meet developers, I ask them a simple question: How often do you typically commit your code? A typical answer is a few times a day or even a few times per hour. However, if you ask the same person a question about how often their application is deployed to production, the answer varies widely.

Some will say weekly or daily or still – very rarely – even a few times a day, which is software development nirvana. However, a more common answer is monthly or quarterly. I’m also not surprised if someone says that they release annually. They say it with an honest level of pride and accomplishment.

Let’s put these two things – code commit and deployment frequency – into a broader perspective. If the goal of measuring software development effectiveness is getting working software into the hands of the users, it doesn’t matter how often you commit your code but how often you can give your users new value.

Delivering small improvements to your customers has more impact on client satisfaction than giving them a big gift (new release) once a year.

2. The Control of the ‘Launch’ Button

Triggering a deployment includes someone instructing a deployment, pushing a “deploy” button, or committing triggered deployments. How many people in your organization can promote the application to a production environment? If this privilege is limited to a single person or just a handful of people – we have a problem.

There are many reasons you might want to limit access to production. It could be because you don’t have safety measures built into your deployment process, such as role-based access control. You may believe in the delusion that you can protect your organization just by having fewer people with access to the production environment.

The reality is that artificially limiting user access to production significantly reduces your chances of deploying frequently. Imagine if the “person in charge” must take a sick day or is traveling. Remember that access to the production environment is also required for bug fixes when your organization applies a fix-forward versus rollback strategy.

3. The Level of Deployment Automation

Measuring software development performance is directly correlated to the level of process automation. You can’t manually deploy to hundreds or thousands of customers in a reasonable amount of time. The manual process does not scale, as time is the one thing we can stretch.

Ask yourself: Is your deployment process manual, partly automated (where parts of the process are automated, such as scripts that can be triggered to perform application deployment tasks), or can you claim that you fully automated your deployment process where there is no manual intervention, apart from push-button approvals.

The more you automate your deployment process, the more productive your development team can be. For complex deployments, you may need to target many customers, sets of infrastructure or even physical locations. You might need to apply different configurations or hit agreed maintenance windows for customers or regions. One way to accelerate software delivery for these scenarios is tenanted deployments.

Tenanted deployments capture these differences and apply them to a shared deployment process, allowing the complexity to be automated. You can manage tenanted deployments with tags, variables and customizations while reducing the cognitive load for team members.

There are many ways deployment frequency impacts software development effectiveness. When you deploy more often, you reduce deployment risk, increase quality and get feedback sooner. One action you can take to reduce batch sizes is to increase deployment frequency. Smaller batch sizes will also allow you to recover faster when a problem arises.

Remember that the longer the time between deployments, the more changes and points of failure build up.

As you think about ways to increase software development effectiveness, think about the deployment process as a way to get close to the ultimate measure of developer success–getting the working software into the hands of customers sooner!

To hear more about cloud-native topics, join the Cloud Native Computing Foundation and the cloud-native community at KubeCon+CloudNativeCon North America 2023 – November 6-9, 2023.

October 11, 2023
Using DORA Metrics to Measure DevOps Success

The DevOps Research and Assessment (DORA) metrics have fundamentally changed how leaders interact with developers—and, in turn, how developers interact with their code. Although these metrics have changed significantly since their introduction in 2014, their intent remains to provide a numbers-based approach to improving the developer experience.

DORA metrics play a critical role in many development workflows. These metrics posit that four focus areas—deployment frequency, lead time for changes, change failure rate, time to restore service and reliability—can differentiate high-performing software engineering teams (elites) from lower-performing teams (non-elites).

Why is this a meaningful difference? High-performing teams reliably achieve faster time-to-market by removing menial tasks from their workload and expediting the development and deployment processes. Elite teams provide a better customer experience, deploy robust code faster and maintain better availability. And engineering teams that codify their procedures and track using DORA metrics are more likely to achieve these results in a shorter time frame.

Why are DORA Metrics the Baseline for Many Developers?

Most departments have tangible objectives and key results (OKRs) to present to executives. For example, the finance department typically looks to achieve a certain revenue threshold, while the marketing department may report on social media traffic or engagement.

Software engineers have spent years grappling with how to demonstrate success to non-engineering departments. Although it’s relatively easy to identify when a deployment goes wrong, many developers have difficulty translating how these breakdowns occur. Engineering teams cannot generate buy-in for necessary process improvements or tool adoptions without the vernacular to discuss success benchmarks.

DORA metrics provide a language for developers to use when speaking with executives and other teams. Moreover, DORA metrics enable developers to understand their process’ weak points and identify areas for improvement internally.

Making the Most of DORA in 2023

It’s incredibly frustrating to fall short of development goals or hit roadblocks like post-deployment errors and bugs. DORA metrics are the secret to circumventing these challenges. Here’s how DORA can go beyond codification to help your team achieve quicker, more reliable development and deployment:

Accelerate Time to Market

Tracking DORA metrics can significantly curb a team’s time to market—a key competitive advantage in the fast-paced world of software development. Enterprises that deploy more quickly and frequently accrue greater revenue over time than less efficient enterprises.

A streamlined deployment process looks different from organization to organization. That is why DORA metrics are essential; they pinpoint each organization’s specific areas of improvement, enabling DevOps leaders to make informed decisions about remediation. Common indicators for lagging time to market include non-orchestrated deployment processes and manual testing procedures, which distract developers from what they do best: coding.

Leaders looking to isolate issues with time to market should scrutinize their organization’s deployment frequency, as this metric can indicate process inefficiencies. Deploying irregularly? Your team may be batching too many updates, leading to overloaded, riskier deployments. Alternatively, infrequent updates may mean your organization has outgrown manual deployments. If that’s the case, consider adopting continuous integration and deployment (CI/CD) processes—these offerings improve time-to-market through immediate feedback and automated testing. Successful CI/CD implementations are proven to increase daily deployments by over 1000%.

Improve Development Processes

Although highly interconnected, deployment and development delays stem from different issues. Think of it this way: Low-performing engineering teams might deploy frequently—several times a day, even—but without quality assurance, those deployments are likely erroneous and may lead to extended system downtime.

DORA metrics are a powerful way to isolate deployment issues from gaps in the development process. For example, an engineering team that tracks DORA may find their deployment frequency optimal, but their time to restore service and change failure rate lagging. This discrepancy indicates the team needs to improve its testing practices by rigorously reviewing code and managing application dependencies better. Additionally, the team should consider implementing more advantageous deployment and rollback processes, including but not limited to progressive deployments and automated rollbacks.

Remove Menial Tasks From the Workload

Some organizations approach DORA metrics and other OKRs as productivity benchmarks that can be wielded against individual engineers. This perspective has even tinged how many developers view DORA metrics. Yet Google research demonstrates DORA metrics are most successful when adopted by high-trust, low-blame cultures. In these enterprises, DORA metrics reveal organizational opportunities for improvement—never should they reveal lagging individual performers or provide reasons for unnecessary busy work.

In fact, DORA metrics often eradicate rote tasks from developers’ workloads. Teams that use these metrics to identify and implement better incident management processes spend less time fighting fires (e.g., reworking code after a costly manual rollback) and more time doing higher-value work, like building new experiences. Automated processes like automated rollbacks and CI/CD empower developers to improve the quality of individual deployments while also reducing stress

Make DORA Work for Your Engineering Team

DORA metrics aren’t going anywhere soon. While they continue to evolve, like the recent removal of the elite category, they remain the industry standard for engineering OKRs, they provide a robust framework for success and a common language for developers and non-engineering stakeholders to communicate about performance, challenges and improvements in the software development process. DORA eases the collaboration and decision-making processes, creating an environment where leaders can consistently and effectively make data-driven improvements.

But these improvements are only possible when engineers are empowered by beneficial processes and tools. I encourage leaders who implement DORA metrics into their benchmarking to take results seriously. Is your organization’s time to market lagging? Interrogate your current developer workflow—and actively take steps to address issues through developer-first solutions. Doing so will not only improve your organization’s software delivery capabilities but also foster a culture of continuous learning and improvement.

October 10, 2023
Roadie Adds Scorecard Tool to Backstage SaaS Platform

Roadie today made generally available a tool that automatically tracks and reports how software development teams are performing against engineering standards defined by a DevOps team. The Tech Insights tool is an addition to Roadie’s implementation of the open source Backstage developer portal and is delivered via a software-as-a-service (SaaS) platform.

Roadie CEO David Tuite said Tech Insights is a proprietary tool that Roadie developed as an extension to its platform. Tech Insights provides scorecards that track software assets in the Backstage catalog and ensure they are meeting predefined quality and compliance targets.

Tech Insights comes with built-in, pre-defined data sources; alternatively, DevOps teams can define them using external application programming interfaces (APIs) or files in a repository. A rule known as a Check can then be created to validate whether a project complies with the engineering standards defined by the DevOps team. Each DevOps team can create an unlimited number of scorecards.

In addition, teams can create prompts and notifications to warn engineers when they are about to make a change that will violate an engineering standard. DevOps teams can also employ gamification techniques to show teams how their performance compares to others.

While Roadie is now adding its first proprietary tool to the platform, Tuite said the company remains committed to enabling organizations to migrate their instance of Backstage to another environment should they ever deem it necessary, he added.

Originally developed by Spotify, Backstage makes it possible to create and manage a catalog of blueprints that developers can readily consume rather than requiring them to repeatedly build these capabilities themselves. The goal is to create scaffolds that developers can consistently reuse across multiple application development projects.

Spotify has since donated Backstage to the Cloud Native Computing Foundation (CNCF). However, Backstage currently requires a significant amount of DevOps expertise to set up and maintain, an issue that Roadie is addressing by making it available as a SaaS platform that can be accessed by any application development team, said Tuite.

The concept of a self-service portal through which developers can address their own needs may not be new, but as an open source project, Backstage is lowering the cost of improving overall developer productivity. At the same time, many organizations are now embracing platform engineering as a means of centralizing the management of DevOps.

Ultimately, every minute developers spend on tasks other than writing code is one less minute they are spending writing the business logic that drives an application. Measuring developer productivity is, of course, an inexact science. No one knows for sure when inspiration might strike, but if developers are busy maintaining code that they created to provision infrastructure, it’s less likely they’ll be struck by a flash of brilliant insight that improves and application. The easier it is to spin up a development environment, the more likely that inspiration will one day turn into code that runs in an actual production environment.

July 11, 2023
92% of Devs Use AI, Survey Says ¦ Intel One Mono Font

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: GitHub touts unbelievable AI stats, and Intel’s beautiful open source typeface. (more…)

June 15, 2023
A Supportive Engineering Culture is Key for Recruiting and Productivity

Skilled engineers are in high demand, as their ability to build new products quickly is extremely valuable for businesses competing in a tight market. Strong engineering talent allows businesses to increase productivity and meet customer demand faster, which is essential for long-term success. However, in the current economic context, companies are being forced to reduce spending while trying to achieve the same results. This means engineers have fewer resources available to achieve their goals–increasing the pressure on their role. At the same time, engineering talent remains a valuable asset; in the UK, for example, just under half (49%) of engineering businesses struggle to find workers with a sufficient skillset for the job.

So, businesses must find a way to attract and retain talented developers while ensuring they feel supported through challenging times. A vital step to achieving this is creating a workplace culture that promotes developer satisfaction. Below, I explore how businesses can create a positive working environment for engineers, make transparent decisions and ensure their teams feel supported – to create a culture where developers want to stay and supercharge business performance.

The Key Pillars to Creating a Positive Culture

Leaders of all stripes are tasked with ensuring that their employees are supported, engaged and motivated to do their best work. However, the route to achieving these outcomes can sometimes seem vague and elusive.

Research shows that there are several key pillars for creating a strong organizational culture. The first is psychological safety. Developers must have the freedom to take risks without the fear of being criticized. Software engineering is an industry in which professionals must be creative enough to be able to create something out of nothing, so it’s important that companies ensure developers have the space they need to experiment and try new approaches.

Secondly, dependability is essential. Developers are more likely to produce high-quality work in a timely manner if their employer believes in them and their abilities. Developers often face immense pressure to ship functional code on a daily basis; feeling trusted can give them the confidence they need to take on more responsibility and drive projects forward. Alongside this, it’s the leader’s role to ensure developers have a very clear and structured mission. They must know exactly the goals they’re aiming to achieve, the part they’re playing in reaching these goals and the plan for execution.

Finally, ensuring developers understand the meaning of their work and are fully aware of the impact it has is an important pillar for cultural success. Sometimes, software engineers spend a huge amount of time on small fixes and updates that may seem insignificant. Business leaders must make efforts to communicate the importance of developers’ work and the value they bring to the business. If developers feel valued and rewarded for their difficult work, they will be more motivated to commit themselves to their mission and stay at the organization.

When engineering teams are happy and supported, they are also more likely to speak highly of their organization and encourage other developers to join the team, helping the company build a strong pipeline of engineering talent.

Making Transparent Decisions Using Concrete Data

Transparency is another crucial element to ensure engineering teams are happy and motivated to do their best work. Developers can’t do their jobs effectively if they don’t have insight into the workflows on their teams or don’t have context into decisions that impact their ability to perform effectively.

With tools such as software delivery intelligence platforms, developers can see the positive impact of their contributions and how they’re helping the business succeed. These tools also enable engineering managers to rely on concrete data to celebrate developer progress on previously invisible work and show how their work contributes to wider business success. This helps developers gain more autonomy to achieve the company’s goals, and eventually create better business outcomes.

For example, Manulife adopted an engineering analytics tool to create an engineering culture that is based on trust and transparency. The concrete data generated is used to analyze engineering processes and highlight talent that may have remained hidden without a data-driven approach. Data also helps managers decide who within the team deserves to be promoted based on precise insights into everyone’s contribution.

Use Data to Help Overcome Complex Challenges

The mission of developers is constantly evolving, with new technologies, programming languages and methodologies changing very quickly and making the job more complex over time. It is up to engineering leaders to help their teams remove potential barriers that are blocking them from being successful in their roles.

With data-driven insights, engineering leaders can better support and uplift their teams. Data about engineering workflows allows leaders to understand exactly where bottlenecks exist and remove them quickly before slowing their projects down. This means that employees can learn what worked–or didn’t work–from one project to the next, as well as develop the necessary skills to remove roadblocks to future success.

Timelines and targets for projects set by business leaders can also then be tailored to each person’s abilities and based on concrete data that show where they can boost efficiency to ensure everyone produces their best quality work and remains engaged and motivated.

In the current technology industry, employee culture is one big factor determining where developers wish to work. In a context where engineering talent is in high demand, it’s the job of every organization to create a stellar work culture to attract and retain talent.

May 8, 2023
Atlassian Embeds Generative AI Across Cloud App Portfolio

At its Team 23 conference today, Atlassian announced it is adding an artificial intelligence (AI) capability to the enterprise editions of its cloud portfolio to automate a wide range of routine tasks.

Sherif Mansour, distinguished product manager for Atlassian, said Atlassian Intelligence uses natural language to drive a virtual agent that resolves routine help desk issues from within Slack or Microsoft Teams. Atlassian Intelligence can also identify incidents that have been previously resolved along with issues that are related to one another.

In addition, IT teams can also leverage Atlassian Intelligence to create summaries for projects being tracked using the company’s Jira project management software, noted Mansour.

The overall goal is to streamline incident management processes while also making it simpler for application stakeholders to collaboratively participate in software development, he added.

Generative AI capabilities are likely to be infused into almost every imaginable application going forward, but Atlassian is clearly at the forefront of an effort to leverage AI to improve productivity. For example, instead of spending time handling routine issues that increase the amount of daily toil, IT teams should be able to spend more time resolving more complex issues, noted Mansour.

The cumulative effect of AI should result in a significant decrease in the backlog of tasks that many IT teams would otherwise have to manually perform, he noted.

It’s not clear just yet how much generative AI will impact the way software is developed and how IT is managed, but it’s already apparent that fundamental change is on the way. The Atlassian Intelligence approach is intended to augment the capabilities of IT teams so they can do more with the same number of or fewer personnel.

The challenge IT teams will face is identifying tasks they couldn’t previously accomplish simply because there wasn’t enough time available.

Fundamentally, generative AI changes the way humans interact with machines. Instead of requiring a developer to create a level of abstraction to communicate with a machine, it’s now possible for machines to understand the language humans use to communicate with each other. That makes it possible for anyone to make use of large language models used to create generative AI platforms to, for example, automate a routine task or, one day soon, create code.

At this point, like it or not, the generative AI genie is out of the proverbial bottle. Just about every job function imaginable will be impacted to varying degrees. In the case of IT organizations, the ultimate impact should involve less drudgery as many of the tasks that make managing IT tedious are eliminated.

Hopefully, as IT continues to evolve, there will still be plenty of demand for human expertise. For better or worse, the nature of the expertise required, however, will undoubtedly be at a much higher level than it has been for the past four decades or more.

April 19, 2023
Don’t Make Big Tech’s Mistakes: Build Leaner IT Teams Instead

One of the biggest narratives in the U.S. concerning the current wave of tech layoffs is the fact that ‘traditional’ sectors have a prime opportunity to snap up new tech teams and IT talent. This has always been a significant challenge for sectors such as banks, insurance and manufacturing that compete with big tech for talent. In 2022, a majority of CEOs (71%) identified skills and labor shortages to be that year’s biggest business disrupter.

And they were right to be worried. According to Salesforce, three in four workers do not have the digital skills needed by businesses to prepare for the future of work. The temptation in this environment for many traditional organizations is to enter the labor market to build larger tech teams to help drive their modernization programs. However, this may be a mistake.

Building large, expensive, bloated tech and IT teams is not always the answer. It’s critical that traditional companies learn this lesson from big tech.

Instead, traditional organizations should consider other avenues to drive their digital transformation ambitions with their lean resources. What does this look like?

What is the Real Challenge you are Trying to Solve?

Since COVID-19 hit, U.S. companies have been forced to reevaluate how they work, with remote working becoming commonplace–even for companies who couldn’t imagine themselves working remotely.

And the challenges have grown as U.S. businesses seek growth to recover lost gains from the last few years. Evanta’s 2022 CIO Leadership Perspectives study found that CIOs rate data and analytics as their second top priority within the IT function. It is clear that business leaders see advancing organizational use of data, analytics and automation as key to reaching enterprise objectives.

For many organizations, the biggest challenge they face is the unprecedented amount of data generated. Critically, more than 80% of all new data is unstructured and messy. This makes it difficult for data-driven companies to accurately review, gather, analyze and rely on what is mission-critical information.

Traditional industries such as health care, banking, insurance or the public sector, have even larger concerns because data is increasingly critical to how they build value and deliver services for customers. So, it is important for their IT teams to create a single source of truth and data governance framework across their organizations to ensure the right people and senior leaders have the most accurate information to make smarter decisions.

For instance, in the manufacturing industry, no-code database platforms can be leveraged to structure daily operational data and visualize insights through digital dashboards for quality assurance, continuous improvement and health safety.

Additionally, at Baserow, we work with treasury customers at some of the biggest international banks that use no-code platforms to keep track of local legislation around the world by centralizing information in real-time databases available to relevant teams, including compliance.

Modern organizations depend on their IT teams to accomplish a lot of their goals. So, it is important to provide them with the tools to focus on more complex development projects. No-code tools free your non-technical teams to address their pressing needs themselves without having to wait for budget or resource availability in the IT department.

Have you Also Considered Upskilling Your Current Team?

We know from the Salesforce survey that the vast majority of U.S. workers lack the digital skills to support their organizations’ ambitions and needs. This suggests that there is a wider issue within most companies at large. Do businesses need to prioritize upskilling their current team instead?

A U.S. Gallup report found that 72% of workers are overwhelmingly interested in pursuing additional digital training to prepare them for an increasingly digitilized workplace. Is there room for no-code technologies to supplement the digital capabilities within companies?

Enterprises are already expanding the responsibilities of application development outside their IT teams as well as increasing the productivity of their existing IT resources by automating and abstracting repetitive developer tasks. Gartner predicted that by 2025, 70% of apps will employ low-code/no-code technology. This trend aligns neatly with the business needs, such as the development of organization-specific applications and tools, because every business’s requirements are different.

Furthermore, no-code/low-code technology enables companies to drive innovation and shorten the idea-to-market cycle times. The technology’s pre-built components make it easier for end-users and workers to intuitively assemble the templates that solve their complex needs.

In Conclusion

U.S. companies that need to fill the IT skills gap should consider how technology can be leveraged to boost productivity and accelerate the speed of innovation while accepting that new technical resources will continue to be expensive and scarce.

These organizations are better off taking the lead in the democratization of IT within their teams. Only then can they keep up with the speed and agility required in today´s competitive environment.

March 27, 2023
Boosting DevOps Productivity Requires Visibility, Automation

Engineering teams continue to struggle with roadblocks and bottlenecks during the development process, according to Software’s recent 2021 Code Time Report.

The study, which is based on feedback from more than 250,000 developers using the Code Time plugin, found the median code time per developer is 52 minutes per day, or four hours and 21 minutes of code time per week.

The data also revealed that only about 10% of developers spend more than two hours per day coding, including on weekends, while about 40% of developers spend more than one hour per day coding.

The study also indicated developers are battling distractions that range from too many meetings and too many interruptions to too much wait time on processes and systems.

Distractions, Disruptions and Meetings Dog DevOps

The conclusion was most companies ineffectively deploy their development and DevOps teams, bogging down engineers with distractions, disruptions and meetings as well as system inefficiencies, such as slow reviews, slow builds and bad tools.

Software’s CTO Mason McLead said based on the company’s estimates, developers spend an additional 41 minutes per day on other types of work in their editors, such as reading code, reviewing pull requests and browsing documentation.

“The key to ensuring the highest levels of productivity from DevOps teams is visibility,” he explained. “We’re all biased toward focusing on what’s readily apparent, but the biggest bottlenecks are often hard to find and difficult to measure.”

McLead said by improving visibility across the entire development life cycle in a way that measures system-level metrics and not individual performance, DevOps teams can focus on the biggest constraint and have a more meaningful impact on their team’s productivity.

He said one example of a productivity metric with hidden barriers is lead time.

“I’ve spoken with many managers who disproportionately focus on how long it takes to review pull requests as a key lever to minimize lead time,” he said. “However, there are many stages in releasing a new feature that might actually be the key constraint—for instance, how long it takes to test and validate changes in a staging environment, or how long it takes to release merged pull requests to production.”

While these stages of lead time are all measurable, McLead explained most DevOps teams don’t have a data pipeline or BI tool set up to measure them.

He added that once an organization can diagnose the key constraint, it’s a lot easier to come up with an effective solution to minimize that constraint.

For example: If pull requests are taking a long time to create, are tickets being properly scoped? Can you see a correlation between the size of the pull request and the time it takes to be approved and merged?

McLean pointed out that if pull requests are taking a long time to be reviewed, it is critical to ensure proper expectations are being set.

He added it’s important to determine if there is a system in place to remind reviewers and enough time set aside in the day to perform the review.

“Taking steps to further automate deployment processes are another potential fix if it currently takes a long time to deploy a change to production,” McLead said. “It really all comes down to being able to measure the top constraint so that you know where to spend your time.”

Remote Work and Visibility

Remote work is also expanding the role of traditional DevOps teams: The trend toward more flexible working styles will demand more investments in DevOps such as secure provisioning of remote infrastructure, better access management and improved developer onboarding to better enable productivity for development teams.

“Visibility into how your DevOps investments are making an impact will play a big role in the decision on whether to stay remote or return to the office,” McLead said.

He added one way to attract and retain a highly productive DevOps team is to show that your DevOps investments are paying off.

“I recently talked to an engineering manager whose team wasn’t getting features out fast enough,” he said. “It took a month on average to complete a ticket, which had a significant impact on their ability to move major roadmap items forward.”

He explained that by implementing measures to improve throughput (e.g. investing in CI/CD, reducing build times and improving test coverage), they were able to decrease lead time from one month to four days.

By setting up a data pipeline and BI tool and increasing visibility, the engineering manager was not only able to report on metrics to his executive team and board with confidence, but also boost morale on his team.

From McLead’s perspective, retaining talented and trained DevOps engineers is critical because many DevOps projects require a longer timeframe in which to implement and measure their success.

“Highly effective DevOps teams measure not only how their investments are improving efficiency in the short-term, but also how changes in throughput and productivity are trending over months and years,” he said. “If your team is experiencing high turnover, it’s even more difficult to consistently deliver results over these longer time frames.”

March 1, 2022
Empowering Developers Through Lean Code
Digital transformation is widely understood as a critical component for increasing user adoption, fueling workplace productivity and innovation, and driving business growth. Software has become increasingly important across countless industries, teams, and functionalities, and as a result, companies are beginning to understand that being an industry leader and gaining competitive advantages starts with software development.

Easier said than done. Modern software apps are a complex orchestration of infrastructure, deployment pipelines, notifications, user experience, data filtering and processing, and error handling. A good engineering team will be able to account for each of these items and integrate them into a larger, comprehensive infrastructure.

So what happens when you don’t have a solid, in-house team guiding your software maintenance and development? Consider a lean code development platform; a developer service that pares down the explicit requirements of standard functions, interactions, errors and software infrastructure into implicit scripts, templates, configurations and API requests. Using a lean code solution will give your team the power to build higher-quality features more quickly than they otherwise would on their own.

There are several ways that lean code platforms can simplify processes for developers. Primarily, these platforms turn explicit requirements into implicit interactions, eliminating the need for developers to pull elaborate infrastructure to solve complex problems. Lean code also gives developers the freedom to customize everything to fit where it is needed, while limiting the amount of code necessary to do so. Lastly, lean code platforms provide tools that assist developers at all levels of the software stack, significantly increasing productivity while cutting down on time and workload.

How Does it Differ from Low-Code?

While many people might be unfamiliar with the term “low-code,” they’d probably be surprised to learn that they use it all the time. Low-code describes platforms that require minimal code in order to build applications and processes.

Essentially, these programs enable users with little to no coding or software development experience to create and use applications. The idea of low-code is to introduce audiences to intermediate level software development concepts such as object-oriented programming, interface design, conditional logic and code syntax.

However, no matter how helpful these low-code approaches might be, many users still run into the problem of wanting more customization than the low-code system is designed to give. In fact, many users become frustrated with the term “customization” because it’s viewed as the enemy, indicating a need for more advanced software development services than the consumer is able to provide.

Lean code platforms, on the other hand, are designed to specifically meet developers’ needs at all stages of the software development life cycle. In essence, lean-code prioritizes simplicity, efficiency, flexibility and accessibility with the goal of making software development accessible on a larger scale.

Instead of encouraging you to reduce your development team, lean code platforms allow users to expand development through exploring new avenues and abstracting away the explicit requirements of traditional software development.

What Does Lean Code Have to do With Productivity Infrastructure?

Many forward-thinking companies have gone beyond simply building technical solutions to specific development problems. Instead, they’ve taken the advancement of lean code platforms to a new level by providing fixes that meet developers at the central stages of the integration process.

Because lean code offers such integrated solutions to developer challenges, the approach is increasingly becoming the norm across the bulk of the productivity infrastructure category — an emerging market category that combines elements of cloud communications services, API platforms, low-code development tools, business process automation and AI software development kits.

If you’re looking to implement a lean-code platform, consider the following features:
- Intelligence: By making it easy to pull information from unstructured data sources and flip it into more meaningful material, machine learning (ML) replaces the manual effort to build, implement and maintain models.
- Automation: Workflows, triggers, templates and notifications can be abstracted away for common use cases.
- Security: When handling user data, security is a top priority. From protecting health records to pet names, data security is crucial.
- Connectivity: The ability to connect to a relevant data source can make or break an infrastructure.
- User experience: User interfaces should follow expected conventions for whichever task the user is trying to accomplish. Maintaining a successful user experience requires constant evaluation.
How will Lean Code Become Market-Leading Software?

Lean code development platforms have emerged as market-leading software development solutions in three major areas:
- Productivity Infrastructure: More companies have pivoted to providing full-stack development services that assist developers in building out native communications, search and indexing, scheduling and financial experiences.
- Software development and deployment workflows: Continuous integration/ continuous deployment (CI/CD) pair down complex build and deployment pipelines to basic configuration files.
- Infrastructure deployment: Infrastructure as a service (IaaS) products assist in deploying scalable web services via API requests and simple configurations.
Where are lean code development platforms headed?

It’s safe to assume that, given their ability to provide efficient and effective infrastructure to development teams, lean code has a bright future ahead. The number of developers in the space is only growing. A Slash Data survey from 2019 estimated there to be just under 19 million active developers across the globe and expected the number to grow to 45 million by 2030.

As the market for software development rapidly expands, it would make sense to assume that the need for a platform that solves problems across the entire software ecosystem would, too. Lean code development platforms are emerging as a top choice for companies that want to build out a leading software platform into the future.
May 7, 2021