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Low-Code/No-Code in Microsoft 365: How Power Platform is Redefining Enterprise DevOps

Low-code and no-code platforms have moved well beyond their early perception as tools for lightweight departmental apps. Today, they play a strategic role in enterprise DevOps, helping organizations modernize legacy systems, automate business processes, and deliver solutions at a pace traditional development models often struggle to match.

Within the Microsoft ecosystem, the Power Platform — Power Apps, Power Automate, Power BI, and Dataverse — has emerged as a mature, enterprise-grade low-code framework. Deeply integrated with Microsoft 365, Azure, and security and governance services, Power Platform is redefining how organizations think about application development and operations.

Why Low Code/No Code Matters in Enterprise DevOps

Modern enterprises face mounting pressure to deliver faster while managing growing technical debt, resource constraints, and increasingly complex compliance requirements. Traditional development pipelines often result in long backlogs of automation and application requests, especially for internal business processes.

Low-code and no-code platforms address these challenges by reducing development cycles from months to days, enabling business users to participate in solution design, and allowing IT teams to focus on architecture, governance, and scalability. However, the true value of these platforms emerges only when they are implemented within a structured DevOps and governance framework — rather than as isolated shadow IT tools.

Power Platform as an Enterprise Application Framework

What differentiates Power Platform from many low-code tools is its enterprise foundation. It is not simply a rapid app builder, but a unified platform designed to support secure, scalable, and governed application development.

Power Apps enables teams to rapidly build business applications using visual design and declarative logic. These apps commonly support approval workflows, request systems, data entry, and mobile workforce scenarios. With Dataverse and SharePoint as underlying data sources, Power Apps supports structured data models, role-based access, and enterprise authentication.

Power Automate serves as the automation backbone of the platform. Organizations use it to orchestrate approvals, synchronize data across systems, integrate SaaS and legacy platforms, and implement robotic process automation where APIs are unavailable. From a DevOps perspective, Power Automate introduces event-driven automation that reduces manual intervention and improves reliability.

Power BI completes the loop by providing real-time visibility into operational performance. When combined with Power Apps and Power Automate, analytics move beyond reporting to drive immediate action, enabling data-informed decision-making across the organization.

Low Code and DevOps: Complementary, Not Competitive

A common misconception is that low-code platforms bypass DevOps practices. In reality, they extend DevOps into areas traditionally underserved by software engineering teams.

Enterprises increasingly apply CI/CD principles to Power Platform solutions by separating environments, packaging solutions, integrating source control through Azure DevOps or GitHub, and automating deployments. Environment variables and configuration management ensure consistency across development, test, and production environments.

Governance and security are first-class concerns. Power Platform integrates with Microsoft Entra ID, Conditional Access, Data Loss Prevention policies, and Microsoft Purview. These controls allow organizations to scale low-code adoption without compromising security, regulatory compliance, or data protection standards.

AI and Copilot: Accelerating Low-Code Development

The introduction of Microsoft Copilot represents a significant shift in how low-code solutions are created. Copilot enables natural language generation of apps and workflows, assists with formula creation, and accelerates onboarding for non-technical users.

Rather than replacing developers, Copilot acts as a productivity multiplier. Architects and engineers can focus on system design, governance, and optimization while business users contribute more effectively to solution creation.

Real-World Enterprise Impact

In large organizations, Power Platform is now used to automate procurement and finance workflows, modernize SharePoint-based legacy systems, streamline external user access, and deliver executive dashboards. When implemented with proper governance, these solutions evolve into long-term enterprise assets rather than short-lived departmental tools.

Challenges and Best Practices

Despite its advantages, low-code adoption introduces new challenges. Uncontrolled app sprawl, inconsistent data models, and a lack of lifecycle management can quickly erode value. Successful organizations establish clear governance models, define environment strategies, implement Centers of Excellence, and foster collaboration between IT and business teams.

Conclusion

Low-code and no-code platforms like Microsoft Power Platform are reshaping enterprise DevOps. When combined with cloud architecture, DevOps discipline, and AI-driven assistance, they enable organizations to deliver solutions faster without sacrificing control.

The future of software development is not about replacing engineers, but augmenting them. Power Platform exemplifies this evolution, bridging business needs and technical execution in a scalable, secure, and intelligent way.

May 21, 2026
VibeCode Meets DevOps: Accelerating Low-Code Innovation
AI-assisted low-code platforms like VibeCode are generating a lot of excitement. They let users describe applications in natural language and produce working code quickly. This speed is impressive, but it raises questions for DevOps teams responsible for stability, security, and reliability.

DevOps has always focused on delivering software faster while keeping systems stable. Low-code and AI-assisted tools change how teams reach those goals. When non-developers create applications or workflows, DevOps practices must adapt to maintain quality and governance.

Understanding the Landscape

Low-code platforms provide visual interfaces and pre-built components, allowing technical and non-technical teams to build applications quickly. They often include ways to add custom logic and integrate with version control systems.

VibeCode-style tools take this further by generating full source code from text prompts. They blur the line between code and no-code by producing deployable code automatically. Unlike traditional low-code platforms, they do not always include structured lifecycle management, which places more responsibility on DevOps teams.

DevOps Challenges with AI-Assisted Development

Quality and Reliability
AI-generated code can work immediately but may have hidden issues. DevOps teams should treat it like any other source code, applying testing, code review, and quality gates before deployment.

CI/CD Integration
Some low-code platforms include visual tools for automating CI/CD workflows. VibeCode-generated applications may require manual setup to connect to standard CI/CD pipelines. Teams can use tools like GitHub Actions or GitLab CI to ensure builds, tests, and deployments are automated and consistent.

Security and Governance
Allowing broad groups to generate applications can lead to fragmented development outside central oversight. DevOps should enforce standard practices, including secrets management, static analysis, dependency scanning, and vulnerability testing.

Collaboration Between Developers and Citizen Builders
Low-code and AI-assisted tools enable collaboration between business users and developers. DevOps can support this by providing shared staging environments and documented deployment processes. Non-developers can safely contribute without bypassing governance, while developers can extend or improve the applications efficiently.

DevOps Best Practices
- Treat AI output as code from the start: Store generated applications in repositories to apply version control, code reviews, and change logs.
- Automate quality checks: Include unit tests, integration tests, linting, and dependency scans in CI pipelines.
- Centralize deployment: Align AI-generated applications with the organization’s standard CI/CD pipelines for consistency.
- Define guardrails without blocking innovation: Implement role-based access, approval processes for production, and security templates to keep citizen developers productive while maintaining control.
Conclusion

VibeCode and similar AI-assisted tools offer faster ways to build applications. They lower barriers for innovation and accelerate prototyping. DevOps remains critical to ensure quality, security, and maintainability. By applying standard DevOps practices to AI-generated code, teams can safely adopt these tools without risking production stability.

The future will likely bring deeper integration between AI-generated platforms and standard DevOps pipelines. Until then, automated testing, CI/CD workflows, and governance frameworks are the key to balancing innovation with reliability.
April 7, 2026
How Low-Code Is Reshaping DevOps Automation and Governance

Jon Scolamiero breaks down how low-code platforms are becoming an increasingly important part of the modern DevOps ecosystem. As organizations grapple with rapid shifts brought on by AI, vibe-coding practices, and an explosion of tooling, Scolamiero argues that low-code isn’t a shortcut—it’s a way to bring structure, automation, and transparency back into software delivery.

He explains that the core mechanics of DevOps don’t disappear in a low-code environment. Pipelines still need to deploy reliably, infrastructure still needs to be provisioned, and applications still need to be secured and monitored. What changes is how teams interact with those systems. Low-code abstracts much of the repetitive orchestration work so teams can focus on governance, quality, and outcomes instead of plumbing. For organizations struggling with shadow AI, fragmented workflows, or inconsistent platform engineering practices, this abstraction can be the difference between chaos and clarity.

Scolamiero also touches on the growing divide between U.S. and EU compliance expectations. While the EU pushes ahead with strong regulatory frameworks—including around AI transparency—the U.S. market often lags in political will but compensates with heavier requirements in highly regulated industries like federal, defense, and finance. That gap puts new pressure on DevOps teams to understand not just how software is built, but how every dependency enters the environment. Software supply chain security, Scolamiero notes, is no longer a niche concern—it’s a foundational requirement.

Looking ahead, he warns that AI-driven development may soon trigger a high-profile security incident unless organizations adopt responsible governance practices. For DevOps teams, the message is clear: abstraction and automation are powerful, but only if paired with visibility, policy, and a strong understanding of the end-to-end delivery chain.

December 8, 2025
Why Software Migrations Fail: It’s Not the Code
Engineers often overlook the human and organizational dimensions of software migrations. They typically perceive these projects as technical undertakings, but institutional knowledge, communication gaps, team morale and resistance to change can significantly influence timelines and outcomes. Examining common pitfalls, effective strategies and emerging trends reveals a comprehensive view of the migration process from a human-centered perspective.

Recent research continues to validate that delays in software migration are the rule rather than the exception. In a 2023 McKinsey & Company report, over 70% of large-scale digital transformations fell short of timeline or return on investment (ROI) expectations, with a lack of cross-functional alignment and insufficient change management cited as leading causes. Similarly, a 2024 Boston Consulting Group survey revealed that nearly half of global C-suite executives reported that over 30% of their organization’s technology development projects suffered delays or budget overruns.

Understanding Software Migrations as a Human-Centered Process

Software migration involves transitioning systems, applications, or infrastructure from one environment to another. These transitions may include moving from on-premises deployments to cloud platforms, retiring legacy systems in favor of modern stacks, or switching technology between vendors. Despite their technical appearance, such migrations cause ripple effects throughout organizational workflows and operations.

These migrations often require retraining end users, maintaining legacy systems during the transition and navigating competing priorities. The disruption can stall development cycles and introduce operational risk. Overlooked in most planning stages is how much these projects rely on people’s undocumented knowledge, assumptions and behavioral responses.

Human and Organizational Barriers That Derail Migration Efforts

Scope creep or technical hurdles are frequently blamed as the cause of migration delays, yet deeper analysis reveals that resistance to change and knowledge gaps within teams are often more significant obstacles. End users familiar with a particular interface or workflow may be reluctant to adopt a new one. Internally, this resistance is not always voiced directly but manifests as disengagement or low adoption rates. Business stakeholders, too, may not fully grasp the strategic rationale behind a migration effort. Executive alignment weakens when the justification isn’t well articulated and cross-departmental cooperation becomes harder to sustain.

Undocumented institutional knowledge is another persistent challenge. Many decisions about data structures, hard-coded values, or interface dependencies exist only in the minds of long-tenured employees. When these employees move on or get reassigned mid-project, teams can lose the rationale behind legacy implementations. This knowledge vacuum causes surprises during implementation, especially when hidden dependencies emerge.

Managing Mid-Migration Surprises and Mitigating Risk

No matter how well-scoped a project is, assumptions made by different teams often go unspoken. Teams often operate in silos, assuming shared understanding when none exists. This misalignment can result in components built on conflicting premises, only discovered during testing or go-live. Mid-migration surprises include unanticipated manual workarounds, deprecated features that remain mission-critical and inconsistent definitions of business logic across systems. Manual processes known only to a few employees become barriers when they cannot be replicated in the new environment and uncovering these issues late in the process leads to delays and rework.

Incorporating discovery sprints before execution has proven effective in managing these risks. These sprints create space to unearth undocumented logic, validate inter-team assumptions and highlight edge cases early. Including a buffer—typically 10–20% of the timeline—also reduces the risk of missed deadlines.

Strategies to Reduce Rework and Support Successful Transitions

While tooling plays a supporting role, successful migrations hinge on clear communication and iterative execution. Automated migration tools can minimize manual tasks and streamline repetitive processes, such as data copying or schema translation. Relying solely on automation overlooks the need for continuous stakeholder alignment, however.

Here are some ways to reduce rework:
- Cross-team workshops. Use workshops to identify assumptions early and establish shared understanding.
- Regular check-ins. Catch evolving issues before they escalate by employing check-ins throughout migration.
- Phased rollouts. Transitioning rollouts over time rather than all-at-once helps organizations validate changes incrementally and apply insights from one phase to the next.
Communication breakdowns lead to duplicate efforts, reactive firefighting and coordination overhead. Maintaining old and new systems requires continuous attention and introduces operational drag. Factoring in learning curves and user adaptation time into project schedules can help set more realistic expectations. Offering flexibility during migration is equally vital for maintaining morale and sustaining trust.

Future Trends and Measuring Human Impact

Recent innovations are changing the migration approach. AI-powered tools now enable faster and more accurate transformations. In one notable case, Airbnb completed a migration, estimated initially to take two years, in just six weeks using AI tooling. These platforms automate repetitive code translations and configuration tasks, reducing reliance on large teams while preserving accuracy.

Low-code and no-code migration platforms simplify transitions by offering visual interfaces and guided workflows. These innovations allow a broader set of employees to participate in the migration process, increasing organizational resilience.

While AI accelerates execution, it does not eliminate the need for human oversight. Engineers now spend less time on rote tasks and more on designing, monitoring and validating migration paths. Prompt engineering, anomaly detection and performance monitoring are emerging as core responsibilities in this new paradigm.

Tools like GitHub Copilot and Amazon CodeWhisperer are increasingly integrated into migration workflows to assist with repetitive coding tasks, generate test cases and validate syntax conversions. These tools reduce the cognitive load on developers and help teams move faster through lower-level tasks, freeing up human resources to focus on architecture decisions, validation and user-centric improvements.

Metrics That Reveal Human Impact

Quantifying the human side of migration is complex but not impossible. Several indicators can provide insight into where people are struggling and may need additional support:
- On-call ticket volume. A spike in support requests during the migration window often reflects friction points, such as unclear interfaces, poor documentation, or insufficient training.
- Employee satisfaction scores. More extensive morale trends can reveal team emotional fatigue or frustration. Measuring satisfaction at different stages of migration provides valuable feedback loops.
- Attrition rates. Higher turnover among technical staff or support teams may signal disengagement, burnout, or disillusionment with the process.
- User feedback on new systems. Capturing qualitative input from end users via surveys, interviews, or feature usage can help determine whether the migrated tools effectively serve their needs.
- Project timeline adherence. Deviations from planned schedules often point to organizational misalignment, unanticipated rework, or breakdowns in communication.
These metrics collectively paint a more nuanced picture than completion percentages or delivery milestones. They help teams identify where to adjust code, expectations, workflows and morale.

Redefining Successful Software Migration

Technical upgrades may motivate software migrations, but the real complexity lies in navigating organizational behavior, knowledge gaps and human responses to change. Recognizing this dimension transforms software migration planning and execution. It’s not enough to have the right tools—teams benefit by fostering alignment, surfacing assumptions early and communicating continuously.

The future of software migration lies not just in AI and automation, but in embracing the human elements that make these transitions sustainable. As platforms evolve, the ability to manage systems and people will be the defining skill of successful engineering leaders.

Disclaimer: The opinions expressed in this article are those of the author. They do not purport to reflect the views of his employer.
June 30, 2025
Gearset Extends Reach of DevOps Platform for Salesforce Applications

Gearset has extended the scope of the observability of Salesforce applications it provides to include software developed using low-code Flex and object-oriented Apex programming tools.

Busayo Longe, a product manager for Gearset, said Flow is gaining more traction as a tool that is more widely employed to build Salesforce applications, while more complex applications are typically built using Apex.

Gearset, a provider of a DevOps platform for Salesforce applications, is now able to surface and analyze Flow and Apex errors in real time.

Unlike other applications where issues are surfaced using alerts generated via agents embedded in an application, the Salesforce platform generates automated error emails whenever there is a failure. It’s then up to the IT team managing these applications to investigate the root cause.

As a result, IT teams can find themselves being inundated with a high volume of hard-to-interpret messages that lack context about what went wrong, who was affected, or how urgent the issue is.

In addition to providing that context, Gearset errors can be filtered by type and further investigated using a set of visualization tools provided.

IT teams can also configure the automated error emails generated by the Salesforce platform to be automatically routed to Slack or Microsoft Teams messaging platforms if they prefer.

Finally, the alerts generated by Salesforce can also be customized to enable IT teams to only be notified when an issue exceeds a specific threshold.

In general, the need for observability will become much more pronounced as more organizations build and deploy artificial intelligence (AI) agents on the platform. As the interactions between AI agents increase, the chances that there will be issues that IT teams will need to investigate will only continue to increase, noted Longe.

The challenge is that a recent Gearset survey finds 69% of the IT teams managing Salesforce applications don’t have access to an observability platform. According to Gearset, IT teams that have access to an observability platform are 50% more likely to catch bugs within a day and 48% more likely to fix them within a day, compared to teams without these tools. On the plus side, 81% of respondents said they have adopted a continuous integration/continuous deployment (CI/CD) platform. In fact, Gearset claims it added 800 new customers in 2024, bringing its total customer count to 2,900 organizations.

It’s not clear who is building the bulk of the applications deployed on the Salesforce platform. While there are a large number of so-called citizen developers building applications using low-code tools, many enterprises also rely on professional developers to build these applications. As a result, the quality of the applications deployed on a Salesforce platform can vary widely. The one certain thing is that the pace at which organizations are building custom applications that are deployed on the Salesforce platform only continues to accelerate.

The challenge that arises is that the Salesforce platform is based on a proprietary, unique mix of programming languages, formats and metadata that require a separate set of DevOps tools and platforms to manage application development and deployment.

Regardless of who or how Salesforce applications are developed, the one certain thing is that it will eventually fall to a DevOps team to troubleshoot them whenever an issue arises.

June 13, 2025
The Future of Application Development in the AI Era

The artificial intelligence (AI) hype has yet to fade. As the technology continues to make headlines, attention is focused on the impact and value AI could deliver for teams, companies and the wider industry.

One of the main questions for those in software development is: Can AI replace human coders?

Despite impressive strides in AI-driven tools, human developers remain essential —though their role is evolving.

Today, 34% of IT leaders report that their organizations use AI-assisted coding extensively, according to The Low-Code Perspective. Meanwhile, nearly half the respondents(47%) are in the experimental phase.

Low-code platforms and AI advancements are creating new opportunities and responsibilities for those involved. Yet, understanding how to make the most from AI-powered low-code requires clarity on the skills and expectations needed from employees.

Let’s take a closer look at the future of application development in this new era of AI — from training teams to navigating stakeholder involvement.

AI Won’t Replace Developers; It Will Help Evolve Their Role

Generative AI (GenAI) tools, such as ChatGPT and Copilot, are currently being used to suggest code snippets, troubleshoot errors and even complete functional code blocks based on prompts.

The role of GenAI in application development is to automate repetitive tasks and reduce low-value activity, but the technology is quickly evolving.

Soon, we could start seeing GenAI work as a co-worker alongside developers. For example, instead of crafting a data model manually, GenAI could assess a requirements document, an existing data schema or an idea formulated in natural language and populate a data model that can then be validated by a developer. The same applies to the generation of user interfaces: Rather than developing UIs from scratch, developers can upload designs or even low-fidelity drawings from a whiteboard session and generate pages that can then be refined.

For some, the productivity benefits of GenAI, as it continues to evolve, pose a question as to whether there is still room for low-code in the future.

Visual development, such as low-code, provides an arena that is not often available to organizations, as it enables people from multiple disciplines to build applications in an environment where everyone understands what’s going on behind the scenes. Not only does GenAI facilitate visual development at pace, but it also increases the speed of the entire development lifecycle when applied to a low-code platform.

AI-assisted low-code paired with skilled developers can unearth significant benefits. Of those surveyed, 85% believe combining AI and low-code would help their organization innovate faster. And 82% say it helps their organization innovate at scale.

Eventually, we will likely see the role of the developer become more of a composer, overseeing the work completed autonomously by virtual software agents. Developers will focus on the management and correction of applications rather than the heavy lifting.

Unlike AI, human expertise can handle nuances to create purpose-driven applications. For instance, understanding user requirements, anticipating potential system failures and integration with existing IT assets are just a few areas where human developers will remain critical. So, as we continue to integrate the technology into application development, it won’t eliminate the need for skilled coders — it will reshape it.

Stakeholder Support for AI is the Next Big Hurdle

We uncovered that a massive 84% of IT leaders say low-code empowers more people to be involved in app development. Yet, 41% report their C-suite lacks the technical knowledge to understand the potential of low-code for their organizations.

Navigating stakeholders is an ongoing consideration for technical teams, whether that is securing buy-in for vital technologies or unlocking future funds to fulfil the development roadmap. Yet, IT leaders are unearthing tension between their goals and those of their stakeholders.

This is concerning, considering that IT leaders report their chief operating officer (COO) as the topmost involved member of the C-suite when making decisions about low-code adoption. And the chief executive officer (CEO) is second.

As non-technical C-suite stakeholders become increasingly important decision-makers in IT capital expenditures and programs, continued conversations between these two stakeholder groups will help create a fuller understanding of low-code benefits.

In the pursuit of easy-to-use applications, businesses can mistakenly assume that low-code and AI tools eliminate the need for technical knowledge altogether — a fear that nearly two in five IT leaders share, with 39% believing their non-technical C-suite wants to use low-code to replace developer talent.

As the lines blur between non-technical and technical leaders in the IT space, goals must be aligned, with the right people in place, so everyone is on the same page for technology investments to be effective.

The Future of AI and Low-Code is Collaborative

Low-code platforms are already facilitating app creation by less technical developers, while AI tools are making coding faster and more efficient. There is a future on the horizon where low-code and AI operate in tandem, allowing developers and stakeholders to collaboratively design and deploy applications.

But the AI skills gap is widening, and today’s developers are expected to keep up. AI, used in conjunction with a powerful enterprise-grade low-code platform, holds significant potential to help bridge this gap when harnessed accessibly for smarter, faster development.

Ultimately, committing to improving productivity and enhancing developer experience is vital for businesses to stay competitive, and that means providing teams with the right tools to make development faster and more efficient. That way, tech teams can focus more on collaborating with the wider organization and problem-solving with accessible tools at the ready.

As organizations move forward, it will be essential to foster collaboration, ensure clarity in roles and encourage ongoing learning.

The true potential of AI and low-code is not in replacing coders but in empowering them. It not only accelerates development but also enables stakeholders to contribute more directly while helping organizations adapt dynamically in a rapidly evolving tech landscape.

June 11, 2025
Scaleups are Turning to Low Code to Build Modern Internal App Ecosystems

For most engineering teams, internal tools are indispensable but notoriously resource-intensive. Whether it is admin panels for configuration, dashboards for analytics or operational systems, these tools demand continuous updates, customizations and maintenance. Due to the lack of developer capacity, long implementation times and the buildup of technical debt from hardcoded non-scalable solutions, traditional development methods frequently result in bottlenecks. That being said, low-code platforms are transforming this narrative. Choosing the right low-code platform for your team could mean enabling faster development, empowering junior developers and reducing the maintenance burden. Drawing from experiences shared by engineering leaders at PhonePe, Yubi and DronaHQ, this article explores how engineering leaders are adopting low code to reshape the development of internal tools and drive operational excellence.

Why Low-Code?

Addressing Legacy Issues and Bottlenecks

For any engineering team, dealing with legacy code and configurations can easily be a recurring theme. Shikhar Kapoor, Software Architect at PhonePe, described how a compliance-driven audit forced the team to update legacy consoles across the organization, “Low code is not just about speed; it is about letting developers move forward without being tied to the past. A developer should not be dragged back into legacy work. They should be solving new problems, not reconfiguring old ones.”

For a firm where compliance is paramount and scalability is a given, the mindset shift was essential. By centralizing updates through low code, PhonePe has avoided the time drain of manually updating multiple consoles, directly impacting the developers’ productivity.

Enabling Reconfigurability for Scalability

Software, ready-to-use or custom-built, will create challenges as your firm scales. Dinesh Kailash Kumar, VP of engineering of Yubi, shared how building hardcoded solutions for every new customer became unsustainable, “We discovered that building custom solutions is wasteful in terms of effort because you are tied and cannot scale. Configurability is key. With low code, we have been able to package configurations, enabling teams to build custom solutions that scale effortlessly.”

Yubi’s approach to low code focused on creating a headless, configurable architecture. This shift empowered teams to dynamically adjust workflows without needing developer intervention for every change. By enabling non-developers to make updates, Yubi significantly reduced their operational overhead and improved scalability.

Reducing Turnaround Times With Low-Code

Kapoor shared how adopting low code at PhonePe compressed project timelines from three months to just three weeks. “This is not just about efficiency; it is about creating a responsive and agile engineering environment,” he said.

By identifying bottlenecks in their traditional development process, PhonePe introduced low-code to centralize configuration management, streamline workflows and improve responsiveness to both internal and external requirements.

Overcoming Resistance and Building Trust

Adopting new technologies, especially something as fundamental as low-code, often meets resistance from within the organization. Developers accustomed to traditional workflows may view low code as a compromise on quality. To address this, Kapoor described a unique strategy PhonePe employed during a company-wide hackathon. “We established our low-code tool and encouraged teams to use it for their projects. Instead of pairing up with a UI developer, we asked them to try building front ends themselves. The hands-on experience helped evangelize the tool and build trust in its capabilities.”

Surprisingly, backend engineers adapted to low-code tools faster than front-end developers. Kapoor noted, “Backend engineers had fewer preconceived notions about how UI should be built, making them more open to experimentation.”

Choosing the Right Time to Invest in Low Code

When should you consider low code? Jinen Dedhia, co-founder of DronaHQ, suggested that the best time is when workloads begin to bottleneck, “There is always a point where you can see your workloads increasing. That is when you realize your team is becoming a bottleneck for growth.”

For organizations like Yubi, this realization came as they scaled rapidly and needed a solution that would not require constant developer intervention. By transitioning to low-code, they were able to address scaling needs without expanding their engineering headcount.

Enabling Customization Without Overburdening Developers

Customization often slows progress in traditional development, as developers must revisit and reconfigure settings repeatedly. Jinen explained how low code disrupts this cycle, “Building configurable platforms that do not rely on developers for every change means faster turnaround times and happier clients. With low-code, developers can move on to more complex problems without being dragged back into configuration tasks.”

Kapoor shared how low-code tools enabled product managers to make changes independently. “The introduction of a WYSIWYG editor meant product managers could sit alongside developers and make real-time changes to dashboards, reducing back-and-forths and shortening delivery timelines,” he said. Interestingly, this empowerment also encouraged some non-technical team members to learn basic JavaScript for further customizations.

The Future of Low Code in Scaling Engineering Teams

Looking ahead, low-code platforms are becoming integral to tech stacks. Kapoor shared PhonePe’s vision for expanding low-code usage, “We are looking to integrate low-code even further by making control panel features a part of our design stage, not just an afterthought.”

Yubi is exploring ways to templatize configurations, ensuring that 80% of a customer’s needs are pre-built. Dedhia explained, “By making tools modular and reusable, we can handle diverse requirements without starting from scratch, enabling faster and more consistent rollouts.”

Is Low Code Right for Your Organization?

Low-code platforms are not just about efficiency gains; they enable engineering teams to innovate, reduce repetitive tasks and scale solutions seamlessly. The decision to adopt low code should align with an organization’s growth trajectory and scalability needs. As Jinen advised, “Identify the bottlenecks, focus on scalability and do not underestimate the importance of training and education. Low-code platforms can be transformative, but only if the team is ready to embrace the change.”

January 28, 2025
No Country for No-Code: Are We Heading Towards a Wild West of Software Security?

Nearly everything we use is built on code, from cars to smart fridges to doorbells. In businesses, countless applications keep devices, workflows and operations running. So, when early no-code development platforms launched in 2010, promising more accessible application development for citizen developers, its success felt inevitable.

It’s hard to deny the success of no-code. These platforms flatten the learning curve for would-be developers, allowing organizations to innovate and automate with useful applications despite a developer skills shortage. Plus, the out-of-the-box applications offered by no-code platforms expedite the application development process in a world where speed-to-market is king. Last year, Forrester found that 87% of enterprise developers use low-code and no-code tools or platforms for at least some of their workload.

But functionality is not the only sign of success. Unintentionally, the same trends that pushed for application development to be democratized have led to a wild west of insecure applications and misconfigurations that expose a whole host of organizations to cyberthreats.

The Importance of Security

While these platforms democratize development, they must be used with caution. The OWASP Top 10 highlights factors such as misconfiguration and using vulnerable components as common security threats. Yet, a reliance on no-code development could introduce un-spotted vulnerabilities directly into an organization.

Forrester has long warned of the risk of no- and low-code, featuring the vulnerability in its predictions for the coming years. The spectrer of an untrained employee creating applications is especially alarming: These platforms empower employees with no application security knowledge to develop programs that security teams are often unaware of.

Organizations must gain real oversight into who is responsible for developing software, whether professional developers leveraging no-code platforms as tools, or citizen developers creating applications for smaller teams and projects. It is no secret that CVEs are rising sharply. They hit a record 28,092 last year and are projected to increase by 25% throughout 2024. Last December, Microsoft revealed a high-severity CVE that affected low-code and no-code users.

When businesses are facing a tide of new exploits each day, skills such as vulnerability detection and remediation are critical to any new software development project.

Software development needs to become more flexible in its roles, but never at the expense of security. By fostering a culture of “security by design” across the organization, security leaders can ensure that all roles in the software development lifecycle (SDLC) understand their responsibilities in their security posture — including citizen developers.

Empowering Human Intervention

Just one in five organizations are confident in their ability to detect a vulnerability before an application is released, according to Security Journey research, meaning that the security knowledge in most SLDCs is insufficient. Developers need to be trained to create secure software and to sniff out insecure code in the rest of the code base – responding and fixing it quickly – before it gets to production. Without this, application security and security teams are left with an unnecessary burden, which ultimately requires more time, expense, and potential for business risk. Securing vulnerabilities after the fact, through regular security scanning and patching, should not be the norm.

Instead, organizations have an opportunity to empower developers with security skills and knowledge throughout their careers. These skills allow them to deliver a higher quality of output and play a vital role in securing the organization itself. And yet, just one in three organizations (36%) train developers to write secure code, which ensures that software security starts at the end of the development process 64% of the time. The same goes for citizen developers, whose work often shows a passion for problem-solving and innovation that should be harnessed and supported with the right training.

A Problem for the Future

It would be reductive to suggest that software security risk is rising purely because of no-code and low-code platforms, or even that citizen developers are a majority contributor to CVEs. The very culture of software development has been forcing the industry down a path of speed and ease over security for almost two decades. The surge in AI-generated coding proves this more than anything.

So long as developers and the project managers above them are incentivized to move fast, each new solution will be valued based on its ability to create functional code quickly. This will be the case until security is made a priority by regulators and, importantly, by executives and the board.

The cultural disconnection at the heart of the software security crisis is human-made. No matter which tool is in the spotlight, building secure software will require human solutions. While large language models (LLMs) aren’t yet equipped to tackle the complex considerations that developers face daily, the biggest risk will come from complacency, overreliance and blind trust from their users. Human developers, equipped to perform rigorous code reviews and remediate any vulnerabilities they find, are central to the safe implementation of any of these technologies, whether no-code, low-code or AI-generated. Without this, the tools run the risk of introducing more vulnerabilities with less critical supervision.

No matter what tools arise, knowledgeable human users will always need to understand what the tool is providing and can act as a stopgap for quality and security.

May 14, 2024
The Rise of Low-Code/No-Code in DevOps

The ever-evolving landscape of technology has ushered in a paradigm shift in software development and deployment. One of the prominent trends gaining momentum is the integration of low-code/no-code platforms within the DevOps ecosystem. This article explores how these platforms are revolutionizing the way applications are developed, deployed and managed, fostering collaboration between developers and operations teams.

1. Democratizing Development:

Low-code/no-code platforms empower individuals with limited coding experience to actively participate in the application development process. This democratization of development accelerates the delivery of software by allowing business analysts, designers and other non-developers—sometimes referred to as citizen developers—to contribute directly to the creation of applications.

2. Accelerating Time-to-Market:

The traditional software development life cycle often involves lengthy coding processes, leading to delayed releases. Low-code/no-code platforms enable rapid prototyping and development through visual interfaces, significantly reducing the time required to bring applications from concept to production. This acceleration aligns with the principles of DevOps, promoting continuous delivery and faster time-to-market.

3. Enhancing Collaboration:

DevOps is all about breaking down silos and fostering collaboration between development and operations teams. Low-code/no-code platforms bridge the gap between these traditionally distinct roles by providing a common ground where both technical and non-technical stakeholders can collaborate seamlessly. This collaborative environment promotes better communication, understanding, and alignment of objectives.

4. Flexibility in Deployment:

Low-code/no-code solutions are designed to be platform-agnostic, allowing for the deployment of applications across various environments, including on-premises and cloud. This flexibility aligns with the DevOps principle of infrastructure-as-code (IaC), enabling teams to deploy and manage applications consistently across diverse infrastructures.

5. Reducing Dependency on Specialized Skills:

In a DevOps environment, reducing bottlenecks and dependencies on specific individuals or roles is crucial. Low-code/no-code platforms enable teams to be more self-sufficient, reducing the reliance on specialized coding skills or DevOps Training. This, in turn, contributes to a more resilient and adaptable DevOps culture.

6. Challenges and Considerations:

While the adoption of low-code/no-code in DevOps brings numerous benefits, it also introduces challenges. This section discusses considerations such as security, scalability and the potential need for customization beyond the platform’s capabilities.

7. Real-World Use Cases:

Explore real-world examples of organizations successfully incorporating low-code/no-code in their DevOps workflows. Highlight the positive outcomes, lessons learned, and the impact on their overall software development life cycle.

Conclusion:

The rise of low-code/no-code platforms in DevOps is reshaping the way software is developed and deployed. By fostering collaboration, accelerating development cycles, and reducing dependencies on specialized skills, these platforms align seamlessly with the principles of DevOps. As organizations continue to embrace this trend, the synergy between low-code/no-code and DevOps is set to redefine the future of application delivery.

March 29, 2024
Low Code: The Key to Accelerating Custom App Dev for Moderate Developers

Custom app development has become a crucial skill in an increasingly digitized world. Many moderate developers face challenges while creating unique and functional applications. This is where low-code platforms come into play, offering a solution to accelerate app development and compensate for those shortcomings.

Who are Moderate Developers?

While every developer is constantly evolving and growing in experience, like any professional, they can be put in three baskets. The first is entry-level developers learning on the job who may assist with debugging, essential documentation, code repository maintenance and some simple feature requests. At the other end are very experienced developers who lead projects, architect solutions, oversee the development of applications and take full ownership of delivering killer features in a new application.

Moderate developers are those in the middle, representing a large swath of professionals with the foundational expertise to implement most app designs and feature requests. With more experience than beginners but yet to be qualified to serve as seniors on a team, they have a shared set of challenges.

Understanding the Challenges of Moderate Developers

Moderate developers often need help with complex application development demands and skill limitations. They are faced with creating high-quality, functional and unique applications, which can be daunting in light of the rapid pace of technological change and user expectations.

These moderately skilled developers often face common challenges such as:
● Limited Expertise: Cultivating an in-depth knowledge of programming languages and development environments is an ongoing process.
● Time Constraints: Developing an application from scratch requires significant time. Dedicating effort to a single project can constrain developers and their organizations.
● Scalability Issues: Growing and expanding applications increase the need for scaling and can create complexity. Making changes and adding new features can drag down an organization’s ability to focus on new projects.
● Security Concerns: Moderate developers may not be aware of an application’s security risks, jeopardizing the protection of a company.

Low-Code Platforms Offer Hope

Low-code platforms have been created to meet the needs of moderately skilled developers and competitively focused organizations. The use of tested drag-and-drop elements offers a secure and powerful way to overcome these challenges.

Creating practical and powerful applications is available through low-code platforms by connecting ready-made templates. This process rapidly creates applications for use as mobile and web-based applications.

Non-IT professionals can overcome their lack of time and knowledge through low-code platforms. Short-staffed organizations in their IT department can still provide a powerful connection for their services. The team can quickly get to work meeting its primary mission.

Visual Modeling is the Secret Power of Low-Code Platforms

Traditional application development involves writing lines of code, testing and managing by an experienced IT staff. Low-code platforms use pre-tested and connected visual components to build and implement successful and secure applications rapidly.

Low-code developers can see the application they are building from the beginning of the process to its launch. The drag-and-drop aspect of these platforms is more intuitive and user-friendly. Using proven templates offered by these platforms can also help reduce errors.

Duplicating Success

Assembling tested and ready-made components boosts the chance of an application’s success. Pre-configured applications are a way to rapidly launch applications with the confidence of a proven track record.

Low-code platforms offer users the confidence to trust the components while looking straight at their ongoing results from a clear visual perspective. More time and attention can be paid to an application’s unique functionalities rather than the complexity and drudgery of coding.

Team Building and Collaboration Opportunities

The visual nature of low-code platforms allows the entire team to play an active role in an application’s development and keeps everyone speaking the same development language.

Built-in collaboration tools facilitate feedback loops, revision tracking, user stories and messaging, making it easier for teams to work together in the same office or distributed worldwide. Everyone can own the solution while having a positive impact upon its release.

Ensuring Scalability

Low-code platforms offer more than a “one and done” opportunity for growth and success. Robust and friendly customer-facing connections await users of low-code platforms who take advantage of their power. They can continue to generate further service opportunities and sales after the initial launch.

Proven internal processing networks can be extended with the same low-code platforms that started this robust development. Low-code connections can be efficiently expanded using earlier low-code work.

Ever-changing business needs can be readily addressed with existing low-code platforms. They can continue to offer ready-made templates for internal and external successes that fit an enterprise’s needs.

The cloud-based nature of low-code platforms ensures a flexible and continuous service of the applications. This helps ensure reliability and responsiveness to a customer’s ongoing needs.

Choosing the Right Low-Code Platform

Identifying the best low-code software development platform is based on several key factors that developers must consider:
● Ease of use
● Scalability
● Integration capabilities
● Ability to customize applications

Decision-makers must also consider their team’s expertise when choosing a low-code platform. Trial versions or free tiers can be beneficial for understanding the team’s expertise and a platform’s capabilities to meet an organization’s needs.

The Future of Low-Code Platforms

As businesses continue to navigate the complexities of digital transformation, analysts predict a bright future for low-code platforms. The trend will be continued enterprise adoption to ensure faster development and specific business needs. It’s also clear that low-code platforms will only partially replace traditional software development. But by democratizing app development and fostering a more robust culture of innovation, low-code platforms are positioned to significantly shape the future of business in the digital era.

March 4, 2024