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Category: Continuous Delivery

Continuous delivery is a software engineering discipline that allows organizations to consistently develop and release quality software at a rapid pace. It is achieved by automating the software development lifecycle, enabling tasks such as development, testing and release to occur concurrently and continuously.

  • Choosing the Right Software Deployment Tools

    Choosing the Right Software Deployment Tools

    Imagine this scenario: After investing countless hours in developing your software, it is finally ready for deployment. Now, you must select the appropriate software deployment tools to guarantee a seamless release.

    This article will guide you through the concept of software deployment and discuss various tools that cater to different needs—from dedicated deployment tools to comprehensive CI/CD pipeline solutions and GitOps approaches. By understanding these categories and their benefits, you’ll be well-prepared to make an informed decision on which tool is the best fit for your organization’s needs.

    What is Software Deployment?

    Software deployment plays a crucial role in the software development life cycle. It involves packaging, distributing and installing an application on target systems or environments, aiming to make your software accessible and usable for end-users seamlessly.

    In today’s fast-paced world, companies must be able to deliver applications rapidly and reliably. A well-planned software deployment strategy ensures that new features reach users promptly while minimizing downtime and errors during updates.

    What to Look For in a Software Deployment Tool

    When selecting the ideal software deployment tool, consider the following factors:

    • Automation: The tool should automate complex software deployments, making the deployment process faster and more efficient.
    • Continuous deployment: Continuous deployment tools allow you to deploy software repeatedly, ensuring consistent deployments. Choose a tool that automates release management and integrates automated builds throughout the development process.
    • Scalability: The tool should be capable of handling large-scale deployments and distributing software across multiple servers. Opt for a tool that enables applications to deploy to multiple servers simultaneously.
    • Integration: The tool should integrate with version control and other third-party tools, making the deployment process seamless. Look for a tool that integrates with modern DevOps processes and connects automated builds to configuration management.

    Full CI/CD Tools

    Bamboo

    Bamboo by Atlassian is a robust tool that integrates seamlessly with other Atlassian products, such as Jira and Bitbucket.

    It offers first-class support for multiple languages and platforms while providing built-in deployment projects for smooth releases.

    GitLab CI/CD

    GitLab CI/CD, an integral part of GitLab, simplifies pipeline management using YAML configuration files stored within your project repository.

    This approach enables easy collaboration among team members while ensuring consistent build environments across all stages of development.

    Codefresh

    Codefresh is a cloud-native solution designed specifically for Kubernetes deployments, It provides a modern interface to manage pipelines visually, along with advanced real-time debugging capabilities.

    Dedicated Deployment Tools

    Jenkins

    Jenkins was originally conceived as a continuous integration (CI) tool, but many organizations use it mainly for deployment. It is an open source automation server that provides support for building and deploying software projects, as well as to schedule and run tasks at regular intervals. Learn more about Jenkins in this in-depth blog post.

    Harness

    Harness is an intelligent software delivery platform that simplifies deployments through automation and machine learning. Their continuous delivery-as-a-service (CDaaS) approach helps you deploy faster while minimizing risks and errors.

    AWS CodeDeploy

    If you’re using Amazon Web Services (AWS), AWS CodeDeploy might be a perfect fit for your needs. This completely managed service automates code deployments to any instance or serverless Lambda function in AWS, guaranteeing consistent results every time.

    Spinnaker

    An open source project backed by Netflix and Google, Spinnaker offers powerful multi-cloud continuous delivery capabilities for deploying applications at scale across various cloud providers like AWS, GCP, Azure, Kubernetes clusters, etc.

    GitOps Tools

    Argo CD

    Argo CD is a declarative, Kubernetes-native continuous delivery tool that uses Git repositories as the source of truth for application definitions. It simplifies rollbacks, provides audit trails and enforces consistency across environments.

    Flux CD

    Flux CD, another Kubernetes-focused option, automates deployments by monitoring your code repository for changes and applying them to your cluster accordingly. Bonus: It supports multi-tenancy and integrates with Helm charts.

    Weave GitOps Core

    Lastly, Weave GitOps Core offers an open source foundation for managing Kubernetes applications using the power of GitOps workflows. This versatile tool can be extended to fit various use cases while maintaining simplicity in its core functionality.

    Conclusion

    There are many software deployment tools available that can help automate the software delivery process, reduce errors and improve collaboration between development and operations teams. From open source tools like Jenkins to cloud-native solutions like AWS CodeDeploy, each tool has its own strengths and features that make it suitable for different use cases.

    When selecting a software deployment tool, it is important to consider factors such as compatibility, automation, scalability, security, monitoring, deployment environment compatibility, integration with existing tools and support and documentation. By carefully evaluating these factors and choosing the right tool for your specific needs, you can ensure that your software deployment process is efficient, reliable and successful.

    Image Source: Freepik

  • The Case For an API-First SCM

    The Case For an API-First SCM

    Somewhere around a decade ago, about the time DevOps really started to manifest, we began seeing technology companies—including some of the largest ones today—investing heavily in their APIs.  

    API-first companies managed to rapidly gain widespread adoption because of the benefits of being API-driven. Everything from automation and scalability to flexibility, performance, speed and monetization.  Once DevOps thinking made it increasingly clear that automation would solve problems like human error and increase performance and velocity, creating more machine-to-machine interaction became a critical factor in software delivery—because the problem in the technology world was not innovation, but rather integration.

    Twilio is a prime example. The company became famous for its API-driven approach to customer management and even had a famous Silicon Valley billboard trumpeting their success. They changed the game for customer communication for some of the largest companies in the industry, from Netflix to DoorDash to Coca-Cola, by making communication completely invisible to users. These APIs largely served developers by unifying communication on the backend and providing powerful customer-facing capabilities on the business side. But they’re not the only ones.

    API-first SCM

    API-driven companies managed to disrupt entire markets nobody imagined could be disrupted, such as Stripe for payment processing and Slack for immediate communication (their former head of developer relations, Amir Shevat, said that Slack’s developers were literally measured by their API’s active tokens). Companies that harnessed the power of their APIs saw unprecedented growth over the last decade due to the integration power they unleashed. 

    Today, there really is no self-respecting dev-first technology that doesn’t invest heavily in the robustness of its APIs. There are even entire companies today built around API integrations—from marketplaces like Rapid API to security companies like Akita Software to companies like Kong that focus solely on simplifying API gateways.

    The API-First Dev Tool Revolution

    The same transformation that disrupted various business industries is now beginning to take center stage in the technology and dev tools space. This is also part of the developer experience revolution that is the stimulus for all the nifty dev tools in the first place. As developers become the new decision-makers—masters of their own domain—and are no longer being forced to adopt and use technology someone else purchased for them, the experience of using these tools impacts their choice of whether or not to add these tools to their chain. This means that those creating the tools today need to deeply understand the developer’s workflow and optimize their products for this user persona.

    This very same evolution that typical tooling underwent is now impacting age-old tooling in the developer ecosystem—and developer pain and friction are starting to come to the forefront. This includes the need for better and more robust API capabilities, “as-code” (infrastructure-as-code, testing and security) tooling, low-code/no-code and code variations and much more.  

    It’s interesting to see that, even with the cloud-native and DevOps revolution, our most core developer tool—our source code management—hasn’t really changed much in the last 20 years. Git remains ubiquitous, but its design is optimized for developer workflows from two decades ago. It’s long past time for an API-first SCM, and there are a number of use cases that can benefit from better APIs.

    Evolution and Anatomy of APIs to be Git-Native

    Even with the most exciting innovations we’re seeing from Git SaaS tools like GitHub and GitLab—from Co-Pilot to Codespaces, pipelines and more—they’re only as strong as the technology they are built upon. As the world evolves, this fundamental weakness is proving to be a sort of kryptonite.  

    Despite Git being an old-school, monolithic tool with proprietary protocols, Git hosting providers like GitHub, GitLab and Bitbucket have invested a lot into making their services API-driven to cater to tool integration. True, each has its own API, which drove some players integrating with the service (especially in the early days) to integrate via an SDK rather than an API.

    GitHub itself provides a variety of APIs—from the simpler REST through the more elaborate GraphQL. These APIs provide you with the ability to do pretty much anything, but are somewhat cumbersome for some use cases. To deal with the core Git functionality, you are required to directly manipulate objects in the Git database.

    Code Deployment and GitOps

    As engineering organizations grow, the need for greater control of code and infrastructure resources has become a real pain—and this is where GitOps provided the methods and the tools to support automated policy management at scale. This automated policy and governance is largely enabled, machine to machine, via APIs, and many of its controls are built on code and configuration files that are hosted via Git (hence its name: Git Operations).

    When using this methodology, a configuration change is first committed to Git (as the single source of truth that will apply changes in all the relevant places). Only then does this trigger automatic processes to apply these changes universally. In some cases, these automatic processes have to commit files to Git via API.

    Another area where SCM APIs play a key role is versioning and release management.  DevOps teams need to manage the release of new versions of their applications, including creating release notes, tagging releases and creating release branches. These processes, which sometimes take place multiple times every day, include many steps and require accuracy—a comprehensive suite of efficient APIs is critical for such an operation.

    UX Customization

    Today, there’s a huge diversity of stakeholders in modern engineering processes, particularly in the context of game development, but this is also true in any kind of web-based or UI-based engineering, as well. Today, product and design are an integral part of engineering processes, but Git still remains the domain of developers.

    There are times when you’d like to have a unified interface for your asset management that pulls data from multiple APIs and sources—such as Git for source control and Google Drive for large files. The added benefit is to abstract and decouple the underlying technology from the user experience and interface so that users can be free to migrate and move between their technologies of choice. This is true whether at the SCM or the storage level without having to change the interface that the team is accustomed to.

    APIs that efficiently perform the full set of SCM functionality allow developers to use a single backend for managing code versions while still providing end users with the desired experience, regardless of what that might be.

    Versioning-as-a-Service

    SaaS products have made it significantly easier to manage and maintain our services through simple UIs and dashboards. However, this simplicity also has a tradeoff. Have you ever made a simple configuration or code change, quickly regretted doing so and then attempted to revert it via your SaaS console? In most SaaS apps that aren’t managed as code, this happens all the time—from Okta to Datadog and many others. Without the benefits of “as-code” and the version control that comes with it, reverting changes is nearly impossible.

    The most you can achieve is “undoing” a previous configuration—if you can still catch it with a CTRL+Z—simply because engineering didn’t bother (or did not have the resources) to implement versioning. Imagine if this could come as a service for all of your SaaS applications!

    For software developers, API-based version control will unlock the possibility of easily incorporating rich version control capabilities into their product—in the same way they can currently use other capabilities such as database, file storage, etc. 

    The World is Ready for an API-First SCM

    TL;DR: API-first models have delivered some of the greatest innovations that ‘dinosaur’ industries—from payments to communications—needed to move faster and do so securely. It is almost laughable that the technology industry has inherent limitations due to a core technology that has a legacy design. This should not be a technology limitation we should accept.  

    Our source code should be able to be controlled, manipulated and transformed via API to remove human toil from places it isn’t really needed and free people to focus on higher-order problems.  With the widespread adoption of generative AI and smarter machine overlords, we’ve discovered that there are many formerly manual tasks that we can offload to machines. Free SCM APIs to unlock the next generation of innovation—because soon there will be more machines than humans to manage them. APIs are the key to tapping into this power. 

  • Pulumi Embeds Terraform Conversion Tool in Platform

    Pulumi Embeds Terraform Conversion Tool in Platform

    At its virtual PulumiUP event, Pulumi this week announced it embedded an ability to convert instances of Terraform into its infrastructure-as-code (IaC) platform via a simple command line interface (CLI) command. In addition, Pulumi added a Review Stacks capability that automatically creates a dedicated cloud environment to review code every time a pull request is opened.

    Pulumi is also making available a beta release of Pulumi Azure Native Provider 2.0, which decreases the size of the software development kit (SDK) by 60%. This is part of an effort to improve deployment times and reduce resource consumption by, for example, removing support for deprecated application programming interfaces (APIs).

    Finally, Pulumi has added support for property names and values to Resource Search for Pulumi Cloud, a search and analytics tool for cloud computing environments. DevOps teams can now additionally search for instances of, for example, versions of databases or specific availability zone as a result.

    Aaron Kao, vice president of marketing for Pulumi, said previously the company made available a separate tool for converting snippets of Terraform code. For the first time, Pulumi is also making available a converter plugin in the Pulumi engine which allows conversion tools from other IaC tools to be used.

    Review Stacks, meanwhile, makes it simpler for DevOps teams to pick up an unfamiliar codebase, make changes to both application and infrastructure code and share a live environment to review that code.

    Pulumi has been making a case for an alternative to Terraform that centralizes the management and provisioning of infrastructure using a set of embedded guardrails. One of the major issues enterprise IT organizations are encountering these days is the number of misconfigurations created when developers use tools like Terraform to provision infrastructure on their own. Those misconfigurations often lead to, for example, ports being left open and cybercriminals exfiltrating data.

    That approach is gaining traction among enterprise customers that are looking to centralize the management of DevOps processes, said Kao.

    In the wake of a series of high-profile breaches, more organizations are now reviewing the security of their software supply chains, including how infrastructure is provisioned. Many of those organizations will need to revisit those processes as pending legislation that requires more stringent requirements for building software eventually become law, noted Kao.

    At the same time, many organizations are also looking to improve the productivity of DevOps teams during an economic downturn that limits the number of full-time employees they might be able to hire. The pace at which software is being developed has not slowed, so there is a greater urgency to do more with less.

    It’s not clear how quickly organizations are centralizing the management of DevOps workflows, but with the rise of platform engineering, there is clearly more interest in defining consistent backend processes that multiple DevOps teams are currently managing individually. The challenge is finding a way to achieve that goal without impeding the pace of innovation enabled by embracing DevOps in the first place.

  • 92% of Devs Use AI, Survey Says ¦ Intel One Mono Font

    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…)

  • Four Ways to Modernize Your Enterprise Monoliths

    Four Ways to Modernize Your Enterprise Monoliths

    In a perfect world, every application would run like Netflix–by which I mean every application would be cloud-native, microservices-based, containerized and, in all other senses of the word, modern. Unfortunately, not every application can be transformed in these ways. Some of the most important enterprise applications–like those powered by SAP or Oracle–don’t lend themselves to architectural transformations simply because the vendors don’t support that strategy. As much as organizations might wish that they could re-architect legacy apps from the ground up, the reality is that they just can’t.

    Fortunately, though, all hope is not lost if you have an enterprise app that you can’t containerize or “microservices-ize.” Even if you can’t “break down your monolith”–to quote the standard advice you’ll find if you read articles about how to modernize legacy apps–there are a variety of practical steps you can take to make legacy, monolithic applications look and feel (in most respects) like modern, cloud-native apps.

    Here are four ways to make your enterprise monolithic apps more cloud-friendly, even if they’re not technically cloud-native.

    Use Cloud Automation to Modernize Legacy Application Management

    Most enterprise apps are compatible with the cloud in the sense that you can host them on cloud-based virtual machine (VM) instances using services like Amazon EC2.

    By taking advantage of cloud hosting for enterprise apps, organizations can also leverage cloud automation tools, such as autoscaling policies and rules that automatically start or stop VMs. In this way, it becomes possible to deploy enterprise apps in a highly scalable, automated way. You get something that resembles Kubernetes-based orchestration, except your apps don’t actually run in containers on top of Kubernetes. They’re just monoliths that benefit from cloud automation tools.

    Deploy Load Balancers to Optimize Performance

    Load balancers, which automatically manage network traffic flowing to and from applications, are another critical tool that organizations can easily leverage when they migrate legacy applications to the cloud.

    Although configuring load balancers for enterprise apps hosted in the cloud is not a strict requirement, doing so can substantially improve application performance and reliability because load balancers help to ensure that requests are directed at application instances best able to handle them. They prevent situations where one instance of your application is overwhelmed with traffic while another sits idle.

    Again, this is something that platforms like Kubernetes also do for microservices apps. But, as I’ve explained, you don’t actually need your app to run as microservices to take advantage of load balancing. You can do it with monolithic legacy apps, too.

    Adopt an Everything-as-Code Strategy

    When your app lives in the cloud and is managed by cloud automation tools, it becomes possible to manage most aspects of application operations via code. Specifically, you can:

    ● Use infrastructure-as-code (IaC) tools to automate infrastructure provisioning and setup.
    ● Automate application configuration management using code rather than applying configuration changes manually.
    ● Codify operational processes, such as application updates and backups, instead of relying on manual operations.

    Practices like these, which enable a strategy known as everything-as-code, significantly reduce the amount of time and manual effort that engineers spend managing applications. They also provide consistency and minimize the risk of errors due to human oversight. And there’s no reason why you can’t leverage these practices for legacy apps as well as modern ones.

    Integrate Legacy Apps With Modern Toolchains

    If your enterprise app is hosted on-premises, you probably manage it using tools and processes designed solely for it. But when you move an enterprise app to the cloud, it becomes possible to manage the application using the same integrated toolchain you deploy for other applications and processes.

    You can, for example, take advantage of cloud-based monitoring tools to continuously collect data about application performance and generate automated alerts when something is wrong. Likewise, you can regularly create image-based backups of your application.

    This toolchain-based operational strategy is another way to streamline enterprise application management, even in situations where you can’t rewrite or containerize the application itself.

    Conclusion: Getting More From Legacy Apps

    Just because you have a legacy enterprise app that you can’t transform into microservices doesn’t mean you have to settle for legacy management and operational practices. Modern automation tools combined with modern operational strategies like everything-as-code make it possible to achieve an enterprise application management experience that closely parallels that of fully modern, cloud-native apps, regardless of which architecture your app actually uses.

  • Cycode Leverages eBPF to Secure CI/CD Pipelines

    Cycode Leverages eBPF to Secure CI/CD Pipelines

    Cycode today added a Cimon extension to its application security platform that uses extended Berkeley Packet Filtering (eBPF) to thwart cyberattacks against continuous integration/continuous delivery (CI/CD) pipelines.

    Alex Ilgayev, head of security research for Cycode, said Cimon uses eBPF to inspect network connections, running processes and file modifications within a pipeline to learn standard behaviors. Armed with those insights, Cimon will then surface any anomaly in real-time, he added.

    DevOps teams can then craft and embed security and compliance rules within their pipelines based on the severity of the anomalies discovered, said Ilgayev.

    eBPF makes it possible to run sandbox programs at the kernel level without adversely impacting performance. In effect, eBPF bridges the boundary between kernel and user space by enabling developers to combine and apply logic across multiple subsystems that, historically, were completely independent of one another. That approach enables, for example, a security tool to scale to the point where it can identify threats at much higher levels of throughput to improve overall scale at a time when the volume of cybersecurity attacks continues to increase.

    Cycode is taking advantage of eBPF to enable DevOps teams to not only defend against known attacks involving malicious package installation, typosquatting, repojacking, dependency confusion, dependency hijacking and other types of dependency attacks but also zero-day threats, noted Ilgayev.

    Cycode provides a platform for mapping metadata and events using graph technology that makes it simpler for application development and cybersecurity to consolidate alerts generated by their DevSevOps tools. Most recently, Cycode added a Cycode Application Security Orchestration and Correlation (ASOC) module that will automatically discover all the tools that make up a DevSecOps workflow without requiring any integration effort.

    The approach enables the Cycode platform to discover, for example, dependency issues that would otherwise be missed by software composition analysis (SCA) or static application security testing tools (SAST).

    While a lot of progress has been made in terms of adopting DevSecOps best practices, many organizations are still struggling with securing their software supply chains. Most of the members of a DevOps team have limited cybersecurity expertise, so they need the help of a cybersecurity professional to determine what specific actions are required to remediate a vulnerability. Cybersecurity professionals, conversely, don’t have a lot of application development expertise.

    As the number of regulations specifically focused on application security steadily increase, every organization that builds software will soon need to embrace DevSecOps to better secure software supply chains. Unfortunately, developers have too often viewed cybersecurity as an obstacle to deployment while cybersecurity teams have historically considered developers to be a primary cause of the breaches they are expected to clean up. The first step toward bridging that divide is, of course, to realize that application developers and cybersecurity teams need to be invested in each other’s success.

  • Revolutionizing DevOps With Low-Code/No-Code Platforms

    Revolutionizing DevOps With Low-Code/No-Code Platforms

    The DevOps industry is growing at an incredible pace, with its worth exceeding $8 billion in 2022. Analysts predict that the market will experience a five-fold increase and reach almost $40 billion by the end of the decade. But with this growth, there is a significant issue within the DevOps chain that continues to escalate: A widening talent gap. The U.S. Department of Labor predicted that by 2030, the global deficit of development engineers will exceed 85 million. Additionally, the demand for DevOps professionals is expected to increase by over 20% annually throughout the rest of the decade. These conflicting trends present significant challenges for software and application companies. While there is a substantial opportunity to generate revenue by creating new and better applications, the shortage of skilled personnel to develop these products is a significant roadblock. Integrating low-code and no-code tools into the DevOps process could be a viable solution to address the talent gap. These tools offer various benefits and efficiencies, including streamlining the work of existing DevOps professionals and enabling organizations to expand their teams beyond traditional personnel sources. Leveraging these tools could give companies in the DevOps industry a competitive advantage.

    Challenges of Traditional DevOps

    Traditional DevOps practices pose significant challenges for companies that hinder productivity and overall success. The first significant issue is the talent shortage. According to a report by the Manpower Group, 75% of employers consider finding tech talent their primary concern. As the demand for experienced DevOps professionals continues to grow, it is becoming increasingly difficult for companies to find the right personnel.

    Another significant challenge in traditional DevOps practices is the high learning curve. The prediction by Gartner that 75% of DevOps initiatives would fail to meet expectations by 2023 highlights the severity of the learning curve and the challenges associated with adopting DevOps practices without proper training and experience.

    To avoid delays, increased costs, and suboptimal productivity, companies should explore innovative solutions such as low-code and no-code platforms. This would enable citizen developers to contribute to the development process and streamline infrastructure management processes, enabling greater efficiency and scalability in their DevOps practices.

    How Low-Code/No-Code Revolutionize DevOps

    Low-code/no-code platforms are gaining widespread recognition for their potential to drive app development across organizations, as Gartner predicts that by 2024, 80% of apps will be developed by non-IT professionals. The adoption of these productivity tools can bring significant benefits to the DevOps landscape, particularly in the following ways.

    Reducing Workloads and Stress
    By using low-code and no-code software, organizations can distribute basic app-building and basic development tasks across the organization, freeing up skilled developers’ time and reducing their workload and stress. This significantly improves the workplace experience and enables developers to focus their time on delivering more complex, high-quality solutions.

    Accelerating Innovation With Low-Code/No-Code Platforms
    Low-code/no-code platforms can accelerate innovation by enabling developers to quickly spin up proofs-of-concept for more complex software development tasks that require coding expertise. Ideas and solutions can be tested before investing time and resources in full-scale development.

    Creating New Roles and Opportunities
    No-code platforms can create new roles and opportunities within the enterprise, such as no-code projects focused on optimizing processes and building solutions. Citizen developers without coding experience can pursue new career paths and opportunities to contribute to their companies’ success. One example is applying no-code technology to digitize paper forms across organizations. Employees without coding experience can create mobile apps that speed data collection, improve data accuracy and allow for instant digital data sharing and analysis.

    Giving Developers a More Strategic Role
    With tactical software development carried out within business units, developers can spend more of their time focused on cutting-edge technologies like mixed reality, quantum computing, and AI. This can give them a more strategic role in the enterprise and enable them to focus on the “next big thing.”

    Considerations and Challenges

    While low-code/no-code platforms have the potential to offer numerous benefits to DevOps teams, it’s important to be aware of challenges that have arisen when pairing the two successfully, and how to avoid them.

    Poorly-Designed or Insecure Applications
    With non-IT professionals developing applications, there is a higher risk of introducing vulnerabilities that could compromise the security of the application and the organization. Additionally, the lack of oversight and governance could lead to poor coding practices and technical debt. For instance, the use of new-generation iPaaS platforms by citizen integrators has made it difficult for security leaders to have full visibility into the organization’s valuable assets. Attackers are aware of this and have already taken advantage of improperly secured app-to-app connections in recent supply chain attacks, such as those experienced by Microsoft and GitHub.

    Companies need to make sure IT staff carefully check how low-code and no-code technologies are adopted and how apps are reviewed in order to reduce vulnerabilities.

    Limited Customization and Scalability
    While low-code/no-code platforms can help speed up application development by up to ten times, their limitations can create hurdles when building large, complex applications. These platforms can be useful for basic application development, but they may not be suitable for complex or highly-customized applications. For example, if your app requires robust offline capability that handles conflict resolution and on-device offline storage, you’re better off selecting a low-code platform like Alpha Anywhere than a drag-and-drop app builder like Appypie, which is a fit for less complex apps.

    Complex Integrations With Legacy Systems
    As organizations try to integrate low-code and no-code applications with legacy systems or other third-party applications, technical challenges can arise. For example, if an organization wants to integrate a low-code application with an existing ERP system, it may face challenges in terms of data mapping and synchronization. Some low-code and no-code applications are built to export data and share it well, but when it comes to integrating event triggers, business logic, or workflows, these software solutions hit limits. Buyers need to consider their requirements carefully before making a purchase.

    To address the potential challenges of low-code/no-code platforms, organizations must establish governance policies and procedures to ensure adherence to security and quality standards. This includes implementing proper access controls with zero-trust security, data privacy measures and vulnerability management processes. Organizations should work with their low-code/no-code platform providers to ensure seamless integration with other systems and scalability to support evolving needs. Along with this, regular assessments and audits of applications developed using low-code/no-code platforms can also help identify and address security risks before they turn into significant issues.

    Conclusion

    The integration of low-code/no-code platforms into DevOps practices represents a promising solution to address current challenges in the industry. By leveraging these platforms, organizations can expand their teams beyond traditional personnel sources and create a more inclusive environment for non-IT professionals to contribute to the development process. The rise of no-code is a win-win for everyone, and as early adopters seize this opportunity, they can gain a significant competitive advantage in the market. The future of DevOps is exciting, and the potential of low-code/no-code development is limitless, unlocking the innovation potential of all employees and empowering them to make a difference in their organizations.

  • Technical Debt? No Sweat!

    Technical Debt? No Sweat!

    As a product manager, I dread the moment a developer says, “Wait a minute; I need to refactor …” (I wish it was just a minute). Something that should take two days starts taking three days and then a week. Over an application’s lifetime, the app starts accumulating technical debt. At that point, innovations become a smaller and smaller percentage of the work due to the vast efforts invested in the extra time required to support new developments.

    It is okay and natural to get into technical debt. As in finance, some people will take out loans to invest in something because they know that later they will be able to sell it for a higher price and pay off the loan with ease. Same with code. You take on technical debt because you want to develop the application faster and get the product or updates out as soon as possible. But in the end, the technical debt has to get paid. This creates friction between R&D and product, and although we both understand at some point that modernization is needed, it is difficult for the team to quantify. Due to all the long cycles, the complex QA, the increasing number of bugs and security issues, engineers start to feel frustrated. And as a product manager, I also feel frustrated when dealing with missed deadlines and inflated estimations.

    It’s not that we don’t want the developers to be happy and to invest in the code (and, let’s face it, in their own mental health, too), but we never know how much time and money is actually spent on technical debt versus how much is reallocated to innovation. For me, that was always a big question, but I never managed to move the conversation from, “I have a feeling,” or “The code looks ugly …” to “For every $1.00 I invest, X% is dedicated to maintenance.” How do we stop guessing and feeling we are in debt and actually start measuring it? And once we make technical debt tangible, when and where do we start modernizing?

    Every application’s innovation cost is affected by its level of technical debt. It’s important to determine how much money invested in the application is put toward innovation and how much is used to repay technical debt. In addition, there are classes of debt that add more complexity and risk overall.

    The newest versions of a monolithic application’s framework can be tagged as modern, aging or unknown (if the jar file isn’t found). This adds another layer of information when deciding what a modernization effort would entail and helps you focus first on aging frameworks that pose the greatest risk to enterprises due to the accumulation of technical debt and security concerns.

    Complexity, Risk and Debt

    The complexity of an application is determined by the degree to which class dependencies are entangled, reducing the level of modularity. A code risk relates to the length of the dependencies: How might a change in the application affect some of its seemingly unrelated components?

    These two metrics affect the architects’ ability to decouple functionality and create independent, isolated microservices in the future. At the end of the day, that is what forms the overall technical debt. Using the average of these three metrics, we can further prioritize applications in the portfolio. This provides insights into immediately actionable areas, such as our next metric.

    The process of modernizing takes time and money and, unfortunately, is a high-risk and often unsuccessful project. To make this process successful, it is first necessary to understand the cost of innovation, the complexity of the application and the risks involved. With these metrics at their disposal, R&D and product are well positioned for a comprehensive, data-driven conversation about modernization.

  • Report Surfaces DevOps Challenges for Mobile Applications

    Report Surfaces DevOps Challenges for Mobile Applications

    An assessment of 1,600 DevOps teams involved in building and deploying mobile applications found that 62% were adversely impacted by manual processes that slowed the rate at which these applications were deployed and updated.

    Based on the Mobile DevOps Assessment (MODAS) created by Bitrise, a provider of a continuous integration/continuous delivery (CI/CD) platform for building and deploying mobile applications, the metric measured the creation, testing, deployment, monitoring and collaboration phases of building and deploying applications.

    The survey also found (44%) of respondents reported their release approval process is mostly or entirely manual, with only 9% having fully automated application releases. Only 22% of teams said they’ve been able to complete internal release processes in less than an hour.

    The survey also found that nearly two-thirds of organizations (66%) have deployed applications that can’t be opened in two seconds or less, which is widely considered the accepted level of performance required.

    In addition, three-quarters of organizations (75%) required more than two days to address bug fixes. Only 21% of teams said that they had implemented some form of app performance monitoring to keep track of bugs, the report found.

    Daniel Balla, chief strategy officer for Bitrise, said MODAS applies many of the concepts from the DevOps Research and Assessment (DORA) metrics that Google now oversees. Those metrics, however, are not specifically designed to assess mobile application development initiatives, he noted.

    It’s not clear what percentage of applications DevOps teams are building today are deployed on mobile devices. But given the emphasis on digital business transformation initiatives, many of these applications are increasingly mission-critical to organizations. The general expectation among mobile application end users is that apps will be regularly updated with new functionality. However, if release processes are largely manual, regularly improving the user experience can become problematic. In addition to the increased likelihood that mistakes will be made, manual processes are often the reason why a vulnerability was introduced into an application environment.

    DevOps teams will also need to also consider the level of scale that will be required to support mobile app development, noted Balla. Many of the tools that developers rely on today to build applications were not necessarily designed to enable developers to build and deploy mobile applications at scale, he added.

    Finally, most enterprise applications need to run on multiple devices, so the tools used to create these applications can’t focus on applications that can only run on one platform, said Balla.

    Regardless of the approach to building and deploying mobile applications, the amount of focus on them within most organizations is high; any issues that arise are likely to be noticed by the highest echelons of an organization. That level of attention can easily put pressure on DevOps teams that frequently work on multiple projects. The challenge and the opportunity now is to create a set of DevOps workflows optimized for mobile applications that almost by definition require much more frequent updates than any other type of application.