devopsy.kinsta.cloud

Category: Doin’ DevOps

  • How IT Services Can Embrace Platform Engineering

    How IT Services Can Embrace Platform Engineering

    We are all familiar with DevOps as a newer approach to software development. The concept is designed to enable developers and IT operations teams to work together. Platform engineering, on the other hand, is a more mature, older approach that has become new again.

    Platform engineering, at its core, is the concept of productizing your internal development platforms to make it easier for developers to work. It is an emerging technology approach that can help accelerate the delivery of applications and the pace at which they produce business value. More recently, companies have grown their complex software architectures which have created silos for the teams that manage these various architectures. There may be multiple teams with various specialized skill sets and a single DevOps engineer who takes care of the continuous integration (CI) jobs to deploy and release to production.

    Now let’s imagine that you have 10 squads that focus on building and maintaining different applications. Now all of these teams are building and operating 10 different platforms to run their applications, which creates inefficiency across the teams and reinforces silos. In this scenario, teams may spend half of their time building and maintaining the platforms instead of delivering business value. This creates a large cognitive load on developers.

    This model becomes very hard to scale. Even though you have these squads managing their own infrastructure and platforms, you may find gaps because there is no centralized standard. So how do platform engineering concepts help with these complex landscapes and boost efficiency?

    The Consulting Mindset

    Platform engineers take all of the tools used to run an application across your various teams and standardize their usage. This enables self-service capabilities for your engineering organizations. Platform engineering can help centralize how you are deploying and running your applications across a complex software landscape. This includes not only the standardization of tools being used but also documentation and processes.

    Establishing platform teams requires a consulting mindset and thinking about what resources, services and components can be centralized to better serve the rest of the organization. Some may refer to this as the center of excellence (COE) model, or simply IT for IT. This boosts efficiency and cuts down the time to delivery by providing a central set of tools and platforms for your engineering organization. Many may see platform engineering as a cost center, but the ROI is higher-quality releases, a standardized way of developing and delivering software and shorter delivery times.

    Applying This Concept to IT Services Firms

    In my consulting days, I worked for firms that focused on delivery for the Salesforce platform. We often had complex projects that we needed to deliver for large enterprise customers who had multiple applications integrating into their CRM. Each project team often had a different way of delivering and developing based on the customer’s needs. This created specialized skill sets, but we had no standard way of developing and delivering. Investing in a platform engineering team to support the delivery organization can add immense benefits for large consulting firms, enabling them to standardize the tools and platforms being used to run and deliver applications at scale.

    Having a centralized place for your developers to go for process, documentation and tools to help them build and run applications can increase the speed at which they deliver. The efficiencies gained in having a smoother self-service flow for your developers and cutting down the delivery time are worth the investment. It brings significant long-term value that the customer will experience long after the engagement is completed, which can greatly impact future considerations for your firm.

    IT services firms should find ways to align and centralize their technologies with platform engineering concepts. You may not be able to exactly build out an internal developer platform, but adopting some of the core concepts will help you be more efficient as an organization. For example, if you are an IT services firm specializing in delivering applications on the Salesforce platform, look for extensible DevOps platforms that can support your development organizations.

    Also, look for ways to enable a self-service workflow to make it easier for your developers to work and scale. This may include investing in a platform engineering function to support the rest of the delivery organization. By establishing platform engineering concepts, you will be able to cut down the delivery time and create consistency in how you deliver and deploy applications for your customers.

  • How Automation Enables Remote Work

    How Automation Enables Remote Work

    In recent years, the world has witnessed a significant shift towards remote working, largely driven by global events such as the COVID-19 pandemic. This transformation has necessitated the adoption of new tools and strategies, with automation emerging as a key enabler of effective remote work.

    So, what does automation mean in this context? Well, it’s the use of technology to carry out tasks with minimal human intervention. It’s a powerful tool that can streamline processes, boost efficiency and cut down on errors, making it an invaluable resource for companies navigating the complexities of remote work.

    The Rise of Remote Work

    According to McKinsey, a whopping 58% of Americans now have the opportunity to work from home (WFH) at least one day per week. And 35% have the opportunity to WFH for the totality of their work responsibilities.

    This shift has brought numerous benefits to both employers and employees. For employees, it means more flexibility, less commuting and a better work-life balance. For employers, it broadens the talent pool, cuts overhead costs and can even boost productivity. However, remote working also presents unique challenges, such as:

    ● Communication Barriers: In a remote work setup, maintaining clear and effective communication can be a challenge. Without face-to-face interactions, messages can be misunderstood or overlooked. This can lead to confusion, mistakes and a lack of cohesion within the team.

    ● Difficulty in Tracking Productivity: When employees are working from different locations, it can be difficult for managers to monitor their productivity. Traditional methods of tracking work, such as observing employees’ work hours, are not effective in a remote work setup.

    ● Maintaining Team Cohesion: Building and maintaining a strong team culture can be more challenging when employees are working remotely. Without regular in-person interactions, employees may feel isolated and disconnected from the team.

    ● Cybersecurity Concerns: Remote work often involves using personal devices and home networks, which may not have the same level of security as office networks. This can expose companies to increased cybersecurity risks.

    The Role of Automation in Remote Working

    Now, let’s delve into the ways automation plays a pivotal role in remote work.

    Automation and Communication
    In a remote work setup, effective communication is paramount. Automation tools such as Slack and Microsoft Teams facilitate better communication by automating tasks like scheduling meetings, sending reminders and translating messages.

    These tools can also automate the process of organizing and archiving conversations, making it easier to retrieve information when needed. Additionally, they can automate the process of updating team members about project changes or important announcements. These features ensure that all team members are on the same page, enhancing collaboration, reducing the chances of miscommunication and ultimately leading to a more cohesive and efficient team.

    Automation and Human Resources
    Automation in human resources (HR) is a game-changer in remote work settings. HR automation software can streamline recruitment, automating resume sorting, interview scheduling and follow-up emails. It can also enhance onboarding, automating welcome emails and account setups.

    Performance management can be improved with automated feedback collection and goal tracking. Furthermore, e-learning platforms can automate training assignments, progress tracking and certification issuance. This ensures a consistent, efficient and effective HR process regardless of location, enhancing the remote work experience.

    Automation and Project Management
    Project management can be a challenge in remote teams due to the lack of face-to-face interaction. Automation tools like Asana and Trello simplify this process by automating task assignments, tracking progress and generating reports.

    These tools can also automate the process of setting deadlines, sending reminders for upcoming tasks and notifying team members about changes in project plans. This allows managers to keep track of projects in real time, ensures that deadlines are met and helps in identifying potential issues early on, making project management more efficient and effective.

    Automation and Employee Monitoring
    Monitoring employee productivity and performance is crucial in a remote work setup. Automation tools like Time Doctor and Toggl track time spent on tasks, providing valuable insights into productivity.

    These tools can automate the process of generating productivity reports, tracking breaks and even monitoring website and app usage. This data can be used to identify bottlenecks, improve processes and ultimately increase productivity. It also allows managers to provide constructive feedback and tailor their management strategies to individual employees’ work habits.

    Automation and Cybersecurity
    Cybersecurity is a critical concern in remote work setups, which often involve multiple devices and networks. Automation plays a key role in maintaining security by detecting threats, installing updates and performing backups. Cybersecurity tools can automate the process of scanning for viruses, blocking malicious websites and encrypting data.

    They can also automate the process of updating security protocols and alerting users about potential security threats. This ensures that data remains secure, protecting companies from potential security breaches and giving employees peace of mind to focus on their work.

    Final Thoughts

    Automation plays a crucial role in enabling effective remote work. By increasing efficiency, reducing errors and saving costs, automation not only makes remote work possible but also profitable. As the future of work continues to evolve, we should expect to see more and more of the remote working processes being handled by automation tools.

  • Google Calls Microsoft Azure Anti-Competitive ¦ Gen-Z Can’t Email

    Google Calls Microsoft Azure Anti-Competitive ¦ Gen-Z Can’t Email

    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: Google complains to the FTC about Microsoft market abuses, and new graduates don’t know how to office. (more…)

  • Developers’ Role in Protecting Privacy

    Developers’ Role in Protecting Privacy

    We live in a world where we always expect things to happen seamlessly. Every time somebody walks into a café and signs in to the free WiFi and opens their Instagram or TikTok to stay up-to-date with trends and friends or retrieves a discount from a retailer by joining their newsletter circulation, rarely do they stop to think about how that convenience and value is derived.

    Technology is the key enabler working away in the background, and developers and DevOps teams are making that happen. Underneath the slick interfaces of the apps and websites that provide these highly efficient and personalized experiences is a complex machine that relies on data to fuel it, built by developers and delivered by DevOps teams.

    In many ways, data is a two-way exchange, and those end-users that are aware of this give and take appear to be happy with how the relationship works.

    Indeed, several surveys in recent years suggested that the majority of consumers are happy to share their data with companies if it improves their experience. Furthermore, a significant minority are still comfortable if they have no control over who sees their data, there is no clarity around how data is stored and used, even if the organization in question has a poor reputation for data privacy.

    The Privacy Balancing Act

    So, if most people already accept data trade-offs in some shape or form, should developers still care about building applications and solutions that guarantee data privacy?

    The short answer is yes, but as developers, that involves a tricky balancing act.

    Although sharing data has become commonplace in exchange for benefits and value, consumers are becoming more aware of privacy issues. Take the EU’s General Data Protection Regulations (GDPR) as an example. Over the past five years, awareness has more than doubled in notable European markets such as the UK, Spain, Germany, the Netherlands and France.

    Meanwhile, there is also commercial pressure, as employers rely on developers to innovate to remain profitable. At the same time, customers expect brands to be responsible with their data, and failure to do so at the expense of trying to commercialize a new application could be detrimental. Indeed, while the pandemic may have ushered in significant changes and altered consumers’ attitudes toward data privacy, end users remain unwavering about the importance of security.

    Maintaining this balancing act is becoming increasingly complex to achieve. However, the question of data privacy is becoming a key business priority, and that means developers have a big opportunity to show their commercial value to their organizations. Indeed, companies cannot afford to get the balance wrong, and developers are central to creating the perfect formula.

    In fact, the privacy conundrum has been around for a long time.

    When the internet was created, privacy was not considered an issue because all content accessed online was deemed to be public. Nothing was encrypted; the introduction of email complicated things, not least because anybody on the internet could, theoretically, intercept personal data and read private messages.

    This prompted the emergence of the cypherpunks, a group of cryptographers who began to contemplate what the future of digital privacy might and should look like. They started to create the tools they believed the world needed to safeguard data privacy–today, their mission is carried on by developers who value user privacy.

    Why Developers Need to Be Familiar With FHE

    However, securing the transmission of data is not enough, as many breaches still occur because data isn’t encrypted during processing.

    So, in a world where more and more data needs to be shared to deliver the sort of experiences consumers expect, is it inevitable that privacy and security will be compromised as the volume of data exchanges grows? Not necessarily.

    Fully homomorphic encryption (FHE) offers a solution, allowing developers to build applications and run services without needing to see or secure the underlying data. This is because FHE enables data to be processed blindly without having to decrypt it at any stage. FHE offers a way for developers to maintain that all-important balancing act between maintaining privacy and offering value to both business and customer.

    In FHE, to guarantee a user’s data privacy, all data is encrypted by the user with their own secret key. Users of a particular service, such as an online medical portal, will use a secret key to send their encrypted data to a server where blind processing takes place. The result is also encrypted and sent back, the user again using their secret key to decrypt the information.

    What this means is that, because data is encrypted end-to-end, the company providing the service can do so in a way that keeps the same customer experience, even though they cannot see the data that is being shared and sent back. From a security perspective, this is also critical. Governments, attackers and service providers cannot see the exchanged information because they do not possess the key–they also cannot break it, as the encryption used in FHE can resist attempts made even by powerful quantum computers.

    Privacy can also be protected during larger-scale data exchanges that underpin collaboration between organizations and nation-states on numerous strategic programs, with each contributor able to add their value knowing that their intellectual property and sensitive information is not compromised.

    Looking ahead, if developers can embed FHE into their practices on a broad scale, then a key milestone for privacy is within reach. Rather than being viewed as an objective relating to digital interactions, privacy can be treated as a naturally occurring by-product of every application, piece of software and service that the developer community creates.

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

    Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    Indeed.com

    SAP
    San Francisco, California
    DevOps Engineer
    $141,378 to $162,000

    LinkedIn

    Colgate-Palmolive
    Piscataway, New Jersey
    DevOps Lead
    $112,000 to $164,800

    CareerBuilder.com

    Northrup Grumman
    Dulles, Virginia
    Principal DevOps Engineer
    $104,600 to $157,000

    SimplyHired

    Crate & Barrel
    Northbrook, Illinois
    DevOps Engineer
    $99,100 to $125,000

    Dice.com

    Tata Elxsi Ltd.
    Philadelphia, Pennsylvania
    DevOps Engineer
    $80,000 to $100,000

  • 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.

  • Avoiding the Pain of a ‘Resume-Driven Architecture’

    Avoiding the Pain of a ‘Resume-Driven Architecture’

    Successful new technologies follow a predictable arc, from initial innovation to technical gold rush and, ultimately, to mass market adoption. As a consequence, they achieve strong standardization and productization. Being highly attuned to where a specific field lies on the maturity arc is how you yield the greatest benefits to a business. But what happens if your developers are not thinking about this, too? You end up with what I call a “resume-driven architecture,” and it can be highly costly to your business.

    A resume-driven architecture occurs when the interests of developers lead them to designs that no longer align with maximized impacts and outcomes for the organization. Often, the developer clings to a technology that provides them a greater level of control and, at least initially, a higher salary. Meanwhile, the organization gets an architecture that only a handful of people know how to manage and maintain, limiting the available talent pool and hindering future innovation.

    To understand why this happens and how to avoid it, it’s helpful to look at this technology arc in more detail. It’s a pattern that has played out up and down the stack, with technologies like big data platforms (now dominated by Snowflake and Databricks), Kubernetes and even the broader move to the cloud. Failing to grasp this concept of a resume-driven architecture can increase costs and hold back innovation.

    Here’s how this technology arc typically plays out, using Apache Spark as an example:

    • Stage One: A technology breakthrough like Spark emerges, providing a significant advantage to early movers.
    • Stage Two: Other companies see the benefits, and the technology receives widespread interest. Specialists are in high demand and command big salaries. Many adjacent professions naturally invest in becoming Spark experts.
    • Stage Three: The technology matures and reaches a level of standardization with an ecosystem of tools and services around it. Specialized knowledge, such as how to tune your Spark job parameters, becomes less valuable.
    • Stage Four: Mass convergence, productization and simplification occurs. As examples, Databricks becomes the primary Spark vendor and launches SQL warehouses for easier data processing. Snowflake launches Snowpark for Python as a simpler model than classic PySpark jobs. Nobody worries about tuning most parameters anymore as the underlying technology becomes part of the stack: Powerful but almost invisible.

    It’s important for businesses to take advantage of this productization stage when it comes along. There’s no sense in investing resources in a bespoke architecture if it’s not providing you with any differentiation—especially when competitors are achieving the same outcome with fewer resources.

    Moreover, getting stuck in a Stage Two mindset when the field moves on to Stage Three (or, worse, Stage Four) and cuts you off from the next wave of innovation. Subsequent technology breakthroughs often build on top of—and interoperate with—the previous technology layers. If you’re stuck with a custom architecture when the industry has moved on, you can miss out on the next wave of innovation and fall further behind competitors.

    The problem is, developers who’ve made a great career from implementing custom architectures are often reluctant to move on. After all, mastery of that previous innovation is what got them to where they are. They may not have realized that the world has progressed around them, or they may worry a standardized architecture with managed services and off-the-shelf products undermines their power and autonomy. This is how organizations fall victim to a resume-driven architecture. I’ve observed this several times when speaking with engineering leaders, and it’s become more common with the rapid innovation happening around data.

    As engineers, our value is in building things and, ideally, in solving innovative, artisanal problems. But this identity and desire can confuse what we want from our own jobs with what our team needs from us. When standard patterns and standard products emerge, we need to adopt them because that’s the way to maximize our impact and ultimately free our time and energy to move further “up stack” and have an even greater impact.

    Developers who would rather stick to a custom architecture often argue that they can squeeze out greater performance, but this is rarely a justification. You may end up with an app that’s 10% faster, but rarely does that come close to making up for the time and energy invested, the loss of flexibility and, ultimately, being held hostage by your own technology stack.

    So how does an organization avoid the trap of a resume-driven architecture? Strong leadership is key. Look critically at the business and ask which areas of your stack are truly differentiators because it’s only those areas that may—just may—justify a unique architecture. If you do go that route, it needs to provide huge benefits to the business to be worthwhile.

    For example, “data” is not in itself strategic to you; every company is now a data company, and the vast majority of things you do with it—how you source, store, process and distribute data—is no different from what everyone else is doing. What does matter are the data products that fuel your business and, most importantly, how fast you can build them.

    That’s why, as a developer or engineer, bespoke stacks are not your friend. Instead, architect your platform in a way that allows other developers to onboard quickly; that allows you to upgrade and swap out components easily over time and that doesn’t leave you held hostage to a developer whose main interest is retaining their value by sticking with an unnecessarily complex architecture.

  • 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.

  • The API Life Cycle Mixer’s Manual: What Goes Into a Single Source of Truth?

    The API Life Cycle Mixer’s Manual: What Goes Into a Single Source of Truth?

    In bartending, the mixer’s manual is a trusted source of information. These books can contain hundreds of recipes for classic cocktails, some of which might be 100 years old, while others might be for drinks that only recently arrived on the scene. Mixer’s manuals also can be great sources of inspiration for new, yet-to-be-tested recipes for exciting additions to a bar’s or restaurant’s offerings. This balancing act of preserving the old while encouraging exploration into the new can provide a valuable lesson for API development in the software world. An API’s “single source of truth” is, in many ways, the software organization’s own mixer’s manual. This is especially true when the right approach is taken to ensure that software remains functional and performant and serves up experiences that delight customers and keep them coming back for more.

    The Rise of APIs and Mixology

    While we might think of mixology and the mixologists who practice this craft as relatively new terms, the first recorded use of the word “mixologist” dates back to 1852 and “mixology” followed shortly after.

    Just how similar are the work, mindsets and passions of mixologists and API developers and designers? Check out this definition of a mixologist and count the similarities for yourself:

    “The term ‘mixologist’ refers to someone who studies the history of mixed drinks, has a rich appreciation of the ingredients and techniques used and regularly creates new and innovative mixed drinks … their job title implies that they do a significant portion of their job behind the scenes, creating new craft cocktails and putting their signature twist on existing favorites.”

    The best API developers, designers and architects of the world should recognize a lot of the above in their own work. They have deep respect for their craft and are always honing it further. They seek to understand the tastes and palates of their consumers. They factor in other stakeholders’ inputs, they test, iterate and test their creations again before “serving” those APIs to production.

    Like mixologists and bartenders (if you see them as two different roles), every professional along the API life cycle should understand the needs of consumers, customers and the business–and then design and develop their APIs accordingly. An essential part of this process is continuous validation and adaptation to market requirements.

    Maintaining Confidence in Ever-Changing Recipes

    Changes to APIs, even minor ones, can have significant downstream effects. And the same can be said for tweaks made to an age-old cocktail recipe, where adding or removing a single dash of this or that can completely change the flavor of a drink … as well as people’s interest in it.

    While there’s no “standard” rate of change to APIs to plan for, you can expect changes to be needed with each new software release. This could mean changes are being made (and need to be tested against and validated) every few weeks, every month or even every day, depending on your release cadence. There also can be as-needed, ad-hoc changes.

    What’s crucial for teams to ensure is that these changes do not disrupt an API’s functionality or performance. To make this possible, teams are increasingly leveraging API contract testing to provide a safety net of sorts. This comes in the form of testing that validates changes against a “contract” that details an API’s original, agreed upon and, therefore, required functionality.

    The ability to foresee the impacts of changes to APIs can depend on the maturity of an engineering team and its ability to collaborate across departments, time zones and varying levels of technical expertise. Tools and guidelines that promote standardization and collaboration can prevent mishaps from overlooking or being blind to negative downstream effects.

    Documentation is Key

    Whether we’re talking about being able to trust a single source of truth for the most up-to-date version of a published API or the latest edition of a mixer’s manual for tried-and-true drink recipes, clear and concise documentation is key. But it’s also not enough for this documentation to simply exist.

    It seems like common sense—although you’ve probably worked somewhere where it wasn’t—that your API documentation also needs to be easily accessible, understandable and usable. Ensuring all of these things leads to smoother onboarding and a positive developer experience and, ultimately, to wider adoption of a functional, performant API that meets or even exceeds expectations.

    API documentation is often the first point of contact a developer has with an API. It serves as a guide, walking developers through the API’s features, endpoints, request/response models and error messages. It also provides insight into the underlying business logic and unique characteristics of an API.

    Good API documentation follows the principle of a single source of truth, meaning that it should be comprehensive, up-to-date, and consistent. It should always mirror the actual behavior of the API, reducing the guesswork for developers and minimizing the potential for misunderstandings and errors.

    Just as a mixologist relies on a detailed and accurate cocktail recipe to deliver a pleasing experience to a patron, API developers depend on good documentation to create and deliver useful, value-add APIs and powerful applications.

    Continuous Improvement = Continuous Education

    Like a mixologist who meticulously adjusts the ingredients of a cocktail or who creates new cocktails to meet the evolving tastes of customers, developers must constantly adapt their APIs to meet changing market demands, business needs and industry standards.

    This is achieved through a potent blend of market research, collaboration, adherence to standards and governance and meticulous testing. However, as software development, testing and deployment technologies and processes continue to evolve, the tech industry must continue educating itself and refining its practices.

    With a mindset focused on constant learning and continuous improvement and a dependable single source of truth as their guide, development teams can confidently serve up exceptional API experiences in every release. In the end, the aim is to create APIs that are reliable and easy to consume and that meet the unique needs of the moment–much like a mixologist’s perfect beverage.

  • 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.