devopsy.kinsta.cloud

Category: DevOps Toolbox

  • OverOps Integrates AI Code Analyzer With CI/CD Platforms

    OverOps Integrates AI Code Analyzer With CI/CD Platforms

    At the DevOps World | Jenkins World 2019 conference, OverOps announced it has integrated its namesake tools for analyzing Java and Microsoft .NET code at runtime with a variety of continuous integration/continuous deployment (CI/CD) platforms, including Jenkins, JetBrains TeamCity, Atlassian Bamboo and Pivotal Concourse.

    Eric Mizell, vice president of solution engineering for OverOps, noted that the more errors that are discovered by DevOps teams early in the development cycle, the less technical debt organizations must address after an application is deployed in a production environment. By pushing testing to further to the left of the application development process, the less troubleshooting will be required later on, he said.

    OverOps employs predictive analytics and machine learning algorithms to identify new, increasing, resurfaced and critical errors in a release. It then generates a code quality report that ranks all severe issues likely to impact end users and application functions. By integrating OverOps within the CI/CD pipeline, DevOps teams can use those reports to determine whether code is safe to promote or automatically block unstable releases from moving forward.

    In addition, because the machine learning algorithms surface the true root cause of an issue, DevOps teams can more efficiently remediate issues by routing code back to the development team responsible for all the issues that are being created downstream.

    Making testing an integral part of the CI/CD process not only tightens the relationship between developers and testers, but also in many cases enables developers to test their own code before submitting it for review.

    Mizell said the need to shift testing to the left has become more critical as customer tolerance for application errors is low, especially in use cases involving mobile applications—consumers are especially unlikely to give a mobile application a second chance after they’ve encountered an issue.

    In an ideal world, of course, testing tools that make use of machine learning algorithms would be employed to coach developers in a way that enables them to develop reliable code more consistently and faster. However, some organizations will use tools that leverage machine learning algorithms to identify developers who are not meeting expectations. That weeding out process is likely to begin much earlier in the application development life cycle as more advanced testing tools are embedded within CI/CD environments. Those tools won’t eliminate the need for developers and testers, but they do promise to increase dramatically the rate at which quality applications can be built and deployed at an industrial scale. Technical debt may never be completely eliminated, but at the very least the rate at which that technical debt is being accumulated should substantially decline.

    It may be a while longer before machine learning algorithms and other forms of artificial intelligence (AI) are employed pervasively across DevOps processes. In most cases, those algorithms will help developers write better code faster. However, it’s also apparent there will be other algorithms at work that one way or another ensure developers will have fewer opportunities to make mistakes in the first place.

    — Mike Vizard

  • GitHub Actions Advances Automation Strategy

    GitHub Actions Advances Automation Strategy

    GitHub Actions, a set of application programming interfaces (APIs) through which DevOps tools can automate workflows, is now available in beta.

    Previewed last year at the GitHub Universe event, GitHub Actions is intended to provide not only a way to automate responses to events occurring within a GitHub Repository but also share those workflows across multiple DevOps teams, said Max Schoening, senior director of product design for GitHub.

    Actions are based on YAML files, which makes it possible to write them in JavaScript or other programming languages or package them up as a set of containers. In either instance, they are designed to interact with the full GitHub API and any other public API.

    In addition, higher levels of automation enabled by GitHub Actions should make it more feasible for DevOps teams to test multiple versions of a project in parallel as workflows written in code replace manual processes, said Schoening.

    As more manual processes become automated, the number of IT teams who are intimidated by DevOps processes today should begin to decline. Organizations also should be able to apply best DevOps practices more consistently across multiple teams. Too often today the DevOps practices within the same organization tend to vary widely. Schoening also noted that given the open source history of GitHub, organizations will be able to see how workflows have been created for popular open source projects and then copy them.

    In addition, Schoening said the arm of Microsoft will continue to invest in analytics that will surface workflow recommendations that can be applied to any project regardless of the language employed or the platform on which it’s destined to be deployed.

    On one level, DevOps is all about a ruthless commitment to automation. But when automation goes wrong at scale, it can be extremely problematic. Rather than relying on “black box” approaches to automating processes, a truly open source approach to automation makes it possible for DevOps teams to see how a process is being automated and then extend it if they so choose, said Schoening. To help address the concern, GitHub Actions also provides access to live logs to provide real-time feedback as builds run, which Schoening said makes it easier for DevOps teams to debug automations created using GitHub Actions.

    It’s too early to say just how automated DevOps processes will get. There’s an emerging school of thought that contends the goal is to make it feasible for developers to spend 100% of their time writing business logic. It’s not clear whether that goal is achievable anytime soon, but progress is made with each update to continuous integration/continuous development (CD/CD) platforms. As complementary advances in machine learning algorithms and other forms of artificial intelligence (AI)—otherwise known as AIOps—occur, it’s apparent many manual DevOps processes will fall by the wayside.

    In the meantime, the workflows that make up any DevOps process should become increasingly sophisticated as advances in automation span everything from hybrid cloud computing environment to internet of things (IoT) deployments. The issue soon may not be how cumbersome any DevOps workflow is, but rather the potential limits of the imagination applied to automating them.

    — Mike Vizard

  • CollabNet VersionOne Advances End-to-End DevOps Strategy

    CollabNet VersionOne Advances End-to-End DevOps Strategy

    At its Agile 2019 conference, CollabNet VersionOne announced it plans to extend the capabilities of its software delivery and management platforms later this month as part of an effort to provide organizations with more visibility into how changing software development project schedules impact the business.

    Company CEO Flint Brenton said updates to the VersionOne value stream enterprise management platform will include a revamped user interface that provides more visibility into events occurring within the Continuum continuous integration (CI) platform.

    Brenton also said those updates will further advance adoption of agile frameworks such as the Scaled Agile Framework (SAFe), a prescriptive approach to combining best agile development and DevOps practices.

    While organizations may opt to employ VersionOne in combination with other CI/CD platforms, Brenton said CollabNet VersionOne provides a more comprehensive understanding of the impact changes to software development schedules will have on the business.

    As part of that effort, CollabNet VersionOne also announced VS Exchange, a marketplace for custom and preconfigured Continuum and VersionOne extensions and workflows, and enhancement to the Continuum TestDrive component within the company’s implementation of Continuum that streamline provisioning.

    With more organizations than ever starting to appreciate how dependent they are on software, Brenton said business leaders are now looking to exercise more control over software development projects. It’s no longer enough to generate more code, he noted; rather, DevOps teams are now being asked to generate more reliable code that has the greatest impact on the business faster. CollabNet VersionOne enables organizations to achieve that goal by providing a management platform in the form of VersionOne that is layered on top of Continuum.

    CollabNet VersionOne is now taking part in a race to infuse more business analytics into a software development lifecycle (SDLC) platform. While SDLC platforms have typically been employed to gather technical metrics, organizations now want to correlate that data against business metrics.

    Less clear right now is whether having access to business metrics will influence the selection of one CI/CD platform over another. Over time, the expectation is that various forms of business intelligence capabilities will be a standard capability of the platform, especially as IT leaders continue to assume larger business responsibilities in the age of digital business processes.

    It may be a while yet before business and IT roles start to converge. In the meantime, CollabNet VersionOne is clearly betting there will be a lot more collaboration between these two camps going forward. In many ways, the DevOps best practices that organizations have adopted to become more agile are about to be extended to the business processes enabled by software. Savvy business leaders will realize their ability to meet financial goals for any given quarter is tied to the timely manner in which new digital customer experiences are enabled. In fact, there may come a day when IT organizations are able to deliver software updates faster than most businesses will be able to consume it.

    — Mike Vizard

  • Twilio Adds DevOps Tool to Invoke Communications Services

    Twilio Adds DevOps Tool to Invoke Communications Services

    At its annual SIGNAL conference, Twilio today launched an initiative intended to make it easier to embed a variety of communication services within an application in the context of a DevOps process.

    Quinton Wall, senior director of developer marketing at Twilio, said the open source Twilio Command Line Interface (CLI) tool, now available in beta, will make it possible to incorporate Twilio cloud services within a larger DevOps toolchain.

    Twilio provides developers will access to a range of SMS, audio and video services that can all be incorporated into applications via application programming interface (API) calls. The pipelines created using those APIs now can be stored and shared via GitHub.

    The CLI tool also makes it possible to extend those services via Plugins, said Wall. In addition, DevOps teams can invoke an existing serverless computing capability from Twilio to invoke the company’s services using functions, added Wall.

    It’s not clear to what degree cloud services such as Twilio will be invoked using serverless computing frameworks going forward. Many of the capabilities that developers once were required to embed in their applications are set to become external services that applications call when needed by launching a function. While that approach makes the application more efficient, it puts additional pressure on IT teams to manage all the calls to various serverless computing frameworks within the context of already complicated DevOps pipeline.

    While serverless computing frameworks are still an emerging IT platform, the rate at which serverless computing frameworks are being adopted suggests the day when they are commonly included with a DevOps toolchain is not very far off.

    In the meantime, Twilio is clearly hoping that by making its communications services easier to invoke within the context of a DevOps toolchain will increase consumption. Twilio has long exposed REST APIs, but the CLI tool will make it easier for organizations to standardize on Twilio communication services across a range of applications. By exposing those services via APIs and a CLI tool, Twilio is betting that the days when end users opened a separate application to communicate are numbered. Instead, most users will invoke communications services within the context of, for example, a business intelligence application that is already open. That approach also eliminates the need to invest in dedicated network hardware to run unified communications applications that, from an API perspective, are often more difficult to invoke programmatically.

    As DevOps processes become more widespread, it will be interesting to see how many other providers of cloud services start to routinely make available CLI tools. Arguably, any provider of a cloud service that doesn’t make a CLI tool available will find themselves on the outside of a DevOps process looking in. Service providers that provide a CLI tool will be preferred among organizations that embrace best DevOps practices. In fact, the challenge DevOps teams soon may face is not whether there is a CLI tool available, but rather determining which of the many available best fits within the DevOps processes they have adopted.

    — Mike Vizard

  • Game On: Gamification for the Win

    Game On: Gamification for the Win

    Staying competitive in today’s fast-moving digital economy is easier said than done. Operating in a digital environment requires a significant shift in company culture and an agile software environment that accelerates time to value. Creating a DevOps environment helps companies keep pace, but it requires a workforce that is empowered, excited and motivated.

    Gamification offers a unique opportunity to continuously engage your workforce by applying game-design elements and game principles into a corporate setting, making work more fun. Companies can develop a team-oriented Pod model that incorporates gamification to improve employee engagement and productivity, enable team members to work more efficiently, accelerate the learning curve and deliver more sophisticated products to market faster.

    When I joined Cognizant Softvision as CEO, I wanted to empower our teams and promote a continuous delivery mindset by developing a delivery model that was customer-centric, differentiated and unique to each client without being prescriptive. Thus, Game of Pods was born.

    The global, Game of Pods gamification program is designed to provide timely and superior customer service. At a high level, Game of Pods inspires and measures team performance and delivery while encouraging and monitoring individual performance. During competition, the Pod and its members are recognized and rewarded for their collective and individual contributions with badges and trophies.

    We typically focus on the output of each pod, rewarding collective behaviors and achievements that help the pod reach higher efficiency and quality targets. Collective badges are awarded to the pod while personal and peer-to-peer badges are awarded to the pod members. Pod badges are earned as a team and are focused on the health of the project, performance of the pod, quality of delivery and alignment with client objectives. A leader board displays the badges each pod earns, their experience points and their trophies. Pod and individual recognitions are celebrated over email and across Facebook Workplace, and shared with all employees.

    While perhaps not as intense as “Game of Thrones,” Game of Pods is the epitome of gamification in action and enables organizations to reach a higher level of efficiency and professionalism while challenging employees to achieve personal goals in a fun, team-oriented process. In addition, Game of Pods offers other benefits such as:

    • A flexible model that can work in any client environment.
    • Team empowerment that incentivizes teams and individuals to achieve more.
    • An approach that encourages diverse thinking that recognizes and rewards teams and individuals for improvement.

    Game of Pods is most effective in organizations that embrace an agile mindset and understand the need for flexibility in today’s fast-moving environment. While gamification has come a long way, successfully incorporating it into the workplace can be challenging. However, integrating gaming into your organization can empower and excite employees, motivating them to overcome obstacles that might otherwise stand in the way of success and sustainable innovation.

    — Andres Angelani

  • Automated Certificate Management No Longer a Luxury

    Automated Certificate Management No Longer a Luxury

    On December 6, 2018, approximately 32 million customers of the UK telecom provider O2 woke up to a frustrating reality: The most widely used mobile network in the country was experiencing a day-long outage of its 4G mobile network.

    For some, not being able to check the weather forecast, traffic report or football scores was a minor inconvenience. For others, the impact was much more severe, as people throughout the country realized they couldn’t collect email, use their connected apps or perform any other task requiring data usage—no matter how critical to their business or personal lives. The world quickly came to realize that O2 subscribers in the UK were not alone: Other mobile providers around the globe, including Softbank in Japan, suffered similar outages in the same time frame.

    What caused this global outage? Was it a software bug? A poorly tested update, shared too soon? Maybe even a cyberattack targeting mobile network infrastructure? In the end, the explanation was much simpler: A digital certificate expiration in a back-end mobile data service from Ericsson caused a cascading systems failure, ultimately resulting in data outage for these mobile services. This issue highlighted the potential impact of certificate errors in our modern digital enterprise and the value of automation in managing such a critical process.

    Human Errors, Absences Lead to Outages

    While the O2 and Softbank service outages had serious consequences in their home countries—the U.S. equivalent would be a provider like Verizon losing data service for an entire day—they are hardly the only ones to experience this issue. Earlier this year, during the shutdown of the U.S. Federal Government, a number of important sites went down or lost functionality because no one was there to manually renew expiring web certificates. Even popular agencies such as NASA and critical services such as those provided by the Department of Justice were not spared, and both agencies and the citizens they serve were forced to watch helplessly as their certificates expired and services went down.

    Although it is of little comfort to the customers who woke up without mobile data or citizens who were unable to use government services, this scenario could easily have been prevented had automation been utilized to manage the certificates in question. When certificates are managed manually, it isn’t always easy to determine the cause of an outage like the one experienced by O2 and Softbank. An expiring certificate may not be the first answer that springs to mind, and may only be noticed after poring over code, looking at network monitoring and checking other potential culprits. Certificates are not always front of mind for IT teams, which underlines the value in simplifying their management.

    The technology sector has made significant strides in this regard, and organizations have tools available to them that can help streamline certificate issuance, management, renewal and revocation. Gone are the days when certificates had to be manually issued one at a time, and organizations kept spreadsheets of certificate expiration dates hoping they remembered to renew them. While we’re not able to say specifically why or how the root-cause Ericsson certificate was allowed to lapse, unexpected certificate expirations can be eliminated through proper use of certificate automation—making such a disaster unlikely to repeat itself if the proper steps are taken.

    Peace of Mind at Scale

    Getting started is easier than you might expect. The rise of automation in managing digital certificates presents organizations with a simple and exciting solution that extends well beyond just outage protection. Perhaps best of all, many organizations operating in a Windows environment may already have access to auto-enrollment and auto-renewal tools using the Microsoft CA, which has been a pioneer in the field of automated certificate services. Chances are, you may already be familiar with using Microsoft CA as an easy way to take care of your internal (private) certificates.

    But what about public certificates? True, Microsoft CA doesn’t handle those, so most organizations will need to find a third-party vendor to manage the SSL certificates for their web servers, load balancers, VPN devices and other networking gear. There are vendors capable of managing all certificate requirements under one roof, whether you operate in Windows, MacOS, Linux or other environments. The rise of standards like the Automation Certificate Management Environment (ACME) have made integrating different environments increasingly simple.

    Designed by the Internet Security Research Group, ACME has become a popular certificate management tool. More than 150 million websites and 130 open-source client tools use ACME. In fact, ACME is supported by a number of tools familiar to those who use DevOps to manage deployments, including Kubernetes, Chef, Ansible, Salt Stack, Terraform, Istio, Docker and others.

    As enterprises look to leverage DevOps with increasing regularity, effective certificate management can help facilitate container, micro-service and application security. Furthermore, orchestration tools such as Kubernetes support certificate management natively, leveraging ACME as the underlying protocol. The private keys may be stored in Kubernetes Secret or Hashicorp Vault so the certificate management system integrates seamlessly.

    Digitally signing your DevOps containers with a private CA helps verify the identity of a given container as it communicates over TLS while also preventing unauthorized applications—and the tools available to ACME users add significant value. Of course, this is just the tip of the iceberg—using automation to manage these certificates means plugging into a vast ecosystem of resources, reducing deployment time and eliminating the possibility of human error. It really is that simple.

    A New Automated Future

    Certificate management is hardly the only area where human error can have an outsized impact, but the O2/Softbank outage clearly illustrates severe effects such errors can have. Service outages, damaged reputations and frustrated consumers lie in the wake of poorly managed certificates, and organizations are increasingly turning to automation to solve the problem. As protocols such as ACME become integrated into an increasing number of commonly used web tools and outside vendors expand their ability to shoulder the certificate management burden, it will only become easier for organizations to incorporate automated elements into their own environments.

    — Abul Salek

  • Micro Focus Lays DevOps Foundation for RPA

    Micro Focus Lays DevOps Foundation for RPA

    Micro Focus has announced the general availability of Micro Focus Robotic Process Automation (RPA), which sets the stage for employing DevOps processes to construct highly automated business processes.

    Thanks to the rise of artificial intelligence (AI) and digital business transformation initiatives, interest in RPA has increased significantly. However, rather than merely using RPA to build bots to automate a narrow set of static processes, RPA is now leveraging machine and deep learning algorithms to optimize a wider range of dynamic business processes and adjust more easily to changes within an application.

    Travis Greene, senior director for IT operations management ay Micro Focus, said new capabilities such as object recognition technology included within Micro Focus RPA enables the platform to detect and automatically adapt to changes to the user interface.

    Other new capabilities now include the ability to visually or programmatically create workflows using a tool that records screen actions, the ability to more easily combine graphical and programmatic workflows spanning multiple platforms and the ability to deploy hundreds of thousands of bots as needed. A centralized dashboard manages the bots, all of which have unique IDs and encrypted, role-based credentials.

    As RPA and other forms of AI continue to be integrated and embedded with applications, Greene said it’s a matter of time before DevOps practices are extended to RPA platforms. Organizations will seek to train bots continuously as more data is made available, which in turn will drive updates to applications that are dependent on those bots. In most cases, depending on the complexity of the task, the bots will be built using a mixture of application programming interfaces (APIs), command-line interfaces (CLIs) and graphical tools. Organizations will need to define the processes to determine how and when each organization will opt to invoke one interface instead of another, either in isolation or combination, added Greene.

    Historically, organizations have been able to apply RPA to static processes with mixed success. With the rise of AI, the scope of those efforts has become more ambitious. Business leaders are too inclined to believe that just about every business process can be automated using a combination of AI and RPA. However, AI and RPA still are confined to relatively narrow use cases involving highly predictable outcomes.

    That’s changing, however, and RPA and AI are becoming more pervasive across the enterprise. DevOps teams will need to find ways to update both their applications and RPA/AI models without breaking one or the other. Most of the current RPA/AI models are highly sensitive to any change made to the application environment they are monitoring. And, unfortunately, the data scientists who are largely responsible for constructing those RPA/AI models don’t yet tend to have much of an appreciation for best DevOps processes. There will, however, come a day soon when these two worlds will collide.

    — Mike Vizard

  • How Serverless Is Impacting the IT Landscape

    How Serverless Is Impacting the IT Landscape

    Although most users will never realize it, with every digital data entry and exchange servers are consuming substantial quantities of energy to file, store and sustain that data’s availability.

    While the average consumer or office worker doesn’t consider the economic or environmental impact they have, IT and C-Suite teams are awakening to the problem and the awareness among energy concerns, legislators and thought leaders is growing. From the expanding troves of transactional data for AI to each video streamed on a smartphone or to a social media platform, hyperconnected companies are hungry to collect, understand, feed and leverage data on our digital habits. In today’s infrastructure models, data centers continuously burn through processing power to be ever-ready to those workloads—even when demand falls during regular off-peak periods.

    That’s one of the two real pushes behind the shift from legacy to new serverless infrastructures: waste, both environmental and economic.

    The world is waking up to the realization that the digital economy is consuming disproportionate levels of energy, putting new pressures on their organizations, their region’s energy infrastructures and, ultimately, on the planet.

    A recent report from Climate Change News predicts billions of internet-connected devices could produce 3.5% of global emissions within 10 years and the communications industry could use 20% of all the world’s electricity by 2025. In fact, data from statistics portal Statista notes the energy consumption of Facebook usage alone amounted to about 2.46TW hours in 2017, compared to 532GW hours in 2011.

    In the U.S. alone, data centers consume an astounding 90 billion kWh of electricity per year, the approximate annual output of 34 (500MW) coal-burning power plants. The data center consumption costs are baked in—organizations pay for always-on computing power to meet peak need regardless of how demand may fluctuate.

    The Promise and Potential of Serverless

    Cutting Energy Consumption: Serverless compute technology such as Amazon’s AWS Lambda or Microsoft’s Azure Functions are native cloud architectures designed to decrease consumption and increase agility and innovation.

    It provides a more efficient function-as-a-service (FaaS) consumption model that enables organizations to pay for what they use, rather than constant peak demand charges.

    Some of the economic impacts of serverless are obvious: Organizations that host their own servers have reconciled themselves to paying for those servers running at full power while sitting idle for much of the time. It’s like keeping your car constantly running, regardless of whether you’re going anywhere.

    In contrast, serverless not only promises far greater energy efficiency from the macro-infrastructure perspective, it also is event-driven. Organizations pay by the computing power consumed, so their costs reflect their actual server usage rather than paying for always-on capacity.

    The Shift Is On, From Managing Infrastructures to Solving Problems

    Reduced energy consumption and cost efficiencies are important for organizations and the planet. Two other major promises serverless offers are the ability to let organizations focus on creating applications and services without chaining them to infrastructure and innovation opportunities.

    Organizations shift the focus of their IT resources away from infrastructure maintenance—the provisioning, patching, operating system maintenance, managing runtimes and capacity planning overhead—to solving business problems. This means the focus of the organization’s IT resources can shift from managing infrastructure maintenance burdens to doing what IT was always meant to do: solve actual business problems.

    But there’s another aspect to serverless that’s even more exciting.

    Unlocking ‘Vendor Lock’ and Unleashing Innovation

    Every great technology breakthrough inevitably tears through old barriers and accelerates innovation. Serverless is no different.

    Furnace is a good example. It’s a new open source, serverless, streaming data processing platform for building big data solutions that are cloud platform and language-agnostic.

    It supports the use of applications that run natively in AWS Lambda, Microsoft Azure and Google Cloud, passporting data between platforms. Using coding languages including JavaScript, Node, Python and Golang, a growing community of developers are creating constructs to connect cloud-based applications.

    Some of the most urgently needed application construct types we’re likely to see in the near term will be for extracting and anonymizing old proprietary data for GDPR compliance, and for honeypot data collection and manipulation, with Elasticsearch and Redshift. Other application foundational on-ramps are in development.

    According to Danny Waite, CTO for the Furnace Ignite organization, the Serverless Furnace source platform was architected to allow deployment and data traversal into and across various cloud, on-premises and hybrid environments, putting the underlying efficiencies of serverless to work on practical applications.

    The application development platform is optimized to ingest massive volumes of data from different sources and in various formats. The Furnace open source community is soliciting feedback and community developers are working on various projects, with plans for constructs to harness and tap into the massive stores of now-untouched IoT data, among other sources.

    Greener, Cleaner, Streamlined Computing

    Serverless is a driver for ecologically greener, operationally cleaner and innovation-driving new computing. Its reduced data-center energy consumption, pay-per-use event-driven model, openness to innovation and seemingly unique ability to help align historical data with new regulatory requirements are all arguments for a shift in thinking and embrace of serverless. The improved economics are another compelling reason, though likely not a primary one for data-driven organizations.

    Serverless communities such as Furnace Ignite are emerging with tools and techniques for adoption. The Furnace application development platform has been architected in a way that allows it to be deployed into various infrastructures, such as cloud, on-premises or within hybrid environments, with the ability to ingest huge volumes of data from different sources, in various formats, so developers can take that data and make it useable. The whole process can be done with speed and agility and removes all the nuances normally associated with working with streaming data.

    Serverless platforms such as Furnace will continue to be developed to drive DevOps and meet the needs of the opensource community.

    — John Blamire

  • Low-Code Has Taken Development by Storm. Why Not the Web?

    Low-Code Has Taken Development by Storm. Why Not the Web?

    For more than a decade, development tools increasingly have made their way into the hands of less-technical people. On the web in particular, we’ve eliminated the webmaster as the middleman with content management systems and moved progressively toward a model where non-technical users could assemble their own sites with little to no coding experience of their own.

    Fast forward and today, the terms “no-code” and “low-code” are used to describe this idea. Furthermore, no-code and low-code tools have been on a decade-long rise, with an increasing impact on the web. Examples include:

    While this has been a strong, decade-long market trend, we’re only at the beginning. This trend won’t stop until new website experiences are automatically generated and optimized by machine learning.

    Trends Driving the Low-Code and No-Code Movements

    According to Wave, “In our survey of global developers, 23% reported using low-code platforms in 2018, and another 22% planned to do so within a year.”

    Major market forces driving this trend include a talent shortage among developers, with an estimated 1 million computer programming jobs expected to remain unfilled by 2020 in the U.S. alone. What’s more, the developers who are employed are often overloaded with work and struggle with how to prioritize it all. Some of this burden could be removed by low-code and no-code tools, allowing marketers and other non-technical professionals to do some of the development work themselves. In addition, the fact that technology has permeated every aspect of our lives, from our smartphones to our smart homes, has driven the need for more people to become creators.

    “As creating things on the internet becomes more accessible, more people will become makers. It’s no longer limited to the <1% of engineers that can code, resulting in an explosion of ideas from all kinds of people,” said Ryan Hoover, founder of Product Hunt, in a blog post.

    In other words, the supply of web creators must keep up with the demand for more digital experiences across more channels.

    But this does not only apply to individuals. Consider this: The typical large organization has to build and maintain hundreds of sites. These organizations need to build, launch and customize sites in days or weeks, not months. Today and in the future, marketers and other non-technical stakeholders can embrace no-code and low-code tools to develop websites rapidly.

    Abstraction Drives Innovation

    As predicted in my middleman blog post, developers won’t go away. Just as the role of the original webmaster has evolved with the advent of the CMS, the role of web developers is changing with the rise of low-code and no-code tools.

    Today, developers tend to focus on creating next-generation digital experiences that require new and emerging technologies not yet available in no-code solutions. In the process, they help invent and build new technologies such as React, Vue.js, etc.

    Successful no-code approaches abstract away complexity for web development. This enables less-technical people to do things that previously only could be done by developers. When those abstractions happen, developers can move on to the next area of innovation.

    Such abstractions are a good thing for both developers and non-technical website creators. When everyone is a builder, more good things will happen on the web. I was excited about this trend more than 12 years ago and remain excited today. I’m eager to see the progress no-code and low-code solutions will bring to the digital world in the next decade.

    — Dries Buytaret

  • Chef Brings DevOps to Windows Platform Migrations

    Chef Brings DevOps to Windows Platform Migrations

    Chef and Microsoft revealed today that they are working together to apply DevOps processes to accelerate the migration of Windows Server 2008 and SQL Server 2008 to more current versions.

    Announced at the Microsoft Inspire conference, the goal is to enable organizations to leverage Chef Enterprise Automation Stack (EAS), which includes an EAS Migration Accelerator for Windows that will scan existing .NET applications running on legacy Microsoft platforms to discover configuration and dependency details, then encapsulate that information as code in a way that enables the application to run on the latest version of a Microsoft virtual machine or as a container.

    Ewan Dalton, partner development manager for Microsoft, said there are roughly a half-million .NET applications running on platforms that are scheduled for end-of-life support beginning in January. In an ideal world, most of those applications would be modernized to be deployed on the Microsoft Azure cloud, said Dalton.

    Vikram Ghosh, vice president of business development at Chef, said rather than merely lifting and shifting legacy applications onto a new platform, Chef EAS will make it possible to employ DevOps processes to modernize how those applications are updated and maintained. Chef EAS makes it possible to, for example, scan, extract and package legacy applications and their dependencies, using source control repositories such as GitHub, and convert them into cloud platforms using pipelines such as Azure DevOps. Customers can deploy these application packages in Azure and run continuous security and compliance scans, added Ghosh.

    Chef EAS

    The biggest challenge many organizations face when trying to migrate applications is the developers who created the application haves long since left the company. As such, most organizations only have documentation, which is usually sparse. They then must determine whether it is worth modernizing the application or whether they should simply replace it. In cases where it is deemed that the business logic contained within that legacy application is still critical enough to continue running, they need to find a way to automate that process as much as possible.

    Longer-term, of course, most organizations will work to modernize legacy monolithic applications even further by slicing them up into a series of more manageable microservices. But many organizations are already running out of time when it comes to existing .NET applications. Once Microsoft ends support for the platforms they are running on, patches to address cybersecurity issues no longer will be provided as part of the standard licensing agreement. In effect, that means there is enough time between now and January to re-engineer an application. Chef EAS essentially throws organizations a lifeline to determine what they want to do next in terms of replacing a legacy application, said Ghosh.

    Of course, there will always be some subset of the IT community that will continue to run .NET applications on outdated Microsoft platforms. It’s also unlikely that any of those organizations will be embracing DevOps processes to maintain those platforms anytime soon.

    — Mike Vizard