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  • WideOrbit Releases WO Network 2021 with New Revenue Generating Features

    Marks key milestone in automation for material instructions and ADU planning

    San Francisco, CA, July 14, 2021 – WideOrbit, the market leader in broadcast TV inventory and revenue workflow management, today announced the latest release of WO Network, the company’s flagship network ad sales and commercial operations platform. Already the cornerstone of business operations for leading national, cable, and broadcast TV networks, the 2021 release includes new features and enhancements to help networks generate new revenue, reduce costs, and improve efficiency.

    While working to help customers navigate and innovate within a rapidly changing industry landscape, WideOrbit also remains committed to working closely with customers to help them improve their existing processes through continuous improvement in our core products. That commitment is evident in the newest release of WO Network, marking a significant milestone in the industry with the introduction of the Electronic Material Instructions module, the first automated solution to address the long-standing need to simplify and streamline the traditionally cumbersome material instructions process.

    A licensed module for WO Network, Electronic Material Instructions integrates with several leading material instructions providers, including ITN Networks, ECN, and PremiumMedia360, with other integrations coming soon, including Warren Lamb. These integrations help networks save time and money by simplifying the exchange of new and revised material instructions between buyers and sellers.

    The WO Network 2021 release also introduces new functionality for Sales teams, including the Master Deals Wizard, a centralized location to view and manage all deals sold under a single proposal. The ADU Prediction Tool, now widely available with WO Network 2021, helps networks increase revenue and reduce liability by minimizing both over-and under-delivery, using predictive analytics to identify the number of Audience Deficiency Units (ADUs) needed to deliver on a deal.

    “With our 2021 release of WO Network, WideOrbit is excited to continue our tradition of ongoing innovation and investment in improving our core products,” says Arden Adair, WideOrbit’s Senior Director of Product Management for WO Network. “Both the Electronic Material Instructions module and the ADU Prediction Tool are game-changers for our broadcast and cable network customers, promising long-term, positive impact on revenue growth, cost savings, and improved efficiency.”

    WO Network 2021 is now available for general release. Please contact us for more information on how to upgrade your existing version or to learn more about WO Network.

    For more information on the new features and enhancements available with WO Network 2021, as well as improvements included in previous releases, request a recording of our recent webinar, One Platform, Multiple Solutions: WO Network.

    About WideOrbit

    WideOrbit helps media companies do more business by making it easier to buy and sell advertising. WideOrbit is the system of record for more than $38 billion in advertising transactions annually. Say hello to a Wider World with WideOrbit, the one platform that ties everything together, from pitch to payment. In a rapidly evolving media landscape, doing more business means doing less paper-chasing, less chair-swiveling, and less data re-re-entry. Only WideOrbit brings a Wider-World approach, providing the broader capabilities, bigger insights, and better connections that media companies need. That’s why so many industry leaders – including A+E Networks, Disney|ABC, AMC Networks, Hallmark Channel, ViacomCBS, The Weather Channel, and Univision – have partnered with us since 1999.

    WideOrbit is headquartered in San Francisco with offices worldwide. Learn more at wideorbit.com.

  • Using ML/AI to Support Infrastructure Monitoring

    Using ML/AI to Support Infrastructure Monitoring

    Successful infrastructure monitoring enables IT teams to ensure constant uptime and performance of their company’s systems. Technologies like machine learning (ML) and artificial intelligence (AI) benefit infrastructure monitoring by more quickly collecting and analyzing data from all of the hardware and software components that comprise the IT stack. Infrastructure changes are occurring faster than ever before, but complex systems, the unique nature of applications and lack of IT skillsets can cause challenges when integrating with these newer technologies. However, it’s more important than ever that sysadmins and DevOps teams understand how ML and AI can mitigate these roadblocks, support them in staying on top of infrastructure performance and rapidly address issues that arise.

    Intelligent Monitoring Support for Complex Systems

    The most tangible result of intelligent infrastructure monitoring tools and processes is near-immediate alerting of performance and uptime issues, which can then be addressed in an efficient and effective manner so no business interruptions occur. However, complex systems can stunt these benefits if ML and AI are not being used and manual monitoring protocols are still in place.

    Tools that use ML or AI lessen the work of IT staff immensely, freeing up critical business resources and aiding in overall productivity. Both technologies can automatically identify and update all IT stacks that comprise an enterprise’s infrastructure to keep systems up-to-date and aligned with established key performance indicators (KPIs). In addition, intelligent offerings can detect and factor those metrics against set standards so that early alerts to an “unhealthy” section of infrastructure can be identified, even as the IT stack is constantly changing. This drastically speeds up troubleshooting efforts.

    Differentiation in Applications

    The different applications supported by the various IT stacks will most often have unique service-level agreements (SLAs) for their performance and uptime, as well as remedies or penalties should those service levels not be achieved. Plus, system loads that stress the underlying infrastructure are frequently changed. For these reasons, it is important to identify what constitutes a “healthy” IT stack so that these minute parts of the infrastructure are not overlooked due to the variation involved.

    ML and AI can be programmed to track system baselines that support a “healthy” IT stack. These technologies are particularly great at finding novel and unusual patterns in data. As the monitoring and observability landscape becomes more complex over time, driven by real changes in how developers build applications and systems, the ability to spot and detect such patterns in data can be crucial in helping make sense of it, further cutting down efforts on manual searching, detective work and “death by dashboards,” which we’ve all experienced at one time or another.

    Supporting IT Team Skills with Intelligence Technology

    The role of sysadmins—and to a greater extent, developers—has shifted over the past few years to become nearly as complex as the infrastructure they oversee. Nowadays, it seems as though developers are required to have expertise in all aspects of infrastructure, from monitoring to Kubernetes to machine learning. This can take quite the toll on developers who possess such skills, but in a more realistic sense, developers that can do all these things are very hard to come by. The lack of these skillsets is pervasive in the industry, which is why ML and AI can be seen as supporting technologies—they can fill in these gaps, to an extent.

    With built-in intelligence and automation, ML/AI can enable even the most inexperienced sysadmin or DevOps professional to monitor complicated infrastructure like a pro, taking on most of the time-intensive work around collecting and analyzing the data and identifying where to troubleshoot. The main goal is to put humans in the driver’s seat, utilizing ML and AI for granular discovery of system issues, providing the metrics or charts that might be most relevant to IT staff as they troubleshoot their system and reducing the cognitive load of developers.

    With the vast benefits that intelligent technologies possess, integrating them into your IT stack can help mitigate challenges experienced with complex systems, application differentiation and the skills deficit experienced in the IT team. The important ingredient in making ML and AI effective in infrastructure monitoring is using tools that incorporate the right formulas, algorithms and automation that can best help determine success when it comes to your desired outcome.

  • Engineering Applications for DevOps (Part 4)

    Engineering Applications for DevOps (Part 4)

    This blog series explains how to engineer applications for DevOps.

    Topics covered in this blog series:
    • Factors to decide whether an application is a good candidate for DevOps.
    • Practices to engineer designs for DevOps.
    • DevOps applied to enterprise apps and software services.
    • DevOps applied to COTS systems.
    • DevOps applied to manufactured (embedded) systems software.
    • Five levels of application maturity.

    This blog covers DevOps applied to commercial off-the-shelf (COTS) systems. You can read part one here, part two here and part three here.

    DevOps Applied to COTS Systems

    I often hear that DevOps does not apply to systems that use commercial off-the-shelf (COTS) software. The idea that DevOps cannot be used with COTS systems is, frankly, a cop-out. Just because someone else designed and developed an application’s source code is not a sufficient reason to avoid engineering a DevOps solution.

    Consider the value stream chain of activities from the source vendor through integration and deployment in your environment. There are limitations and constraints to the level of automation allowed, the return on investment in automation and influence over the development life cycle that DevOps practices can introduce when dealing with COTS applications.

    COTS applications will typically have predefined and supported interfaces for managing configuration or accessing data. These endpoints may not be accessible or compatible with your existing toolchain or automated change management practices.

    Types of COTS Applications

    COTS applications typically come in one of three flavors; namely, closed, open and platform, and each should be evaluated differently.

    Closed COTS applications allow little to no customization to their functionality and/or interfaces. They typically have predefined management consoles and a published list of commands or APIs that will allow external applications to interact with the COTS applications. A good example of a closed COTS application is Microsoft Exchange.

    Key considerations for DevOps with closed COTS applications are as follows:

    • Can configurations be scripted and integrated with existing automation and orchestration toolchains?
    • Can configuration scripts be managed and maintained in external version control systems?
    • How are updates, patches and service packs applied and managed? Can these practices be automated?
    • What developer tools (APIs, software development kits [SDKs], etc.) are available to extend and/or interact with the application and/or data?
    • Are these tools compatible with existing tools and expertise in the enterprise?
    • Can these developer tools be integrated within the existing toolchain?
    • How frequently are changes made to the base product?

    If these applications can be managed by external systems and code developed to automate deployment and configuration and/or integration can be managed through a version-controlled pipeline, closed COTS applications make good candidates for DevOps and continuous delivery (CD). By applying CD principles, COTS binaries are versioned and stored in an artifact repository; installation and configuration scripts are managed through version control and IaaS workflows and applications and integration endpoints are auto-tested through deployment pipelines.

    This is only made possible when consumers of the COTS application collaborate with operators of the COTS platform to ensure that the solution is aligned with enterprise goals, objectives and standards related to portfolio management.

    Open COTS applications allow significant modifications to functionality, data and/or interfaces. These platforms typically have rich SDKs, APIs and embedded developer utilities that enable users and developers to modify all layers of the applications; namely presentation, business logic and data. Open COTS applications typically have a large, complex footprint consisting of core services, data and/or GUI customizations, embedded applications, etc. Classic examples of open COTS solutions include ERP/ CRM platforms (like SAP or Oracle) or portal platforms (like SharePoint, ServiceNow or WebSphere).

    Key questions to ask when considering whether DevOps can be applied to an open COTS application:
    • How are customizations (created through internal design editors, logic builders or data schema extensions) version controlled? Are these configurations stored in a database or code?
    • How are customizations created through internal tools and packaged, installed and configured in higher-level environments like staging or production?
    • What does the development life cycle for customization created with internal tools look like? What quality gates are required? How about architectural standards?
    • How are custom, embedded applications/applets packaged, installed and configured?
    • Can these custom applications/applets be run and tested separately from the underlying COTS application?
    • What does the development life cycle for customizations created with external tools look like? What quality gates are required? How about architectural standards?
    • Does the COTS application provide testing frameworks, mocks and/or stubs for testing external dependencies?
    • What automated test suites are supported by the platform (unit, functional, regression, capacity tests, etc.)?
    • What is the upgrade path for customizations (historically)? As you can imagine, open COTS applications add layers of complexity.

    When considering DevOps and CD with open COTS solutions, it is recommended that you build multiple pipelines to support each layer of the application in the dev or continuous integration (CI) stage of the value stream. Subsequent stages, like staging and production, will use a converged pipeline built from known good artifacts of the dev and CI stages.

    Before implementing a solution, it is important to study the development life cycle and practices of the target COTS application before building your toolchain. Understanding how the end-state platform is created and how change is introduced will strongly influence your toolchain and pipeline design.

    Platform COTS Applications provide a set of services and tools, as well as proprietary runtimes, that enable users to build and run custom applications on the platform. These are the most difficult type of applications to integrate into existing DevOps practices and CD toolchains because common practices like version control, testing and build are done through the platform rather than using external tools.

    Platform COTS are packaged applications that enable customers to build applications on top of the base platform. As a blend of closed and open systems, all the previous considerations are valid. In most cases, the base platform acts as a closed system, whereas the custom-developed applications on top act like open systems.

    For this type of application, it is critical to understand what hooks and services are available to support DevOps practices and CD. Many of these platforms are not going to fit within your existing toolchain and may not be able to employ the workflows, dashboards and reporting you have grown accustomed to from your current toolchain.

    What This Means

    This blog one of a series that explains how to engineer applications to be most suitable for DevOps. This blog series explains how to engineer applications for DevOps including:

    • Factors used to decide whether an application is a good candidate for DevOps.
    • Practices to engineer designs for DevOps.
    • DevOps applied to enterprise apps and software services.
    • DevOps applied to COTS systems.
    • DevOps applied to manufactured (embedded) systems software.
    • Five levels of application maturity.

    This blog covered DevOps applied to COTS systems. You can read part one here, part two here and part three here.

    For more information regarding how to engineer applications for DevOps refer to my book Engineering DevOps.

  • Maximizing Capabilities and the Importance of Value Stream Management

    Maximizing Capabilities and the Importance of Value Stream Management

    Even if we don’t use them  to the full extent, applications shape our entire lives. And more than half the time we have no idea what our applications are capable of. On a daily basis, the average person uses seven to eight apps on their mobile phone. Throughout the week, the average person uses 30 applications. But, how many of those applications do we thoroughly know how to use? That’s where Eric Robertson, SVP strategic advisor and Tim Stiling, manager of product marketing from ConnectALL come in. Both are speakers and will be holding sessions at TechStrong Con 2021.

    Tell us more about ConnectALL and what you’ve been up to lately.

    Tim: We really want to try to figure out how we can best deliver value to our customers’ businesses. On a very basic level, ConnectALL helps customers connect their tools! Now once your tools are connected—what you do with it—that’s where the fun can begin. I know Lance Knight, our president and COO, he has a fun saying where he talks about how it’s almost like electricity. So the electricity itself—kind of like the connecting of tools—it’s cool, but in and of itself doesn’t do anything. It’s what you can do with the electricity.

    To answer the second part of your question about what we’re up to lately, it’s really trying to find and figure out all those possibilities (synchronizing records, facilitating communication, triggering different actions, etc.) and making sure that our customers in the market are aware of it.

    Digital transformation is at the top of the mind for every organization and as consumer consumer demands are changing, in what ways has this affected the value stream management (VSM) industry?

    Eric: Companies are organizing their entire businesses around delivery of business goals that are essential to customers and are leveraging value streams as an essential part of their digital transformation mission. Basically this allows them to improve business IT integration and better manage changing priorities across different organizations. This is happening because we are seeing that organizational teams, the processes, the tools and tech platforms are constantly changing because they need to adapt to different conditions in the marketplace. As a result, value stream management is quickly being seen as essential for building, transforming, and optimizing those organizations’ technology enabled business models and that’s why it’s critical right now.

    Value stream management has kind of been a buzz word in the tech industry recently. Can you share the true business value behind utilizing value stream management?

    Tim: Ultimately with value stream management, it’s hard to say that this will lead to business value because business value could be different for every company. When it comes to value stream management, it’s more about the methodology and the mindset behind it. It’s all about this idea of continuous improvement. It helps you and your organization constantly drive toward your business goal by continuously improving and being better today than you were yesterday and better tomorrow than you are today. 

    Is VSM for every business? And if so, how can these businesses effectively start incorporating this solution into their overall business strategy and operations?

    Tim: Value stream management is absolutely for every business because whether they know it or not, every business has value streams. In fact, everything we do has a value stream, even something as simple as making a cup of coffee.

    One of the prevailing myths when it comes to value stream management is that it’s synonymous with DevOps or that you have to be in a DevOps transformation in order to be able to do it. Some organizations might be in an agile transformation or DevOps transformation—which is great, we aren’t saying don’t do that and do value stream management instead—VSM is a way to make that transformation more effective.

    You might already have all you need on your desktop right now, but there’s a chance you’re missing that link between your applications. It’s important to understand your applications—how they can maximize your workflow and cut down on time. So if you’re feeling disconnected, reach out to ConnectALL to connect all of your apps and don’t miss TechStrong Con 2021.

    Register today and tune in to Eric and Tim’s sessions on value stream management happening Wednesday, July 14 and Thursday, July 15. The clock is ticking!

  • Rocky Linux Emerges as a CentOS Replacement

    Rocky Linux Emerges as a CentOS Replacement

    Rocky Linux was created to offer the community an alternative following Red Hat’s recent decision to shift its focus away from CentOS—the open source version of Red Hat Enterprise Linux (RHEL). However, the Linux distro’s popularly can also be attributed to how its creator sought to offer a superior alternative based on lessons learned during CentOS’ development—and less as a perceived backlash to Red Hat’s controversial move, said Gregory Kurtzer, Rocky Linux’s creator, who is also founder and CEO of Ctrl IQ.

    “As one can probably imagine, there were a lot of lessons learned from the founding of CentOS—we did a lot of things correctly, but we made some mistakes, as well, that set into motion some of the difficulties the project went through,” said Kurtzer. “I was not—nor am I now—upset at Red Hat or anyone else. It’s important to understand that companies have a legal responsibility to do what they need to do. But I will say, this is why open source communities should not be controlled by a single company, especially if that company has a competing product to the open source project.”

    In addition to applying experience gained from the CentOS project to help “recreate the initial goals of CentOS in a new project,” Kurtzer said he was prompted to create Rocky Linux following Red Hat’s decision to end-of-life (EOL) CentOS. The move “affected my company, our customers, as well as the entire industry,” said Kurtzer.

    “To be blunt, my knowledge—in terms of doing it myself is severely dated. Luckily, after I made the announcement that I was considering recreating CentOS, thousands of people reached out to me wanting to be part of the project and contribute,” said Kurtzer. “From that, our development team and open source community was born.”

    Additionally, CentOS Stream offers value to the community by allowing “us and others” to take part in developing the upstream Enterprise Linux standard, said Kurtzer, who added that his team will continue to debug Rocky Linux so that solutions are properly integrated into the Enterprise Linux Standard.

    “The necessity was absolutely clear, so I founded Rocky Linux and the Rocky Enterprise Software Foundation (RESF),” Kurtzer explained. “Together with our contributors, sponsors and partners, we all have united for a common goal: to create an open source community that will provide us all with an enterprise operating system to stand the test of time, attrition and commercial agendas.”

    Interest in the development of a CentOS alternative was strong when Kurtzer first floated the idea of the project to the community. Since its release in June, the total number of ISO downloads is 56,000, according to Rocky Linux Tier0 mirror data.

    “We have zero visibility as to any other ISO downloads from any of our other mirrors, but if I were to guess, I’d say it would be about two to three times more, in total,” said Kurtzer. “When we all get a moment to breathe, it will be fun to see how many people are using Rocky Linux, and take in all the feedback the community has provided,” he said.

    With this team of developers,  Kurtzer said it took about seven months to build the general availability  (GA) release. “We didn’t just jump right into building the operating system because the goal was to create an infrastructure where many contributors and developers can take part without putting the security of the product at risk. Building that infrastructure took about four months,” Kurtzer said. “Once the infrastructure was completed, we spent about two months building the first-release beta candidate and then spent the following month ensuring that we did everything correctly.”

     

  • Engineering Applications for DevOps (Part 3)

    Engineering Applications for DevOps (Part 3)

    This blog series explains how to engineer applications for DevOps.

    Topics covered in this blog series:

    • Factors used to decide whether an application is a good candidate for DevOps.
    • Practices to engineer designs for DevOps.
    • DevOps applied to enterprise apps and software services.
    • DevOps applied to COTS systems.
    • DevOps applied to manufactured (embedded) systems software.
    • DevOps applied to software services.
    • Five levels of application maturity.

    This blog covers the topic of DevOps applied to enterprise apps and software services; part three in the series. You can read part one here and part two here.

    DevOps Applied to Enterprise Apps

    An enterprise application assists an organization in solving business problems. Enterprise applications are typically designed to interface or integrate with other enterprise applications used within the organization and to be deployed across a variety of networks (internet, intranet and corporate networks) while meeting strict requirements for security and administration management.

    Proprietary enterprise applications are usually designed and deployed in-house by specialized IT development teams within the organization. However, an enterprise may outsource some or all the development of the application and bring it back in-house for deployment.

    The size and complexity of large enterprise applications, especially older monolithic-architected applications that are not designed in modules, are a challenge when it comes to implementing DevOps. Given the large scale and distributed nature of the people, process and technology components of enterprise applications, it is recommended that enterprises engage very experienced DevOps consultants to determine strategic requirements, roadmaps and plans for DevOps that fully consider all three dimensions (people, processes and technologies) and nine pillars of DevOps before embarking on a major DevOps transformation journey.

    Despite the complexity, with the right strategy and plan, DevOps can deliver enormous ROI for enterprise applications. Amazon and Adobe are just two of many examples of large corporations that have benefited enormously from applying DevOps across the enterprise.

    DevOps Applied to Software Services

    I often hear people ask, “Does DevOps apply to software services as well as it does products?” These are usually people who have only worked in product-oriented organizations, such as companies that manufacture things that have embedded software.

    Ironically, I often hear people ask the opposite question, “Does DevOps apply to products with embedded software as well as it does to services?” These are usually people who have only worked organizations in which software is consumed as a service over an intranet or internet for a price or for free. Examples of these organizations are IT departments (even the IT departments of manufacturers!), government agencies and enterprises such as banks, insurance companies, hospitals and financial trading companies.

    You already know the answer to these two questions if you read the earlier parts of this blog series. The answer to both is clearly ‘Yes!’ Cloud services are doubly interesting to DevOps because not only are cloud services used by DevOps as a preferred infrastructure, as described in the next chapter, but cloud services also use DevOps in the process of creating and deploying software for the implementation of cloud components.

    While we are on the topic of DevOps and services, I want to help clarify some confusion regarding whether “newer” DevOps renders “older” IT service management (ITSM) obsolete or less important. This confusion exists because ITSM has often been regarded as a gatekeeper run by Ops to prevent Dev from getting out of control. While some organizations may have, in fact, implemented ITSM that way, this is not the purpose of ITSM.

    “DevOps tends to focus on the software delivery life cycle and on building and delivering software,” said Jayne Groll, president of the ITSM Academy. For its part, ITSM tends to have a broader focus; it is really looking at all aspects of customer engagement, from fulfilling standard services to ongoing support and operations activities. So, ITSM is “almost like the left and right ends of DevOps.”

    Using ITSM With DevOps

    Here are some recommended engineering practices for using ITSM with DevOps:

    • Training to help DevOps professionals gain an understanding of ITSM, and vice versa, will help both teams find points of integration—not just in technology, but in process, as well.
    • Find ways to automate service change approvals implementation of known, good changes to allow for agility, iteration and innovation. At the same time, hold back high-risk, high-impact changes that might need more than just an individual contributor to sign off on before they make it in front of a customer.
    • Self-service requests, automation flows and IT orchestration are now the front door to IT service management actions. These can and should be happening in the background, automagically created, maintained and measured by our DevOps tools.
    • Embrace Agile service management to take Agile values and apply Scrum-like development practices to process design and improvement. Aim to make more frequent incremental changes rather than design and implement a total end-to-end process in the traditional way.

    What This Means

    This blog is part three of a series to explain how to engineer applications to be most suitable for DevOps. This blog series explains how to engineer applications for DevOps including:

    • Factors to decide whether an application is a good candidate for DevOps.
    • Practices to engineer designs for DevOps.
    • DevOps applied to enterprise apps and software services.
    • DevOps applied to COTS systems.
    • DevOps applied to manufactured (embedded) systems software.
    • Five levels of application maturity.

    This blog covered how DevOps can be applied to enterprise apps and software services. You can read part one here and part two here.

    For more information regarding how to engineer applications for DevOps refer to my book Engineering DevOps.

  • Aqua Security Acquires tfsec to Advance DevSecOps

    Aqua Security Acquires tfsec to Advance DevSecOps

    Aqua Security today announced it has acquired tfsec, an open source project that provides a static analysis scanner for infrastructure-as-code (IaC) that is designed to be integrated within a DevOps workflow.

    Amer Jerbi, Aqua Security CTO, said tfsec extends the security platform the company already provides in a way that advances adoption of DevSecOps best practices. In addition, to prevent developers from misconfiguring cloud infrastructure using tools such as Terraform, the scanner surfaces examples of code that provide developers with insights into how to properly configure infrastructure.

    Jerbi noted that tfsec is already integrated with Aqua Trivy, an open source tool that scans container images for vulnerabilities. Integrations with the rest of the Aqua Security portfolio will follow, added Jerbi.

    Tfsec co-founders Liam Galvin and Owen Rumney will join Aqua Security as cloud engineers. The challenge Aqua Security is trying to address is the need to enable organizations to proactively prevent cybersecurity issues from arising in production environments rather than only identifying vulnerabilities that need to be fixed, said Jerbi.

    Aqua Security tfsec

    The decision to acquire tfsec comes in the wake of a series of high-profile breaches when many organizations are scrambling to make sure software supply chains are secure. Cloud platforms are rife with misconfigurations mainly because developers often lack the expertise needed to ensure infrastructure is secure after they have provisioned it. Organizations are embracing DevSecOps best practices in the hopes of educating developers to assume more responsibility for application security. However, developers are not going to acquire that expertise overnight. The tfsec scanner provides a way to enforce security policies today while at the same time affording the time to teach developers how to avoid misconfigurations.

    It’s unclear how many cybersecurity events arise because of cloud misconfiguration issues. The cloud service providers have adopted a shared responsibility model that makes the organization employing the cloud responsible for both the applications deployed on those clouds and for how that infrastructure is provisioned. Many developers that provision cloud infrastructure themselves within the context of a DevOps workflow often assume the cloud service provider is doing more than it is to prevent misconfigurations. Cybercriminals, meanwhile, have become very adept at scanning for those misconfigurations.

    There are, of course, a lot of layers and nuances when it comes to DevSecOps. Arguably, Jerbi said, the most critical thing for most organizations is to simply get started. Tools that can be quickly and easily integrated within an existing DevOps workflow with minimal disruption are critical, Jerbi added.

    In the meantime, DevOps teams should expect cybersecurity teams to become more involved in their workflows, especially as government mandates aimed at securing software supply chains become stricter. Eventually, as organizations gain confidence in the ability of their DevOps teams to secure their application environments, those cybersecurity teams will refocus their efforts on hunting for threats. In the meantime, DevOps teams would be well-advised to make those cybersecurity professionals feel as welcome as possible, given the application security mandate most of them have been given.

  • 4 Ways to Manage Up for Automation

    4 Ways to Manage Up for Automation

    IT decision-makers understand how important a role process automation can play in a post-pandemic recovery. In a recent survey, 68% of these leaders said remote work caused key business processes in their organizations to break down. In the same survey, 97% described process automation as being vital to digital transformation and an important factor in achieving business outcomes.

    So, full speed ahead? Not exactly. While process automation’s benefits are well documented, many organizations remain hesitant to automate too many tasks because they’re afraid they’ll further complicate an already complex IT environment.

    This is where developers can help process automation initiatives get off the ground. They don’t control their organizations’ purse strings and they often don’t take the lead on planning new IT initiatives. But developers are the ones responsible for designing and building the software and tools that drive real business results. In a large sense, they occupy a key role at the heart of digital transformation.

    For organizations to gain the full benefit of process automation, developers need to be more intimately involved in automation projects. They need to have more say in how these initiatives are constructed, how they’re carried out and how they’re improved.

    Automation initiatives aren’t set-it-and-forget-it projects. They must tie in with end-to-end organizational processes, which will evolve over time. Organizations don’t want to bake in processes that won’t suit them two months or two years from now. With this in mind, process automation needs to be nimble, adaptable and smart–and it’s developers who have the skills and the insights needed to drive these initiatives forward, impacting broader organizational success. 

    To take on this larger role, though, developers must be given the right resources, tools and access to make their voices heard. Part of this is empowering them to manage up to senior leaders–on both the IT and business sides–to advocate for the types of automation projects that can drive true digital transformation.

    Here are four ways they can do it.

    Build Automation Demos

    The biggest enemy of a process automation project is time. The C-suite and senior IT leaders don’t want to spend months–if not years–debating the merits and feasibility of automating a series of tasks. They want to know quickly whether a project is viable and whether they should commit resources to it.

    Developers can set a project on the right course by creating a basic demo. It doesn’t need to integrate the complicated set of dependencies planned for the finished project; it just has to show people in power that the project will work. Demonstrate how a manual calculation project gets triggered by a quarterly deadline and estimate the time it will save a department on an ongoing basis. Show the leadership that the pain point workers have cited on feedback reports can be solved.

    Show Proven Examples

    While a demo visualizes how a process can work, a use case can illustrate how such a process has worked in another setting. Examples can be found in any number of places–in a formal case study, a tech article, a GitHub posting, a developer message board or materials supplied by a technology partner. Developers should tap their networks to get advice and run scenarios by peers. The goal is to find a situation where someone solved a similar problem with a manageable set of procedures–and it worked. Having a solid example takes the initiative out of the theoretical realm and gives the developer more credibility.  

    Get an Enterprise Architect on Board

    Once the demo and the use case are secured, the next step is getting buy-in on the vision for the automation initiative. This is the domain of the enterprise architect. It’s important for a developer to get this person on board as an ally. They should work with the enterprise architect to ensure that the set of tasks fits into the company’s architecture – today and in the future. If the company is pursuing a microservices strategy, the developer needs to show how automating a series of product quality checks can be accomplished inside this technology infrastructure.

    Keep Things Simple

    While organizations try hard to operate in an agile manner, sometimes that’s easier said than done. The people developers report to like to plan. Enterprise architects like to define perfect, future-proof architectures. The C-suite likes to envision scenarios and debate ramifications. Developers can break logjams by encouraging others to avoid the temptation to drown in detail. They should get comfortable with the concept, the demo, the use case and the vision–in that order–and then roll it out to the larger organization. 

    While process automation is widely seen as being vital to business transformation, building a project is often more challenging than it needs to be. Encouraging developers to take on larger roles can help organizations move automation initiatives past square one and on the path to digital transformation. 

  • Engineering Applications for DevOps (Part 2)

    Engineering Applications for DevOps (Part 2)

    This blog series explains how to engineer applications for DevOps.

    Topics covered in this blog series:
    • Factors to consider when deciding whether an application is a good candidate for DevOps.
    • Best practices for engineering designs for DevOps.
    • DevOps applied to enterprise apps and software services.
    • DevOps applied to COTS systems.
    • DevOps applied to manufactured (embedded) systems software.
    • Five levels of application maturity.

    This blog is part two, and covers best practices for engineering designs for DevOps. You can read part one here.

    Poor design practices severely limit the potential for improvements provided by DevOps. As stated in my blog post Design for DevOps—Recommended Engineering Practices, “Without good design practices, a DevOps implementation has no hope of delivering on its promise of accelerating innovation with high quality and scale.”

    Following DevOps-recommended engineering practices for application design is important for legacy, greenfield or brownfield products, platform projects, feature enhancements or repairs. It is important for enterprise three-tier applications or multilayer products. And it is true whether the developers are using Agile, waterfall or ITIL development processes. In every application design case, designers face tough challenges and are expected to balance conflicting goals.

    Designers are expected to rapidly drive down the work backlog yet produce quality products that avoid costly rejections and rollbacks. In addition, there is pressure to increase the percentage of effort spent on creative content rather than corrective content and do so with limited time and resources. Balancing these conflicting goals is a tall order. If not supported by recommended engineering practices, the overall design experience is a cauldron of stress and a fast route to burnout.

    Recommended Engineering Practices

    The following recommended engineering practices improve the design experience and the products of that design in a way that is streamlined for the DevOps pipeline:

    • Designers must thoroughly understand customer use cases.
    • Usability, reliability, scaling, availability, testability and supportability are more important than individual features! Quality over quantity is recommended. Designs that anticipate actual customer use are the most successful.
    • The culture needs to support designers.
    • Leaders must support the designers with motivation, mentoring and training.
    • No designer can be expected to know everything. It is OK for designers to make some mistakes if lessons are learned and improvement quickly follows. Continuous monitoring and quick remediation are examples of good DevOps practices that help minimize the impact of any mistakes.

    Design Coding Practices

    Design coding practices are critical in the following ways:

    • Products are architected to support modular independent packaging, testing and releases. In other words, the product itself is partitioned into modules with minimal dependencies between modules. In this way, the modules can be built, tested and released without requiring the entire product to be built, tested and released all at once.
    • Where possible, applications are architected as modular, immutable microservices ready for deployment in cloud infrastructure, in accordance with the tenets of twelve-factor immutable non-monolithic apps, rather than monolithic mutable architectures.
    • Software code changes are pre-checked using peer code reviews prior to commit to the integration/trunk branch.
    • Software changes are integrated in a private environment together with the most recent integration branch version and tested using functional testing prior to committing the software changes to the integration/trunk branch.
    • Developers commit their code changes regularly—at least once per day.

    Good Design Practices Support QA and Ops

    Good DevOps design practices support QA in the following ways:

    • Design practices consider and understand the QA process.
    • Software code changes are pre-checked with unit tests prior to commit to the integration/trunk branch.
    • Software source code changes are pre-checked with static analysis tools prior to commit to the integration branch. Static analysis tools are used to ensure the modified source code does not introduce critical software faults such as memory leaks, uninitialized variables, and array-boundary problems.
    • Software code changes are pre-checked with dynamic analysis and regression tests prior to commit to the integration/trunk branch to ensure software performance has not degraded.

    Good DevOps design practices support Ops in the following ways:

    • Design practices consider and understand delivery and deployment pipeline processes.
    • Software features are tagged with software switches (i.e., feature tags or toggles) during check-in to enable selective feature-level testing, promotion and reverts.
    • Automated test cases are checked in to the integration branch when code changes are checked in. Evidence that the tests passed are included with the check-in.
    • Tests are conducted in a pre-fight test environment that is a close facsimile of the production environment.

    Supporting Tools

    The following supporting tools are needed to realize design for DevOps best practices:

    • Elastic infrastructure that can be easily orchestrated, created and released, as needed, to support designers’ tasks on-demand with minimal delay.
    • Design, code management, monitoring and test tools are readily available and scalable with minimal delay.
    • Monitoring tools that track application process performance and report the results to designers in easily consumable formats without delay.

    Applications for Which DevOps Does Not Apply

    “If you build it, they will come,” made for a great movie idea in Field of Dreams, but the reality is that many DevOps journeys led to nowhere despite the excellence of the people, processes and technology involved. As indicated above, applications that will not benefit from faster lead times, incur insufficient costs to justify investment in DevOps or that are too rigid to accept change are not good candidates for DevOps.

    What This Means

    This blog is part two of a series explaining how to engineer applications to be most suitable for DevOps. This blog series explains how to engineer applications for DevOps, and covers topics including:

    • Factors used to decide whether an application is a good candidate for DevOps.
    • Practices to engineer designs for DevOps.
    • DevOps applied to enterprise apps and software services.
    • DevOps applied to COTS systems.
    • DevOps applied to manufactured (embedded) systems software.
    • Five levels of application maturity.

    This blog covered practices used to engineer designs for DevOps. You can read part one here.

    For more information on how to engineer applications for DevOps, refer to my book Engineering DevOps.

  • Cellular Generations

    Cellular Generations