Tag: developers

  • Don’t Make Me Code: Environment Protection

    Don’t Make Me Code: Environment Protection

    Thanks for listening to “Don’t Make Me Code,” a Heavybit podcast that discusses developer experience design and the unique challenges of building developer-facing products. “Don’t Make Me Code” is hosted by Steve Boak, co-founder and CPO at Opsee, and David Dollar, co-founder and CEO at Convox.

    In this episode, Steve and David are joined by Sean Li, lead product designer at Docker. Sean, Steve and David discuss Docker’s acquisition of Kitematic, the friction of attempting to replace a developer’s existing tool, and the increasingly prominent role of design in developer tools.

    This podcast is brought to you by Heavybit, a program that helps developer-focused companies take their product to market.

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    Steve: We’re calling this episode of “Don’t Make Me Code” “Environment Protection,” and we’re here with Sean Li, lead product designer at Docker and one of the founders of Kitematic.

    Sean: Thank you.

    Steve: Thanks for being here with us. This is a really exciting conversation for me because we get to talk to a product designer for a company like Docker.

    Sean: It’s good to be here.

    Steve: Kitematic is a real interesting project for a bunch of reasons. I mean, it caught the interest of Docker. It’s also proven to be a really novel bit of development environment technology. And so we’re curious how it all got started.

    Sean: It got started in a university dorm room. I was a student from University of Waterloo in Canada, and the school actually offers a pitch competition. So we had this idea around making development environments easier, and so we pitched the idea and won. That’s how we got enough money to get started.

    Steve: Wow, and was it at all tied to Docker at that point?

    Sean: Docker was actually what we used for the back end. At the time, Docker was version 0.3. And then we’re on Hacker News, and we’re like, “Oh, this is interesting. It could be super useful technology to do what it wanted to do.” Our idea was essentially like Dropbox for your code.

    You get a Dropbox-like icon on your task menu, and then you can put code in it. For example, Django, it would just run it for you. And you can see it on the browser.

    Steve: Oh, nice. And so you have your production environment there, compiling for you and ready to go.

    Sean: Yeah. Then, when you added the code, it will sync to the cloud environment and then update right away.

    Steve: Nice. That’s awesome. It’s like a step beyond GitHub. It’s not just committing the code; all the CI and everything is built into this one workflow.

    Sean: That’s like the future plan right at the time, but at first, our MVP was super simple—just syncing code to a remote server and then seeing the changes.

    Steve: From the beginning it was implemented as a desktop application, you said like a Dropbox tray application.

    Sean: Yeah, because Dropbox was obviously the inspiration.

    Steve: And so why a desktop application?

    Sean: At the time, we actually didn’t realize the power of desktop application yet. At one point we used to pivot a lot, as startups usually do. And then we’re talking to customers, and they start realizing what we’re using underneath.

    We talk to Canadian Tire, the biggest retailer in Canada. They were looking for something like this, and they’re like, “Are you using Docker underneath? We want to use that.”

    At the time, the product we have is in the cloud, like an on-prem web browser setup. And then we started thinking of, instead of abstracting away Docker, why don’t we embrace it and then make it easier for the customers? Then we start brainstorming ideas, and it came across that having a desktop application is actually super beneficial.

    It’s like the best platform for developers, because they can import their code super easily. They can open a directory instead of having to upload files in a browser. You can also get a lot of access to their desktop, so once your tool gets more powerful, there’s more things that you can do.

    It’s also super cool because we use Chrome in an electron shell. And we wrote the UI in React, so that means we only have to worry about how the UI runs in that one browser, instead of having to worry about browser compatibilities across the board.

    Steve: So it’s not something React needed, it’s just running in a web view in the electron browser.

    Sean: And we make it feel as native as possible.

    Steve: All right, nice. So it’s a true desktop app in many ways, but specifically the UI, it’s a web UI.

    Sean: A lot of inspiration comes from the Atom Editor by GitHub. They’re using the same technology.

    Steve: And so this whole bit was open-sourced from the beginning?

    Sean: We were working on it, and then we open-sourced it.

    David: I’m curious what made you decide as you’re releasing this tool. Was open-source service a strategic decision, or you figured you could get more users by doing that? Or is it just wanting contributions from the community? Could you talk through a little bit of your inspiration behind that?

    Sean: I think the biggest part is if it’s something that touches their code, it’s really important that the developer trust it by seeing what the code is like.

    We’re really open about what we do, and also the part on gathering the feedback from the community is super, super helpful. I feel like, in general, open-source projects get more feedback from the community.

    Steve: With developer tools it seems like a great way to encourage participation. If you’ve got an open-source project, you’re inviting people to contribute. Obviously, our Opsee product for example, it’s closed, a SaaS application. So we don’t have the level of community support from developers that we would really like in some ways.

    Sean: We hired an engineer from Docker because he was a maintainer and he was super passionate about the project. It really helps on that front as well.

    Steve: Following from that, you launched this to an open-source community, did you have an idea of the kinds of users you were targeting at that point?

    Sean: We sort of did from the original product that we had, the Dropbox-for-code product. We had a signup list. A lot of these users are more leaning towards willing to use UIs and prefer something simpler. The super active ones are actually consultants that work on multiple projects.

    Steve: That’s an interesting segment. People there, maintaining a lot of projects, and they’re looking for an easy way to keep track of all that stuff. And Kitematic fit that mold.

    Sean: Yeah, and Docker being isolated also provides that value.

    Steve: That too. Now, if I’m maintaining multiple projects, I can have a Docker environment for each one. The app makes it very easy to move between those. And so specifically the React UI and the GUI, what was it like having that be part of the open-source project? Did you get contributions for that as well, or was that entirely internal?

    Sean: The React UI helped us in a way, because React is, according to a Google trend, almost on the same trajectory as Docker. So there are a lot of people willing to work on something that’s built in React. It was in a way accidental, because when we started, it was a really good technology to use.

    Steve: Did you have any designers contributing to the project?

    Sean: We do have design-minded people but not professional designers.

    Steve: For example, you’re a lead product designer at Docker and you, I assume, identify mostly as an engineer, or your background in coding. But there’s definitely this hybrid world in the developer tool space.

    Sean: Definitely. In the beginning we had hackthons. A lot of participants were trying to add features to Kitematic, then make a huge effort on figuring out the right UI right experience to build there. By default, I think what I wanted is sort of like designing an OS.

    A UI is very extensible, and you want to figure out the right points where you can extend on it. You actually focus on per component and really set an example of how you extend the current UI. When people contribute, it can follow that pattern. And you only had to make slight adjustments to it.

    Steve: That seems true of open-source projects, generally, too. You want build a broad base that people can build on top of and customize.

    Sean: Yeah, but the initial effort has to be really strong. Because otherwise you will get swayed by different opinions. And design by committee isn’t always a nice thing.

    David: That’s pretty interesting because you oftentimes see open-source projects that are sort of notorious, especially visually, for bad design or design by committee that ends up being a little too weird. I can think of some Linux desktop managers that I won’t name, but Kitematic is actually a beautiful application.

    Sean: Thank you.

    David: I’m curious how you managed to maintain that, even when you’re doing community-driven design.

    Sean: I think a big part of it is keeping focus and actually be willing to cut things. In the beginning, Kitematic actually had build, you can actually build an image and then push it. But to keep focus and make things simple before we figure out the next steps is actually making it run content only.

    Essentially the focus of Kitematic was helping users install Docker on their computer. You know, in a visual way, it feels very reliable. We solve a lot of underlying issues with VirtualBox in the beginning. And then after that choose a beautiful catalog where you can click one button and run a container. And then that’s the experience we were aiming for and focused on. So it’s super obvious what to do.

    Steve: Did you ever get push-back on those decisions from the community where you had to assert your position strongly there?

    Sean: No, I think the community is mainly supportive. What I had to manage was people trying to add too many things that are not focusing on that road map currently.

    Steve: I think I remember you saying, on the Software Engineering Daily podcast, that you did end up cutting quite a few things from the product after a bit of time. Can you talk more about that? You were trying to clean it up?

    Sean: The one thing that was cut was building images from it. Even though it’s a super important thing, we decided to delay it because we want to do it right. Instead of releasing something super early, and then get sidetracked into different things, we want to keep focus until we figure out this is it.

    And then release that as a whole. Talking about cutting more, the next version of Kitematic is sort of Docker for Mac. It really solved the core issues that Kitematic was trying to solve in the beginning, to install Docker reliably on people’s desktops in a way that it almost feels like it’s seamless.

    You don’t feel like it is running inside a VM at all, and that’s the goal in the beginning. You install Docker for Mac. When you open the terminal you can type “Docker run,” and it just works.

    Steve: Had the Docker for Mac project begun before the Kitematic acquisition?

    Sean: It was after the acquisition.

    Steve: So you were involved with that from the beginning.

    Sean: Yeah, I was the founding member of Docker for Mac.

    David: So it’s interesting to think about this this sort of internal debate. I guess with most design questions it’s customizability and configuration versus limited options, and this curated a beautiful experience. I feel like that happens even more with developer tools.

    It seems like Kitematic and Docker for Mac, some of these tools, are definitely trending towards the latter there, where you’re removing some of the optionality of Docker to make a better user experience. I think that’s really interesting.

    Sean: I think the two tools are, in a way, more complimentary. People usually use Kitematic by having the Kitematic UI side by side with the terminal. So they like the transparency that they’re getting from the Kitematic side, and the sense of it feeling reliable.

    “I see things are running. I can check the logs super easy.” On the other end, the terminal is how they’re used to working before, and that was sort of expected in the beginning. And then you go from there. You never want to displace a tool that they’re already using, one they’re so familiar with.

    So instead we embraced that but made Kitematic more of a complimentary to the Docker CLI.

    Steve: That’s really interesting. I’ve seen similar comparisons made with GitHub and some of their tooling. GitHub has their Mac app and their web UI and stuff like that. And I found myself going to them for things like diffs and comparison, merge states, something where I want to get a lot of text or get some status update.

    But for actions, if I want to do merges, everything I’m actually doing with it I’m still doing through the command line. But that’s a really interesting comparison, because it sounds like you’ve made the same distinction. To view things, maybe you go to the UI. But to actually take action?

    Sean: GitHub desktop is like a huge inspiration for all these decisions as well.

    Steve: I never really heard that distinction made this clearly, that there are certain things that developers are going to continue to want to do through the command line and through terminal. But that we can make the experience better in some ways, like just figuring out whether a container is running or not. That’s really nice to have a UI to see that all the time.

    This podcast is brought to you by Heavybit, a program that helps developer-focused companies take their product to market. Throughout the program, founders work on developer traction, product market fit and customer development. If you like what you hear, be sure to subscribe to Heavybit’s Podcast Network on iTunes.

  • Tales of DevOps Discovery, Part 3: Q&A and Explanations

    Tales of DevOps Discovery, Part 3: Q&A and Explanations

    This is part three of the series, Tales of DevOps Discovery. To catch up, Read part one and part two.

    In preparing for a DevOps transformation a critical first step is to perform upfront discovery, often asking even the most fundamental, seemingly obvious, questions of stakeholders. The major portion of such discovery should be done in a group setting. Asking stakeholders these fundamental questions in a group setting can provide key insights into differing perspectives and even differing objectives regarding a planned DevOps implementation. Sharing these different perspectives during the discovery phase sets the stage for mutual empathy and enables stakeholders to identify and align, an important step to aligning on shared objectives. In this article we will outline common questions asked, share real-world answers and offer guidance on interpreting and applying the results.

    Discovery Question: What do you want to achieve with this transformation/DevOps?

    One of the first things to consider is, “Why are we doing this?” as this establishes the goals and objectives. Accordingly, I usually begin by asking the stakeholders during discovery what they expect to achieve through the transformation to DevOps. The answers I receive to this question often differ distinctly, depending on the role of of the person answering. Understandably, they are heavily influenced by the unique perspective of that role.

    Answers:

    CIO: “We want to increase our ability to “scale-up” delivery as we shift to a primarily SaaS (software-as-a-service) model and see a rapid increase in business. These means we have to increase developer productivity, and respond to customer requests faster, all while reducing our number of Severity #1 issues.”

    Operations:
    “We want to reduce technical debt, to minimize firefighting and increase our ability to adopt modern best practices such as Infrastructure-as-code. We have to be able to keep the lights on while delivering applications to production.”

    Development:
    “We would like to minimize customer-specific one-off work, which is resulting in painful complexity in development, QA (quality assurance) and deployment, and is an overall source of inefficiencies. We would like to be able to spend more time improving user experience, performance and increasing valuable functionality. But, instead, we are chasing bugs and reworking misunderstood requirements.”

    Guidance:

    Not surprisingly, executives often respond with a focus on business-oriented goals such as increased productivity and customer response, while Operations focuses on stability and minimizing firefights and Development wants to innovate. But within these differences we see some commonality that can be harnessed, such as productivity. For example, one point of commonality is productivity:

    CIO: “We have to increase developer productivity.”

    Operations: “… minimize firefighting and increase our ability to adopt modern best practices …”

    Development: ” … spend more time improving user experience, performance and increasing valuable functionality.”

    Another point of commonality in the CIO, Development and Operations answers is the focus on quality:

    CIO: “ … reducing our number of Severity #1 issues.”

    Operations: “We want to reduce technical debt … keep the lights on …”

    Development: “… instead, we are chasing bugs … ”

    These points of commonality can be used to establish common goals with cross-functional buy-in, such as:

    • Our effort will result in increased productivity and minimize overtime and firefights (across teams)
    • Our efforts will result in increased application quality and uptime

    They then can be used not just as driving principles that inform decisions such as process or tool choices, but also to establish key performance indicators (KPI), which will be used to quantifiably measure success of the transformation. Example KPIs may be:

    • Reduction in cycle time, from story acceptance to user acceptance (or release)
    • Number of Severity 1, or Severity 2 production issues per release
    • Defects per build
    • Defects per release
    • Hours worked by Development? Operations?

    Discovery Question: Do you practice agile today? If so, how do you define done for a story or sprint?

    Continuous delivery (CD) and lean practices are foundational to a successful, sustainable DevOps transformation (though not required to meet the some definitions of DevOps.) If we look at CD and lean practices as a pipeline through which we need to manage a continuous flow of changes represented by work, then it is important to consider what work is sent into the pipeline, how the work is initiated and how the changes are managed. Accordingly, it is important during discovery to ask customers high-level questions about development methodologies used and overall practices for definition, planning and coding.

    The answers given vary between different levels of, “Yes, we are agile,” “No, we are waterfall,” and, “We practice both.” Most Most often, organizations’ answers describe adherence to a form of agile with room for improvement.

    Answers:

    “We practice agile and/or scrum. We work in two-week iterations, planning the work for a sprint at the end of the prior sprint.
    We consider a story done once the code has successfully been committed and merged to a team branch, and is successfully built. We consider a sprint complete when all stories for that sprint are committed and successfully built.

    “Roughly every three months we integrate code from team branches to trunk and perform a mix of automated and manual regression and acceptance tests. Once the build passes QA we manually deploy to preproduction environment, validate and schedule a manual deployment to production.”

    Guidance:

    This is a classic story of agile adoption in traditionally waterfall organizations. The organization adopts agile within Development without involving other key functional teams such as QA or Operations. Usually, this is because it simply is easier. There are a number of obstacles to overcome in extending agile practices across organizational, technical and cultural boundaries, so the obstacles are avoided by limited the agile adoption to these boundaries.

    This is a case of confining the adoption to “agile upstream” while practicing waterfall or legacy “downstream.” Studies show that less than 33 percent of organizations have adopted “agile upstream” and exercise agile or iterative development practices for the planning, coding and team builds, yet only 13 percent of organizations have adopted agile downstream, and follow practices such as continuous integration (CI), CD, automated provisioning testing and deployment.
    Screen Shot 2016-07-18 at 11.07.34 AM

    The negative effects of limiting agile adoption to agile upstream are multifold, but can be summarized as, “You never really know when you are done-done.” As a result, you cannot accurately measure progress, introduce deferred risks or disrupt the development plan to address issues found during the downstream portion of the process, such as poorly understood requirements surfacing during acceptance testing or runtime issues discovered during deployment to a production-like environment or, in the worst case, issues found in production by the end user.

    A seminal book on DevOps is, “The Phoenix Project,” by Gene Kim, which presents three ways of DevOps thinking. The first way, “Systems Thinking,” addresses to this gap between agile upstream and downstream, Dev and Ops, business and customer by taking a systems view across the traditional boundaries and establishing “flow” of the system through the boundaries.

    Screen Shot 2016-07-18 at 11.05.09 AM

     

    Discovery Question: Do you practice CI today? What types of validation do you perform?

    As CD is foundational to DevOps, CI is foundational to CD. CI can be scene seen as the connection point for agile upstream to agile downstream, and the pump that fills the CD pipe. It is both the practice most organizations say they follow and the practice that most often is implemented incorrectly. So when surveying a customer’s current state during discovery, it is important to know whether CI is currently part of the picture.

    Answers:

    “Yes, we practice continuous integration. Each team has a Jenkins CI server. Developers commit their changes multiple times per week. Jenkins then builds the changes as part of a nightly build.”

    “We do some unit testing, but we do not track code coverage. If the nightly build fails we may continue to commit, but we usually fix the issues within a few days.”

    Guidance:

    This is a common answer and an example of how CI can be improperly implemented. CI is more than having a shared Jenkins CI server and running scheduled builds. CI can be defined as:

    “A a software development practice where members of a team integrate their work frequently, usually each person integrates at least daily – leading to multiple integrations per day. Each integration is verified by an automated build (including test) to detect integration errors as quickly as possible.” — Martin Fowler

    The benefit of practicing CI includes identifying integration and quality issues close to the source of the issue, thus reducing the time to correct and enabling higher-quality software to be developed more rapidly.

    Essential elements of properly implemented CI are :

    • Integrating changes frequently, ideally multiple times per day or even per change.
    • Performing consistent validation of quality through component level testing, code scans, etc.
    • Always maintaining a working build, suspending development when a build fails, and not resuming development until the issues is corrected or reverted.

    Teams that allow a broken build for “a few days,” deferring commit or builds to just “multiple time per week” or that do not validate consistently through testing practices are not practicing CI and will not yield the benefits of CI.

  • 7 Reasons to Move to Parallel Testing

    7 Reasons to Move to Parallel Testing

    While development operations are more scalable now than ever, there is one area that continues to constrain the ability of organizations to scale: functional testing.

    Most organizations still rely on sequential tests to deliver quality assurance. No matter how rapidly a business can produce great products, its ability to bring them to consumers quickly is limited by its dependency on a slow, tedious testing process that does not adapt well to changing development needs or ever-faster business processes.

    That, at least, is the way things traditionally have been. But today there’s a replacement for sequential testing: parallel testing, which lets you leverage the cloud and virtualization to perform more tests at faster speeds than your physical infrastructure or homegrown testing grid could support on its own.

    What is Parallel Testing?

    First, a definition: Parallel testing is the process of running multiple test cases on multiple combinations of operating systems and browsers at the same time. The process is automated, and it often runs on virtual machines. For the QA professional, no additional effort is required once the appropriate test scripts have been developed. All the testing solution needs is the test suite and a pool of resources.

    Granted, new does not always equal better. But it is hard to make an argument against parallel testing, especially if you leverage a robust testing cloud. Here are seven key advantages of parallel testing to consider over sequential testing:

    You Can Test for Wider Compatibility

    Because parallel testing is faster, it allows you to test for wider compatibility in the same amount of time. If you’re releasing a new app and want to test the user interface (UI) functionality, you don’t have to limit yourself to testing against only the most popular OS and browser combinations or mobile devices—you can test all the combinations that are important to your users.

    You Can Radically Reduce Testing Time

    Good software testing must be thorough and comprehensive. In a sequential testing environment, it can be (and usually is) a very time-consuming process. Parallel testing can divide invested time (roughly) by the number of test machines being used in parallel, so that overall testing time is a fraction of that required for sequential testing.

    For example, if you are running 10 concurrent tests, you can reduce your testing time by a factor of about 10. This can cut days or even weeks from delivery time. This reduction in testing time also allows you to make more efficient use of your engineering team. They are freed from a set of necessary but time-eating and repetitive tasks, allowing them to concentrate on more forward-looking and innovative projects.

    Parallel Testing Optimizes Continuous Integration and Delivery

    Modern development best practices such as continuous integration and delivery require frequent and rapid functional tests. The execution of pre-scripted tests on a web or mobile app saves considerable time, plus having test data accessible in detailed reports is valuable to development teams who can use this information to quickly identify issues. Parallel testing in the cloud allows you to execute test suites continually as developers submit and integrate code changes throughout the day.

    The Cost per Each of Your Tests is Less

    Because parallel testing is automated and and can run at high concurrency in the cloud, the cost per test is considerably less. Leasing test time on a cloud testing service generally will be much less expensive than building and maintaining your own test infrastructure.

    Even the common practice of using development hand-me-down computers as test machines has its costs and practical limits. For example, as used systems age, they require more maintenance and they become less capable of duplicating real-world deployment conditions. Cloud-based testing grids mean environments have high availability, and they are up-to-date, making parallel tests the better option.

    It Supports Testing Science

    Parallel testing enables teams to focus on making tests repeatable, measurable and accurate. By simply testing faster, you can test more, and testing more produces more actionable data to find bugs and also improve test cases. Automated parallel testing delivers strong data on test results with key indicators of where tests can be improved. The net result is a test process that is more scientific.

    You Can Still Perform Sequential Tests, If and When Needed

    Parallel testing simply offers a different framework for testing, which can easily accommodate most or all of your existing test regime. This means that transitioning from sequential to parallel testing does not force you to sacrifice test targets, strategic testing goals or test quality.

    If anything, moving to parallel testing increases the range and depth of your test program, allowing you to better meet your test goals and it improves the quality of your testing. When you make the move to parallel testing, you are not abandoning traditional software testing. You are simply applying modern development practices and technology to it.

    You Do Not Need to Make the Switch to Parallel Testing All at Once

    The great thing about parallel testing is that you can transition to it in steps, starting with the tests that are most easily converted to parallel, then adapting some or all of the remaining tests after your team has had time to adjust to the parallel testing environment. Once you have started to use parallel testing and have integrated it into your development process, it is easy to expand the quantity and scope of parallel tests as the need arises.

    Conclusion: A Faster Test Run is a Penny Earned

    The faster you run a test, and the more tests you run, the more frequent the releases and the more defects you can find. The math is simple. Parallel testing in the cloud decreases the cost of maintaining test infrastructure, the cost of lengthy testing cycles, the cost of delayed releases and, finally, the branding cost of unhappy customers due to poor application quality.
    Even without changing the way you test, a shift to a parallel testing environment will provide an immediate speed enhancement—which means every test that still runs serially is a cost that can be avoided. And every test run in parallel is an opportunity to test your application better and faster at the same time.

    About the Author / Lubos Parobek

    Lubos ParobekAt Sauce Labs, Lubos Parobek leads strategy and development of Sauce Labs’ web and mobile application testing platform as VP of product. His previous experience includes leadership positions at organizations including Dell KACE, Sybase iAnywhere, AvantGo and 3Com. Parobek holds a Masters in Business Administration from the University of California, Berkeley.

     

  • Follow the Simple Path of Nirvana to DevOps

    Follow the Simple Path of Nirvana to DevOps

    Perhaps the title of this post is a misleading, as nothing is truly “simple. But there is a well-defined pathway to achieving DevOps goals for any size company. Just follow a step-up pattern by adopting the principles of agile, continuous integration and continuous delivery, and you will reach your goal of DevOps. This path is a natural progression of DevOps maturity that an organization can follow while adopting key principles and technology solutions along the way.

    pipe

    Agile Development

    Adopting agile development methodologies often is the first step maturing organizations take, as they no doubt have heard the resounding benefits of leaving behind waterfall software development life cycles. There is a reason this is the first step. It helps your organization’s employees mature into a tightly knit working machine that fosters improvements in driving down technical debt while also laser-focused on building key features.

    As agile teams continue their maturation, they’ve roped in key business stakeholders who are able to grasp the drivers of technology challenges and are able balance out the growth needs of the business with the sustainability requirements of the technology teams. Suddenly, teams are investing a minimum of 20 percent of their sprint time to dealing with technical debt and reporting out these victories to their product owner(s). These small wins become major victories as the unwieldy pieces of infrastructure and software of the business become relics and folklore of yesteryear.

    But there is an underlying reason why agile development is the most crucial first step: It truly empowers the developers to improve the customer experience and feel good about it. With the scrum master’s shields up protecting the team from burnout and ensuring sprint planning happens, team members are more likely to be passionate about their work and the results of their efforts to the business and customer. This is where the empowerment of DevOps really begins.

    Continuous Integration

    As teams mature along the agile development continuum, the next step in their DevOps maturation is moving on to  continuous integration. Continuous integration is the process by which a company automates its software build process: code check-in triggers a build job that then triggers a test validation job and so-on. This process enables teams to continuously integrate their code build with downstream processes, avoiding manual touchpoints.

    In addition, this paradigm allows for faster feedback loops to ensure a higher quality product, and empowers diverse teams to work together utilizing automation as the “middle man.”

    Continuous Delivery

    The third step in DevOps maturation is continuous delivery. Often businesses confuse “delivery” with “deployment”—in fact, continuous delivery is simply the process to ensure that at any given point a company’s software is in a state where it can be deployed. This is useful for quick iterations, A/B testing and a more mature way of delighting customers fast and often.

    A key component of continuous delivery is ensuring that software is ready for production. When a team is doing continuous delivery, they’re assured that they’re nimble and responsive and adhere to the highest quality standards.

    DevOps

    At this point, the company has reached the DevOps nirvana state. This is where software is not just delivered continuously, but all of the operational needs are constantly met. Monitoring, metrics, the ability to automatically roll back software releases, scalability and much more are the key building blocks to a powerful DevOps organization.

    With this thoughtful step-by-step process of DevOps adoption, organizations can meet the needs of business in a mindful and cohesive way without compromise.

    I’d love to hear any feedback or tips on DevOps at @jsin.

    About the Author/Jason Shawn

    jason-profileJason Shawn is a technology leader in DevOps and Cloud. His began his career as a software developer and has held multiple functional and managerial roles which has found him with a unique perspective on the software development lifecycle. He’s extremely passionate about Continuous Delivery, Agile software development, and empowering teams to adopt DevOps and Agile principles in their daily lives. He is also a member of the Cloudbees Customer Advisory Board and enjoys public speaking, travel, and time with his family.

  • Avoid the DevOps Temptation to Build It Yourself

    Avoid the DevOps Temptation to Build It Yourself

    As tempting as building your own DevOps incident communication tool sounds, you should think twice.

    My colleagues and I recently were on the phone with a company seeking an IT incident communications and collaboration solution (a.k.a. IT alerting) to eliminate the time wasted with inefficient communications between teams when dealing with major IT issues.  We were talking to Jeff, the director of IT operations, and Alec, the incident manager, about how our customers benefit from using IT service alerting solutions to automate the communication to their Dev and Ops teams, the stakeholders and the impacted customers every time a major IT incident is identified.

    We insisted on the fact that communication automation not only would save them a significant amount of time but also provide a consistent, predictable and repeatable process with timely and relevant communications to the different groups of people. We then moved to the ROI discussion; very easily we were able to quantify the hard dollar gains they would realize. In fact, the company estimated that an unplanned downtime of its most mission-critical business application costs the organization an average of $1,700 per minute during business hours, and half of that when issues occur at night. Depending on the nature of the incident, they need to get anywhere between five and 14 people from several teams on a restoration call or war room, and it takes them at least 20 minutes to get the right people.

    Right there, by automating the communication and the escalation, they could reduce that time down to five minutes and save the business at least $25,500 per incident.

    We were 20 minutes into the call when the conversation took a very interesting turn. Based on the cost savings we had calculated, Jeff and Alec start thinking  they may just be able to build their own communication automation solution in-house. “I’m pretty sure we can find a few developers and a DBA for a few weeks and get this done,” Jeff said.

    An IT communication automation solution provides the ability to reach out to the right on-call people via different communication channels (voice, text, SMS, mobile app) until they reply. If they don’t, automated escalation kicks in and the next person is contacted. Once they acknowledge they’ve received the notification, they can jump on the incident restoration call in one click. The solution also enables the incident manager to notify hundreds or thousands of impacted customers within a few minutes so frustrated users don’t start calling the help desk.

    “That’s a possibility, of course,” I said, “but do you really have an idea of what it would take to design the solution, build it, maintain it and support it when it is being used in production?”

    Jeff had raised a very good point, indeed. Why not build your own solution when you have software development resources available internally? The conversation had shifted from talking about our out-of-the-box solution to digging into what it would take for DevOps to build their own.

    What Does it Really Take to Build an IT Communication Automation Solution?

    The problems Jeff and Alec raised are all really big problems, and they are big enough for many IT departments for them to decide to go down the path toward building and deploying their own internal IT alerting solution. This may be the right way to go, but you need to think through the development effort involved and, more importantly, support the maintenance of this new DevOps tool.

    For some small shop, it may seem like a good idea, but building a reliable and economically viable IT alerting solution in-house requires more than just funding a development team for a few years and negotiating a good plan with telecom providers for SMS, voice and conference calls in the United States and in the countries where your IT people might be.

    You will need to consider the cost to develop the solution, host it, support and maintain it.

    To develop the solution, you’ll need to assemble a team comprised of a software architect, a few developers, a mobile app developer, a dba and a UX designer. Also, make sure they stick around for a few years so they can support and maintain their custom code and bring new features together as the tool becomes utilized across the enterprise. You surely want to avoid turnover here. The great benefit of such a custom-built solution is that it should address your specific needs, whereas a solution from a vendor may only accommodate 90 percent of those.

    These seven developers will cost you about $1 million U.S., and this is not including resources for QA and UAT, the infrastructure guys and a technical writer. That’s another few hundred thousand dollars per year, at least, until the tool is ready for prime time!

    In addition, you will need to reserve some operational budget to cover the cost associated with hosting, operating, monitoring, supporting and maintaining the solution:

    • Hosting the tool. Account for the hardware, the databases and the software you’ll need to build, test and run the solution in the production environment. If you want the solution to be highly available, you will also consider active-active clusters and a disaster recovery site. That’s another few thousand dollars U.S. every year.
    • Monitoring the tool. This new IT alerting tool most likely will be flagged as a critical application in your IT ops toolset and will require monitoring by the NOCs along with a runbook and an escalation procedure in case of a problem. Isn’t this a catch-22? When something wrong happens with your brand new IT alerting tool, you won’t be able to use it to reach out to the on-call people. Make sure you have a special emergency runbook for when this occurs. If you include technical maintenance, bug fixing, QA, that may add up to a half full-time employee, or roughly $75,000 per year.
    • Integrating the tool. It is most likely that you will want to integrate your IT alerting tool with other IT infrastructure and IT service management (ITSM) tools you are currently using so that communications can be triggered automatically as soon as a critical incident is detected. You may need to find a few API developers to make this happen. Remember, those integration connectors all must be maintained and tested with every new release of these IT operations management and ITSM tools.
    • Communicating with the tool. Besides voice, text and SMS, if mobile app push notification is a requirement then you need to build a mobile app so people can update their schedule and availability from their smartphone. This is a great feature that also will need to be developed, hosted, supported and maintained.
    • Running the tool. You will need to provision for all your communication costs should they be voice, internal voice, SMS, international SMS and collaboration tools such as conference calls. This can become significantly expensive, especially if you have distributed teams across continents. Jeff said the company had on average two critical incidents per week, with an average of 10 people on each call who would spend an average of three hours per conference call. That’s almost 200,000 minutes per year for conference calls only, not including SMS and voice. Prices range from a few pennies per minutes in the United States to a few dimes in other countries.

    What’s The Alternative to Building it?

    There are several IT alerting solutions available out there. Some are:

    • Designed for small local teams, others for broader and more distributed IT organizations.
    • Built for IT operations teams, others are built for the Service Desk.
    • On premise, others are cloud-based.
    • Only cover the USA, others offer worldwide coverage.
    • Are more expensive than others.
    • Subscription based, others offer perpetual licenses.
    • Mono product, others offer a platform you can leverage for other use cases.

    There’s a large variety of solutions you could choose from which will address most of your current needs. As a result, you may be tempted by a subscription based plan so you are not stuck with perpetual software licenses and lengthy onsite installation and configuration, support and maintenance. In additional these vendors need to meet their SLAs which will give you the assurance of a constant and good quality of service. Remember that they are also incentivized to deliver best in class customer service because subscription models imply they need to keep you as a happy customer year over year.

    How Should I Decide Which is Best for My Organization?

    It should be pretty straightforward. If you are passionate about IT alerting then go for it and build or hire a team, provide them with a roadmap and cross your fingers that everything will go smoothly and on time.

    At the opposite, if IT Alerting is outside your core business, if you don’t have bandwidth to develop this new IT Ops tool or if you need it sooner than later, then I think you are better focused on other IT projects which will have a direct positive impact on the core business of your enterprise. Save the time and budget to better align with the business and bring the new features that the business demands faster to market. If this is the case then you may consider speaking with an IT Alerting vendor. Gartner can provide insight on these vendors and how they integrate with the appropriate IT tools.

    There are so many dependencies that it will always be less expensive to buy the service from a vendor whose focus is on IT Alerting than it would be for you to build one from scratch. Today most companies are undergoing some kind of digital transformation which means more and more of the services they deliver will rely on IT. The odds of something going wrong with IT and impacting the company’s business operations have never been so high and they are only growing exponentially. Add to this the increased mobility of employees and distributed nature of teams due to acquisition, or cost optimization, and you now realize how challenging the Build-it-Yourself ­­option can quickly become.

    At the end of the day, you and your teams have a much greater chance to be rewarded and recognized by your upper management for helping the company being more efficient and gain market share over your competition than for developing a new IT Ops tool which you could have bought from a provider!

    Prior to this call, I doubt Jeff had thought through all the details of building the solution in-house, all the associated costs he would have to engage for building, supporting and maintaining his new IT Ops tool.

    We’ll see what comes out and what Jeff, his team and the CIO finally decide to do, but here’s what he said when we wrapped up: “Good thing we talked today, and I am sure we’ll be speaking again very soon”. We’ll be talking again to Jeff and his team and find out what way they want to go with their IT Alerting solution: Build it or Buy it?  This is the question.

    Can We Remain Sane Without IT Alerting?

    Without IT service alerting, when a critical IT incident occurs, the service desk or the critical incident manager ends up manually going through the following:

    • Internal procedure documents or runbooks to find out “what team(s)” should be responding to the incident.
    • Spreadsheets to identify “who” within the team should be contacted, then through listings to check “who is actually available.”

    And this becomes tricky when the teams are distributed across buildings, across geographies and countries, as you need to account for time zones, vacations, time-off, sick days and anything of this nature that may prevent someone from responding to notifications.

    Let’s say a dozen people from different teams have been identified to investigate a mission-critical application failure. That means you need to pull someone from the database team, two from the infrastructure team, three developers, two network engineers, the incident manager for this case, someone from UAT, two people from the NOC and someone from support. The developers are in Beijing, the service desk is in Atlanta and the two NOCs are located in the U.K. and the United States.

    Now, they need to be contacted as quickly as possible and the war room needs to be assembled so they can start investigating the issue and come up with a resolution action plan. Plus, in some cases, more than a hundred people would be involved in a single restoration call for a few hours, and sometimes for days. I’m not going to throw any company names here, but you can easily find these disastrous stories online as they very often make mainstream press headlines.

    In the meantime, don’t forget, the clock is ticking and every minute that passes means:

    • Bigger revenue losses for the company, particularly  in the case of an e-commerce website failure or slowdown,
    • Employee productivity drop-off when the ERP system fails,
    • Patient safety degradation if your EMR/EHR experiences a full or even a partial outage, and
    • Big mess ahead when an airline reservation system has a hiccup.

    As a reference point, the website Geekwire estimates that Amazon loses around $120,000 per minute when the site is not performing fast enough.

    In these situations, you need all hands on deck to act quickly. Not only do you need to contact every person individually, but also ensure they respond to the call and commit to working on solving the issue. As you know, emails don’t wake people up, especially on a Sunday at 2 a.m. What if not all the IT experts answer the message within the allocated time frame? You now need to escalate to the next person on the list and try reaching out …

    Also, people are not always reachable via the same channel at all time, in all countries. Some may prefer a phone call during the night and a SMS during weekends. For others, the best way to reach out is via mobile app push notifications. Ask yourself, is English OK for everybody, or do you need to take into account possible translation needs for different languages?

    Even though you are able to get the right contact information for all the right people, calling each and every person and explaining the situation can take a very long of time, and the clock is still ticking. By that time, users of the IT service may have already experienced service degradation and have started calling in to the help desk or entering tickets online. Not only do you have to deal with the outage, but your IT department is now drowning in a ticket storm. The clock is ticking and the phone is now ringing!

    If you are facing an e-commerce website slowdown or outage, you will also need to deal with bad reviews and negative comments being Tweeted and shared about your company over social networks.

    Vincent Geffray


    About the Author/Vincent Geffray

    Vincent Geffray is Senior Director of Product Marketing at Everbridge with focus on IT Service Alerting & Communications Automation and IoT.

    He has more than 14 years of experience in the information technology business, designing, promoting and selling Enterprise IT Operations Management solutions, including Critical Communications, Application Performance Management, IT Process and Workload Automation. He also has international experience as he started his career in Europe. Vincent holds a Master of Science (Mechanical Engineering and Computer Science) and executive certificates from the MIT – Sloan School of Management.

    Vincent’s LinkedIn: www.linkedin.com/in/vgeffray

    Vincent’s Twitter: @vgeffray

     

  • Iterative Indicators: Measuring DevOps ROI

    Iterative Indicators: Measuring DevOps ROI

    It’s well-established that application of ROI measurements to IT investment remains an imperfect science, and the same goes for ongoing adoption of DevOps methodologies.

    The fuzzy math of vendor-driven ROI calculators aside, even the most respected industry watchers have long struggled to create concrete parameters for assessment of technology spending. This, in large part, has been related to the fact that the requirement for continued investment has outweighed the value of short-term metrics.

    At the same time, it’s hard to put a price on the influence that paradigms including mobility, virtualization and the cloud are having on today’s business world. The scope of the so-called Applications Economy is only truly beginning to be realized.

    For in-depth discussion of DevOps ROI, register today for the upcoming webcast “Maturity Metrics – Analyzing the 2016 State of DevOps Report” with noted industry expert Gene Kim.

    With DevOps, the challenge of ROI measurement evokes similar characteristics as with these other bellwether movements. The affect that leveraging DevOps to become more agile and respond adeptly to changing customer expectations will have, long-term, ultimately will be realized as much in organizational viability as in any immediate cost-savings or other factors.

    That said, the recently published 2016 State of DevOps Report, assembled by the researchers at DevOps Research and Assessment (DORA), goes further down the path toward creating meaningful ROI metrics than any other such previous effort.

    For starters, the 2016 report builds on previous year’s conclusions that so-called “high-performing organizations”—those already deeply engaged in DevOps practices—are “decisively outperforming their lower-performing peers in terms of throughput,” and this gap continues to widen.

    Moreover, DORA contends that high performers deploy applications code 200 times more frequently than slow performers and achieve 2,555 times faster lead times. Perhaps even more importantly, in particular as it relates to the ability to improve applications performance, the report estimates that leading DevOps practitioners lay claim to 24 times faster recovery times and three times lower change failure rates.

    The State of DevOps Survey, completed by roughly 4,600 technology practitioners, also found that high-performing teams spend far less time on so-called “unplanned work and rework”—most often required to address existing problems—allowing them to spend nearly 50 percent more of their time on new work. The latter brand of effort is typically aimed at adding or improving feature functionality—or, in simple terms, innovation.

    As increased software velocity and reduction of MTTR represent the most critical differentiators in today’s environment, where an end user may wait only seconds for an app to load before abandoning your brand altogether, these conclusions obviously carry impressive weight.

    Finally, based on a framework established by research analysts at IDC which suggests that hourly application downtime costs can range from $1.25 to $2.5 billion for a Fortune 1000 firm, and that the average cost of a critical application failure is $500,000 to $1 million per hour, the State of DevOps Report allows for the conclusion that high-performing organizations save an average of more than $91 million per year.

    Much of this advantage is found, the researchers note, in the form of lower applications change failure rates, or those updates to software code that result in subsequent performance issues or outages. While high-performing DevOps practitioners experience an average change failure rate of 7.5 percent, medium-performing organizations see that figure rise dramatically, to a whopping 38 percent.

    If the undeniable adage that “time is money” applies in today’s Applications Economy as much—if not more than ever—than these ROI calculations would appear to infer substantial meaning.

    Later this month, Gene Kim, one of DORA’s founders and a key contributor to the State of DevOps Report, will host a webcast with CA Technologies expert Aruna Ravichandran to discuss DevOps ROI and many other related topics. Register for that event today.

  • Q&A: CNCF on Instilling a DevOps Culture, Part 2

    Q&A: CNCF on Instilling a DevOps Culture, Part 2

    In part one of this two-part series, devopsy.kinsta.cloud introduced the Cloud Native Computing Foundation (CNCF), a nonprofit organization with 49 members engaged in promoting the development of cloud native applications. Let’s continue with the CNCF’s thoughts on instilling a DevOps culture.

    devopsy.kinsta.cloud: Why do developers need the freedom to choose how they build software? What kinds and levels of freedom? Is this about approaches, development tools or something else?

    Brian Grant: All of the above: approaches, tools, languages … Different solutions work better for different workloads, scenarios, environments and people. Even new applications developed from scratch to be cloud-native aren’t typically developed in a vacuum—their developers may be familiar with particular languages or tools, the new application may need to interact with legacy applications; it may need to be built with and/or deployed onto existing infrastructure, etc. Often developers need to be able to adopt new technologies or approaches incrementally.

    devopsy.kinsta.cloud: How do you recommend providing this freedom to developers? How do you help provide it?

    Grant: Containers provide an ideal mechanism for providing this freedom, since they can be used to deploy both new and legacy applications, written in any language, built by any tool, into any environment. It’s a goal of the CNCF to foster an ecosystem of composable technologies, such as Kubernetes that facilitate the management of container-packaged applications.

    devopsy.kinsta.cloud: How does this align with instilling a DevOps culture?

    Grant: Because containers are small and fast, one application can be packed in each container image. Consequently, immutable container images can be created at build/release time rather than deployment time, since each application doesn’t need to be composed with the rest of the application stack nor integrated into the production infrastructure environment. This empowers developers to deliver deployable artifacts to operations.

    devopsy.kinsta.cloud: How is code reuse a need of the developer?

    Craig McLuckie: The vast majority of the actual code that is run in any given deployment is written by others. Only a tiny fraction of code in any given instance is actually written by the developer. The rest is everything from common libraries, to full OSS subsystems, to commercial software that systems, to adjacent software projects that provide some business functions. Developers need a common way to integrate with existing systems (when it makes sense) or to find and reuse existing code in a way that is controlled and operations-friendly.

    devopsy.kinsta.cloud: How do you recommend giving developers the ability to reuse code? How does your organization help with this?

    McLuckie: CNCF stands behind two technologies that are critical to code reuse. The first is the use of containers, which represent an intrinsically easy and predictable way to reuse even a relatively complex piece of software. The second is microservices-based architecture that make it easy to wire together systems and reuse existing services versus having to build their own.

    devopsy.kinsta.cloud: How does this align with instilling a DevOps culture?

    McLuckie: Containers make operations far more predictable and reduce possible avenues of error when deploying and updating systems. Rather than run potentially error prone imperative configuration systems to reuse code, containers are simple, lightweight and predictable, and reduce the potential for errors.

    Microservices allow for better operations specialization and create systems that are more intrinsically agile and easy to evolve. They allow for smaller teams that are focused on delivering a specific function versus having to align around large system boundaries. This creates a more productive and operationally viable environment.

    devopsy.kinsta.cloud: What is cloud-native? What does that mean?

    McLuckie: For CNCF, ‘cloud native’ is about a new pattern of application development that was pioneered by the internet companies, but that is equally applicable to developers and operators running more traditional workloads.

    We see three common attributes that make systems ‘cloud-native’:

    Container-packaged: Applications and processes are run in software containers as a unit of application deployment, which facilitates reproducibility, transparency and resource isolation. This improves overall developer experience, fosters code and component reuse, and simplifies operations.

    Dynamically managed: Applications are actively scheduled and managed. This radically improves machine efficiency and resource utilization while reducing the costs associated with maintenance and operations.

    Microservices-oriented: Applications are loosely coupled, with dependencies explicitly specified. This significantly increases the overall agility and maintainability of applications.

    Together, these three capabilities allow developers to build systems that are intrinsically agile and scale well. They significantly reduce the operational complexity of running an application, allowing operators to be more focused on application-level concerns and relying heavily on smart systems to do the operations heavy lifting.

  • DevOps Matchmaking: APM + CI = A Perfect Marriage

    DevOps Matchmaking: APM + CI = A Perfect Marriage

    As anyone who has ever been set up on blind dates by friends can attest, finding the right match in today’s world is a tricky feat.

    There’s a lot of evidence suggesting that the frantic pace of life makes such matchmaking more difficult than ever. That said, when the right set of complimentary traits exist and there’s a willingness to find common ground, things can work out.

    Spike Jonzian-notions of artificial intelligence aside, certain technological partnerships are increasingly being perceived as “a perfect marriage” within the context of DevOps automation.

    Register today for the upcoming webcast: “Using APM to Turbocharge Continuous Integration”

    These technological matrimonies closely support the underlying tenets of DevOps methodology—collaboration, experimentation and increased velocity. In fact, it’s easy to wonder why no one ever conjoined them before. But we were using traditional waterfall development and operations and so couldn’t conceive of such a thing. On the other hand, emerging availability of tooling supporting new integrated workflows represents a significant catalyst.

    Finding the Perfect Fit

    One such DevOps confederation getting a lot of attention is the matchmaking of continuous integration (CI) and application performance management (APM) technologies. Tying together these once-disparate systems makes a lot of sense, despite the fact that few tools would seemingly appeal to more (traditionally) polarized constituencies.

    Continuous integration has been a staple of the development community for many years. It emerged as teams evolved the practice of long build times into more frequent check-ins to deliver code and look for potential errors more quickly. Today, with the rise of CI tools such as the Cloudbees Jenkins platform, some development teams are touting tens of thousands of builds per day.

    On the other end of the spectrum, squarely on the turf of IT operations, APM has been evolving rapidly over the past few years as organizations have sought to improve use experience and applications reliability via dedicated monitoring. Enabling this ability to identify and address emerging issues has resulted in APM becoming the fastest-growing segment in the IT ops management market, according to Gartner.

    DevOps matchmaking factors in when you bring these tools together to create an automated workflow that spans their respective use cases. A cross-functional team can leverage APM-level monitoring and KPIs within the domain of CI and testing to identify potential performance obstacles introduced in new code. Doing so then rather than waiting to respond later in the applications life cycle benefits everyone.

    Reaping the Benefits

    For example, say an e-commerce applications developer has implemented a new inventory search functionality—something considered a key differentiator by business management. The developer knows this feature could rely heavily on some back-end database system and wants to ensure it’s tested properly, even as the code is being introduced.

    Integrating APM and CI allows the entire team to monitor the process and test various conditions related to the update, tracking multiple builds and looking out for related performance issues. Such integration also allows for centralized tracking of other key attributes such as build number, status and build date, to further ease management.

    Most importantly, by tying these two critical aspects of the applications delivery life cycle together, the collaboration and feedback loops required to truly embrace DevOps methodology become ever more valuable as these core Dev and Ops functions become intrinsically linked.

    If this type of DevOps advancement gets your heart pumping, you’re not alone. Later this month, we’ll host a webcast here on devopsy.kinsta.cloud featuring experts from CA Technologies and Cloudbees. They’ll be discussing the benefits of matchmaking with APM + CI integration. They’ll also detail real-world benefits organizations leveraging integration of our respective technologies (CA APM and Cloudbees Jenkins) enjoy.

    We obviously feel that this is a DevOps tooling marriage that will mature, change and stand the test of time. We’d love to garner your questions and feedback on the topic.

    Which is all good, because thankfully there’s no such thing as Tinder for DevOps … yet.

  • To Be Continuous Podcast: Have We Forgotten How To Code?

    To Be Continuous Podcast: Have We Forgotten How To Code?

    Welcome to To Be Continuous, a show about continuous delivery and software development, hosted by Heavybit members Paul Biggar, founder of CircleCI, and Edith Harbaugh, CEO of LaunchDarkly.

    In this episode, Paul and Edith discuss the fallout after the widely covered “left-pad” incident, and while they agree that these sorts of moments move the entire open source community forward, they wonder: Have we forgotten how to code?

    [soundcloud url=”https://api.soundcloud.com/tracks/264605904?secret_token=s-Kv9Ep” params=”auto_play=false&hide_related=false&show_comments=true&show_user=true&show_reposts=false&visual=false” width=”100%” height=”166″ iframe=”true” /]

    Edith: Hey, Paul. So, somebody unpublished a module called left-pad and the internet basically exploded. And now it’s been a couple weeks since then, so there’s a lot of different topics to cover in terms of what this means for open source, whether it means that people have forgotten how to program.

    Paul: So LaunchDarkly. Or, I’m sorry, the left-pad. I’m obviously looking at my own t-shirt.

    Edith: You’re looking at your LaunchDarkly t-shirt?

    Paul: The left-pad incident was pretty interesting and one of the things that we did when coming up to this was just, like, looking at all the Hacker News discussions and comments on it.

    And there’s wildly varying positions on what this means for open source, what it means for whether people can program, what it means for, like, about the Node ecosystem. So to kick this off, why don’t you give us a recap of the entire incident?

    Edith: Yeah. So, in short, a programmer had a module called Kik, K-I-K. Which is also [the name of] a very popular messaging app. I mean, even I’ve heard of it and I’m not a teenager.

    Paul: The Kik lawyers contacted the dude. Said, “Please take down your module, change it.” And the programmer said, “No. I basically don’t believe in copyright laws.” So then, the Kik people contacted NPM. The NPM people took down the module called Kik. And the guy, in I’d say, kind of a fit of pique, said, “Okay, you took down my one module, I’m gonna take down all my modules.” Basically, I’m taking my marbles and going home.

    So, he took down all of his modules. One of which turned out to be an incredibly popular module called left-pad, which did basically what the name implied. It sorted left pads. And without this in NPM, the quote I read was, “Builds all over the world started to fail very quickly.”

    Paul: So as I understand it, left-pad was used by another module, which was used by another module, which was used by something core, or like, this incredibly popular module—

    Edith: Yeah, it was basically turtles on top of turtles on top of turtles, and at the bottom turtle was this guy who—

    Paul: Took his marbles and went home.

    Edith: Yeah, or yank the bottom Jenga, basically.

    Paul: Gotcha. And so all the builds started to fail. People’s deploy started to fail. And people got pissed.

    Edith: People got pissed because they didn’t even realize that they had this dependency. So what happened was NPM basically republished it. They said that, even though you’re the original publisher—

    Paul: So there was a lot of outcry on the internet and then they republished it.

    Edith: Just basically said, “You don’t have the right to un-publish this.”

    Paul: Gotcha. So, um, but they had an Unpublish button, as I understand it. So he did something that was built into NPM to remove a module.

    Edith: Yeah, and since then they have tightened their rules a lot. They basically said that this should be something that’s used extremely rarely, if at all, and not something you can just do capriciously.

    Paul: So one thing that’s interesting about the NPM ecosystem, and the Node ecosystem in general, is they’ve had a bunch of things like this. Things that are security-related, or that are drama-related.

    And people have repeatedly come out and say, “Oh, no, JS is a tar pit, or ghetto,” or whatever it is that people use to describe poor ecosystems, that normal programmers don’t know how to code, and so on, so on.

    And what it looks to me like is, you know, each of these incidences brings the Node ecosystem quite a bit forward. To the point that, I mean Node is relatively new, it hasn’t had 15 years before prime time in the way that Ruby or Python did, or 20 years before it got big, and it’s a real, kind of bottom-up thing.

    I mean, if someone built it and there were some steroids and then someone else took over, and then NPM took over, and then. It’s this sort of weird language from the ecosystem perspective. It didn’t have the same advantages that, like, Java had, or that C or C++ had, in order to get to maturity. And so each of these incidences propels it closer to maturity.

    Edith: Yeah, I compare it somewhat to when electricity first started coming out. And then you were just working through all the issues that could happen. Like, for example, when a power line went down or a transformer blew.

    Like, you work through, Okay, what are our points of failure? Let’s not make that a point of failure again.

    Paul: Hmm. So, NPM changed their policies on this basis, right?

    Edith: Yep, so now you can’t have an individual contributor be able to unpublish, even if they originally published. Now you have to contact them, and it’s much more stringent.

    Paul: Gotcha. The response, despite people being … Well, people were annoyed at their response.

    Edith: It seems perfectly rational to me.

    Paul: Oh, I think it seems perfectly rational. This is the thing about the in trend. There’s always some set of people who are annoyed at everything you do.

    Edith: Well you know, the internet is full of billions of people. I mean, there’s gotta be some sort of standard deviation, or otherwise it would be a very boring internet.

    Paul: Right, right, and this is why there’s always haters on Hacker News. No matter what you do. If you do it one way, there’ll be one group of haters, if you do it another way, there’ll be a different group of haters.

    And so, with left-pad, there were people who were annoyed that NPM retroactively decided that they had ownership over their namespace, which previously, they had sort of gifted to people in the community, the first people to take the namespace.

    Edith: You mean the original thing about Kik?

    Paul: So there’s that, but there’s also the left-pad. They took away the sort of autonomy of the left-pad offer.

    Edith: I read a good article that basically says part of open source is, if it truly is open source, do you maintain the rights to it? Or is it a community project?

    Paul: Hmm. The traditional way of deciding that sort of ownership was the fork. That you could go, and you could fork, and when you forked, you weren’t necessarily entitled to the same name, you weren’t entitled to the same trademarks. When Debian forked Firefox, they called it Iceweasel.

    When Jenkins was forked, or Hudson was forked, it became Jenkins. GCC got forked. They all got new names. But what was the fork here, it wasn’t even a fork. It was a republish of the same thing, the same software, in a namespace that the original author didn’t control.

    So typically you’d own the URL, you know, if you have a software library, you’d own the URL. And they did own, in some sense, the URL within NPM, or the name within NPM’s space, and NPM, the sort of owners of that namespace, overrode it.

    Edith: I think they did what was necessary for good order.

    Paul: Sure. I completely agree, I think that was a good decision.

    Edith: I mean, so to take this to the logical conclusion, what if you had a module named left-pad, and you decided that, like, as a prank you were going rewrite it to be right-pad? Like, sure, that’s … Is that within your rights? Kind of, but it’s a real jerk thing to do that you probably want to prevent.

    Paul: This is kind of one of the dangers of the whole ecosystem around centralized package managers, of sorta trusted package managers, where there’s no actual trust involved. So, what I mean by that is what is published does not have any gatekeepers.

    Edith: Yeah, exactly.

    Paul: I mean, it’s great, it allows an ecosystem to grow much faster, but it has safety concerns because people generally don’t pin their packages to an exact version.

    Edith: You’re basically pinning it to a floating value.

    Paul: You’re pinning it to a floating value. And that floating value could change. There’s no guarantee of what a minor number means or what a major number means or what a patch number means or what a patch even means. There’s some sort of, like, general community guidelines in semantic versioning, but there’s no enforcement of that.

    Edith: Yeah, and I mean this basically goes back to the whole Cathedral versus Bazaar thing.

    Paul: Right, right. It’s very Bazaar. And intentionally so. It’s the thing that allows a community to grow, and is there a point at which open source communities need to, like, batten down the hatches to prevent that sort of behavior? Or prevent that sort of risk?

    Edith: Yeah, and it’s really interesting. I think this goes back to something we’ve talked about with Nadia Eghbal and Sean Byrnes a couple episodes ago about when you buy from a corporation, you have some sort of guarantee of standards that they publish somewhere. You know, this is our guarantees versus with open source, you don’t normally have those same sort of guarantees.

    Paul: Even when you do, it tends to be—

    Edith: There’s no enforcement mechanism.

    Paul: Right. So there’s no enforcement mechanism in the Bazaar.

    Edith: Well, there’s no, um … Like, so with a company, if a company has said, “Okay, we’re gonna release twice a year and it’s gonna have this level of quality,” and they break that, you can walk with your feet or your money. If an open source project stops or does something that you don’t like, there’s very little enforcement end.

    Paul: Theoretically, you could walk. You know, you could fork the thing, but when you end up in an ecosystem that has massive network effects, and in the way that NPM does, you can’t walk with it. Because the pends is all transitive. The left-pad was, you know, a turtle way at the bottom of the stack.

    Edith: It was almost like a turtle hatchling.

    Paul: So, to fork left-pad, you would have to fork the entire NPM ecosystem.

    Edith: Yeah, and it’s not even. The fork is not the issue, though. The issue was that people were depending on it being in a certain place in a certain way. It wasn’t that it wasn’t forked, it was just like this entire structure at the bottom was gone.

    Paul: I guess what I’m saying is that if you get pissed off with a certain set of developers or a certain set of practices within the NPM community, because they’re so interlinked, you don’t have the traditional open source option of forking.

    Edith: Absolutely. Absolutely.

    Paul: You could rename it. You could pick a different library, but because of the way—I’m not sure if they still do this, ’cause I read something about it, but in NPM, it used to be that the version of the software that your library took was the version that library got. Do you know what I mean by that, okay. So let’s say there’s some software, let’s call it left-pad.

    Edith: Let’s call it right-pad.

    Paul: Right-pad. So, right-pad version one is being used by library A. And right-pad version two is being used by library B. In the Java ecosystem, and many, many other ecosystems, only one version of right-pad would be used.

    And I believe in NPM, both versions of right-pad would be used. So library A will use version one, and library B will use version two. Now that’s definitely the way that it used to be, I’m not sure if they’ve actually changed that.

    Edith: Yeah, I don’t know, but that sounds very messy, very quickly.

    Paul: So both options are terrible. And there isn’t a right way to do it.

    So, really, what it depends on. So, the NPM way of doing it, every library get its own version of the dependencies, is fantastic. Because it lets that library do what it actually intended to do under the covers.

    If, however, you start having an object that gets sent around, or that two modules are, let’s say it receives a, I think, an HTTP packet or something like that would be a good example. Let’s say you take an HTTP packet from one module and just hand it to another module, and they have different understandings of the shape of that object, or what functions you can run on that object, then that’s messy.

    But, on the other hand, if you override the version of right-pad that some other library’s using, you end up with all sorts of problems. This is a major problem in the, sort of the Maven ecosystem. And at CircleCI, we used Clojure, and Clojure is built on top of the Maven ecosystem, and we would have bugs where the library that we used.

    One library that we used had a dependency, and that was in the package file for another thing. And so, that’s the version of the packets that we used. So we would have to pick. And as a result of that, we have to pick the library that works. And, often, there isn’t a library that works for both, or there isn’t a, sort of subdependency that worked for both. So those are close to forked no matter which way you do it.

    Edith: Yeah, I mean, we ran into the same issues with our STKs. I mean, ’cause we have dependencies on other libraries that sometimes conflict.

    Paul: Right, disaster.

    Edith: On the other hand, I mean, the bigger point, I think, was. So there was an interesting backlash, I think, that everybody kinda projected what they wanted on the NPM thing.

    People said, Oh, people don’t know how to program anymore. You know, why do you even use what they called left-pad? You know, why don’t you just grind your own wheat and make your own bread from scratch and eat it at lunch also?

    Paul: I have no sympathy at all for this view of the world.

    Edith: Uh, that you should make everything from scratch? Or—

    Paul: That, “Oh, we’ve forgotten how to program because we need left-pad.”

    Edith: Yeah. The fact that we have modules available that make it easier and easier and easier to program is a good thing.

    Paul: I think it’s kinda different to that. I think it’s more of a curmudgeon view of the world. It’s a get-off-my-lawn—

    Edith: Wait, that you’re the curmudgeon?

    Paul: No, the people who complain, “Have we forgotten to program anymore?” I think it’s a no true Scotsman kind of argument. Real programmers know how to write their own left-pad, real programmers write in statically typed languages, real programmers write in C, real programmers, and I’m going back in time here, real programmers write in Assembly, real programmers hand-code their. Tweak the needles on the.

    Edith: They do their own garbage collection.

    Paul: Oh, and it’s garbage collection, what is this? Garbage collection is for amateur coders, right? I mean, you could just as easily have written, have we forgotten how to manually allocate memory?

    Edith: Or, you might as well say, like, nobody knows how to make their own transistors anymore. I mean, like, the entire computing revolution has been that you no longer have to assemble a computer by hand.

    Paul: Right. And each layer of the ecosystem allows a vastly larger number of people to take part in it. So I think the thing that we’re seeing now. This has been happening for five or 10 years, but what’s getting really, really big now is people who only know how to front-type program.

    People who only know Javascript and HTML/CSS, and they go to boot camps and they come out, they maybe have some, like, vague real understanding.

    And they call themselves coders, and we, the real programmers, who know how to write a quick sort, and who know how to write left-pad, we don’t welcome them to our community. And frankly, I mean, I have felt this in the past, I have since changed my mind, but it’s a very, very common perspective.

    This podcast is brought to you by Heavybit, a program that helps startups turn products loved by developers into successful businesses. Throughout the program, founders work on developer traction, product market fit and customer development. If you like what you hear, be sure to subscribe to Heavybit’s Podcast Network on iTunes.

  • Q&A: CNCF on Instilling a DevOps Culture, Part 1

    Q&A: CNCF on Instilling a DevOps Culture, Part 1

    The Cloud Native Computing Foundation (CNCF) is a non-profit comprised of some 49 industry participants that have come together to drive development and adoption of cloud-native applications and services. The CNCF is uniting such giants as Google, IBM, Intel and Cisco Systems to distill a collection of container technologies that end-user companies deem praiseworthy to reach its goal.

    The CNCF intends its membership to represent end users (the CNCF website lists one end user, Goldman Sachs), cloud and container technologies, online and IT services, and academic institutions.

    On behalf of the CNCF, Craig McLuckie, its Governing Board chair, and Brian Grant, its Technical Oversight Committee representative, weigh in on leading the DevOps transformation and instilling a DevOps culture in this two-part Q&A.

    devopsy.kinsta.cloud: How is the CNCF specifically involved in leading the DevOps transformation by instilling the DevOps culture, in the industry or in member companies, for example?

    McLuckie: We believe that at the heart of the DevOps culture is the need to reduce the friction and, indeed, the barriers between teams that build an application and the teams that run an application. Developers learn to think about an application as a living service that evolves continuously and rapidly to meet the evolving business needs. Operations is there to deliver the tools and environment needed for them to successfully drive their application.

    devopsy.kinsta.cloud: Why do developers need an environment that is safe to change? What kind of change? Safe how?

    McLuckie: Safe change has many potential meanings: The first kind of “safe” is about creating deterministic behavior in operations. Does the system handle a change correctly every time? If I make a change to two systems, will they have the same state? How about to 1,000 systems? It’s important to focus on creating strong determinism by removing the moving parts in a production deployment.

    The second kind of “safe” is about being able to validate that a change is good—not just in pre-production environments, but in the actual production environment—with a simple and deterministic rollback. It is important to make it trivial to replicate environments, and offer a way to run a simple experiment in production (e.g. route 1 percent of my traffic to this new version) with the option to deterministically roll forward or backward without effort.

    A third kind of “safe” is about being able to ensure that every change is deliberate. One of the problems we often see in production systems is “configuration drift” that isn’t driven through any kind of formal process. This should be addressed by creating a strongly declarative toolset that makes every change deliberate and trackable.

    devopsy.kinsta.cloud: How do you recommend providing these things that developers need? How do you help provide them?

    McLuckie: There are multiple issues like data, security governance and applications that need to be addressed. Additionally, companies want to deliver apps with high velocity. How do you solve all of this? A vendor-neutral organization that can harmonize emerging technologies is important for facilitating cloud-native. Given the large number of players in the marketplace with competing approaches, having an open source way to solve this is also important.

    Grant: Cloud-native infrastructure enables self-service and “hands-off” operation, including provisioning, deployment, scaling, healing, discovery, monitoring and more, with relatively little marginal effort for specific applications. By supporting open source projects such as Kubernetes and Prometheus that provide such functionality, the CNCF hopes to democratize high-velocity application delivery, which was previously achievable mainly by web-scale companies.

    devopsy.kinsta.cloud: How does this align with instilling a DevOps culture?

    Grant: In a DevOps culture, operators are both partners and customers of the developers. Developers take responsibility for meeting operational requirements: security, reliability, availability, scalability, efficiency, actionable monitoring and logging output, necessary configurability, compatibility with the production environment, etc. Cloud-native infrastructure provides mechanisms developers and operators need to facilitate and capitalize on those capabilities.

    Stay tuned for part two of the CNCF interview.