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Tag: DevOps workflow

  • Opsera Leverages AI to Simplify DevOps Platform Migrations

    Opsera Leverages AI to Simplify DevOps Platform Migrations

    Opsera is leveraging a generative artificial intelligence (AI) model it built to enable DevOps teams to migrate from one platform to another.

    Gregg Holtzrichter, chief marketing officer for Opsera, said the Hummingbird AI model makes it simpler to migrate source code from, for example, a Bitbucket on-premises continuous integration/continuous development (CI/CD) platform to GitHub.

    Opsera originally developed Hummingbird as an orchestration engine that integrates DevOps workflows spanning multiple tools and platforms. The primary goal is to make it possible for DevOps teams to unify their workflows, said Holtzrichter.

    At the same time, Opsera is now making it possible to leverage a generative AI model to reverse engineer the source code a DevOps team may have developed to extend the capabilities of a specific platform. That new code then makes it possible to significantly reduce the total cost of switching DevOps platforms, said Holtzrichter. As part of such an effort, Opsera is also now providing support for organizations looking to specifically migrate to GitHub Copilot and GitHub Actions.

    It’s not clear how many DevOps teams might be looking to switch platforms, but with the rise of generative AI capabilities for writing code, interest in platforms such as GitHub has increased, noted Holtzrichter. In addition, support for platforms such as the on-premises edition of Bitbucket is being sunsetted by Atlassian as part of an effort to drive more customers toward the cloud edition of the CI/CD platform.

    Regardless of the underlying platforms involved, generative AI promises to reduce the ability of any vendor to lock customers into a specific platform. As DevOps teams extended DevOps platforms over the past decade, many of them have discovered that the integrations they created and maintained made it all but impossible to switch platforms. With the ability to refactor much of that code based on the insights surfaced by the Opsera platform using generative AI, the time and effort required to switch platforms has been substantially reduced, noted Holtzrichter.

    At its core, Opsera makes it possible to apply analytics to DevOps workflows as they become more complex. The number of dependencies that exist between various application modules, for example, makes it exceedingly difficult for DevOps teams to manually identify the impact a delay in one project might have on any number of other downstream projects.

    The Opsera platform surfaces that intelligence by scanning all repositories and branches, including commit history and generating alerts and notifications whenever KPI thresholds or compliance requirements are exceeded. DevOps teams can also use the platform to assess their overall DevOps maturity using, for example, the DevOps Research and Assessment (DORA) metrics defined by Google. In addition, many organizations are keen to discover what best practices should be adopted by other application development teams.

    Now that AI is being applied to that analytics capability, it’s become possible to extend the reach of the Ospera platform beyond analytics to include source code migration. Each organization will still need to determine whether such an effort is worth the remaining time and effort still required, but at the very least, most DevOps teams can take comfort in the fact they can now keep their options a lot more open.

  • How GitHub Actions Simplifies Your CI/CD Workflow

    How GitHub Actions Simplifies Your CI/CD Workflow

    In today’s fast-paced world, being able to deploy applications quickly is essential for success. However, setting up a CI/CD pipeline can be a tedious and time-consuming task. Fortunately, GitHub Actions can help simplify and automate your workflow, making it easier than ever to get your applications up and running in no time. In this blog post, we’ll take a look at how to set up a React application with GitHub Actions and explore the benefits of using this tool for your CI/CD needs.

    Continuous Integration and Continuous Deployment

    Continuous integration (CI) and continuous deployment (CD) are essential components of any product development workflow. CI is the process of automatically building and testing code changes, while CD is the process of automatically deploying code changes to a production environment. Both CI and CD help to ensure that code changes are deployed quickly and efficiently, with minimal errors.

    Setting up a CI/CD pipeline can be a tedious and time-consuming task, particularly if you are not familiar with the required tools and technologies. However, using GitHub Actions can help to simplify and automate your CI/CD workflow, making it easier and faster to deploy your code changes.

    GitHub Actions is a powerful tool that can be used to automate many different tasks, including building, testing and deploying code changes. In addition, GitHub Actions can be used to trigger other actions in response to specific events, such as when a code change is pushed to a remote repository. This makes it an ideal tool for automating your CI/CD workflow.

    There are many advantages to using GitHub Actions for CI/CD. First, it is easy to set up and use, even if you are not familiar with the underlying technology. Second, it integrates seamlessly with GitHub, making it easy to track and manage code changes. Finally, it is highly customizable, allowing you to tailor the automation process to meet your specific needs.

    Setting up a React Application

    React is a popular JavaScript library for building user interfaces. Setting up a React application is not complicated, but there are a few important steps you need to follow.

    1. Choose your development environment. You can use create-react-app to set up a development environment with all the necessary dependencies and scripts.
    2. Install React and ReactDOM. React is the library that handles rendering of UI components while ReactDOM takes care of interaction with the DOM.
    3. Create a component file. In this file, you will write your UI code using JSX syntax.
    4. Include the component file in your HTML page. Now you can see your component rendered on the page!

    Development Mode and Production Mode

    In software development, there are two primary modes that code can be run in: development mode and production mode. Development mode is typically used by developers when they are actively working on code. In this mode, code is usually not optimized and may include debugging features that help developers identify and fix errors. Production mode, on the other hand, is used when code is ready to be deployed to end-users. In production mode, code is typically optimized for performance and security.

    One of the benefits of using GitHub Actions is that it makes it easy to manage both development and production workflows from a single platform. With GitHub Actions, you can create separate workflows for development and production, or you can create a single workflow that automatically detects whether code is being pushed to a development or production branch. This flexibility can simplify your CI/CD pipeline and help you avoid errors that can occur when manually managing multiple workflow files.

    To learn more about how to use GitHub Actions to simplify your CI/CD pipeline, check out the following resources:
    – [GitHub Actions documentation](https://help.github.com/en/articles/about-github-actions)
    – [Tutorial: Use GitHub Actions to deploy a static website](https://help.github.com/en/articles/configuring-a-workflow#creating-a-workflow-file)
    – [CI/CD with GitHub Actions blog post](https://blog.github.com/2019-08-08-introducing-github-actions/)

    Setting up GitHub Actions

    Setting up GitHub Actions is simple and only requires a few steps.

    First, you’ll need to create a new file in your project’s root directory called “.github/workflows/ci.yml”. You can name this file whatever you like, but for the purposes of this article we’ll call it “ci.yml”.
    In this file, you’ll need to specify the language your project is written in and the name of the action you want to run. For example, if your project is written in JavaScript and you want to run the “lint” action, your file would look like this:

    name: CI
    on: [push]
    jobs:
    build:
    runs-on: ubuntu-latest
    steps:
    – uses: actions/checkout@v2
    – name: Use Node.js ${{ matrix.node-version }}
    uses: actions/setup-node@v1
    with:
    node-version: ${{ matrix.node-version }}

    Breakdown of the Actions File

    In the “ci.yml” file, there are three main sections: “name”, “on”, and “jobs”. The “name” section is where you specify the name of your CI workflow. The “on” section is where you specify the events that will trigger your workflow to run. In this example, the workflow will run every time code is pushed to any branch. The “jobs” section is where you define the actual jobs that make up your workflow. In this example, there is only one job called “build”.

    The “build” job has two steps. The first step checks out the code from GitHub. The second step runs a Node.js linter on the code to check for syntax errors. If any errors are found, they will be displayed in the GitHub UI.

    You can also add additional jobs to your workflow, such as testing or deployment jobs. For example, you could add a job that automatically deploys your code to a staging environment whenever code is pushed to the development branch. This would allow you to test new features in a safe environment before deploying them to production.

    Adding additional jobs can help simplify your CI/CD pipeline by automating more of the process. This can free up time for other tasks, such as writing documentation or working on other features.

    Running the Action

    Assuming you have already set up a workflow file (ci.yml) and added a job to it, running the workflow is simple. All you need to do is push some code to your GitHub repository and the workflow will automatically run.

    You can also manually run a workflow by going to the Actions tab of your GitHub repository and clicking the “Run Workflow” button. This can be useful for debugging purposes or if you want to run a particular job without pushing code.

    If you want to see the output of a workflow, you can go to the Jobs tab and click on the job that you want to see. This will show you the log output of the job as it ran.

  • Forget Automation: Why IT Should Take UX Cues From Fine Dining

    Forget Automation: Why IT Should Take UX Cues From Fine Dining

    As a college student, I worked at a five-star Italian restaurant where I learned the discipline and practice of customer service. The general manager knew exactly which corner to stand in to get a view of every single table during service. They would gauge diners’ experience according to how they were interacting, their microsignals, how much food was left on their plate and the way they glanced around the restaurant. What does this intense attention to detail and individual customer experience have to do with running a service-oriented technology business? Everything.

    The tech industry is notorious for automating processes at the expense of personalization, and that aversion can extend to building the relationships necessary to produce a successful end product. Understandably, some companies and their developers prefer to keep relationships with their clients strictly functional because these connections are messy, people are unpredictable and nothing ever goes completely according to plan. It’s a dance we have to do over and again with every new client and project. 

    For those of us who wish to function as service-oriented tech companies, keeping on top of client and customer experiences requires us to stay attentive and listen with active care. Just like the veteran restaurant manager, we have to constantly scan our environment for cues of satisfaction and dissatisfaction.

    Service is More Than an End Product

    Before opening every night, the general manager would make staff hold long pieces of string to measure the angles and distance between tables to ensure they were straight and the edges perfectly aligned. Then, after telling staff the evening specials, he would randomly quiz them about the menu. What color is a fava bean? 

    Seeing the value of such old-school standards left a deep impression and helped me embed attention to detail as a foundational practice across the board, from designing good UX to cultivating relationships. Creating a desirable environment is about successfully orchestrating a million tiny details and always looking for tweaks to make the customer experience better. 

    That seemingly omniscient Italian from my earliest experience in the restaurant industry also taught me that being empathic goes hand-in-hand with the hard-nosed realities of running a service-oriented business. They showed me how to take care of people, how to make them feel good and how to read body language. 

    It might be easy to stereotype tech companies as impersonal dispensers of products (and their developers as cogs in the machinery), but we don’t want to just take orders. Our job is to become strategic partners from the ground up for long-term success, and that requires constant care and continual adaptation. 

    Mapping the Client Experience

    We must be willing to redesign how we work with customers and end users over and over again—it’s always changing because expectations are always changing, and market norms are always changing. The moment that we stop trying to get better through small incremental improvements is the moment we stop being service-oriented.

    In the same way that a restaurant has a sequence of service that maps a diner’s journey from the moment they enter the door, we can architect a customer experience from every touchpoint. 

    In the sales process, it’s valuable to layer in different people to create more relationship touchpoints throughout an organization, so, in our case, a new client meets a member of our operations team and then somebody from our engineering team in order to ensure that they feel fully supported. Then, we set expectations in terms of communication as part of a scripted onboarding experience. In our review meetings, we seek feedback to determine whether we have under-delivered and course correct if necessary. 

    The other thing I learned from that Italian restaurant is that no mistake is irredeemable. It doesn’t really matter if you get it right or wrong the first time, it is how you respond when the unexpected happens that matters. Turning a situation around after making a horrible mistake—even sending out a cold steak—can breed even more loyal customers because it demonstrates that you really care.

    The Creative Heart of Service

    Despite the image of tech as cold and distant, it’s important to recognize that coding and development itself is creative and we should seek to nurture a healthy environment so that people can perform at their best. To that end, it makes sense to think of your responsibility as running the entire length of the chain, from employees to clients and, finally, to end users. Finding humanity in the work along each link is key to building successful partnerships. 

    In the context of building products, we must be creative to design seamless, curated experiences for end users. There are plenty of apps that sit on someone’s phone unused before ultimately being deleted. The only way to grab the attention of people that share the same interests and problems is by understanding their needs. 

    To that end, we must always be asking our clients: What is the easiest point of entry for the user? Creating a low barrier is a quick win that in and of itself is an onboarding experience and an opportunity to build trust. 

    Equally, what may make one customer happy may not actually have any resonance in the wider market. If customers were only hiring us to write code, we would only be interested in meeting their expectations. The goal is not just to build products, but successful products that establish or reinforce a client’s reputable presence in the marketplace. 

    Adding Value Through Relationships

    When we stand in our metaphorical corner of the room to observe the customer experience, we are consolidating data from products that have millions of users and harvesting insight. We are not interested in quick fixes. Customer service and a focus on the end-user experience means being oriented to what the market wants, not designing in a vacuum. We can then continue to build value over time.

    In the restaurant business, the little surprise at the end of dinner adds value because it is unexpected. A complimentary after-dinner liqueur with a pithy origin story is a point of detail at its finest. Creating a richer, fuller customer experience can set a tech business apart in an exploding marketplace. For my old mentors, paying attention to every nuance from the beginning to the end is what defines five-star service.

  • How to Prepare Your DevOps Environment for DevSecOps

    How to Prepare Your DevOps Environment for DevSecOps

    The COVID-19 pandemic has created a deep, irreversible change within work environments, as most organizations are reimagining this “new normal” with a combination of fully remote or hybrid work. DevOps practices are being increasingly normalized and relied upon to respond to the needs of modern, digitized companies. Coming out of the pandemic, organizations now better understand the need to efficiently deploy the software applications necessary to thrive in this new world of work.

    This isn’t surprising given organizations have realized the value of DevOps to help product teams deliver quality code at a fast pace. DevOps enables them to be more agile and move more quickly to respond to evolving market changes and business demands. To maintain the speed of software delivery, product teams are integrating various tools within their CI/CD pipelines and minimizing tool citations and validations outside of their pipelines.

    As the rate of change increases alongside these DevOps practices, automating compliance to enterprise security controls becomes more important than ever, especially given that security vulnerabilities in code and configurations present dire business risks. For DevOps to truly succeed, organizations need to modernize and automate security processes, making them an integral part of the DevOps build and delivery pipeline—readying the overall DevOps environment for DevSecOps.

    But successful DevSecOps deployments depend heavily on the maturity of an organization’s current DevOps environment and security operations workflows. This includes prioritizing the core principles of automation, measurement and collaboration because these same principles also drive positive security outcomes. Referencing these principles, here are four best practices organizations should consider incorporating when evaluating how to mature their DevOps ecosystem and security operations processes to be ready for DevSecOps.

    Embed Security Tools in Developer Workflows and Governance Processes

    The first step in the journey prioritizes a “security-first” mindset and related skills for development teams. Security shouldn’t be an afterthought, and development teams shouldn’t rely on security teams to check vulnerabilities later in the life cycle. Instead, security experts need to become an integral part of the development phase so that the code accounts for security from the get-go.

    This can be achieved either by moving responsibility for security skills into the development teams or by having the security team play an advisory role earlier in the life cycle. Development teams can then automate the necessary security vulnerability checks—like static application security testing (SAST), software composition analysis (SCA) and dynamic application security testing (DAST). But more importantly, sharing insights and streamlining communication between development and security teams is crucial to ensure policies are working and are being consistently applied across the organization.

    Continue Automation Beyond the Pipeline

    Puppet’s 2020 State of DevOps Report revealed that organizations have matured their DevOps environment by improving governance processes such as change management, preparing enterprise infrastructure and applications for organizational change. In fact, they found that organizations with automated change management and governance processes are nearly three times more likely to outperform competitors in DevOps transformations.

    This is because automation improves change management processes, which in turn eliminates barriers to applying governance to DevOps. This is also backed by Puppet’s survey, which cited that automation makes organizations more confident that their change management solutions are effective. A comprehensive, automated change management process instills governance by applying policy-based rules to a code or configuration change before allowing it into production. It does this in real-time by leveraging data collected from the pipeline. When applied correctly, DevSecOps tools prevent vulnerabilities and automated change management conducts a ‘last mile’ check to ensure the correct scans were run and adhere to compliance policies.

    Provide End-to-End Traceability Across DevOps

    Product teams—and all involved in the delivery of an application—should have an accessible audit trail, providing visibility into security checks, users, code and configuration changes, code quality, testing and more. This paints a clear picture of what happens to the software from ideation to production. In an ideal world, product teams include both operations and security personnel, but these functions often remain siloed in large organizations.

    Companies can break down these silos and make it easier for teams to collaborate by centralizing visibility. Providing visibility and centralizing security policies makes it easy for teams to efficiently operate the delivery process of software since they are provided a single source of truth. Additionally, an automated system for gathering audit data improves the consistency and reliability of audit information. Automatically collecting data from the entire pipeline and eliminating the need for developers to enter information diminishes the likelihood of data anomalies—saving valuable time and resources.

    Empower Cross-Enterprise Collaboration to Address Security Issues in the DevOps Pipeline

    Applying artificial intelligence and machine learning to DevSecOps processes helps organizations quickly identify and remediate security issues before they are manifested in production, enhancing proactive and actionable collaboration and coordination across product teams.

    As Puppet cited in its 2019 State of DevOps Report, sharing and collaboration are two of the most impactful things teams can prioritize to improve DevOps initiatives, including DevSecOps, and this still holds true today. The 2020 survey results signaled how many more organizations are reaching this peak point of DevOps maturity.

    Ultimately, we’re already seeing how operational activities—like checking software for security vulnerabilities—are moving into the DevOps pipeline and are being handled as “code.” But organizations should take this a step further by keeping in mind factors such as reliability, predictability, measurability and observability across DevOps deployments to foster more secure environments and pipelines.

  • Does it Matter That We’re Still Working in Silos?

    Does it Matter That We’re Still Working in Silos?

    Seventy-two percent of business leaders believe that cross-departmental working at the enterprise level benefits their employees’ experience and engagement. However, 68% of these same organizations admit to working in silos—the complete opposite of collaboration.

    So, there seems to be a conundrum. We know that working in silos is detrimental to our employees, customers and the business as a whole, yet, we’re still doing it.

    The question is: why?

    Our Protective Bubble

    To work in a silo means to build a protective bubble around you and your team, where nothing comes in and nothing goes out. It’s a zone of comfort, shielding your department from the rest of the organization.

    Siloed teams keep processes and knowledge to themselves. They work independently, for the most part, toward their own goals. By actively keeping themselves to themselves, they resist cross-functional collaboration of any type.

    As a result, those in the protective bubble are oblivious to the problems, processes, knowledge and successes outside of their immediate vicinity. Imagine what they’re missing! Someone from inside the bubble could have an idea that could solve one of an enterprise’s issues, or they may be the key to elevating an existing idea to the next level. But they’re in the bubble because they tend to feel overprotective of their work and that of their team–so forget about hearing those great insights.

    Silos Are a Hard Habit to Break

    The likelihood is that if one of the teams in your organization is working in a silo, then many others are too. And letting departments stay safe in their protective bubbles is far easier than rocking the boat and trying to change the way that several groups work.

    And once we have silos, they become part of the furniture. We build our routines and the way we work around them and suddenly they become ingrained in who we are, much like a bad habit we never intended to continue, but now cannot stop.

    This explains why we continue to work in silos despite knowing the detrimental impact they are having. A habit is hard to break. And even if we do start on the journey to change, it’s often easier to give up when the going gets tough than push through the problems. Take smoking for example; (one of the most difficult habits to break, sure, but hugely beneficial if you can do so) a 2015 survey found that only 7% of those who attempted to quit did so in six to 12 months. Changing ways of working has to be easier than that, right?

    Bursting Those Bubbles

    If staying stagnant and failing to grow or develop is more your thing, then, by all means, stay in your safe silos.

    But if becoming a more efficient, engaging, and effective business is important to you (which it should be), then you cannot expect to grow if all organizational teams are moving in different directions, not sharing their processes, ideas and insights. And much like quitting smoking cold turkey is a recipe for failure, expecting to diminish our silos in one day also is not a viable option.

    There is a solution that can incrementally burst those bubbles in a manageable and effective way: enterprise service management (ESM). Collaboration and communication are the main benefits of working in an ESM system; it provides organizations with one place for all departments to work in. Each team can set up and share processes, import knowledge and provide services through ESM.

    And by working in this unified area, departments are unconsciously collaborating. Teams can learn from each other, thanks to the universally available knowledge, and can share processes without even realizing it’s happening.

    For example, say the IT department is alerted to a printer fault in the ESM system. They first try to fix the defective item, but unfortunately, it’s not possible; they mark the printer as needing to be replaced. A notification is sent to the purchasing team asking them to buy a new printer; the order and delivery information then goes to facilities that will procure and fit the new device.

    Departments are able to keep their responsibilities and meaning, which was often their primary reason for staying siloed, while also being empowered to work better with their colleagues–and they don’t even have to lift a finger to improve the collaboration; ESM provides the space and the processes to do so.

    The Domino Effect

    The thing with ESM is, though, that we can’t just chuck all of our departments into the system at once and expect it to solve all our problems. We must implement it slowly, sometimes even one team at a time. But once we have freed one department from its protective bubble, it becomes the catalyst for something of a domino effect.

    It’s easy to work independently when everybody else is doing it, but the minute others start collaborating, it’s a different story. Imagine it’s a Friday night and you’re at home with no plans and all your friends are, too. It’s easy to be content with the situation. Now, imagine all your friends are out at a bar socializing and having fun instead, with all the pictures flooding your social media feed—the fear of missing out sets in.

    The same is true of siloed working. When we’re all in our bubbles, there is no organizational connection that we’re missing out on. But if we suddenly start to see departments collaborating and succeeding thanks to shared knowledge and processes, we want to be involved, too. And the more teams suffer from the fear of missing out, the more bubbles we’re bursting until there aren’t any more left.

    Stick or Break the Silos?

    It’s easy to unconsciously take up the habits of siloed working; after all, we thrive with our own responsibilities and a close-knit team. But it has to be a conscious decision to break down our organizational silos; it can be a long, difficult journey to do so.
    So, are you going to stick with the habit? Or find a way to collaborate and communicate better together?

  • Atlassian Extends Open DevOps Ambitions

    Atlassian Extends Open DevOps Ambitions

    At an online Atlassian Team 2021 event this week, Atlassian launched a two-pronged effort to provide organizations with more insights into software development workflows constructed using tools from multiple vendors.

    Suzie Prince, head of product for Atlassian, said an Open DevOps initiative will tighten integration between the Jira project tracking and management tools provided with Atlassian and a wide range of tools commonly employed by DevOps teams. The goal is to not only make it easier to correlate issues that are listed in Jira with artifacts found in various software platforms, but also to collect data from DevOps tools to automatically update Jira.

    That data will then be employed to inform the key performance indicators (KPIs), based on graphs that Atlassian provides within Jira, to keep track of value streams. Rather than having to acquire a separate value stream management (VSM) platform to track software development progress, the insights needed to understand the impact of, for example, a delay to one project becomes a dividend of using Jira.

    At the same time, Atlassian is moving to making it easier for other stakeholders in an organization to track software development projects. A Jira Work Management application is specifically designed for business users that require a higher-level tool to track projects. At the same time, Atlassian revealed this week it has acquired ThinkTilt, a provider of low-code application development tools optimized for Jira.

    Atlassian for the first time this week revealed that half of Jira users are not software developers. As organizations increasingly appreciate the degree to which they are now dependent on software to drive digital business transformation initiatives, Atlassian is adding a set of project tracking applications designed specifically for users that need to consume Jira data in a more intuitive fashion.

    Prince said Atlassian is committed to making it simple to replace one DevOps tool integration for another with a single click. Rather than requiring organizations to standardize on a single DevOps platform, Prince added that developers will be able to continue to rip and replace tools and platforms as they see fit without compromising visibility into application development workflows.

    In addition, the integrations being provided by Atlassian will reduce the time and effort required to configure all the tools that make up a DevOps workflow, from roughly 60 steps today to about six.

    As DevOps workflows become more pervasive, the way organizations operate is fundamentally changing. Formal product launches are giving way to a steady stream of software updates that add new capabilities to any platform with little to no fanfare. End users ranging from sales teams to custom support personnel now need to track updates to platforms more closely as new capabilities are continuously added.

    Of course, not every organization has the same level of maturity. However, as competitors start to add new features to rival offerings, it is now only a matter of time before most business processes – that increasingly revolve around software updates – begin to evolve and change. As the pace of software development continues to accelerate, the pressure on legacy business processes will only continue.

  • Split Allies With AWS to Advance Feature Flagging Adoption

    Split Allies With AWS to Advance Feature Flagging Adoption

    Split today announced it has integrated its namesake platform for managing feature flagging with the Amazon’s Simple Storage Service (Amazon S3) as part of an effort to streamline the process of adding new capabilities to applications.

    Company CTO Pato Echagüe said one of the most challenging aspects of feature flagging is providing a way for development teams to access data required to test those capabilities. Integration with Amazon S3 will now make it possible for Split to ingest millions of customer events per minute as Parquet files from Amazon S3.

    That capability will make it possible to have enough statistically relevant data to analyze how a feature is being employed within minutes, said Echagüe. Previously, software engineers would have had to spend hours manually configuring the Split feature flag management platform to ingest gigabytes or terabytes of data, he noted. The integration with Amazon S3 makes it possible to now analyze terabytes of data in near real-time.

    Split next year also plans to make it possible to send feature flag data to Amazon S3, where it can be combined with other types of data that could be analyzed using a third-party application.

    The end goal is to make it easier for product and engineering teams to collaboratively iterate new features and capabilities faster in a way that aligns better with a product road map, added Echagüe.

    Interest in feature flagging has been on the rise as organizations invest in digital business transformation initiatives to better engage end users that are working from home to combat the spread of the COVID-19 pandemic. Feature flagging capabilities make it easier for those organizations to test new capabilities without having to expose every ens user to a capability that ultimately may not have enough appeal to be included in the application.

    Feature flagging, of course, is already employed within many DevOps workflows. Split, however, is providing a platform that is designed to make it easier for DevOps teams and application owners to collaborate on the rollout of features based on feedback from end users regardless of what DevOps platforms application development teams are employing, said Echagüe.

    As IT becomes more complex, Echagüe noted it’s more important than ever for organizations to have a consistent approach to change management. The bulk of issues many IT organizations wind up addressing usually have something to do with a recent change to an application, he said.

    There’s no doubt that as organizations begin to rely more on digital processes, organizations will want to have more confidence in the capabilities being added to these platforms. As a result, many application owners who don’t have a lot experience working within the context of a DevOps workflow still want to be able to exercise and maintain control over what features are added to an application.

    Regardless of the approach to feature flagging, it should be apparent to all involved by now that this capability going forward is going to play a much larger role in application development and deployment.

  • Mattermost Offers DevOps Command Center in the Cloud

    Mattermost Offers DevOps Command Center in the Cloud

    Mattermost today launched Mattermost Cloud, a software-as-a-service (SaaS) platform for managing DevOps workflows using pre-built playbooks that comes integrated with a wide variety of third-party developer tools.

    Chandar Venkataraman, executive vice president and chief product officer for Mattermost, said Mattermost Cloud enables IT teams to take advantage of a single-tenant DevOps platform that they don’t have to maintain in a way that forces developers to give up their preferred tools.

    In contrast, other DevOps platforms that are managed as a service require developers to make use of a narrow range of tools provided by the platform vendor, he said.

    Built on top of an instance of Kubernetes, the single-tenant capability also ensures that any data or artifacts stored on the platform remain private. The Mattermost Cloud Professional edition, available today, provides a full set of collaboration and DevOps features, while the Mattermost Cloud Enterprise edition, currently in beta, adds dedicated single-tenant cloud infrastructure, enterprise-grade secure network topology and strict data residency options.

    By building the platform on Kubernetes, he noted, it becomes much easier to scale the Mattermost Cloud platform up and down as required.

    Mattermost Cloud is essentially a DevOps command center that provides single pane-of-glass pre-built workflows that address most common DevOps processes. IT teams can add their own custom workflows as their DevOps processes mature, Venkataraman said, noting plugins for Jira, Opsgenie, PagerDuty, GitLab, GitHub and Jenkins are already available.

    The cloud platform also includes a pre-built best-practices incident management playbook to enable DevOps teams to address issues as they arise rather than trying to resolve them using a legacy ticket-based approach to IT service management (ITSM), he added.

    Venkataraman noted Mattermost doesn’t expect DevOps processes to supplant existing ITSM platforms based on ITIL-frameworks. However, many DevOps teams are looking for ways to resolve incidents within their existing workflows using, for example, a messaging platform versus a workflow designed for IT support staff.

    In general, Venkataraman said, many organizations that are relatively new to DevOps don’t want to manage the underlying platform. At the same time, he noted there are also many IT organizations that want to allocate more resources to writing code versus managing a DevOps platform.

    Each IT organization will need to decide when it makes sense to stand up their own platform for managing DevOps workflows and playbooks instead of building and maintaining their own control plane. Many of those IT teams are already making use of artifact repositories and continuous integration/continuous delivery (CI/CD) platforms that are accessed via the cloud, so a DevOps command center is only one more logical extension.

    Just as importantly, isolating the DevOps command center from the rest of the underlying DevOps platforms ultimately makes it easier for IT teams to switch out tools and platforms over time as they best see fit. The challenge now may be in finding a way to decouple workflows that are deeply intertwined with a specific platform.