Category: Features

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

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

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

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

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

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

    Indeed.com

    AT&T
    Dallas, Texas
    Software Engineer
    $158,766 to $210,100

    LinkedIn

    Northwestern Mutual
    Syracuse, New York
    Senior Systems Software Engineer – DevOps
    $97,300 to $139,900

    CareerBuilder.com

    United Healthcare
    Remote
    Senior DevOps Engineer
    $85,000 to $167,300

    SimplyHired

    GEICO
    Remote
    Azure DevOps Engineer
    $82,000 to $185,000

    Dice.com

    Integrated Practice Solutions
    San Diego, California
    DevOps Engineer
    $80,000 to $140,000

  • CDF Marries Emporous Repository to Ortelius Management Platform

    CDF Marries Emporous Repository to Ortelius Management Platform

    The Continuous Delivery Foundation (CDF) has added the open source Emporous repository for software artifacts to an Ortelius platform for managing the software artifacts that make up a microservice.

    Ortelius was originally created by DeployHub and subsequently contributed to the CDF, which also oversees the development of the open source Jenkins continuous integration/continuous delivery (CI/CD) platform.

    Emporous is based on a Universal Object Reference (UOR) conceptual model that enables dynamic schema registration and decentralized content-addressable reference of a wide spectrum of software artifacts. Originally developed by Red Hat, Emporous will now be managed as a sub-project within the larger Ortelius incubation-level project by the CDF.

    DeployHub CTO Steve Taylor said this integration would make it simpler to store, organize and search metadata related to software artifacts, along with the artifacts themselves, within the context of the Ortelius platform for managing microservices.

    Ortelius provides insights into the relationships and dependencies between different software components and applications. It does this by collecting and aggregating pipeline data from multiple sources within a software supply chain. Emporous will be incorporated within Ortelius to enhance metadata search capabilities and provide a single repository to store any type of artifact, from containers to jar files. It will now also be able to store metadata and also the artifacts themselves within the same Emporous catalog.

    Those capabilities will significantly improve security and compliance reporting across a software supply chain, added Taylor. DevOps and cybersecurity teams will be able to automatically apply and enforce supply chain policies and procedures, he said.

    DevOps teams need a way to aggregate all the data from the various tools they use and the data must be easily searchable. Armed with those insights, it should become simpler to surface insights into, for example, which components of an application contain known vulnerabilities.

    In the longer term, IT organizations will be able to apply machine learning algorithms and other forms of artificial intelligence (AI) to automatically surface insights that will enable DevOps teams to automate workflows, said Taylor.

    Microservices-based applications are considerably harder to build and manage than monolithic applications, but they are also easier to maintain because individual microservices can be ripped and replaced.

    Most microservices today are built using containers, but there are also microservices that are written in Java, for example. In some cases, developers view monolithic applications as being a large, less flexible microservice that they invoke via an application programming interface (API).

    There’s no doubt that the rise of microservices made application environments a lot more complex. The tools needed to simplify the management of the next generation of applications are finally starting to become more widely accessible. In theory, the number of organizations that can successfully build and deploy these types of applications should steadily increase in the months and years ahead.

    In the meantime, there’s clearly still plenty of work that needs to be done to improve the overall state of software delivery. A recent CDF survey found only 22% of respondents were using continuous integration and continuous delivery (CD) to automate the building, testing and deployment of code in a production environment. As CD becomes more distinct from CI, however, the number of organizations that can achieve that goal when deploying microservices-based applications should steadily increase.

  • GitLab Adds More AI and Cybersecurity Capabilities to CI/CD Platform

    GitLab Adds More AI and Cybersecurity Capabilities to CI/CD Platform

    GitLab this week delivered an update to its continuous integration/continuous delivery (CI/CD) platform that adds additional generative artificial intelligence (AI) and cybersecurity capabilities.

    The GitLab 16 release included cybersecurity capabilities such as centralized policy management, expanded compliance reports and controls, compliance dashboards and default Level 3 attestation for the supply-chain levels for software artifacts (SLSA) framework.

    At the same time, GitLab this week also made available an emergency patch for two modules that have a path traversal flaw, tracked as CVE-2023-2825, that could allow unauthenticated users to read arbitrary files on the server under certain circumstances.

    In terms of generative AI, GitLab 16 added a value stream forecasting capability that automatically generates workflow summaries for senior managers. GitLab is also adding a code refactoring capability and the ability to automatically resolve vulnerabilities to an update to GitLab 16. Previously, GitLab made available a ‘suggested reviewers’ features, an ‘explain this code’ and an ‘explain this vulnerability’ capability that are all enabled by large language models (LLMs) developed by Google. GitLab has also partnered with Oracle to provide additional AI capabilities enabled by machine learning algorithms. In 2021, GitLab acquired UnReview, a provider of a tool that uses AI to identify which expert code reviewers to assign to a project based on the quality of their previous efforts and current workloads.

    David DeSanto, chief product officer at GitLab, said with 10 AI capabilities GitLab is providing more of these types of capabilities than any other DevOps platform provider. In addition, those capabilities are distributed across the entire software development life cycle rather than being focused solely on making developers more productive, he noted.

    That’s critical, because if AI capabilities are only focused on developer productivity, an imbalance is created; DevOps workflows will not be able to absorb the increased amount of code that will soon be moving simultaneously through pipelines, DeSanto added.

    AI will also further fuel adoption of platform engineering as a means for centralizing DevOps management. It’s becoming more apparent that infusing these types of capabilities into DevOps platforms built and maintained by an internal IT team is going to be a major challenge, he added.

    There is no doubt that generative AI capabilities will soon become widely integrated across DevOps workflows. That will enable developers to build more secure code faster while at the same time making it simpler for software engineers to maintain large codebases. Just about every job function imaginable will be impacted to varying degrees. In the case of DevOps teams, the ultimate impact should involve less drudgery as many of the manual tasks that conspire to make managing DevOps workflows tedious are eliminated. In fact, AI may ultimately make DevOps, as a methodology for managing IT, more accessible to a much wider range of organizations.

    As AI advances, there should still be plenty of demand for human expertise. For better or worse, the nature of the expertise required, however, will undoubtedly be at a much higher level than it has previously been as more low-level tasks are automated. The challenge is determining how and where to refocus the efforts of the DevOps teams to add higher value.

  • The Metrics Disconnect Between Developers and IT Leaders

    The Metrics Disconnect Between Developers and IT Leaders

    A survey of 350 software developers found a majority (91%) of respondents are unhappy with the actual metrics leadership teams are measuring.

    The survey, conducted by Atomik Research on behalf of Uplevel, an enterprise intelligence platform provider, found the top metrics developers say should be tracked include hours worked (52%), work allocation (49%) and the amount of time they have to focus on writing code (46%).

    Unfortunately, the survey also revealed more than half of respondents (56%) reported that the CTOs that lead software development efforts make significant strategic decisions without realizing the negative impact on their team. They also often move people around on projects or tasks without knowing the full implications (51%) and overwork developers (44%).

    Just under a third (30%) noted their engineering leaders rely solely on gut feelings to measure the effectiveness of their teams, while a third of respondents observed most engineering roadblocks go unnoticed by leadership.

    Additionally, 96% noted that not knowing what their own leadership team is working on is detrimental to the larger team.

    Christina Forney, vice president of product management for Uplevel, said many CTOs clearly need to be more engaged. Developers don’t mind being measured, but they clearly want to be evaluated based on metrics that matter, she added.

    Managing software development teams has become a lot more challenging in an era where many developers are working remotely. IT leaders can no longer manage by walking around as easily as they once did, said Forney. Aligning workflows across a highly distributed team of developers is a challenge no matter how many communications platforms are used.

    Surprisingly, the Uplevel survey found more than half of respondents (54%) said they feel more productive in the office. More than a third (35%) also said they preferred some form of synchronous communication to engage with other members of their team versus 27% that preferred some form of asynchronous communication. A total of 38% said they preferred a mix.

    It’s no secret that despite long-standing commitments to automation, there are still a lot of manual processes in DevOps workflows that create bottlenecks. In an uncertain economy, however, there’s a lot more focus on developer productivity, so eliminating DevOps bottlenecks has become a major priority. The challenge is those bottlenecks are not as apparent to senior IT leaders, many of whom may have simply become inured to them over time.

    Regardless of how bottlenecks occurred, DevOps teams would be well-advised to reevaluate the metrics they track. Mean-time-to-recovery (MTTR), for example, is not as important a metric to the business as the amount of quality code that finds its way into a production environment.

    In theory, all the data required to track more meaningful metrics that could improve productivity already exists in the tools and platforms DevOps teams use to build and deploy an application. The challenge has been finding a way to automatically surface that data without adding yet another bottleneck to a DevOps workflow.

  • US DoJ Makes PyPI Give Up User Data ¦ Tape Storage: Not Dead

    US DoJ Makes PyPI Give Up User Data ¦ Tape Storage: Not Dead

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: PyPI complies with a “string of subpoenas,” and LTO continues to grow, despite predictions of its demise. (more…)

  • Dell Looks to Expand Pool of Available DevOps Expertise

    Dell Looks to Expand Pool of Available DevOps Expertise

    Dell Technologies has quietly launched a training and education initiative to significantly expand the number of IT professionals that have DevOps skills.

    Brad Maltz, senior director for DevOps and developer relations ecosystems for Dell, said the next era of IT will require IT professionals that understand how to automate the management of application development and deployment. Given its long infrastructure history, Dell is especially interested in helping IT teams to use a mix of graphical tools and command line interfaces (CLIs) to programmatically deploy software at much faster rates and at scale, he added.

    Dell has already hired more than 200 specialists to provide that training as part of a DevOps Transformation Services consulting services engagement, said Maltz. The primary area of focus will be working with IT organizations that are embracing platform engineering to centralize the management of DevOps and GitOps workflows, he noted. Many of those teams are now relying on declarative automation tools that ultimately make DevOps more accessible to a wider range of IT professionals, added Maltz.

    The number of IT professionals that employ graphical tools based on IT management frameworks such as ITIL still far outnumber the number of IT professionals that have DevOps skills. The ongoing debate between these two camps essentially comes down to the need to be able to consistently manage IT at scale versus being able to adroitly keep pace with the needs of organizations that are increasingly dependent on software. In the digital transformation era, it’s become clear that more of the organizations that hire IT professionals are placing a higher value on agility, said Maltz.

    Bridging the divide between ITIL and DevOps to address that requirement is largely a psychological challenge that requires IT teams to address a range of cultural issues in addition to mastering different types of tooling, he added.

    Regardless of whether organizations continue to manage IT infrastructure internally or rely more heavily on managed services provided by Dell, the need to continuously deliver secure software faster has become a business issue. The trouble is the level of DevOps expertise within organizations tends to vary widely. A recent survey published by the Continuous Delivery (CD) Foundation found only 22% of respondents are using both continuous integration (CI) and continuous delivery (CD) to automate all building, testing and deployment of code in a production environment. Most organizations that have adopted DevOps make extensive use of CI to build applications, but CD has proven to be more challenging to master. In fact, the CD Foundation survey found only 7% of respondents described themselves as DevOps engineers or specialists.

    The bulk of the managed services that Dell provides are focused on managing infrastructure rather than deploying software, but the company does have a managed DevOps offering based on the application development and deployment platform that an internal Dell DevOps team built to construct and deploy applications. Naturally, Dell has a vested interest in accelerating the rate at which software can be deployed on IT infrastructure it provides and manages.

    It may be a while before the overall size of the DevOps community expands, but the training initiatives such as the one launched by Dell will help. However, it may become a lot easier to find and retain that talent in the months and years ahead. In the meantime, organizations would be well-advised to invest in upskilling their own IT teams. After all, it’s less expensive to train someone that already works within an IT organization than it is to compete against thousands of other organizations willing to pay top dollar for the best DevOps expertise money can buy.

  • FinOps Foundation’s FOCUS Aims to Standardize Cloud Billing

    FinOps Foundation’s FOCUS Aims to Standardize Cloud Billing

    Cloud spending is on the rise. As organizations shift more applications to the cloud, there is a growing need to optimize workloads and reduce spending when possible. But a lack of visibility into complex cloud bills often impedes these goals. This is compounded by a lack of data standardization across the multi-cloud landscape, with cloud vendors producing lengthy billing reports in various formats. With things so decentralized, FinOps practitioners often struggle to make sense of it all.

    FinOps Open Cost & Usage Specification (FOCUS) is set to change this status quo. FOCUS, an initiative sponsored by the FinOps Foundation, a Linux Foundation technical project, aims to create a standard, vendor-neutral specification for cloud cost, usage and billing data. A common schema for cloud billing should help unify cost data across cloud vendors and greatly aid FinOps objectives in areas like allocation, chargeback, budgeting and forecasting.

    I recently met with Udam Dewaraja, FOCUS lead at FinOps Foundation, to understand the context that led to creating the specification. Below, we’ll dive a little deeper into FOCUS, examining the details of the proposed specification and considering what benefits it will bring to cloud consumers and cloud service providers (CSPs).

    Why the Cloud Needs a Common Billing Schema

    The complexities of today’s cloud services can often create headaches around cloud billing. For instance, AWS alone has hundreds of services and potentially thousands of SKUs. Cloud service providers each have their own data formats and terminologies, which are reflected differently in detailed bills. And with the granularity of cloud metering, enterprises could be staring at hundreds of millions of rows of cost data. Now, extrapolate that across multiple cloud service providers, SaaS and APIs, and you can see the dilemma that the modern CFO faces.

    “There are many nuances that FinOps practitioners need to understand,” said Dewaraja. “And a lack of a common definition can be a scalability challenge as you add more things.”

    It’s relatively easy to spend money on more and more cloud-based consumption models. As Dewaraja said, “Everyone has the company credit card.” Of course, you can use tools like AWS Cost Explorer, Cloudability or Datadog to garner some insights to reduce spending. But to really get the fuller picture, you need to rationalize cost metrics across many areas. Plus, in 2023, The State of FinOps report found the widest variety of cloud cost management tools in use in the history of the report, indicating tooling sprawl.

    Overview of FinOps Foundation

    First, for those unfamiliar, the FinOps Foundation is a Linux Foundation-supported group that aims to help practitioners understand the discipline of FinOps. Representing a community of over ten thousand FinOps practitioners, the FinOps Foundation routinely shares best practices and oversees a FinOps framework. “FinOps is more of a cultural practice that should be adopted,” explained Dewaraja. As such, the initiative aims to oversee training, meetups and events and encourage executive buy-in around the FinOps concept.

    Understanding the FOCUS Specification

    So, what exactly does FOCUS entail? Well, FOCUS is an open source royalty-free specification for cloud billing data. It will provide standard dimensions, attributes, and terminologies for cloud billing data sets. To formalize the specification, the project contributors are actively considering the essential FinOps capabilities and what requirements these cloud bill data sets have in common.

    The specification itself has yet to be officially released and is still being formalized at the time of writing. Microsoft and Google have joined the initiative, as well as numerous cloud finance and cost analysis vendors. And while the group waits for additional CSPs to join, the community is building out open source validators and converters, said Dewaraja.

    Benefits of a Standard Cloud Billing Spec

    Cost management solutions are already available, but what’s not readily available is a method to make business decisions based on broader richer datasets, explained Dewaraja. This is where standardized cloud billing can greatly aid efforts by creating a more holistic picture.

    Specifically, this can aid objectives like allocation, chargeback, budgeting, and forecasting. Doing so is often an incremental process, explained Dewaraja—as you gather insights into data, you iteratively use this visibility to make improvements over time.

    Some other benefits of adopting FOCUS will likely be:

    Putting finance in engineering terms. In the cloud, finance is quite dynamic. And interestingly, the FinOps discipline is becoming engineering’s responsibility as part of the shift left approach, said Dewaraja. Engineers now need to understand this problem and how to architect their solutions cost-effectively. As such, bringing specifications into the mix will help put financial responsibility squarely on the shoulders of engineering terms.

    Bringing accountability to cloud consumption. A standard specification should empower essential FinOps capabilities that rely on usage segmentation like internal cost reporting, showback and chargeback. Because if invoices are just one big pie, there is no accountability for individual departments, and you can’t drive the behaviors you need, said Dewaraja.

    Win-win for practitioners and cloud vendors. With FOCUS, cloud providers will drive more trust in cost data, providing more visibility. And corporations using the cloud can make their adoption more efficient, likely influencing them to bring on more workloads. “Driving trust and understanding of this cloud data is mutually beneficial,” Dewaraja said.

    FOCUS Set to Improve FinOps

    Dewaraja, who previously spearheaded FinOps practices at Citigroup, knows all too well the strains of managing disparate cloud billing data. He oversaw a broad, dynamic cloud-native platform of distributed cloud and SaaS and sought to embrace platform engineering principles. In this environment, you need a holistic cost picture that associates various expenses to make the right calls, he said. “You really see success if you can plug this into the workflows of those developers and into business processes themselves,” he said.

    Theoretically, FOCUS could deliver on these goals. But although the project is gathering momentum, it’s still in an early stage. For the standard to gain a foothold, it will require greater awareness and more contribution from other CSPs. The specification is community-driven but is being led from the practitioner down, adopting corporate contribution licenses instead of individual developer contributions. Thus, cloud vendors and cost management vendors will likely lead the initial charge.

    FOCUS looks great in the long run but will require a little bit of work upfront to get folks on board. That said, it should be on the radar for 2024 roadmaps, said Dewaraja. To learn more about FOCUS and how to contribute, software providers should check out the FinOps Foundation materials.

  • Microsoft Adds Slew of Developer Tools to Azure

    Microsoft Adds Slew of Developer Tools to Azure

    At its Build 2023 conference this week, Microsoft announced general availability of an Azure Deployment Environment service that provides developers with a portal through which they can employ infrastructure-as-a-code (IaC) templates based on Terraform or Azure Resource Management files.

    In addition, Microsoft has enhanced Microsoft Dev Box, a workstation environment for developers that run Azure, to include a portal through which they can manage multiple environments.

    Scheduled to be generally available in July, Microsoft Dev Box is also previewing a capability that makes it possible to customize environments using configuration-as-code files stored in a Git repository. Microsoft is also previewing tighter integration between Dev Box and its Visual Studio integrated development environment (IDE) and Windows to further customize developers’ environments.

    Scott Guthrie, executive vice president of the cloud and artificial intelligence (AI) group at Microsoft, told conference attendees these and other tools for building cloud-native applications, along with GitHub Actions, make it simpler than ever to build applications in an Azure cloud service that includes an integrated continuous integration/continuous delivery (CI/CD) platform.

    Microsoft is also previewing GitHub Advanced Security for Azure DevOps that natively embeds automated security checks using scanning tools into the Azure DevOps platform.

    Other additions to the Azure environment include tools for centralizing the management of application programming interfaces (APIs) using an Azure API Center service that is available in preview.

    The Azure Event Grid has also been updated to enable it to use HTTP to pull delivery of discrete events in addition to pushing them.

    Finally, Microsoft is also previewing generative artificial intelligence (AI) capabilities to make it simpler to manage cloud costs by, for example, using prompts to summarize invoices or breakdown costs.

    Microsoft, along with its GitHub subsidiary, is at the forefront of applying generative AI to application development using tools like GitHub Copilot that developers can use to write better code faster. That copilot capability is now being disseminated across the portfolio of applications and services that Microsoft provides.

    It’s not yet clear what the downstream impact of such tools are just yet, but the overall quality of the applications being built should improve as, for example, fewer mistakes are made that can lead to vulnerabilities.

    Obviously, the way application software is built, constructed and secured is about to change in the generative AI era. Thanks to its alliance with OpenAI, Microsoft has a significant head start on rivals building generative AI platforms that can similarly be applied to improve developer productivity.

    In the meantime, DevOps teams should assume the volume of code simultaneously moving through pipelines is about to dramatically increase as developers become more productive. There will inevitably be more opportunities to apply multiple forms of AI to reduce any DevOps bottlenecks that might arise, but it’s clear most of the immediate benefits are being provided to developers.

    One way or another, however, the overall rate at which applications are built and deployed is about to change drastically. The issue is understanding how those advances will impact downstream DevOps workflows that were constructed for a different era of application development.

  • Red Hat Enhances Insights to Simplify RHEL Management

    Red Hat Enhances Insights to Simplify RHEL Management

    This week at its Red Hat Summit event, Red Hat introduced an expanded set of capabilities to Red Hat Insights that simplify management of Red Hat Enterprise Linux (RHEL).

    Managing Linux across the hybrid cloud is complex, and it’s made even more so because of current macroeconomic conditions and the challenge of finding and retaining highly skilled DevOps and IT professionals, said Gunnar Hellekson, vice president and general manager, Red Hat Enterprise Linux, Red Hat.

    The enhanced Insights capabilities add a layer of abstraction to help reduce enterprise Linux complexity across the hybrid cloud and make RHEL management easier by lowering skill level requirements for managing Linux server estates, the company said.

    Using a single UI, entry-level systems administrators and IT support teams can access Red Hat Insights’ predictive analytics to identify potential bugs, misconfigurations or security vulnerabilities and remediate them. Systems administrators of all skill levels can detect, assess and push fixes for potential problems without a deep understanding of Linux management systems like Red Hat Satellite Server and without having to interact with the command line, the company said.

    These enhancements help organizations maintain services and systems even in uncertain macroeconomic times when hiring is constrained. Red Hat research also claimed that these enhanced capabilities enabled IT organizations to find IT issues up to 90% faster and remediate them nearly 66% faster across the hybrid cloud.

    A Red Hat Insights image builder service also helps lower the skills level needed to manage Linux estates by enabling IT teams to build standardized, optimized operating system images, including the creation of their own ‘golden images’ that adhere to organization-specific needs for security and compliance. These images can be deployed across public clouds, hybrid clouds, data centers and the edge using the same console.

    As the economic downturn continues, organizations are looking to do more with less and identify ways to make the most of the resources, talent and skillsets they already have. Red Hat is making the case for adding a layer of abstraction to allow less-highly-skilled IT and DevOps team members to contribute to managing Linux estates across hybrid, multi-cloud and edge deployments.

    “The demands of managing Linux across the hybrid cloud are stretching the ability of resource-constrained IT departments to keep pace,” said Hellekson in a statement. “CIOs need to be able to extend existing skillsets and lower the skill barriers for overseeing Linux estates, which is exactly what the management capabilities of Red Hat Insights are designed to do.”

  • Red Hat Unveils Developer Hub to Boost Dev Productivity

    Red Hat Unveils Developer Hub to Boost Dev Productivity

    At its Red Hat Summit conference today, Red Hat unveiled its Red Hat Developer Hub, a developer portal that provides access to an opinionated set of development tools based on the open source Backstage project.

    The portal pulls together a set of curated tools and resources so that developers encounter less friction and avoid the complexity of numerous optional tools that span disparate vendors. The goal is to increase developer productivity while reducing the volume of optional tools and information that must be sifted through to actually deliver production code.

    Red Hat Developer Hub aims to streamline the development process and allow organizations to maximize existing resources and developer skills while reducing sprawl, said Chris Wright, CTO and SVP for global engineering at Red Hat. This will help organizations maintain application development velocity and drive a consistent user experience for developers based on tools and skills they’re already familiar with, Wright told attendees.

    Rather than building and maintaining their own internal developer portal, Red Hat is making a case for using Developer Hub to deliver a platform approach to addressing the complexity and sprawl DevOps teams face. Red Hat Developer Hub is, in essence, an opinionated and optimized version of Backstage that aims to deliver improved developer experiences across environments, including Kubernetes and container application platforms such as Red Hat OpenShift.

    Developer Hub will offer a single pane of glass to view all available developer tools and resources, developer self-service capabilities and security and compliance guardrails for cloud-native application development that comply with enterprise-wide best practices, according to the company.

    Additionally, Red Hat Developer Hub includes a set of ‘golden path’ templates—pre-defined, pre-architected and supported templates for further accelerating application development.

    The developer hub is based on the Cloud Native Computing Foundation (CNCF) incubating open source project Backstage, originally developed by Spotify and donated to the CNCF in 2020. Backstage is now being advanced by contributions from multiple vendors, including Red Hat.

    Backstage has been gaining traction in cloud-native application environments that are especially challenging to develop using multiple tools. There’s a lot more focus on developer productivity, which Backstage addresses by creating a catalog of blueprints that developers can readily consume rather than requiring them to build these capabilities themselves multiple times over. The goal is to create scaffolds that developers can consistently reuse across multiple application development projects.

    Red Hat has also developed Red Hat Plug-ins for Backstage, a bundle of six plug-ins that integrate various key systems into Backstage, helping to extend the project’s functionality, ensure a consistent user experience and improve workflow efficiency. The plugins can be used across all Backstage installations, providing even more flexibility for developers across platforms and Kubernetes distributions and include:

    • Application Topology for Kubernetes, which enables developers to visualize real-time status of application and infrastructure workloads deployed to any Kubernetes target, including Red Hat OpenShift, with greater consistency.
    • Multi-Cluster View with Open Cluster Manager (OCM), which provides a view into clusters from Open Cluster Manager’s MultiClusterHub and MultiCluster Engine in Backstage.
    • Container Image Registry for Quay, which improves the integration and speed of interactions with Quay registries by providing a view into container image details. This includes security vulnerabilities (CVEs) associated with deployed images.
    • Pipelines with Tekton, which gives users a view into the details of all Tekton pipeline runs and their respective statuses across all services.
    • Authentication and Authorization with Keycloak, which enables platform engineers to load users and groups from Keycloak into Backstage, allowing the use of multiple authentication providers to be applied to Backstage entities.
    • GitOps with Argo CD, which helps track the health and status of the Argo CD status for services within Backstage.

    Red Hat said additional plugins are in the works. Red Hat Developer Hub will be generally available later this year, but Red Hat is offering a ‘test drive’ through the upstream IDP project Janus.