Tag: cloud-native

  • Challenges with the Rapid Adoption of Cloud-Native Technologies

    Challenges with the Rapid Adoption of Cloud-Native Technologies

    To keep pace with the ever-changing digital landscape, today’s enterprises are trying to move to the cloud as fast as possible. As more and more companies move toward implementing cloud native and open source technologies to enable agility and increased time-to-value, the operational impacts to the business can be significant. While these challenges can cause serious setbacks and complexity, if an organization addresses them from the very beginning as part of its cloud strategy, it can overcome any trial.

    The following are top challenges enterprises may face when rapidly adopting cloud native technologies. 

    Intense Competition and Market Pressure

    As businesses fight to keep their competitive edge, they are feeling significant pressure to adopt new initiatives to achieve greater business velocity. New initiatives such as data analytics, data science and cloud computing are being leveraged by organizations to gain an advantage while disrupting how businesses have traditionally been performed. 

    Lack of Maturity and Interoperability of Many Open Source Technologies

    Understanding the cloud landscape is a critical component for kicking off any digital transformation project, but the state of each technology varies significantly. Because so many of these technologies are open source, getting a true understanding of maturity can be challenging. Some solutions are in very early stages with low commercial adoption and support, while other solutions are at a later stage and much more mature.

    Unfortunately, most of these technologies were not built to ensure interoperability from the beginning and the efforts of jamming together multiple disparate solutions from the cloud native landscape is complex and rife with challenges. This is why it is imperative that modern organizations ensure its solutions are enterprise-grade, ready to scale and nearly fool-proof to challenges. 

    No Clear Best Practices or Architectural Standards

    Because many of these new technologies lack maturity, the right information and proper documentation is scattered and difficult to distill. How can developers trust if an application is safe to include in their implementation if they are unsure whether documentation is correct and up-to-date? Since many of these open source technologies do not have well-defined best practices or architectural standards, implementing these solutions can be a huge business risk.

    Limited Choices for Leveraging External Domain Expertise and Support

    In order to ensure that organizations’  Day 2 operations go smoothly, they need the right expertise to provide guidance and support. Unfortunately, because so many of these technologies are new, there is a very limited pool of talent—both internally and externally—organizations can pull from. Organizations need the right technical support and services to operate and scale effectively, and with limited options available, the complexities of long term success can be a huge barrier.

    The Complexity of Managing Ongoing Operations

    Implementation is just the beginning, what really enables businesses to be successful with any digital transformation initiative is tackling ongoing Day 2 operations. This means ensuring that technologies work well together, the team understands how to leverage the technologies and organizations have an operational readiness plan for continued development and ongoing improvement. So many businesses focus their attention on what happens before production and as a result, success is not always achieved. 

    When beginning a cloud native journey, enterprises must be conscious of the inherent challenges rapid adoption poses. Competition, lack of maturity and best practices, limited choices and complexity can all complicate an enterprise’s journey to the cloud. Awareness of potential problems can help stop issues before they arise while easing the transition to the cloud.

    — Tobi Knaup

  • JFrog Delivers on Hybrid Cloud Promise for DevOps

    JFrog Delivers on Hybrid Cloud Promise for DevOps

    JFrog announced the availability of what it claims to be the first available hybrid DevOps platform capable of spanning multiple clouds.

    Dror Bereznitsky, chief product officer for JFrog, said the JFrog Platform integrates a range of DevOps tools within the context of the continuous integration/continuous deployment (CI/CD) platform that the company previously developed, with the goal of making it possible to continuously release software originating from any source on to any platform.

    Announced late last year, the JFrog Platform also provides DevOps teams with the first universal package manager with JFrog Artifactory along with support for both REST application programming interfaces (APIs) and a command line interface (CLI), he said.

    In addition, the JFrog Platform provides a common integrated user interface to access all capabilities and has been integrated with JFrog Pipelines for CI/CD, which is based on code JFrog gained via its acquisition of Shippable last year. The JFrog platform also enables DevOps teams to now also deploy applications on Kubernetes clusters.

    Finally, because the platform is managed by JFrog, DevOps teams can count on high availability and cybersecurity updates that are automatically delivered, said Bereznitsky.

    Bereznitsky said thanks to the rise of microservices based on containers and other cloud-native technologies, organizations are reaching a tipping point in terms of the amount of complexity their existing DevOps platforms can absorb. As such, many organizations that have already adopted a DevOps platform will be re-evaluating them. JFrog is betting that rather than spending more time on managing their underlying DevOps platform, more organizations will prefer to divert more resources to application development.

    It’s too early to say precisely how application development will evolve going forward. There is certainly an opportunity to centralize DevOps processes in a way that will make organizations more efficient. Most organizations today employ multiple platforms for building and deploying applications that often conspire to increase total costs unnecessarily. The challenge those organizations will face is overcoming the cultural issues it is likely to create within their organization.

    In the meantime, JFrog rivals clearly see the same opportunity. The race to become a de facto standard for building and deploying a new generation of highly portable applications is now on, at a time when many of the providers of DevOps tools are starting to consolidate. At the same time, the number of applications that will be deployed across an extended enterprise that now spans everything from public clouds to edge computing platforms soon will dramatically increase. As the volume of applications increases, the level of friction associated with building and deploying applications will ultimately determine the DevOps platform any organization is going to be inclined to standardize on.

    — Mike Vizard

  • Ten Years Later — What Is Cloud Native?

    Ten Years Later — What Is Cloud Native?

    Ever since the term cloud native made its debut in 2010, its usage has grown in popularity. Today cloud native is used as a qualifier for innovative, leading edge applications, platforms and systems or cloud-savvy organizations and processes.

    However, what is cloud native exactly? There are some definitions, there are many opinions, but first and foremost there is a lot of confusion: Is my system already cloud native if I follow a microservice-based architecture? Is my system already cloud native if I run containers? Do I have to change development and operations?

    In this post, we cut through any uncertainty and ambiguity and provide an accurate and concise definition of cloud native systems.

    However, first, we have to discuss a set of prerequisite concepts.

    Application + Platform = System

    Frequently, in our day to day conversations, we use the terms application, platform and system interchangeably. Yet in this blog post, we draw a strict distinction:

     

    • Application: An application is the set of components that are designed and implemented for a specific use case.

     

     

    • Platform: A platform is the set of components that are designed and implemented independently of a specific use case.

     

     

    • System: A system is the combination of an application and a platform. Generally, we refer to an application as being hosted on a platform.

     

    End users do not interact with applications or with platforms only; end users interact with systems. Consequently, we will focus our discussion on system-level properties, not application—or platform-level properties.

    Application + Cloud Platform = Cloud System

    A cloud platform is a service provider that enables a service consumer to request and release resources on demand via an Application Programming Interface (API).

    According to this definition, a cloud platform is any service provider that enables a service consumer to request and release resources on demand:

     

    • Public Cloud Platform: A public cloud platform is a service provider that offers resources outside of its own organization.

     

     

    • Private Cloud Platform: A private cloud platform is a service provider that offers resources within its own organization.

     

    Consequently, a cloud system is any application that is hosted on a cloud platform. However, what is a cloud native system? 

    Responsiveness, Scalability and Reliability

    The distinction of cloud native systems versus non-cloud native systems is drawn along the lines of responsiveness, scalability and reliability. 

    In a nutshell, responsiveness is a system’s ability to meet the users’ expectations. In order to quantify responsiveness, we rely on a set of four related concepts: 

    • Service Level Indicator: A service level indicator is a quantitative observation about the behavior of a system.
    • Service Level Objective: A service level objective is a predicate (a function that yields true or false) on a service level indicator that determines whether the behavior of a system meets an objective.
    • Error Rate: The error rate is the ratio of the number of observations that do not meet their objectives to the number of observations in total for a fixed time interval.
    • Error Budget: The error budget is an upper limit on the error rate.

    Based on the above, we can now define responsiveness of a system as the ability of the system to keep its error rate below its error budget.

    These concepts are best explained with a tangible example: Consider a web application processing HTTP transactions, that is, accepting HTTP requests and returning HTTP responses.

    Service Level Indicators

    Here, we define two SLIs.

     

    • SLI Latency: determines the latency of a transaction, that is, the time when the request enters the system to the time the response leaves the system. 

     

    • SLI Result: determines the result of a transaction, that is, the status code of the response.

     

     

    SLIs are recorded at the edge of a system, here the Ingress component, to exclude any variation that is outside our control and focus on the performance of the system that is within our control. For example, we do not want to include any variation in observed latency or observed results originating in the users’ network connections. However, we do want to focus on the performance of the system once Ingress accepts the request until Ingress returns the response.

    Next, we define two SLOs.

     

    • SLO Latency: For this example, we define the SLO Latency to be met if a transaction’s SLI Latency is less than 250 milliseconds.

     

    • SLO Result: For this example, we define the SLO Result to be met if a transaction’s SLI Result is not in the HTTP 500 range.

     

     

    Finally, we set the value of the error rate’s time interval to a 30-day sliding window and the value of the error budget’s to 1%.

    By definition, this system is responsive if the ratio of the number transactions over the last 30 days that do not meet their SLOs to the number of transactions over the last 30 days in total does not exceed 1%.

    Scalability and Reliability

    At this point we have the necessary tools to define scalability and reliability:

    • Scalability is responsiveness in the presence of load.
    • Reliability is responsiveness in the presence of failure.

    So Finally, What Is Cloud Native?

    With the definition of cloud systems and the definition of responsiveness in place, we can now define cloud native systems: A cloud native system is a cloud system that is scalable and reliable by construction.

    The operator “by construction” is in stark contrast to “by requirement”: The design and implementation of a cloud native application guarantees scalability and reliability within the limits set by the service level objectives and error budgets.

    According to this definition a cloud native application must be able to:

    • Autonomously detect and mitigate the presence of load.
    • Autonomously detect and mitigate the presence of failure.

    Discussion

    This post defined the term “cloud native” as a property of a system, not as a property of organizations or processes.

    The defining criteria of a cloud native system are scalability and reliability by construction. Here, the employment of microservices (an architectural choice) or containers (a technological choice) is not a defining criteria of cloud native systems. If you want to know more, head over to—or better yet, get involved with—the Cloud Native Computing Foundation, a Linux Foundation project founded in 2015 with the mission to build a sustainable ecosystem for cloud native systems.

    — Dominik Tornow

  • DevSecOps: A Renewed Commitment to Secure Delivery, Part 2

    DevSecOps: A Renewed Commitment to Secure Delivery, Part 2

    If done right, DevSecOps eliminates the cultural roadblocks that often prevent organizations from getting IT security proactively involved with development and operations. Barriers are the last thing any organization should contend with when comprehensive security is an absolute priority at a time when data breaches, intellectual property theft and other cybercrimes can almost immediately cripple a business.

    Still, companies are far from perfect. Misunderstandings, ill-defined policies and turf wars can prevent development and operations from collaborating in a way that naturally bakes-in security into their work. To effectively transform a DevOps pipeline into a DevSecOps one, organizations need to change the way people work and collaborate; make processes inclusive of quality, security and compliance activities; and integrate the right tools.

    Those three steps are the focus of this two-part series on becoming a true DevSecOps enterprise. We reviewed processes in part one and now we’ll cover people and tools in this article.

    For enterprises with deep-rooted DevOps, a renewed focus on security might entail modernizing the release pipeline and involving IT security people even more. For enterprises that are modernizing heritage-monolithic application portfolios and moving to cloud native architectures, pipeline modernization should include a DevSecOps approach that considers containers, microservices and APIs. 

    DevSecOps done right gives organizations a level of visibility and accountability that helps accelerate coding, testing, production deployments, problem determination and defect resolution–all accomplished because of an organization-wide acceptance and commitment to security that should shatter any and all roadblocks.

    Don’t Forget About the Humans in DevSecOps

    When was the last time you heard a developer say, “Hey, let’s get the security guys in here, to hear what they have to say?” Reality is far harsher. Collaboration with IT security often triggers visceral reactions that are not exactly positive. IT security is often stereotyped as the organization of “no” and “you can’t do that.”

    DevSecOps aims to tear down those cultural barriers. DevSecOps is all about embracing your IT sec organization and even inviting auditors to collaborate early on in the release process. 

    Ultimately, security is everyone’s responsibility. Being a developer, there was nothing like the mention of security to make me feel super uncomfortable. I don’t believe that developers set out to purposely create insecure code. However, when IT sec is not involved in a collaborative, cooperative relationship with dev and ops, there is an uncertainty that creeps in, and trust and confidence are shattered.

    We know developers develop and release code, while operators control and manage the runtime environment. What is the expectation of IT security in this process? What are they looking for? What risks do they need to mitigate when a digital product is delivered? Understanding the objectives of IT security in the delivery process will clarify the steps that must take place in the process and reveal which tools should be used to create a product that’s secure and delivered with velocity and quality.

    Understanding what stakeholders do along the pipeline reconciles personal and organizational accountability with tangible value-add in the release process. DevSecOps can be a catalyst to re-examine and provide clarity on who is doing what, when it is being done and why the effort is being exerted.

    Clarity might reveal that personas need to be updated to more modern roles. For example, an operations system administrator might become more of a site reliability engineer (SRE). The SRE role involves more proactive activities, earlier in the release pipeline, to infuse greater fault tolerance in code and greater resilience in the environment configurations–and to solve problems by engineering solutions with developers and IT security.

    Determine who does what and where. Develop personas that outline responsibilities along the pipeline, from the sourcing of code to production, to create necessary transparency. Value-stream mapping is a good way to capture the current state of a release pipeline and an excellent way to construct a desired state pipeline with the necessary people performing value-add activities to releasing a product. 

    Use Tools that Provide Necessary Visibility

    Tools are the enablers. These are the cogs in the machine that will be running test cases, static analysis, vulnerability scans and integration tests. Tools will automate DevSecOps processes and provide the most critical function: visibility. The ability to observe all DevOps processes and determine their origins in the pipeline is critical. Visibility lessens risk and supports compliance and audits. The process that defines how code is governed through the promotion path should drive the tools that will be integrated into the release pipeline. Most tools serve to automate build, testing, scanning, movement through the promotion path and integration with other tools. It only makes sense that end-to-end visibility in the release pipeline should be engineered in.

    Tools, though, must integrate and communicate to achieve end-to-end visibility. In the heritage era of DevOps (basically, the time before cloud native), it was tough to gain visibility because tools came from different vendors and often couldn’t talk with one another. Fortunately, cloud native platforms offer more integrated capabilities. Build and CI tools naturally share information because these capabilities are being refactored into the cloud platforms themselves.

    An example of this is the cloud native CI/CD capabilities of Tekton, which leverage and extend the operator framework in Kubernetes. Translation: CI/CD tools are starting to look like extensions of the cloud native platform, in stark contrast to heritage CI/CD tools which were standalone third-party software products. The result of this tool trend is tighter integration and better visibility built into the platform–you don’t have to engineer it.

    Companies need to review how effectively their tools communicate and close any visibility gaps. When possible, consider some of the next-gen automation tools and technologies such as Tekton, Kabanero.io and Jenkins-x that bring greater visibility, integration and consideration for cloud native apps which heritage tools have struggled with.

    DevSecOps Is a Catalyst for Pipeline Modernization

    A modern security framework will let companies take full advantage of the cloud native technologies that are changing DevOps. Granted, most companies won’t completely shift their entire infrastructure to the cloud, nor should they. Most organizations need to identify a partner to help them assess which processes and tools are worth moving to the cloud, and which ones–like a mainframe that runs core business functions–should be left alone. 

    For those enterprises that have a large heritage application portfolio, DevSecOps could mean retrofitting automation into systems and applications that were often designed and developed without the scaffolding of a secure DevOps pipeline. DevSecOps applies to heritage application, too. After all, what pipeline wouldn’t benefit from the visibility and traceability of tracking a user story to its production release? By automating the delivery of these heritage apps, you’re optimizing the effort of manual activities such as build, test and deploy, and retrofitting the capability of pipeline visibility.

    Cloud has changed the DevOps game, newly defining the fundamental technical underpinnings of what an application really is. And it is cloud that’s driving companies to look at the security of DevOps in an entirely new way. With much on the line–the purity of products, compliance, brand reputation–companies need to rebuild their security frameworks so they can take full advantage of cloud and their on-premises programs. They don’t have to do DevSecOps alone.

    — Andrea C. Crawford

  • The Top Six Cloud Computing Trends of 2019

    The Top Six Cloud Computing Trends of 2019

    Cloud computing was one of the hottest topics in the technology and business media throughout 2019. This is no surprise as the cloud sector has been growing rapidly for the last few years. Synergy Research Group recently reported a 37% overall growth year-over-year in public cloud. They also note that it has taken just two years for the public IaaS and PaaS markets to double in size and their forecast shows them doubling again within the next three years.

    While steady growth was expected this year, a few trends of note stand out. When the experts look back at 2019, they will likely stress the following cloud computing trends shaped the year.

    Rise of the Enterprise Cloud Manager

    We recently did a study on ParkMyCloud users which showed that a growing proportion of company technical leads have cloud or the name of their cloud provider–such as AWS–in their job title. This indicates a growing degree of specialization for individuals who manage and architect cloud infrastructure. Whether called enterprise cloud manager, cloud architect or something similar, 2019 saw the rise of a specialized role to oversee and direct cloud operations.

    Consolidated Multi-Cloud Views

    As enterprises large and small continue to adopt and use more than one public cloud, we have seen a rapidly growing need for a consolidated multi-cloud view and ability to take actions across multiple clouds in 2019. Third-party tools that do this provide enterprises the ability to pick a single tool to orchestrate, manage, govern and optimize their hybrid and multi-cloud environments. Many customers also sight the need to simplify operations—native cloud provider tools are not always easy to use.

    Multi-Cloud Arrives

    Multi-cloud truly arrived in 2019 and will only grow in 2020. The majority of organizations now use multiple clouds. In fact, most studies suggest that more than 80% of enterprises have a multi-cloud strategy. Reasons cited include the need to avoid vendor lock-in, the ability to leverage the best in class cloud services from each cloud provider and application efficiency choices.

    More Automation

    One of the biggest tech benefits to a DevOps approach is automating away the manual tasks that bog down operations and critical projects. Thus, the trend toward automation continued to expand in 2019.

    More Abstraction

    IT became more and more abstracted in 2019. This means container usage grew, along with models that allow developers to worry less and less about infrastructure (such as serverless and PaaS).

    Containers Became Mainstream

    Application containerization is more than just a new buzzword in cloud computing; it is changing the way in which resources are deployed into the cloud. More and more companies utilize container services such as Kubernetes and cloud native services such as EKS, AKS and GKS in 2019, 

    Business continued to move to the cloud in 2019 and the six trends described above showed that the sector is growing–sometimes in unpredictable ways. Next year will, no doubt, also contain some surprises. But the trend for expansion of the cloud and related services is unmistakable for the foreseeable future.

    — Jay Chapel

  • An Overview of Cloud Migration and Open Source

    An Overview of Cloud Migration and Open Source

    Most businesses are moving toward making their business processes more user-friendly, through digitization. This shift of business modernization comes with a heavy price for them in terms of money and in terms of time. It is going to take time and a great amount of investment in new innovative technologies.

    Cloud computing is the biggest trend in digital transformation due to its ability to make business applications and infrastructure easily accessible. In the roadmap toward cloud migration, businesses are looking to save capital investment or expenses (CAPEX) and operational expenses (OPEX). 

    Open source technologies come to rescue for such businesses. Be those who are present at public cloud platforms such as AWS, Azure or Google Cloud, or private data centers. The role and emergence of open source technologies simplified the equation of overall expenditure for all enterprises and organizations of any industry domains. Year by year, more open source projects are coming up and solve major challenges which businesses are facing. Companies such as Red Hat and communities like Linux Foundation have a major role in promoting open source projects at the heart of digital transformation.

    Why Open Source at Cloud?

    • The main reason to adopt open source technologies in the process of cloud migration can be avoiding vendor lock-in in the future. Most public cloud vendors have a similar portfolio of open source supports in their offerings. As open-source projects are not owned by one company and its overall framework is common to all of its consumers, any updates to its core files have an impact on all projects. And businesses can simply move their application environment from one cloud to another without worrying about backend environment that is powered by open-source projects. There can be a seamless integration of applications and services developed or deployed by different businesses and vendors.
    • Open source adoption for cloud will help in interoperability with other enterprise solutions that can be located in different data centers. Though, other data centers should be equipped with the same open source projects. This interoperability enables the reuse of software stacks, libraries and components. Such interoperability can help deploy multi-cloud environment for businesses.

    The Cloud-Native Approach in Cloud

    Application containerization has been adopted by many solutions providers and vendors in the last few years and has become significantly popular. This containerization surge has triggered the use of cloud-native applications. Most of the popular cloud-native projects are hosted in Linux Foundation’s CNCF (Cloud Native Foundation) community which nurtures the development of various open source projects. Some of the popular projects are Kubernetes, Prometheus, Envoy, Helm, rkt, Linkerd, Etcd, Jaeger, etc.

    The cloud-native approach involves the utilization of tools for handling containers, micro-services, service mesh, DevOps and continuous integration (CI) and continuous deployment (CD). Cloud-native tools for CI/CD can be Check, Ansible, puppet, etc., and service mesh can be Istio, Linkerd, etc.

    Most of the enterprises tend to involve open source projects from various umbrella’s to build the Cloud migration strategy. Moving to cloud-native management of application can be a prominent requirement for many enterprises.   

    Open Source Cloud Migration Tools

    There are open source tools and frameworks that help with cloud data migration. These tools require modification in terms of coding to make the migration process that suits your infrastructure. To make coding customizations in these tools you might need investment for skilled resources.

    The above projects help enterprises to move data. Bluethroat is an open source project which can be used for migration of overall infrastructure from data center to data center, data center to the cloud, cloud to data center and cloud to cloud. Currently it is powered with limited features and used specifically for AWS. It offers the following features:

    • Migration of infrastructure to AWS.
    • Agentless.
    • Environment discovery.
    • Automatic network creation and server deployment.
    • Linux server migration.

    Conclusion

    Cloud migration has its own challenges in terms of uptime, security and data loss. Most public clouds are evolved to handle data as well as application workload migrations. There are many benefits to open source projects, as discussed in this article. The main advantages of migrating open source frameworks to the cloud are cutting back on expenses and avoiding bottlenecks.

    — Sagar Nangare

  • DevOps Chats: Software Architecture for Cloud Native, .NET Core and Open Source

    DevOps Chats: Software Architecture for Cloud Native, .NET Core and Open Source

    In this episode of DevOps Chats we talk with Donald Lutz, principal software architect specializing in systems integration and creating large, scalable cloud applications. Occasionally DevOps Chats is fortunate to spotlight DevOps and cloud native developers doing trailblazing work in contemporary software architectures. Donald fits that bill to a T as an entrepreneur and employee at startups such as Faction, BoldTech Systems and his own company Technetronic Solutions, and established companies including Via West.

    Our discussion focuses on creating cloud native applications in startups and large enterprise IT. Donald’s currently working with one of the world’s largest financial institutions to move from legacy applications directly to cloud native apps, bypassing any interim lift-n-shift moves. His work spans many Microsoft technologies, including .NET Core, runtime framework Dapper for RDBMS mapping, Service Fabric and Azure, opensource Kubernetes, Terraform and Puppet (and Enterprise).

    During our discussion, we cover the challenges of architecting and scaling very large cloud native applications, implementing DevOps in less mature software organizations, how established software patterns benefit DevOps and cloud app developers, and the importance of giving back by hosting meetups to share knowledge and mentor others. Donald also gives back as an active leader and mentor of the FIRST Robotics Team 1410 since 2005.

    Join in on our conversation as we explore the complex and sophisticated inter-workings of a cloud native software architect.

    Transcript

    Mitch Ashley: Hi, everyone, this is Mitch Ashley with devopsy.kinsta.cloud, and you’re listening to another DevOps Chat podcast. Today, I’m joined by a very special person, a good friend of mine, Donald Lutz. He’s a principal software architect at many companies. We’ll kinda get into that, but he’s focused on microservices cloud, he also is very involved with Microsoft in his background.

    He’s currently involved in several things, but he’s with his own company, Technetronic Systems, and he’s worked with Faction, ViaWest, he actually was one of the original co-founders of BoldTech Systems with me back a while ago.

    So, our topic today is microservices going cloud native. Donald, welcome to DevOps Chat.

    Donald Lutz: Thank you, Mitch. Thanks for having me on. I really appreciate this.

    Ashley: Oh, it’s a great honor of mine, you’re a good friend. And to that point, why don’t you tell us a little bit about yourself, introduce yourself to our audience, tell us about what you do.

    Lutz: Yeah, I’ve been sort of a principal software architect and a director of software engineering for different companies like Faction, my own company TSI and I’ve really in the past five or six years focused on cloud native and taking—you know, getting microservices and applying that to building cloud native applications. That’s really kind of what my focus has been. And there is a lot of DevOps that goes in there. There’s also a lot of architecture and design, so it’s kind of a combination of all of the above.

    Ashley: Mm-hmm, excellent. Well, just full disclosure, I mentioned before, you and I have known each other a long time. We started working together back in the telecommunications industry and I did a startup called BoldTech Systems, which you were a part of founding and getting going and, you know, you’ve hired me, I’ve hired you. [Laughter] We kinda worked with each other—which, by the way, for folks earlier in their career, that’s a great thing to do. Keep your friends close, because you’ll get to work with them again.

    But you’ve had this consistent pattern in your career where I know you were very Microsoft and .NET focused for a while and then kinda moving into cloud and broader technologies. I mean, you’ve worked on Java and other things, too, it’s not like you just did Microsoft, but tell us a little bit about your philosophy on technology. Are you a fanboy Microsoft or how do you kind of view that with everything else that’s going on in the technology world?

    Lutz: I mean, I could be viewed as a fanboy of Microsoft. I mean, I helped—I’m running now .NET Core, an open source Meetup for Microsoft. I really like where they’ve taken .NET Core. I mean, I would claim, six or seven years ago, Microsoft realized that they needed to stop being so proprietary and get more into open source.

    Ashley: Mm-hmm.

    Lutz: So, they really kind of redid all of .NET, and .NET Core is fundamentally, it allows you to build microservices, traditional apps, too. But, you know, they moved to the open source arena because they knew their future was Azure, it wasn’t really Windows in the traditional sense. You know, 75 plus percent of all their things that were under Azure are Linux that run with another product called Service Fabric and, you know, that to me, is a great technology. I have done Java, I’ve done Go, I’ve done a lot of different things, you know? I have a large Microsoft contingent, but they’re all part of the same thing where everybody’s trying to get to cloud native—what does cloud native look like? Whether you’re Microsoft, Pivotal, VMware—everybody’s trying to figure out how to you get there, you know?

    And a lot of people have taken steps in between, like, some people are trying to run VMware on the cloud, but I’m seeing a big push where I’ve been talking to a lot of people, I’ve been working with a really large financial institution right now, and they’re actually punting on the in between and they’re going completely cloud native using both multi-cloud and in their definition, is Azure an AWS?

    Ashley: Interesting. And I’m aware of who you’re working for. I know we’re not talking about the company name specifically, but give us an idea of the scope and magnitude. Because we’re not talking like, you know, a credit union or a large regional bank.

    Lutz: No, they’re one of the largest financial institutions in the world. So, they are looking—they’re moving everything at the top level of their management, you know, CTO level, they decided that they wanted to do microservices, domain driven design. They wanna go all cloud native. It’s either gonna be running in AWS and Azure. They don’t wanna own any hardware any more, they don’t wanna have any of it. For them, it’s an amazing kinda revolution, because they’ve never gone there, and they’re kinda viewing that they wanna run their company in a technological era kind of like a startup, so they’ve really changed their whole view.

    So, I was kinda surprised that they were that interested in that and the fact that they looked at the cloud and they said, “We need to go cloud native, because we don’t really need in between steps because then again, we have another shift and lift then in five years,” and we only wanna have one shift and lift, so I was really surprised they even thought of that.

    Ashley: Well, it is, and I’m very surprised by that, too. It’s certainly—you know, I don’t talk to every big financial institution in the world, but to make that level of commitment of, we are gonna go cloud native, not like we’re gonna lift and shift what we have and just kinda live with legacy, if you will, and build new things in cloud native, they’re actually taking the major part of their software assets, the systems rely on day to day and they’re shifting that just going to cloud native in one big step—well, several one big steps, apparently. [Laughter]

    Lutz: It’s a lot of big steps, but I mean, it was kinda surprising, because you know, they brought in executives who had been more out in Silicon Valley and not traditional financial people. So, they’ve made a different, and they went and found a bunch of us who have been kind of in the cloud native microservices space and brought us on. They kind of viewed it as, they’re trying to build, like a, sort of the Super Bowl winning football team, that if you get the top players, then you can get this to happen.

    Ashley: Mm-hmm.

    Lutz: That doesn’t mean there still aren’t interesting political battles, since this is a company that’s historically, you know, they still have DB2 and green screens, so, you know—

    Ashley: Sure.

    Lutz:—it’s not like it’s completely, “Oh, yeah, this is awesome!”

    Ashley: Right. [Laughter] It’s not like they started in the Linux area, though—era.

    Lutz: Yeah.

    Ashley: So, say a little bit about—so, you have a unique perspective of, you’re not the kind of entrepreneur that’s worked in a from scratch startup in the garage every time, repeat, repeat. You’ve done that, but you’ve also worked with a lot of existing organizations. I know ViaWest had been acquired, I think, by Shaw Communications before you joined and they were going through a transition.

    Lutz: Yeah. I went there because they were—I was looking for a place that wanted to move to microservices and they had been acquired by Shaw. I knew their CTO, we chatted, so they hired me as a Director of Software Development, and the goal—they were all .NET, so I moved into .NET Core and we started building microservices, which is the whole idea of, there’s a lot of stuff that comes out of major design and bounded context.

    So, instead of having, you know, your monolithic application that has customers and data center stuff, we started building services like, “Here’s your customer service.” And it all deals with that. We also brought in some other, DevOps people know about more CQRS and event sourcing. So, the whole idea, each service has its own database that it writes its data to. It then issues commands—so, say I created a customer, I say “create customer.” That causes an event called Customer Created that gets stored in an event store, which almost looks like an audit log. You never delete from it, you only add to it.

    So, if you ever have any problems with all these distributed services failing, you can rerun this audit log and get back to where you were in the beginning.

    Ashley: Mm-hmm.

    Lutz: So, it’s kind of a powerful concept. These concepts have been around for a while, but you’re starting to see them being employed at a larger level. Because, you know, the idea of synchronous communication doesn’t work well in cloud native. In fact, you really just want to expose public APIs, and behind the scenes, you want data streaming, you want eventing. You don’t want any asynchronous communication, because it’s not the right approach. You can’t scale, and you’re gonna be dealing with eventual consistency.

    So, you know, once you start dealing with that, once it’s not in one box, you know, eventual consistency is it.

    Ashley: Mm-hmm. Where you’re going to kinda stateless applications, right? Microservices—it’s interesting that the trend is, obviously, is build much smaller things, reuse them, create services out of them. But there’s gonna be many, many more mass quantities of them. It’s not like you’re going from—you’re going from one monolith with a lot of functions and APIs to really small pieces of software that are containerized microservices.

    But what comes with that is now, all of a sudden, you have the problem of managing that, communicating across and synchronizing when it is asynchronous how you communicate, handling troubleshooting, knowing what all those services are. It sounds like what you’ve done is, you’ve reached back into some maybe techniques and technologies or knowledge of past things and bringing that into this microservices Fabric world. Is that true?

    Lutz: It’s true. I mean, I get a lot of Kubernetes and all that, and you know, even though you start doing Kubernetes and a lot of DevOps things, it’s sort of the thing that I find interesting. It’s kinda like, sorta what you on the Phoenix Project, you know, you need to be able to manage all those things and be able to deliver all the time and monitor it and log it. The problem is that that’s not just answered by creating a bunch of scripts, you know what I mean? Like, even though I’ve used Terraform, Puppet, I think there’s a larger scale of solution.

    Microsoft just released a new framework called Dapper, and Dapper is basically dealing with the microservices run time. So, it’s a run time that can sit on top of whether the microservices can go talk to Kubernetes, because you need to be able to handle that run time stuff as well as the development issues that go on. Those things are not two separate things, and I still think that’s the—one of the large DevOps challenges is how do you get everybody on board, you know?

    And at ViaWest, it was pretty sophisticated, because all our DevOps people were software engineers. So, we just wrote software for most of our problems. We either built it ourselves or used various tools. But then I went to a company called Faction where we had a less mature DevOps practice, and we were building multi-cloud storage, so we had a lot of microservices that allowed us to do Isilon, Dell storage, you know? So, we built a fairly sophisticated microservices platform. We didn’t have the DevOps practice, which resulted in some interesting issues, because the organization was not mature. Everything was manual. So, it’s really hard to roll those out, because you roll them out and then you can’t roll them out as well as you’d like to, because nobody’s catching up.

    Ashley: Mm-hmm.

    Lutz: They’re like, “Oh, well, how do we do that?” I’m like, “Eh, yeah, that’s an issue.” There’s no tests going on, you couldn’t do a Chaos Monkey. So, that was—in that case, in that case, it was pretty challenging, you know? And also the whole—I’m thinking a lot lately about security and the fact that you have all these cloud native accounts, but you have, you know, you have these very, you have credentials that give you access to RDS and Amazon, and then those aren’t really secured real well, and there’s Vault and there’s multiple ways to do it. And the whole security thing is, I don’t think, well cooked in a lot of ways. I would claim it’s not. [Laughter]

    Ashley: Well, application security is now become—becoming, maybe both—you know, one of the top topics. It seems like we’re just sort of, we do things differently, and then we have to go back into and go back and address, like, “Okay, well, how are we doing this now?” Because, you know, it’s not about protecting servers and network devices. We’re exposing so much of the tax service as an application through all these microservices, APIs, et cetera. You gotta kinda rethink it.

    And then you’re automating the development environment to do 15, 20, 100 code deploys a day, potentially. Well, that takes automation—that means all those credentials, security keys, certificates, whatever are built into a process that’s all that secure. I think that’s what you’re talking about is, you have to do it, but you have to also go back and re-look at it to say, “Are we doing this securely?”

    Lutz: Right. You have to look at things, “Do I have—is data at rest encrypted? Do I check any kinda hash on it? Is the data in flight encrypted? What are the levels of security? Do I let my JWT token float to one service, to another service, because that could be an attack, too.” Because I went to service one and now I go to service two and I’m using the same JWT token, but maybe the claims on that second service, it shouldn’t be allowed to do those things, because the claims that it used from the first service lock it down better, but in service number two, it allows you suddenly, “Hey, I could go look at different accounts that Mitch has, and well, that’s interesting.”

    So, then you start thinking about, you know, how—there’s a couple good security books about that whole idea of, you know, JWTs are interesting, but the problem is that if they float, if we haven’t figured out the right way to share those, that’s another thing that causes lots of problems.

    Ashley: Mm-hmm. And for me and for our listeners, can you define what a JWT token is?

    Lutz: Yeah, it’s a JSON web token. It’s just—

    Ashley: JSON, right?

    Lutz: Yeah, yeah. It’s just a token that basically you can use with an API. You know, it’s a little—it’s really for APIs. OAuth, you can do both. OAuth is more effective with users, but those are, you’re seeing the industry starting to adopt JWTs between services. So, now people are saying—but the problem is, the concept behind it is a claim. I wanna make a claim that your name is Mitch and you live at this address and you have this phone number. And in this case—oh, by the way, you can look at your Social Security number, but in this case over here, you shouldn’t be able to look at this other person’s Social Security number.

    So, you start making all these claims, and then you have to start getting really smart about how do we define all these claims for these very distributed systems.

    Ashley: Mm-hmm.

    Lutz: Which, historically, distributed systems were everybody—oh, if you had the root password, you’re golden. We’ll just use that and everything will connect to it.

    Ashley: Yeah, interesting. It’s really interesting, not being that close to it but following what’s happening with it. I think it’s based on, like, RFC 7519, so it’s based on a spec. It’s about how claims essentially get bedded into what we traditionally think of as a data interface specification between services and applications. Anyway, we’re not a JSON JWT podcast, but interesting sideline.

    I wanna get back to talking about microservices in cloud native. So, as you’ve worked with existing applications, and even at Faction with something that maybe didn’t start out in a DevOps world, what do you see as some of the kinda approaches that make sense and maybe things that you or others have tried that turned out not to be the best path or dead ends that you’ve corrected from and now here’s how you do things?

    Lutz: The first problem I see is, you make nanoservices. So, instead of—you know, you make a microservice that tracks time, and it’s so small that it’s not very effective. There’s a software architecture discipline called the main driven design, which is about when you build an application and a service, there’s a domain that it covers, whether it’s a customer or a product, and it needs to be the right size. And if it’s the right size, it’s what’s called bounded context. Because the whole idea is, you want that service just to answer that bounded context, which is based off the idea of a single responsibility principle. If it does more than one thing, you have a problem.

    So, kinda getting people to understand that is complicated at a business level, because you know, business people historically want to throw everything in whatever they’re building. Like, “Oh, can’t we just, why do we need to have such a small bounded context? Can’t we, like, throw all the addresses and products in here?” I’m like—no, because we need to keep those separated, because we’re trying to, each microservice has to have a very distinct separation of concerns, because if you don’t have that separation of concerns, you end up with a monolith, which is what we’re trying to avoid.

    Ashley: Yes, end up back into the spill over again of domains into, this microservice has too many things in it and now one thing’s affecting another, versus let it be a single purpose in our service.

    Lutz: You know, and that’s why we actually saw that this large, large financial institution has adopted domain driven design and they’re actually building domain models for all their applications and everything. So, there will be demand models behind them.

    So, it’s just not the microservice, they actually can say, “Oh, by the way, this is what this financial instrument looks like, and it actually maps to our true domain model and then will map to a true microservice.”

    Ashley: Mm-hmm, okay, so domain driven design, nanoservices, or kind of focused functional microservices that don’t kinda spill over.

    Lutz: There’s another thing, too, you need is what historically—Chris Richardson has a book called Microservice Patterns, and it’s the idea of what’s called a microservice chassis. So, once you start building microservices, you either need to make a framework or use a pre-existing framework, whether it’s Spring Boot or some stuff in .NET Core so that when you write the microservices, all the logging is done the same, all the separation and concerns are handled so you deal with all those non-functional requirements so you don’t spend any time developing it.

    Ashley: Mm-hmm.

    Lutz: But then once you do that, then you have to start saying, “Well, how does this play in the run time world of Kubernetes?” Which gets into something you said earlier—we need to sort of connect the framework with the run time stuff, so that’s kind of a problem you see in Pivotal, Microsoft. They’re all looking at how do we get these really interesting software engineering frameworks that then wrap into run time things that are equivalent, so we end up with, you know, “Oh, they’re the same thing, they’re isomorphic.” They’re not different, they just look different because we view them as different domains.

    Ashley: Mm-hmm. Interesting. Well, we have a couple minutes left. I wanted to just take a little bit of a left turn—not quite a squirrel moment, but a little bit of a left turn. I’ve been doing some podcasts here recently with folks, usually developers, DevOps engineers, Ops folks who are talking at the Spinnaker Summit Conference, speaking on Kubernetes and Spinnaker Open Source.

    So, we’ve had a great opportunity to have other developers, real hands on technical folks on the podcast. And one of the things that I always encourage folks is, even in the open source community, you contribute not just by writing code, it’s by sharing your knowledge, applying these tools and software and sharing the knowledge and networking and building community with others. That’s vital to having, you know, vibrant software is having a vibrant community about it. And I know you’re very active in your own developer circles and communities in creating those. Tell a little bit about what you’re involved in now and why you do it.

    Lutz: I like doing it to share. I mean, I would say about four years ago, there was a gentleman running a group, there’s a group worldwide called ISO, the International Association of Software Architects. And he was trying to get the group growing locally in the Rocky Mountain region—you know, Denver, Wyoming, that kinda area. He hadn’t gotten very far, so I got kind of involved, and we’ve actually grown it over the 4 years that we have 2,000 members and we get about 60 to 100 members coming every meeting, and it’s truly talking about architecture. It could be the Kubernetes architecture, it could be domain driven design. Last month, I talked about how to build microservices that are stateful. Surprisingly, there’s a company called Cloud State. Microsoft and ACCA, they figured out how to build stateful microservices. We won’t get into that.

    Ashley: They didn’t bring pitchforks and, you know—

    Lutz: They didn’t bring pitchforks. It works pretty well.

    Ashley:—torches? [Laughter]

    Lutz: But we get different people. We got the guy who’s the original guy at FedEx who created all their stuff that looked like Kubernetes in the ‘60s come talk. We’ve had people from Slack. We get a lot of people to come talk. I’ve talked at the Carnegie Mellon architecture conference, I can’t remember what it’s called. I talk at a lot of Microsoft groups. I run a Meetup for Microsoft. They have a few .NET groups that are dying, so I pitched to them—why don’t we turn that into a .NET Core and open source group?

    Ashley: Mm-hmm.

    Lutz: And so, I’ve been running that. I’ve grown it—that’s almost to 1,000 members now. It was actually only 200. So, in the three or four months, I’ve actually grown it. I like creating communities of technical people, because when you do that, you actually can solve interesting problems. You also get to hear other people’s experiences.

    I can give you an example—one of the guys who get involved with ISO, I was talking in Colorado Springs at an event, I can’t remember where. And I was outside the event and this guy, Tyler, came up to me and started talking to me and I discovered he was really technical. And he said, “What are you doing?” I said, “Oh, I’m talking about microservices and that.” And he says, “Why don’t I come in?”

    And we actually—he became the person who asked me the most questions during the event and then he became one of the four members to help us run the Denver Software Architects Group.

    Ashley: Mm-hmm. Interesting.

    Lutz: And we became really good friends and it was like, you know, just talking to somebody outside an event I was gonna speak at.

    Ashley: Very interesting. Well, you know, I think it’s also, all of the things you said, I totally agree with. It’s also a way for someone who wants to know about a topic, maybe, and I like how you’re kinda keeping the groups fresh on what’s happening and new in Microsoft and other worlds of software. It’s a place for folks to go and learn about it and hear what other people—even if you’re very engaged in a new technology already, it’s, what are other people doing and what have they learned from it? What can you share, what can they share with you, and vice versa. So, it’s a healthy thing to do.

    Lutz: Yeah, I really enjoy it. I find it more enjoyable—it’s up there with this robotics stuff FIRST I do in terms of raw enjoyment, because it’s so, you’re plugged into so many people where, when you know, when I’m doing consulting or helping build a startup or all of the above, it’s enjoyable. But it has—this has more of a kind of like, not selfless, but it has more of a giving back vibe that I like a lot.

    Ashley: Mm-hmm. Very good. Well, hey, we’ve run out of time. You and I could talk for 12 hours and, you know, up ‘til 3 a.m. in the morning. There’s so much fun things that you’ve done. I really appreciate you being on the podcast.

    Lutz: Well, thank you for having me on. I really appreciate it. I really enjoyed it.

    Ashley: Well, good. Me, too. You’ve listened to another DevOps Chat. I’m very pleased to have my guest, Donald Lutz, on with us today. Donald is a principal software architect, he focuses on microservices, cloud, cloud native, generally Microsoft technologies, but a lot of other things and he’s with Technetronic Systems. He’s also been with Faction, ViaWest, BoldTech Systems, a number of different companies, so he has a lot of software background. And again, our topic today was microservices in cloud native.

    Thank you, also, to your, our listeners, for joining us. This is Mitch Ashley and you’ve listened to another DevOps Chat. Thanks, and be careful out there.

    — Mitchell Ashley

  • Predict 2020: What Will the New Year Bring?

    Predict 2020: What Will the New Year Bring?

    With the holiday season upon us, our thoughts naturally turn to the next year and what it has in store for us. Will we come into more money? Will we find true happiness? Will there be better integration between DevOps and security? Will there be more Kubernetes instances? The first two may be a little hazy, but it’s a good bet the second two will be discussed during Predict 2020 Virtual Summit, Jan. 23, 2020, where an all-star lineup of industry luminaries will offer up their visions for the future.

    Crystal ball? Check. Swami hat? Check. Insight relevant to the industry? Check. Very smart people who know what they’re talking about? Double check.

    Similar to last year’s event, Predict 2020 will feature a virtual environment with a conference lobby, presentation theater, expo hall and more. More than a series of YouTube live presentations, it is truly a conference experience from the comfort of your desk.

    Speakers

    Our keynote speakers for this daylong event include analysts, practitioners, venture capitalists and thought leaders from the realms of DevOps, cloud native, cybersecurity, digital transformation and IT. Each will share their best predictions for the year 2020 and beyond.

    Among those slated to speak are:

    There will also be an exhibit hall where you can interact with other attendees and sponsors, watch videos and download more information.

    It should be a great day of learning and networking right from the comfort of your own chair.

    Registration and Sponsor Info

    You can register now at https://predict2020.io. Attendance is free.

    If you are curious about what the experts, pundits and luminaries think will be the big trends and stories of the coming year, mark your calendar and attend Predict 2020.

    Save Your Virtual Spot

    — Alan Shimel

  • Logz.io Adds Monitoring Service Based on ELK and Grafana

    Logz.io Adds Monitoring Service Based on ELK and Grafana

    Logz.io today at the AWS re:Invent 2019 conference launched Cloud Observability Platform, a monitoring and security cloud service based on ELK—open source Elasticsearch, a search engine; Logstash, a data processing pipeline; and Kibana, a set of visualization tools—and Grafana, an analytics and monitoring platform.

    Company CEO Tomer Levy said it’s become apparent that developers have a strong preference for open source tools for managing cloud-native applications. As such, the adoption of ELK has increased substantially. With the increasing maturity of Grafana, it’s also becoming clear that organizations want to meld the open source analytics and monitoring tool with previous investments in ELK tools, he said.

    However, not many IT organizations have a lot of ELK and Grafana expertise. To fill that gap, Logz.io is launching a managed cloud service based on Logz.io Log Management, an instance of ELK that the company has enhanced with machine learning algorithms and data analytics capabilities to enable DevOps teams to discover and resolve issues faster.

    That core platform is being extended via Logz.io Infrastructure Monitoring, a beta release of a monitoring platform based on Grafana, and a security information and event management (SIEM) platform dubbed Cloud SIEM, based on an ELK stack that includes built-in threat detection tools.

    In addition, Levy said Logz.io plans to add support for Jaeger, an open source distributed tracing tool being developed under the auspices of the Cloud Native Computing Foundation (CNCF).

    Levy said it’s apparent to all that observability is a core tenet of DevOps, which he said is why there are already a half-million developers making use of ELK software. The challenge organizations are finding is that monitoring modern IT environments based on cloud-native applications is cumbersome and time-consuming. Logz.io is addressing that issue by providing an enterprise-grade instance of an open source monitoring platform that comes with hundreds of built-in connectors, which enables DevOps teams to employ a monitoring platform without having to be worried about becoming locked in to a specific vendor because they can switch over to open source code anytime they like, Levy noted.

    Developers tend to favor open source tools because they don’t have to wait on purchasing approval to employ them. However, enterprise IT organizations tend to favor platforms that are supported by a commercial vendor. Logz.io is trying to address that issue by providing support for an open source platform that will make enterprise IT organizations comfortable enough to give up relying on a proprietary monitoring platform. Thus far, Logz.io has more than 700 customers, which the company expects to expand now that it has an instance of its platform that can be consumed as a cloud service.

    It’s too early to say to what degree an open source platform might usurp proprietary platforms in the enterprise. Change tends to come slowly to enterprise IT organizations. However, as organizations embrace next-generation applications based on microservices and containers, enterprise IT organizations are clearly evaluating their monitoring platform options going forward.

    — Mike Vizard

  • DevOps Deeper Dive: SUSE Sets DevOps Course

    DevOps Deeper Dive: SUSE Sets DevOps Course

    There was a time when SUSE was considered to be the second-biggest force driving the adoption of Linux in the enterprise, after Red Hat. Then came an odyssey to rival any epic written by Homer. A few short years after moving its corporate headquarters from Germany to Oakland, California, the company was sold to Novell, which was then later acquired by Attachmate. Three years later, Attachmate was acquired by Micro Focus. Three years after that, SUSE (as an arm of Micro Focus) acquired distributions of OpenStack and the Cloud Foundry platform-as-a-service (PaaS) from Hewlett-Packard Enterprise (HPE).

    That brings us to 2018, when SUSE was spun out of Micro Focus to become an independent company once again, headquartered in Germany once again. A year later Melissa Di Donato, formerly chief operating officer (COO) of SAP, was named CEO of SUSE. A few months after that, SUSE announced it would withdraw its distribution of OpenStack from the market to focus its efforts on emerging cloud-native opportunities stemming from the rise of Kubernetes.

    For SUSE, those opportunities arise from a distribution of Kubernetes deployed on its Linux operating system, which also serves as the foundation for its container-as-a-service (CaaS) environment, along with a version of Cloud Foundry deployed on top of Kubernetes.

    Brent Schroeder, global CTO for SUSE, said his company’s strategy is being driven by an acute need for increased flexibility. IT environments are inherently becoming hybrid as more workloads move to the public cloud, and many organizations will want to leverage a common substrate based on Kubernetes for building and deploying applications. In some instances, Kubernetes will be deployed on top of virtual machines, while in other use cases Kubernetes will be deployed on bare-metal servers. IT organizations will then decide to deploy a CaaS or PaaS depending on their requirements, said Schroeder, noting that regardless of the path chosen, IT modernization initiatives will create a significant opportunity for SUSE.

    “Virtual machines, bare-metal and the cloud will be a huge catalyst,” said Schroeder.

    DevOps, of course, is playing a major role in driving those transitions, which Schroeder said has become a major focus for SUSE as organizations think through how to not just build and deploy applications faster, but also secure and govern those processes. That latest version of SUSE CaaS Platform 4, for example, added support for Cilium open source project for securing network connectivity between containerized application services.

    Of course, SUSE is not the only IT vendor making this journey. Red Hat was the first to deploy a PaaS environment on top of Kubernetes and since then has been on a mission to obliterate the distinction between a CaaS and a PaaS environment. As an arm of IBM, Red Hat has also significantly expanded its market research as IBM builds out a hybrid cloud computing strategy based on the Red Hat OpenShift platform.

    Of course, Red Hat’s acquisition by IBM might create new opportunities for SUSE. After all, more than a few of the IT organizations that opted to embrace Red Hat OpenShift had plenty of opportunities to consider alternatives from IBM. Now that the acquisition has been finalized, some of them may be reconsidering their options.

    It’s too early to say when SUSE might arrive at its ultimate destination. When venture capitalists buy a company such as SUSE the goal is to either take the company public or recoup the investment by selling it to another entity. Whatever the outcome, it’s clear SUSE intends to leave its mark in the brave new world of containerized applications.

    — Mike Vizard