Category: Features

  • CA Technologies Positions Automic at the DevOps Core

    CA Technologies Positions Automic at the DevOps Core

    After acquiring Automic earlier this year, CA Technologies suddenly found itself with an embarrassment of IT automation riches. Now the company is moving forward by further integrating the Automic IT automation platform with the rest of the portfolio of tools and services that it says are required to construct a software factory.

    Ron Gidron, technology evangelist for Automic, says the latest version of Automic increases the number of integrations with the rest of the CA Technologies portfolio to include support for CA Test Data Management, Service Virtualization, Privileged Access Governance, Application Performance Management and Veracode application security software, among others.

    CA Technologies has made it clear it intends to make the release automation software originally developed by Automic the foundation of its overall DevOps strategy. Most of that effort is now focused on integrating the various elements of the CA Technologies portfolio. Longer term, CA Technologies will eventually move to rationalize any duplication in functionality.

    Version 12.1 of Automic also brings forward orchestration tools and self-service capabilities to enable developers to provision resources within guidelines defined by IT. Gidron says that while there will always be a need for IT operations specialists, CA Technologies is making a concerted effort to “shift left” to provide developers with more programmatic control over the IT environment. To facilitate that process, Automic and the rest of CA Technologies have been investing in creating a standard set of external-facing REST APIs, which also will be used to make it easier for products and services created by the company to consume a wide variety of external data and metrics.

    Via acquisitions and internally developed software, CA Technologies is clearly trying to unify application, infrastructure and security management with the context of a single DevOps framework. The company doesn’t plan to force organization to consume that entire stack of software. But it will try to make acquiring as much of its portfolio as financially attractive and frictionless as possible to drive what the company describes as intelligent automation across a modern software factory. Driving that need is the realization that just about every company in every industry is now dependent on some form of custom software to drive one digital process or another.

    The rate at which CA Technologies has been expanding its DevOps portfolio via acquisition is a major contributor to what appears to be a wave of consolidation starting to occur across the DevOps category. Regardless of how advanced any organization might become in terms of building a software factory, major IT vendors realize that it’s only a matter of time before IT organizations start to pressure them to bundle more DevOps-related functionality together. In fact, the line between what’s DevOps today and tomorrow versus what was considered traditional IT management appears to be getting more blurred with each passing day.

    — Mike Vizard

  • With Distelli Technology, Puppet Expands DevOps Portfolio

    With Distelli Technology, Puppet Expands DevOps Portfolio

    At its PuppetConf 2017 conference, Puppet made it clear its ambitions now extend well beyond its namesake IT automation framework for IT infrastructure. On the heels of acquiring Distelli in September, the company announced it is adding several products to its portfolio based on technologies developed by Distelli.

    The new offerings include Puppet Pipelines for Apps, to automate commits; Puppet Pipelines for Containers, to automate the building of Build Docker Images from a source repository and then deploying them on a Kubernetes cluster; and Puppet Container Registry, to host Docker images and unify views of them regardless of whether the repositories are local or remote.

    At the same time, the Blueshift platform developed to automate deployments of container platforms such as Kubernetes, Docker Swam and Mesos is also being enhanced. The Kubernetes module now installs the container cluster in a more secure way that is also highly available. The Docker module adds support for Puppet Code Manager, Docker Swarm mode and Docker Secrets. A Kream tool makes it easier to deploy Kubernetes and Helm, a package manager for Kubernetes, at the same time. Helm also now can manage applications deployed on Kubernetes.

    In addition, the company announced Puppet Discovery, a tool that makes it simpler to identify infrastructure distributed across a hybrid computing environment, and Puppet Tasks, which employs new open-source agentless software dubbed Puppet Bolt to automate entry-level IT tasks. Bolt is capable of running existing scripts written in any framework and executing them on any platform that Puppet supports.

    The company is also adding a Task Manager to Puppet Enterprise that makes it easier to manage ad hoc tasks and executing them across hundreds of Puppet nodes. The latest release of Puppet Enterprise includes tools for inspecting packages deployed on and a tool to simplify configurations of those nodes.

    Puppet has also expanded its alliance with Splunk to tighten integration between the two IT operations’ platforms, and formed new alliances with Baracuda Networks, CloudPassage, Conjur/CyberArk, Cumulus Networks, Electric Cloud, F5, Intelliment Security, Onyx Point, Praecipio Consulting and Sensu. In addition, the Puppet module for the Microsoft Azure cloud has been updated to provide access to more disk storage, expanded networking support and support for Azure tags.

    Tim Zonca, vice president of marketing and business development, says with these products Puppet should no longer be considered a one-product company. It is now committed to developing a full range of DevOps management capabilities. That’s significant, notes Zonca, because today there is too much tension between IT operations teams and developers caused by silos of automation across various DevOps processes. As part of that effort, the company is also committing to start to synchronize the release cycles of the various elements of its portfolio.

    As DevOps continues to mature, the line between how infrastructure, applications and security are managed continues to blur. Many IT organizations prefer to acquire a set of DevOps tools from one vendor because it simplifies purchasing and support. Over time, those vendors combine those tools into an integrated suite that aims to unify the management of infrastructures, applications and security. Most vendors today are a long way from unifying those functions, but a wave of consolidation across the DevOps sector suggests the race is on to provide a unified DevOp stack capable of being employed across multiple platforms.

    The percentage of IT organizations that make extensive use of IT automation frameworks such as Puppet is relatively small. Much of the resistance to IT automation frameworks can be attributed now to simple inertia. But as the size and scope of IT environments exceed the capabilities of an internal IT team to manage manually, it’s now only a matter of time before reliance on IT automation increases.

    Puppet and other vendors also have infused their platforms with machine learning algorithms to expand the scope of what can be automated within an IT environment. In general, Zonca says reliance on those capabilities tends to increase in time once the DevOps teams gains confidence in the algorithms’ abilities to make the right decision. Until such time, Zonca says most IT professionals employ those algorithms to either present them with a series of suggested options based on the most recent events that have occurred. Given the nearly infinite number of possibilities that can be inferred from those events, most DevOps teams already are going to need all the machine learning algorithm help they can get.

    — Mike Vizard

  • DevOps Dozen Nominations Are Now Open

    DevOps Dozen Nominations Are Now Open

    [su_heading]The 3rd annual DevOps Dozen awards are now open for nominations. [/su_heading]

    The DevOps Dozen honors the best of the best in DevOps. The third annual DevOps Dozen awards opened for nominations today. Finalists will be selected based upon how many people nominated them. The top 4 to 6 nominees in each category will then make it to the finalists. The winners will then be voted on by our panel of judges.

    You can nominate up to two entrants in the 12 categories for the DevOps Dozen. It is one nomination per person though. We are also requiring name and email address for all people nominating. While that is not going to thwart ballot stuffing, we hope people take these awards in the spirit they are meant to be.

    As stated earlier, we will take the top 4-6 nominees in each category and designate them finalists. Our panel of judges will then pick the winners from that finalists list. Finalists can submit a presentation on why they deserve the award. These can be sent to judges@devops.com. Finalists will be announced 2nd week of November and winners will be announced in December.

    Who are the judges? This is tough. We couldn’t have anyone who might be eligible for an award. That disqualifies vendors, practitioners and many others. However, I think we have 4 great judges:

    1. Alan Shimel, founder, editor-in-chief, DevOps.com
    2. George Hulme, long time tech journalist and editor at DevOps.com and Security Boulevard
    3. Jayne Groll, CEO and co-founder of the DevOps Institute
    4. Ericka Chickowski, an original editor of DevOps.com and well know tech journalist

    So what are the dozen categories for the DevOps Dozen this year? Well you can get the full story at the site itself. Here they are as well:

    [su_custom_gallery source=”media: 117944,117942,117948,117947,117946,117943,117950,117951,117949,117941,117945,117940″ width=”600″ height=”130″]

    If you have questions after visiting the DevOps Dozen website, write us at DD@devops.com.

    The DevOps market is so crowded with worthy winners that we know some great companies and people won’t make the cut. However, there can be only one (as they say)

    Voting for finalist nominees is open for just 2 weeks, so don’t waste time. Nominate your favorites today. Good luck to everyone vying for the DevOps Dozen.

     

    — Alan Shimel

  • CA Technologies Acquires Runscope for API Monitoring

    CA Technologies Acquires Runscope for API Monitoring

    There’s a pressing need for a variety of monitoring tools more than ever. But given the proliferation of application programming interfaces (APIs) inside the enterprise, demand for API monitoring tools in particular is rapidly expanding. To address that requirement, CA Technologies has acquired Runscope, a provider of an API monitoring service delivered as a software-as-a-service (SaaS) application.

    Ali Siddiqui, general manager for agile operations at CA Technologies, says Runscope will complement CA Blazemeter continuous testing tools the company acquired last year and the CA API Management platform based on the technology CA Technologies gained when it acquired Layer 7 Technologies in 2013.

    While the API Economy has been a phenomenon for external-facing web and mobile applications for years now, Siddiqui notes that IT organizations have only begun to rely on APIs to ingrate internal applications in recent years. The number of private internal APIs that have been published already dwarf the number of external public APIs. Because those internal APIs have now reached a critical mass, Siddiqui says the time is now right for CA Technologies to add an API monitoring service to portfolio of DevOps tools.

    He notes that the rise of microservices inside enterprise IT organizations also will exacerbate existing API monitoring and management challenges. Each microservice generates its own API, which needs to be maintained and monitored. Before too long IT organizations will find themselves trying to unravel the interdependencies of thousands of microservices that all expose an API that can be developed in any number of programming languages.

    These days it’s not uncommon to see dedicated management teams focusing on specific APIs. Rather than treating the API as an afterthought, many IT organizations have come to realize it’s the quality and robustness of the API that ultimately determines the quality of the application experience. In fact, most service level agreements (SLAs) going forward will require access to data being generated by APIs to make sure the terms of any agreement are being met. As such, it’s starting to make sense in some organizations to organize DevOps teams around critical APIs, rather than specific elements of application logic that, in the age of the containers, will soon be more frequently updated.

    There’s no shortage of API monitoring tools these days, and Siggiqui says CA Technologies is committed to making sure the Runscope service remains open in terms of integration with other API management and testing tools. However, eventually there will be incentives provided to organizations that choose to standardize on multiple DevOps tools from CA Technologies.

    Despite the proliferation of monitoring tools, the percentage of application workloads that are instrumented remains relatively small. The reason for this is that the cost of monitoring every enterprise application has often proven prohibitive. The issue that enterprise IT organizations will have to confront as dependencies between microservices increase will be figuring out how to implement instrumentation across all those services in a way that doesn’t wind up breaking the budget.

    — Mike Vizard

  • Oracle on the March Toward Automated CI/CD Services

    Oracle on the March Toward Automated CI/CD Services

    At its OpenWorld 2017 conference today, Oracle charted a course forward that essentially creates a managed DevOps platform spanning a broad number of application types and styles.

    The Oracle Application Development Platform is a subset of the Oracle Cloud Platform optimized for application development. Siddhartha Agarwal, vice president of product management and strategy, says the company is working to automate every aspect of DevOps with an eye toward making it possible for organizations to concentrate all their efforts on developing applications versus managing them.

    The latest step in achieving that goal are updates to the Oracle Application Development Platform, which now incorporates the Oracle Container Native Application Development Platform based on the open-source Kubernetes container orchestration engine, and Oracle Container Engines, a container pipeline management service based on the Wercker software the company acquired earlier this year. The company also announced it is adding support for the Go and Java Enterprise Edition programming languages to existing support for Java Standard Edition, Node.js, PHP Ruby and Python runtimes.

    Other options being added to the Oracle Application Development Platform include Fn.a, an open source serverless computing project based on software the company gained when it acquired Iron.io, as well as an implementation of the Open Service Broker that enables applications developed for the Cloud Foundry platform-as-a-service (PaaS) environment to be deployed on Oracle Cloud. The company is also making available an instance of a BOSH Cloud Provider Interface to automate the deployment of those Cloud Foundry workloads.

    Meanwhile, the Oracle Data Hub Cloud Service now also supports the open-source Cassandra database alongside existing support for MongoDB, Postgres and other databases to be added in the future. However, the core Oracle database remains the primary data engine service. In fact, Oracle Database 18c, announced earlier in the week, employs machine learning algorithms to manage instances of the company’s relational database autonomously with no human intervention required.

    Finally, the company is adding a Blockchain Cloud Service that allows developers to access an implementation of open-source Hyperledger blockchain software, as well as an intelligent chatbot platform that can incorporate in mobile computing applications.

    Agarwal says his company is committed to making available both commercial and open-source platforms available via an Oracle Cloud Platform that provides access to x86, Sparc and graphical processing units (GPUs). Agarwal says the company expects IT organizations to mix and match back-end services as they see fit. But increasingly all those back-end services will be managed under the auspices of a fully managed continuous integration/continuous development (CI/CD) platform.
    Long-term, Agarwal says there may even come a day when application workloads are able to self-describe themselves, which would then enable the company to deploy them automatically on the best-suited back end.

    Naturally, it may be a while before the level of DevOps nirvana gets achieved. But as machine learning algorithms and other forms of artificial intelligence (AI) advance, it’s clear that the weight IT organizations are expected to carry is increasingly shifting more toward building applications than managing the underlying infrastructure on which they run.

    — Mike Vizard

  • Using AI to Automate Incident Management Sparks Debate

    Using AI to Automate Incident Management Sparks Debate

    When it comes to incident response with an integrated DevOps environment so much depends on the ability of an IT team to respond quickly and consistently to a specific set of events. Because of that requirement, many IT organizations have invested in incident management systems that everyone in IT can consult whenever an issue arises. Now PagerDuty, a provider of incident management software, is taking that concept a step further by applying artificial intelligence (AI) to automate as many incident response tasks as an organization deems appropriate.

    As promising as that may sound, however, Resilient Systems, a unit of IBM that is an arch-rival to PagerDuty, contends most organizations today do not have anywhere near the level of incident management maturity to make investing in AI worth their time and effort yet.

    Eric Sigler, head of DevOps for PagerDuty, says the the latest edition of the company’s namesake incident management platform is designed to augment the capabilities of the local IT administrator by providing:

    Alert Grouping: Rules-based automation and machine learning algorithms automatically group related issues together to make it simpler to identify related issues.

    Similar Incidents: IT administrators and support specialist can see previous related issues and surface information around incident severity, impact and remediation steps.

    Response Automation: A Response Plays capability allows teams to design and execute an automated response pattern to recruiting responders and stakeholders by a single click.

    Dynamic Notifications and Event Routing: IT teams can select notification and assignment behavior and automatically route events to different teams based on event payloads.

    Sigler says PagerDuty has also redesigned the company’s user interface, creating an enhanced live incident details page that makes discovering events simpler.

    Those capabilities, says Sigler, will collectively prove to be critical in an emergency because most of the time the specialist associated with a specific IT discipline is usually not immediately available when needed. First responders to any given event need as much information as possible as their fingertips to resolve issues as quickly as possible.

    But Ted Julien, vice president of product management for Resilient Systems, says most organizations simply don’t have incident response processes in place that would benefit from that level of AI. Machine learning algorithms require access to massive amounts of incident response data to learn what to do, but most organizations don’t collect that data, much less learn from it, he says. That doesn’t mean AI doesn’t have potential. But he believes AI is not nearly as far along when it comes to incident response as anyone would like. In fact, he notes, machine learning algorithms and other forms of IT automation could just as easily wind up doing more harm than good.

    There may come a day when incident response in an IT environment is fully automated. But the distance between where most IT organizations are today and the achievement of that goal is still nothing less than considerable.

    — Mike Vizard

  • LogicMonitor Extends Reach to the Cloud

    LogicMonitor Extends Reach to the Cloud

    LogicMonitor has been making available performance monitoring tools as software-as-a-service (SaaS) applications for several years now. At the Microsoft Ignite conference this week, the company announced it is adding a module through which IT organizations can gain similar insights into public cloud computing services.

    Steve Francis, founder and chief evangelist for LogicMonitor, says LM Cloud is designed to provide real-time visibility into the performance of Amazon Web Services (AWS) and Microsoft Azure clouds, including resource performance monitoring, detailed billing analysis and cloud provider availability.

    Many IT organizations don’t realize just how different managing a public cloud is compared to an on-premises IT infrastructure environment, he says. Not only is too easy to let a workload waste resources, spiraling cloud service costs out of control, but also cloud service providers have policies that limit consumption of resources in a specific region.

    Capabilities provided by LM Cloud include automated discovery of an organization’s entire cloud environment and dashboards that can be employed to troubleshoot issues.

    Francis says that as an extension of the core LogicMonitor service, LM Cloud provides a means for IT organizations to employ one monitoring tool across what have become de facto hybrid cloud computing environments. In fact, using multiple clouds will require IT organizations to rely more on monitoring tools based in the cloud. Otherwise, Francis notes, IT organization would have to correlate data across multiple incompatible tools.

    One of the things that holds IT organizations back from using public clouds is simply that they are more familiar with their on-premises environments. Francis says tools such as LM Cloud will make it much simpler for IT administrators to explore a public cloud environment using a set of capabilities that cloud service providers are not inclined to provide.

    Thanks to the rise of public clouds, DevOps arguably has never been more complicated, with applications distributed across multiple public clouds. But it’s very difficult to manage what can’t be seen, and it’s nearly impossible to compare one public cloud with another—much less an on-premises IT environment—without access to a common baseline of metrics. All too often deciding where to deploy a workload is based on either instinct or corporate fiat rather than detailed analysis.

    While many IT organizations expect to reduce costs by moving workloads to the public cloud, the truth is more nuanced. Long-running applications tend to be less expensive to deploy on-premises. Shorter-run applications lend themselves well to public clouds. Yet, many IT organizations are simply not fast enough when it comes to deploying applications on-premises. Internal IT organizations that have embraced DevOps processes, however, are now more agile. That, coupled with software-defined infrastructure, is narrowing the dexterity gulf that exists between on-premises and cloud computing environments.

    All things may not be equal just yet. But the day when an on-premises IT environment is just another cloud that needs to be managed is that not that far off.

    — Mike Vizard

  • Automation: Where Did My Mind Go? Or, No Need to Remember

    Automation: Where Did My Mind Go? Or, No Need to Remember

    Allow me to share a secret: My handwriting is atrocious. If it were not for the keyboard upon which my fingers are tapping and the laptop that is processing the result of my taps, this article would not be happening.

    I’ve always had poor handwriting. But, it’s gotten worse over time. Other than the occasional grocery list, I don’t write things out by hand anymore. It’s just me and the keyboards on my laptop and phone. Luckily, my mind still works—sort of. The stuff I produce has gotten better. Using a computer allows me to edit faster. But, I don’t retrieve words as quickly as I used to. I find myself using online tools continually during a writing session. I could blame age for the impediment. And that may be the case. But still, a part of me says, “Why remember words when I can just grope around a thesaurus to find what I need?” That I can still spell most words correctly is a bit of miracle. But then again, a computer has been correcting my spelling for the last 25 years.

    I’ll share another secret: I don’t remember phone numbers anymore. At one time, I had all the phone numbers associated with all those close to me committed to memory. I knew the phone numbers of my sister, parents, in-laws, friends, steady customers and even my favorite restaurants. I didn’t have to look anything up online. I just carried the numbers around in my head. Now, the only numbers I have memorized are my own and my wife’s. When I want to talk to my sister, I look up her name in the contact list on my cell phone and hit the “call” button. When I am in my bluetooth-enabled car, I just say, “call sister.” The machines do the rest.

    I can still sum a short list of numbers in my head. Also, I can multiply two numbers together as long as neither number is greater than a thousand. If I want to do multiple operations—say, add some numbers up and then divide by another—I need to use a calculator. I haven’t tried to do this sort of arithmetic on paper in a long time. Maybe I can, maybe I can’t. Dunno. It’s just easier to use a calculator.

    I still read a lot. But I find that I spend more time learning things by watching videos on YouTube. In fact, I just got through brushing up on JMeter by watching a playlist of 20 videos on the topic. It took me about two days. I can’t remember the last time I spent two days completely engaged in reading a technology book. It’s embarrassing to say this, given that I am a technology writer.

    But, there is good news here: I can still make change. I learned how to do this before cash registers reported the change to give back upon purchase. You start with the sale amount and work your way through the cash drawer taking out coins and bills until you reach the amount the customer gave you. Funny that I should remember this small piece of mental acrobatics. But, then again, I haven’t used a cash register in a very long time. Making change has yet to be made simple for me.

    However, the computers I use continually throughout my day make things very simple. They allow me to write out my thoughts clearly. They tell me when to pay my bills. They correct my spelling. They make going to the grocery store a breeze. I just take want I want from the shelves, put my credit card into the card reader at the automated checkout line and pay only what is due—no cash required, no change made.

    Automation has made me really smart in a few areas and helpless in most others. I can design an elegant microservice. I am wicked good at working my way through the ins and outs of Amazon Web Services. I can create the automation code that tests my software so that Jenkins can move everything along the deployment path easily and reliably. Yet, I have no idea how to fix my car when the warning lights go off. I don’t know how to repair my cell phone when it stops working. If my voice-responsive TV no longer delivers video on demand, I’m not even sure who to call. The cable company? Netflix? Linksys? Samsung? Denon? When my microwave breaks down, I throw it out.

    My world is simple on the surface and yet terribly complex underneath.

    At one time, the complexities were more apparent. Information was not at our fingertips. Research meant hours in the library poring over the card catalog. Chemistry was part of professional photography. Acting meant memorizing a script that had to be recited over a period of hours, not minutes. Things were more difficult then. But, we sort of figured it out. We had the ability to negotiate the complexities of life. We had no choice. The machines had yet to be invented.

    Now the machines have been invented. Overall, they have been good to us. Smallpox is gone. Lasik is here. Doors open before us automatically, no pushing required. Delivery is overnight, if not same day. Should I want to run my program on a supercomputer, all I need is an AWS account bound to a credit card. Just 1 percent of the population in the United States feeds the rest of the country. We don’t lack for toilet paper.

    Technology is a wonderful thing.

    But, I can’t help but wonder what becomes of a culture when everything is automated to essential simplicity. What happens over generations when we no longer need to know how to write legibly, remember a phone number or make change? How will our minds work when the stuff that used to make our minds work goes away? I don’t know. I am still trying to figure it out. In the meantime, I’ll leave it up to you to decide.

    — Bob Reselman

  • New Relic Tracing Software Pinpoints Source of IT Issues

    New Relic Tracing Software Pinpoints Source of IT Issues

    At a FutureStack 2017 conference this week, New Relic previewed an implementation of distributed tracing software that has the potential to close the war rooms where IT operations assign blame for application failure.

    New Relic CEO Lew Cirne says a Distributed Tracing capability that New Relic previewed this week will enable developers or IT operations teams to pinpoint the precise source of any given performance issue. Rather than wasting hours on root cause analysis, Cirne says DevOps teams will now be armed with dashboard they can navigate to visually inspect what elements of a distributed computing environment are specifically affecting their applications.

    Based on the open-source Open Tracing software being advanced by the Cloud Native Computing Foundation (CNCF), Cirne says New Relic opted to embrace an open initiative that should lead to more actionable intelligence being derived from the data New Relic collects.

    At this juncture, Cirne contends that deploying an application in production that has not been instrumented borders on the criminal. He concedes, however, the preponderance of applications deployed in production environments today are not instrumented largely because the total cost of instrumenting legacy applications has been cost-prohibitive. But as IT monitoring software becomes less expensive to invoke using agents that communicate back to a software-as-a-service (SaaS) application, most new applications being deployed in the cloud are now being instrumented.

    To help further that goal, New Relic this week also announced support for .Net Core 2.0 framework recently made available on Microsoft Azure and added support for six additional Amazon Web Services (AWS) services. New Relic now supports a total of 25 AWS services.

    At the conference Cirne also showed how IT organizations can now invoke New Relic application programming interfaces (APIs) to spin up a dashboard to track specific events associated with, for example, the rollout of a new application.

    Access to the data New Relic surfaces, notes Cirne, in turn helps fuel adoption of DevOps because organizations gain confidence in their ability to more rapidly build and deploy applications. That confidence will only increase as IT organizations avail themselves of artificial intelligence (AI) software in the form of machine learning and, soon, deep learning algorithms to make more reliable decisions based on patterns in their IT environments. New Relic, he adds, is able to fuel those algorithms because the service collects 1.5 billion metrics and events every minute. That said, humans will still be required to manage the overall IT environment.

    Cirne maintains that the best way to collect all that data is to employ agents, noting New Relic is adopting those agents to make them lightweight enough to even deploy on microservices based on containers.

    New Relic naturally is not the only provider of IT monitoring tools investing heavily in advanced algorithms. In the not-too-distant future, it’s probable that algorithms deployed by different vendors will share insights with one another. In the meantime, IT administrators can take some comfort in the fact that it should soon become easier to manage IT at scale.

    — Mike Vizard

  • CloudBees Applies Analytics to DevOps

    CloudBees Applies Analytics to DevOps

    At the heart of many DevOps initiatives is an automation server based on open-source Jenkins software developed by CloudBees. At the recent Jenkins World 2017 conference, CloudBees showed that Jenkins is now becoming the foundational element through which DevOps teams can now manage a continuous integration/continuous deployment (CI/CD) process end to end.

    New additions to the portfolio include CloudBees DevOptics, an analytics application to aggregate data from software development pipelines as it moves through a Jenkins server. CloudBees CTO Kohsuke Kawaguchi says once organizations are armed with those insights they will be able to, for example, identify potential bottlenecks in their software development processes. CloudBees DevOptics creates a single point of reference on the status of any application delivery project, all the way down to individual commits, says Kawaguchi.

    CloudBees also launched CloudBees Jenkins Advisor, a free plug-in for a Jenkins environment that Kawaguchi says provides another watchful eye capable of continuously analyzing a Jenkins environment using algorithms the company developed. Cloudbess Jenkins Advisor comprises a knowledge base and diagnostic tools that can be employed to detect and resolve issues ranging from simple configuration issues to security and other forms of best practices.

    Finally, the company revamped the user interface provided with CloudBees Jenkins Enterprise, an implementation of Jenkins that comes pre-configured with built-in security and integrations with more than 1,400 DevOps tools. It also announced that a few select managed services providers are now building a practice around Cloudbees Jenkins Enterprise.

    CloudBees reports there are now more than 150,000 active installations of Jenkins worldwide that span a user community of more than a million. Those numbers represent a 50 percent growth rate from January of 2015.

    Most organizations employ DevOps processes to accelerate development of software. But along the way it’s not uncommon for many organizations to lose control over those processes as the amount of software being developed begins to overwhelm their management teams. CloudBees clearly sees providing tools to optimize DevOps processes based on Jenkins as its next big opportunity.

    In general, DevOps is much more of a journey than an event. But rather than being a simple article of faith, analytics can be used to show all the participants in a process that progress is in fact being made. Otherwise, resistance to increasing the number of application development projects being undertaken at the same time starts to mount. Whatever the reason for gathering those metrics, however, that old “Things Measured Are Things Done” maxim continues to apply. Those metrics also help IT organizations justify the return on investment in DevOps to senior managers.

    Of course, managing DevOps processes at scale is as much a cultural challenge as it is a technical issue. When many organizations first embrace DevOps there’s a lot of initial enthusiasm. But the further down the DevOps maturity curve an organization gets, the more they encounter various hurdles. Metrics collected and analyzed by the tools provided by CloudBees help organizations determine to what degree those hurdles are related to simple technical glitches versus organizational issues that are almost always a lot harder to resolve.

    — Mike Vizard