Tag: digital transformation

  • Coronavirus Economic Shutdown: Analysts Hit the Brakes on Global IT Spending Estimates

    Coronavirus Economic Shutdown: Analysts Hit the Brakes on Global IT Spending Estimates

    By most accounts, 2020 was set to be a pretty good year for U.S. gross domestic product and enterprise IT budgets. That was before the novel coronavirus, and the subsequent economic shutdown that is designed to blunt its spread and avoid overwhelming the nation’s health system. Analysts are now slashing their economic growth rates and enterprise technology spending estimates.

    Previously, research firm IDC estimated that real GDP in the U.S. would reach 2.4%, but downshifted that to a “pessimistic scenario” of 1.4%. While IT spending dropped from an expected 5.1% year over year growth to a pessimistic scenario of 1.3%. The base scenario for GDP growth is now 2.0% and for IT spending 4.3%.

    “The pessimistic scenario is not a worst-case scenario,” said Stephen Minton, vice president in IDC’s Customer Insights & Analysis group. “Things are moving so quickly that we need to constantly recalibrate our assumptions and expectations, but the pessimistic scenario reflects an IT market in which weaker economic growth translates into weaker business and consumer spending across all technologies over the next few quarters. Things could get worse, but hopefully not.”

    Earlier this month, Forrester analyst Andrew Bartels wrote in this post that the U.S. and global technology market spend will slow to 2% this year.

    “That assumes the U.S. and other major economies have declined in the first half of 2020 but manage to recover in the second half. There is also a 50% probability that U.S. and global tech markets will decline by 2% or more in 2020 if a full-fledged recession hits,” Bartels wrote.

    Not all areas in technology will be impacted equally. Forrester expects there will increased demand for cloud infrastructure services, specialized software, communications equipment and telecom services for remote work and education.

    However, Forrester expects computer and communications equipment to potentially decline 5% to 10%, while technology consulting and systems integration services spending could be flat to down 5%, should companies really belt-tighten.

    “Software spending growth will slow to the 2% to 4% range in the best case and will post no growth in the worst case of a recession. Tech outsourcing and telecom services will hold up better, though contract revisions could cause spending to go down, as well,” stated Bartels.

    S&P Global Ratings also predicts slowing IT spend. According to its update, Global IT Spending Set To Slide As Coronavirus Hits Hardware Sales, S&P Global economists cut their global GDP growth rate by more than half to 1% to 1.5% from 2.8%—in just two weeks.

    “We believe the spread of the coronavirus will hurt enterprise and consumer IT spending across the globe with particularly bleak ramifications for the hardware and semiconductor segments. However, we expect some of the deferred spending to return gradually in the latter half of this year through heavy government stimulus in the U.S., China, and elsewhere,” wrote S&P Global Rating Analyst Andrew Chang.

    S&P Global Ratings anticipates IT spending to decline 3% year over year, compared their prior estimate of 2% to 3% growth. S&P Global Ratings expects some of the biggest hits to hardware, with smartphone revenue falling to negative 9% from up to 2% growth, and PCs to negative 9% from a previous range of negative 3% to a positive 4% growth.

    While enterprise technology budgets are being slashed, the need for business-technology isn’t going away. In fact, it’s accelerating as more knowledge workers shift to working from home, more remote collaboration and keeping legacy systems running and moving forward with digital transformation efforts.

    — George V. Hulme

  • Laying the Foundation for a Successful Digital Future

    Laying the Foundation for a Successful Digital Future

    Digital infrastructure is under mounting pressure from a variety of powerful technology trends. Whether that pressure stems from DevOps, the cloud, AI, mobile or big data, almost every organization is looking to the future with an eye on modernizing their mission-critical IT systems.

    Unfortunately, the challenge of future-proofing IT infrastructure is often exacerbated by the widespread reliance on legacy technology. Add to that the growing data connectivity complexities across the entire technology landscape, and you face the difficult task of balancing your networking strategy with your other—sometimes competing—technology priorities.

    In particular, legacy networks often lack the performance, control and flexibility today’s digital business models rely on. And they’re increasingly vulnerable to security risks. If that wasn’t enough to give you pause about your network, older technologies often consume a disproportionate amount of your IT budget that you could otherwise invest in modernizing your underlying IT infrastructure.

    That fundamental disconnect leaves little room for maneuvering when current thinking shows that agility is so closely linked to success—and where having a purpose-built network infrastructure is key to successful digital transformation. Just as a new house needs a solid foundation, your digital future requires the right digital infrastructure to meet your long-term challenges. 

    The Issues of Network Modernization Raise Some Big Questions

    Think for a moment about the key issues you face. Can you afford to be at the mercy of an outdated or inflexible network? Can you ignore the enormous potential of transformative technologies? Are you prepared to risk falling behind more agile competitors? Or, alternatively, can digital transformation give you a significant competitive advantage?

    Whatever your priorities are, the bottom line is digital transformation almost always requires advanced on-demand connectivity that can be deployed quickly and cost-effectively. To meet this need, many businesses are turning to software-defined wide area networks (SD-WANs) and network functions virtualization (NFV) to build agile networks designed to solve your data connectivity needs today and well into the future.

    Meeting the Challenge 1: SD-WANs

    SD-WANs are purpose-built solutions that deliver agile, secure and scalable connectivity by leveraging intelligent software. One of their main advantages is the centralized network orchestration, control and zero-touch provisioning that provides high-performance networking within a borderless infrastructure across highly distributed enterprises. 

    This high level of flexibility facilitates digital transformation, because SD-WANs can leverage all types of connectivity options (such as MPLS, broadband, 4G and 5G) while automating network functions. One big advantage is the ability to simplify the connection of people, devices and locations to the cloud, providing seamless access to the virtual functions and business services they need.

    SD-WANs also help abstract the complexity of the underlying network to create a virtual layer that simplifies a wide range of network operations. The major benefit here is that there’s no need to manage multiple layers of hardware (such as routers, firewalls and load balancers) that have historically complicated network management.

    This is particularly important for geographically distributed organizations that want to simplify branch or remote office networks, given that SD-WANs can connect new offices or branch locations to the corporate network in hours, rather than weeks or months. This provides a proven way to quickly deploy new apps and services while controlling, or even reducing, networking costs.

    Meeting the Challenge 2: NFV

    Combining SD-WANs with NFV can deliver even greater business benefits since NFV utilizes key network functions on an “as-a-service” basis, improving both network agility and efficiency. It achieves this by replacing legacy network hardware with software that runs in the cloud.

    This approach offers a cost-effective way to modernize diverse network functions ranging from intrusion detection to traffic prioritization and network performance optimization. In this way, you can easily reconfigure your networks to meet the data connectivity needs that lie at the heart of digital transformation. Best of all, you can do so without introducing unnecessary risk, complexity or cost.

    Modernizing Your Network for Digital Transformation

    Modernizing your network infrastructure can deliver the appropriate scale, security and performance needed for modern business. In particular, SD-WANs can help ensure your digital transformation goes hand-in-hand with an equivalent modernization of your network infrastructure. As a result, you can simplify your operations, improve security, respond more quickly to business demands and deliver a much more compelling customer experience.

    — Michael Cabra

  • How to Build Creativity into Distributed DevOps Teams

    How to Build Creativity into Distributed DevOps Teams

    Today, more people than ever work remotely or are part of distributed teams. The DevOps world is no different. While working remotely has definite advantages, it also poses distinct challenges for teams trying to build strong internal cultures, coordinate product launches and hit shipping deadlines. It’s not enough to just slot in a communications app anymore. Teams need tools and processes that foment creativity and the frictionless sharing of ideas.

    Leaders know that the greatest ideas often come at the most unpredictable moments. With distributed teams, the risk of losing those great ideas in the shuffle dramatically increases. Given these realities, how can DevOps teams replicate the spontaneity and creative energy of an in-person brainstorming session when employees are located in different places around the world? 

    Get Personal

    It’s human nature to withdraw when feeling uncomfortable in a new group of people. Be it a party or work function, people will choose not to participate in conversation if it risks embarrassment among strangers. The same thing can happen due to the seemingly cliquish nature of certain distributed teams. If a new employee doesn’t know anyone personally, it is imperative to bring them into the fold and establish comfort as soon as possible. Then they’ll feel more confident sharing ideas.

    For extroverted people, this rarely poses a problem. However, introverted team members may not take so easily to unstructured casual conversation, and will need to be drawn in. This is where a bit of planning can go a long way.

    Leadership should start every team meeting with an icebreaker question that draws people out of their shells and reveals new aspects of their personalities. There is no need to get too intimate. These questions can be playful and funny. For example, asking people about their favorite hobby, restaurant or vacation destination is an easy way to kick start a conversation. Questions about long-term personal or professional goals—perhaps completing a marathon or learning to code in new languages—can also spark meaningful conversations or potential mentorships. The goal is not necessarily to force friendships (though that is not discouraged) but to make everyone comfortable interacting while knowing the company is a safe space for the expression of new thoughts, ideas and strategies. 

    Use Both Live and Asynchronous Video

    Modern DevOps relies on a high degree of automated processes. With modern pipelines that deploy code live several times a day, it becomes incredibly important to have a tight communication loop across the DevOps, Site Reliability Engineers (SREs) and development teams. In the unfortunate event that there are production issues, it becomes crucial to engage in meaningful conversations with team members and stakeholders while working on a terminal or actively fixing issues.

    Instant audio-visual collaboration plays a key role in creatively solving these types of problems. Text tools are clunky and slow. Plus, anyone late to the Slack channel then has to wade through piles of messages that further delay action. The ability to leverage synchronous and asynchronous workflows becomes indispensable when teams need the agility to communicate effectively. 

    With live video, details and nuances that are difficult to relay via text can be instantly shared without the worry of misinterpretation. Plus, talking is faster than typing, and allows for an easier back-and-forth when problems need to be solved quickly. Voice and video encourage free-flowing conversation. When a DevOps team spends less time thinking about how to communicate, they can better concentrate on how to solve a problem. 

    Because distributed DevOps teams often operate across different time zones, live video may not be practical if someone is asleep or enjoying life outside of normal working hours. This is where recorded video has special advantages. For example, recorded videos express context clearly and more effectively than sending an email when dealing with “show and tell” walk-throughs, bug reproductions, release audits, commentary on visual assets or user feedback. A lightweight video recorder can also aid in memorializing and documenting fast-changing deployment models, pipelines, scripts and configurations. These videos excel at capturing a thought in an instant, bringing energy and clarity to a conversation.

    Make Flexibility Fundamental

    With a DevOps team scattered across the world, standups and regular team meetings often take place during odd hours. Someone might be joining during morning coffee while another hops on after putting their kid to bed. Now think about how creative you feel in the morning versus the evening. If a scheduled check-in constantly fell during a time you felt mentally and physically drained, it would be hard to bring your A-game. Have you ever successfully brainstormed first thing in the morning, when hungry or right before bed? 

    Regularly switching the times of these check-ins is key. This way, leadership can show DevOps that it understands some hours of the day are just not as conducive to creativity and brainstorming as others. By accommodating employees through switching the call times weekly or monthly, leadership gives each team member the opportunity to shine. Plus, this approach gives people a fresh perspective to share unique ideas.

    Random, on-the-fly check-ins can also be a boon to remote developers. Hopping on the phone or a video call when hitting a snag can help quicken the solution process. After all, two (or more) heads are better than one. This can also relieve some of the pressure associated with sharing a new idea in front of the whole team during a formal meeting. Perhaps just bouncing a nebulous thought off of a trusted coworker is enough to bring that idea from half-baked to reality. This is certainly faster than a Slack message or email chain.

    The ability to encourage creativity with remote teams is only growing in importance as more and more people work offsite. Building a strong, open culture where team members know they can express themselves freely without fear of negative repercussions is paramount to successfully navigating these changing workplace environments. Hence, we strongly urge that modern DevOps concepts, new tools, strong releases and tight team coordination must jointly evolve to help establish a strong culture and bolster the importance of nurturing creativity in-house.

    — Badri Rajasekar

  • How to Compare and Contrast APIs to Improve DevOps Processes

    How to Compare and Contrast APIs to Improve DevOps Processes

    The cloud is driving digital transformation, from web applications to mobile applications, from partner integrations to API monetization. Even custom applications are moving into the cloud. If you draw a line through all these trends, APIs would be at the heart of it all.

    We know we need to eat our vegetables to keep our heart healthy, but sometimes it is easier to order takeout after a long day of work. Healthy API hygiene works the same way. In a perfect world, developers would register their API specifications and blueprints in an API catalog, and they would keep them up-to-date as the application changes. But this is a tedious manual process, and sometimes after a long day of work it is easier said than done.

    An API catalog is critical for improving the DevOps process through quality assurance and testing. Furthermore, the production environment for APIs can be subject to even harsher and more hostile access and usage patterns compared to the Dev and Test environments, which tend to be more self-contained. The good news is that by maintaining an API catalog, DevOps can gain more visibility into the contrast between these environments to identify gaps that should be closed. The end result is an improved DevOps process that drives the production of better products and services.

    There are a number of approaches to creating an API catalog, from manually logging APIs into Wikis, spreadsheets and vendor solutions, to more automated discovery tools. An API catalog should include meta information, such as the creator, the date it was last modified, which application it belongs to and so forth. At a deeper level, an API catalog should also include the parameters such as the data type, the bounds for the data type, the transport mechanism, the authentication and authorization mechanism, and a brief description about the data carried within the parameter.

    Compare and Contrast APIs from Dev to Test and Test to Production

    During the application testing phase, which is subject to quality assurance, regressions, performance and interaction cases, an API catalog should be updated and compared against its development state. The contrast between the development API catalog and those generated from the test environment can help identify:

    • An API listed in the Dev catalog, but not in the Test catalog, which would indicate that QA has not tested the API or its payload; therefore, the QA process could be improved.
    • An API listed in the Test catalog, but not the Dev catalog, which would indicate that the Dev catalog was incomplete; therefore, you cannot assume it is a “golden” image. This also suggests an area for improvement in the DevOps process because the developer has not maintained an up-to-date API catalog. Automated tools can help even more here since they generate an API catalog where there is none.

    There is a third scenario, where an API isn’t recorded in the Dev catalog, and it doesn’t show up in the Test catalog, but may later show up in the production traffic. This is considered an unpublished or “out of spec” API.

    Likewise, when moving from test to production environments, the API catalog should be updated to mirror real-world application access. The contrast between the Production API catalog and the Test API catalog can help identify:

     

    • An API listed in the Test catalog, but not the Production catalog, which could identify an API that is not being used. This would indicate that QA testing did not align with the real-world use of the application and suggest that development cycles could be prioritized elsewhere.

     

    • An API listed in the Production catalog, but not in the Test catalog, which would indicate the API catalog did not capture the most up-to-date specification. This is one example of a Shadow API, an API that was intended to be part of the application, but has not gone through the required processes related to testing and application security.

     

     

    Additionally, identifying an API in the Production catalog, but not in the Test catalog can be useful in identifying threat actors searching for vulnerabilities to exploit an unpublished API.

    Comparing and contrasting dev, test and production environments can help identify opportunities for improvement. However, manually creating and maintaining an API catalog is often neglected because of its tedious nature. DevOps needs automated tools to help discover APIs, generate blueprints and store them into the catalog. It is too much of a burden for developers to manually document APIs, but a continuously updated API catalog is the most important key to derive success using the compare and contrast methodology.

    — Ravi Balupari

  • EP 6: How to Lead a DevOps Transformation

    EP 6: How to Lead a DevOps Transformation

    Is C-level support required to have a successful digital transformation? In the sixth episode of DevOps Unbound streaming broadcast on TechStrong TV and devopsy.kinsta.cloud’s sister site Digital Anarchist, Mitchell Ashley of ASG and Alan Shimel are joined by Eveline Oehrlich of the DevOps Institute, Louise McCarthy of Bain & Company and Mark Settle, author of “Truth from the Valley, A Practical Primer on IT Management for the Next Decade,” to discuss DevOps and digital transformation at the C level.

    The video is immediately below, followed by the transcript of the conversation. Enjoy!

    Transcript

    Alan Shimel: Hi, everyone. Welcome to another edition of DevOps Unbound. DevOps Unbound is brought to us by our friends at Tricentis. So, thanks for their sponsorship. But, you know, they sponsor but we pick the topics. We pick the guests. And we have a lot of fun here talking about relevant topics around DevOps. Today’s topic centers around DevOps and digital transformation at the C level. And let me introduce you to our panel. First of all, we have Louise McCarthy. And, Louise, I’m gonna ask you to kinda introduce yourself with a little background for our audience.

    Louise McCarthy: Yes. Thank you, Alan, and hi, everybody. I’m Louise McCarthy. My background more recently is doing large, complex digital transformations mainly for the financial services. And mainly through the eyes of the business rather than the technology, although I have held roles as CFO and I’ve held roles COO and CIO as well.

    Shimel: Excellent. Next, we have Mark Settle. Mark, welcome.

    Mark Settle: Thank you. So I am a seven-time CIO and I most recently left Okta about a year ago and have been advising startup companies since then. I’m based here in Silicon Valley. And probably my encounters with DevOps are focused on supporting DevOps communities in terms of infrastructure requirements if they have, and also introducing the concept in actually business application support within a conventional kind of an IT group.

    Shimel: Thank you and welcome. And then Eveline Oehrlich, Eveline, please.

    Eveline Oehrlich: Yes, hello there. Eveline Oehrlich. I’m the chief research director at the DevOps Institute. Before that I spent 13 years as vice president at Forrester Research studying a variety of topics, and DevOps of course was one of them, working with many enterprises and C levels and others to explore the challenges and the fun of DevOps.

    Shimel: Very good. I’ve never heard anyone talk about the fun of DevOps but I’m looking forward to discussing that. And then, last but not least, of course is my cohost here on DevOps Unbound, Mitch Ashley of Accelerated Strategies Group. Mitchell? 

    Mitch Ashley: Good to be here. I’m Mitch Ashley, CEO of Accelerated Strategies. We focus on digital transformation, DevOps, cloud native, and cybersecurity. I’m also a former CIO. Not nearly as experienced as Mark is, but have led transformations and also implementation of DevOps as well as been a CTO, CEO of product companies. So I’ve lived on both sides of DevOps. 

    Shimel: Great. What a great panel we have today. I’m really looking forward to it. So we’re talking about DevOps at the C level. As I mentioned to you all before we started today’s show, our friend Gary Gruver wrote a book, “Leading the Transformation.” He wrote several books. One of ’em was “Leading the Transformation.” And Gary is a big proponent of what he calls the top-down approach to DevOps and digital transformation. And in Gary’s view – and I’m not saying right or wrong. In Gary’s view, you cannot have a successful digital transformation or DevOps transformation without sponsorship, support, air cover, if you will, from the C level, including the CIO or CTO, depending on the organization. CEO, et cetera. 

    Let’s start there. Is C-level support absolutely positively required to have a successful transformation? Anybody?

    [Crosstalk] 

    McCarthy: Do you mind if I go first, Alan?

    Shimel: Sure.

    McCarthy: I would actually say, my recent – I’ve done about five or six transformations and tried all sorts of ways to actually get them going. There’s always blockers on the way and it’s usually the blockers that slows the whole problem down. And the blockers either come from the ground up, from the employees or the people that run the processes today, or you get the blocker in terms of the C-level-suite people who tend to wanna own things, and it’s a big of ego that actually blocks things going that way.

    And the most recent transformation was successfully owned by the C-suite. So they drove it. They owned it. They were the stakeholders. But most of the engagement actually came from the employees, from the process owners. So we ran the whole transformation from the process owners actually owning and identifying where the transformation needs to take place. And that really made it hugely successful because you didn’t have people fearing for their own jobs. ‘Cause with digital transformation it always means or often means that there’s gonna be heads that unfortunately are lost in various areas of the – in the transformation. But mainly doing transactional-type work. But if it’s the transactional people that are running the processes, they highlight their pain points and then we work with them to actually change those pain points into something positive. 

    So, I would arguably say both from top-down, but also if you don’t do it with engagement of the people running the processes today, it won’t work.

    Settle: I’ll chime in. I think I have the same answer but I’m gonna state it in a slightly different way. I think the way the question gets asked, it sounds as if the CTO or the CIO’s gonna come down from the mountain with the DevOps tablets and then ____ employees and team members _____.  “I’ve been converted and now it’s your turn. We’re all gonna go do this together.” [Laughs]. Most of the time that doesn’t work. For one person to come in – well, take an example where a startup company here that’s been reasonably successful. Maybe they get up to a product team of, I don’t know, a generic team of 500 people or something like that. They hire a new chief product officer or a chief technology officer who says, “We’re gonna do this completely different. I have a vision.” Et cetera. Well, they’re gonna do it but that’s gonna be a slog to kinda get there.

    What I’ve seen be more successful is almost like – what’s the right term in a battle when you send the beach guy out? The beach master that’s moving people around. So you really want almost like a fifth column movement down at the grassroots level of people who are genuinely interested in exploring these ____ ways of doing business. And then I think what the C-level person adds are the methodological resources to drive scale. And so many DevOps initiatives fail because they sound interesting; they sound contemporary; people think, “Other people do it so it must be beneficial.” 

    But then after like 18 months, everybody scratches their head; “Where are the benefits? We thought this was gonna be transformational.” It’s not. The technical people are having fun. They’ve developed this new terminology, et cetera. And if you scratch below the surface, well, guess what? You’re doing DevOps in like five different ways because the little C-groups have all picked the tool they wanted and decided that they’re gonna have a daily scrum twice a week or whatever. They’ve got their own little process set up. And then people say, “Where’s the benefit? This was supposed to be transformational.” So at some point in the early stage of the journey, it’s needed to drive scale and ____ of endorsement. But I think it can almost backfire if it’s launched from the brain of Mark Settle that, “Yea, and verily, I’m gonna lead you to the promised land.”

    Shimel: Sort of a Charlton Heston beard I’m picturing on you there, Mark. Eveline, how about you?

    Oehrlich: Yeah. I actually would say it should be outcome-driven DevOps. It doesn’t really matter if it is from the C level, from the individual, from the inside-out, from the outside-in, from the top to the bottom, the bottom to the top, from the middle to the whatever. It needs to be outcome-driven. What I mean by that is: Only metrics will make us change. Just like I drive through my town here – this is a little analogy. I drive through my town. They installed one of those things where they measure the speed and if you go over 50 kmh you get a ticket. Well, my husband, even though that thing has been there for two years, my husband manages to get a ticket every three months. But what he does is he intercepts the mail and then he doesn’t tell me that he has gotten that ticket. 

    So now what I have done to stop those 15-euro tickets every two months – because if you add it up you can go for a nice dinner – I am going to go through the mail before he gets home so I see how many tickets he gets. And he gets little lines. And that metric is on the refrigerator – I should’ve brought a picture of it – and that has actually reduced how he is driving through town.

    And so if you go back to the DevOps teams and the digital transformation and you ask the individuals at C level or VP level or practitioner level, “How successful have you been or what’s the challenges around?” It’s easy to point to somebody. But data, if you have data which shows where you are and it maps to where you want to go and you share that amongst all these different individuals, there is no argument. It’s not the guy with the long beard, as Mark would come in, or it is not somebody at the lowest level who could argue with that. We could huddle around it and figure out: What do we need to do?

    So I think it’s not really about who – of course we do need some individuals who pays for it. We need some kind of a fund and budget and all of that. But I really think it’s outcome-driven rather than organizational-level-driven.

    Settle: Can I just chime in on that one, too? So I would agree 100%. And outside of maybe the CTO or CPO or IT organization, bringing evidence of improved sophistication, operational metrics around the process to almost any other C-level executive – they don’t really care. The CFO – if you show that, I don’t know, the year throughput, the story whatever – in one of my books, it’s like reading a Bible to the cat. The cat will look at you and feign interest. But it has absolutely no idea what you’re talking about. And that’s sorta what you get outside the technical functions, everybody – “But that’s your job. You figure out what needs to get done.”

    And, again to your point, it’s more of a business outcome. Like, are we actually getting customer request enhancements through in greater quantity or are we able to respond to a competitor’s new feature set faster than we did at their last result cycle? Or whatever those things are. That’s what people wanna talk about.

    McCarthy: Yeah. And – [Crosstalk]

    At the end of the day, the outcomes is aligned to the strategy of the organization. So you’ve gotta be doing a transformation for a reason. And there’s usually three or four reasons why you’re doing a transformation. It’s around the customer journey so the customer needs to improve the satisfaction. You’ve gotta costs. You’re trying to grow your revenue. And then the one that’s usually an outliner that’s become ____ at the moment is carbon emissions. So for every one of these paint points that I mentioned earlier, there should be a business case that shows measurement of success against each of those four measures. And that’s what you – bottom-up, you report at top level to the C suite to say, “This is why we’re doing it. This is the measure of success of what we’re doing it.” And even breaking some of the pain points and the business cases down to quick wins. So ones that you can be getting on with relatively quickly that free up cash that then can pay for the more strategy-type things.

    Shimel: Yeah. So I think this brings up – all three of you have touched on it. And it brings up what I think is really sort of an entry question, which is – it’s the genesis of digital transformation. Why and how does any organization decide to go through the potential pain, heartache, and change of digitally transforming, of adopting DevOps or agile? Louise, I’m pretty sure we spoke about this – was it at an Emmet Keeffe Insight IGNITE in Iceland that you were at?

    McCarthy: Yes.

    Shimel: I was there with you and I remember talking to you about this. You know, Eveline, in your day, someone like Mark might go to a Forrester conference and come back and say, “Wow, Eveline Oehrlich from Forrester just presented this presentation study on the benefits of digital transformation and DevOps adoption. And, god darn it, she described us to the T. We really need to do that here.” And maybe that worked then, right, seven years ago, ten years ago? I don’t know if that’s the genesis of digital transformation today. I think a lotta times digital transformation today does start with technical champions lower down whispering in Mark’s ear that, “If we were doing DevOps or agile or whatever, we could really make better customer experiences. We can give customers what they want. We could do it better, cheaper, faster.”

    [Crosstalk] 

    Ashley: I think we have a chasm that we have to cross, and that is: DevOps can be sort of a vanity project for the IT or the development organization, right? It can be a purely self-interest: “We’re doing what we do better.” Which is always a good thing, but at the end of the day does it move the needle for the business? You have to be able to translate that into what Eveline said was the why. Louise also said the why. But what is the real benefit we’re trying to get out of it? And when you have a purpose for doing it, now you have metrics you can put around that. Is it revenue? Is it competitiveness? Is it responsiveness to the market? Is it changing customer expectations and behaviors? What is it? That’s truly – then the development or the IT organization knows that they’re making a difference. 

    Otherwise how do you know whether you should be working on more releases per hour, per day, or you should be working on just fixing the backlog? How do you know? You don’t other than just sort of your own internal metrics. And I guess it kinda reminds me of that phrase of the – what was it? Belly-button gazing, right? You’re sorta looking at yourself and what you think’s important. But I think that connection – you have to cross that chasm, whether the business is coming to you or you have an idea of what we can do better and how it might help, and then let’s then make that connection. 

    Shimel: That’s my point. Someone like Mark – Mark, what does it take to push you over the edge and say, “God darn it, we gotta do this; we’re committed”?

    Settle: Yeah. Let me _____. One thing’s funny about this whole line of conversation is of course, in the world that I live in out here, there’s no question about doing it. It’s like: Who is the most sophisticated – [Crosstalk] or more sophisticated? So, in the war for talent, that same 500-person organization I referenced – they might look at each other and say, “Who do we know at Google or Facebook, in their engineering group? We know we should be doing this better. We’ve kind of played around with the concept. We’ve hired some lower-level people who’ve said, “You guys are just behind the times here. So we need some real leadership inserted.” So that’s the other side of the coin. In parts of the country where maybe it’s like an accepted practice, there’s almost a competition to be the most sophisticated or get the most benefit. 

    But the spark plug, the question you’ve asked – I’m thinking about some second-tier markets – and I really hate to call out specific locales, but what the hell? As a consultant, you can talk like that. So if you’re in a place like St. Louis and you’re in an organization that just has done business the same way forever, all the IT management, all the technical management has come up through the ranks kinda doing things the old-fashioned way, quarterly releases, and they don’t keep the same kinda metrics that you would in a DevOps environment, to blow a place like that up – there’d have to be some kind of competitive imperative.

    Or, you know, the white knight does show up from time to time, right? So if you think about it, sometimes when the new CPO or the CTO comes in – and I’ve experienced this in my own career – there’ll be a cause or a initiative that I promoted during my entire tenure – the new guy or gal comes in and they get it done like in a year. And I think, “What the heck happened here?” 

    There was one company where I was trying to get them off of Microsoft Dynamics, get ’em onto Salesforce. There was another company, I was trying to get production systems up into the cloud. And we did every kinda seed activity you can imagine. The cloud one, we sent people up to Redmond for some AWS instruction. We did some prototyping, et cetera. New CIO comes in and says, “We’re going to the cloud,” 12 months later like half the production systems are in the cloud. Like, “How did that happen?”

    So sometimes change at the top – which gets us back to where this kinda started – maybe that is the seminal spark plug. And especially if that person’s been brought in because there’s a broader C-level recognition that, “We’re not keeping up with the times; we need to make some kinda change.” So you have that broader support. When people start to whine, they know that the whining’s not gonna get them out of the change that’s about to come. 

    But for just self-generated change for people that’ve – then I go back to, you know, Mitch, where you said: then you can always have a vanity project which you can point to as evolutionary. Like: “We’ve got a small group. They’re putting their toe in the water. They’re doing some interesting things. So we are keeping up with the times.” But then you just don’t get the scale benefits at the end of the day. 

    Oehrlich: I think there was – just to add to something to what Mark said, as the ecosystem of our organizations has expanded, we have to think of – well, the travel industry doesn’t exist at this point in time, but think of maybe manufacturing, right? In the area where I am in, I’m in Stuttgart, we have large car manufacturers, and they’re connected to Bosch and others, and the ecosystem is rather broad. And these folks at all levels are collaborating, connecting. Not as much now with where we are, but they have exchanged thoughts and ideas, they go to events, and they learn from each other. At all the different levels. And so I think there is that – as Mark said, to some extent there is this – not really a competition, but the exchange of ideas, which has brought additional adoption of DevOps at all levels, right? 

    So if I am the C level of Bosch and I go to a genomic car-driving event and I meet the CF C level of the CF industry down in Friedrichshafen and they are telling me about, “Wow, we really improved our reliability scores and we have really punched up our cadence around the product X, Y, and Z,” I go back and I say to my team, “Hey, I just met this team over there. They’re doing something fantastic. Can we start?” It’s that spark, which to some extent happens to cross over in this ecosystem as we start to be much more connected and dependent. I think that’s one point.

    The other one is: if you look at the individuals who are today in IT, they don’t look like this anymore. I’m a Cobol, Pascal, HP 3000, JCL person. That’s when I grew up. That’s my heritage in operations. The guys and the girls today in these teams – they are completely different. They want Python. They wanna do sexy things. They wanna do fun things. They wanna show what they can do. And they’re looking for inspirations from their leaders as well, and they want to see that they can make a difference. I think that is also, from a cultural perspective, I think – of course it’s important but I think that’s also a driving force. And that’s not just the individual contributors but also the consultants and the C levels who are – I call them the flip-flop-wearing, chino-looking guys who go to the conferences, which we’re seeing them; I’m like, “Oh, I think I’m overdressed with my suit.” That’s the people who actually make DevOps happen, and they wanna have fun. They wanna do things. They don’t wanna do JCL and things like I did in a boring ops group dying of boredom.

    Ashley: I think you’re talking about a couple of things, Eveline. One is the attracting talent, right? People have more selection, economic conditions aside, more selectivity about the kind of work that they wanna do, the companies that they wanna work for. There’s also just: how do you learn to develop software? If DevOps is what you’re coming into, a way of developing software, you’re looking for organizations and you expect that approach. So I think your point is right on. It’s also the audience of the people who are gonna be the adopters or the embracers or the champions of doing this. So that all makes a big difference. The command from on high, as Mark was talking about, the tablets – there’s an expression for that: “This too shall pass,” right? That’s the reaction, usually, of those kinds of initiatives. You have to have an option. And I think you spoke to that really well.

    Shimel: Look, if you’re a Silicon Valley cool kid or you work at one of these organizations where flip-flops and jeans are the rule and you do the hair thing and all of that – I don’t do that so well anymore – that’s cool. But, Louise, you’ve done transformations at what we may think of as large, stodgy financial organizations, right? And they’re not Silicon Valley-based and they’re not a jeans and flip-flop culture. So how does it play there?

    McCarthy: Actually, funny you were talking about flip-flops, high fives and cappuccino. I worked in government actually for a little while, the tax authority, and that was a time when the government was setting up its ____ global digital authority. And everybody in the government, all of a sudden they change from suits to wearing flip-flops and high fives and cappuccinos, and it was like a world away from the starchy government.

    But, anyway, moving on to the financial services, yeah, the financial services – I’ve been lucky enough actually to do transformation in legacy financial services, and the big boys like the HSBCs, for example, which is complex. It’s like turning the Titanic around. And I’ve often written articles around: it’s like moving deck chairs around. The reason why I say that is because automation is the way forward. We talk about automation in many guises. Automation takes out people. It takes out transactional-type activities. But the legacy banks just struggle to do it. So I say it’s like moving the deck chairs around the Titanic because of the legacy system they’ve got. Transformation – they talk about it. They move things around. But nothing real and concrete actually comes out of their transformation, which is really sad. Because there’s great opportunities there in the legacy banks. 

    And on the other side of the fence, I’m working currently with a contender bank, a digital bank, which is new. It’s new. It’s fresh. It’s green. It’s almost as green as your screen there, Alan. It’s a green ____. And it’s great to be able to take the whole end-to-end customer journey and see it digitalized. And how quickly you can change and transform. And developing and changing technology with that suite, the same thing end to end, it’s just awesome to be able to see how quickly it happens. Whereas the legacy banks are still thinking about planning it, talking about it, cogitating over it, when the small guys are out with a new technology. 

    And one of the things that I’m often transforming whenever I do my transformation – it’s not transformation, it’s Christmas; it’s for life in my mindset. So it’s around continuously thinking about the innovation and it’s about encouraging these legacy banks to have innovation departments that are constantly thinking about the new technology that’s out there to take them ahead of their competitors. So like these digital banks, if the legacy banks are doing this, they’re actually seeing a way of making it happen quickly. And I think that’s the problem that we’re constantly battling: the bureaucratic slowness of moving Titanic.

    Shimel: So clearly the kind of organization you’re at determines, or will have a huge impact on this. Guys, we’re coming on the back side of our time limit here. I wanted to talk a little bit about: okay, we’ve made the decision. We are moving forward with our transformation. We are adopting DevOps and agile and these new ways. How at the sea level do we – short of coming down from the mountain with the two tablets in God’s own writing, how do we translate that to the troops? How do we effect the organization? That this isn’t some passing fancy of the CIO and it’s not gonna pass in the next quarter. This is really the way we’re doing it. How do you make that change down the ranks, get people adopting as champions and being successful with it? Mark?

    Settle: You know, it’s not unlike an initiative around security. When you talk about cultural change within an organization, I think leaders don’t always appreciate what a huge impact they have on the people that they lead. You know, people take cues from the way you use your time, the things that you show interest in, things you follow up on. Your time management sends tons of signals to the organization. And some of the operational metrics that I poo-pooed before as being of no interest whatsoever to people outside the technical areas are a great way to kind of keep score. You go back to what Eveline said: If there’s a sense we’re making progress, some of those ____ celebrations can be really important.

    I’ll just leave you with a thought. I worked with a guys several years ago who used to say, “What interests my boss fascinates me.” As long as there’s some sustained interest – and to go back to, Alan, what you said before: I can just come back from the Forrester meeting all jazzed up, and then two months later I go to a Gartner meeting and now I’m on a whole different tangent. Now I think it’s automation; we gotta get RP robots in here. That’s gonna blow the business up. And then people in the trenches are like, “This too shall pass. He’ll go to another meeting. But I’m not gonna get my –

    [Crosstalk] 

    Shimel: Come back with some other toy, yeah. 

    [Crosstalk] 

    Settle: “He’s so crazy.”

    Shimel: Yeah. I used to feel it was whatever was the last book I read. That was the next greatest thing to me, right? ‘Cause I just read that book. But, Eveline, fundamentally – and this is something the DevOps Institute is deeply ingrained in – it also becomes a question of: how do we upskill our workforce? How do we prepare – do we just go out and hire new people? That’s hard. Do we upskill our existing people for this? At the C level, how do we effect that?

    Oehrlich: Yeah. So, from our research at the DevOps Institute, we know that most organizations are actually preferring to leverage their existing resources to train them and to upskill them. Now, upskilling of course has its challenges because you don’t just upskill around processes of learning a new way of doing continuous delivery, or it’s not just about upskilling new technical skills. It’s also about human skills. That’s I think the challenge. A lot of organizations are biting themselves into that – or pushing themselves, or actually locking themselves into the corner. They think, “Yeah, let’s give them AWS training. Let’s let them understand what the latest DevOps platform is and give them some language skills around whatever the latest hotshot technology programming language is.” 

    But it’s also soft skills or human skills which are necessary. People need to understand how to work empathetic, how to collaborate, how to connect, how to cross functional borders, how to understand when a security individual tells me something. So having skills around these different categories is important. And there is investment needed. We see that, unfortunately, 7% of survey participants we had last year said that they have no idea what their upskilling programs are. We know 37% of these individuals – a very large sample size of almost 1,200 – said that, “We don’t have a program in upskilling.” And the rest of them either are planning one or have one. So that’s really unfortunately poor and not enough. So, anybody listening in, get ready to upskill your people. Start thinking about training. Start thinking about exchanging knowledge and allowing them to learn. Give time.

    I, for myself – and we’re doing that at the DevOps Institute a little more, and our CEO does that a little as well. I call Friday my learning day. And it doesn’t matter what happens. Unless the CEO wants me there, Friday is my learning day. I learn French. I learn about design thinking. And I’m learning about metrics. That’s it. And we all have to do that. It’s very important. 

    Shimel: Agreed. Louise, you go in as a consultant. In terms of the skill level of the workforce, do you try to upskill them? Do you supplement it with fresh talent? It’s hard getting fresh talent in. Mark, you know in the Valley they cut each other’s throats for this. How do you do that?

    McCarthy: It’s an interesting thing because you’re trying to fly an aircraft while changing the engine in some cases. And the same people _____ transform are the same people that need to drive the aircraft. And also if you call in too much fresh talent, then you would probably put the noise in the joint of the people that are supposed to be helping you run the process anyway. 

    So the way I’ve done it is I’ve gone in and we’ve identified some highly skilled people that know the processes really well and then supplement them with some more transactional process mappers and people like that. So that those people that run the processes can also see things like: how do they do the process mapping and how do they identify the paint points? How do they convert it into business cases? How do they use it and then convert it into technology?

    So on that journey, the people that are running their processes are also being upskilled at the same time into continuous improvement and transformation. But I’d say that there’s also – it’s not about upskilling necessarily on all sorts of things. Because as technology’s changing, there’s less the need for upskilling because a lot of technology is self-serve-type technology now. A lot of the RPA touring now. People can do it like they learn Excel, like they learn Word and things like that. so the upskilling like it used to be, about spending months and months programming and that type of thing – there’s less the need for that. It’s more about the upskilling in terms of continuous improvement. And it’s a cultural change, I think somebody mentioned earlier. So it’s going in and using the resources that’re there, upskilling those people, and slightly supplementing them and doing hands-on job training.

    Shimel: Excellent. Mark, Mitchell, I’m gonna give you each a chance to kinda close it out here, and then I think we’re about outta time. Mark, final thoughts?

    Settle: Let me just make a final comment along the lines of this last topic. I’ve gone through many of these reskilling things, and seeding that group with new talent I think is essential. I mean, if somebody came into me and said, “We’re gonna go to DevOps and you can have consultant money; the consultants will come in; they’ll be here 90 days, 120 days” – this is an acquired skill. It’s almost an art form at its finest. And the devil is in the details. And the day the consultants leave, everybody’s left to their own devices, and it’d be just like saying, “Let’s just shut down the data center and move everything in the data center up on AWS, and we’ll get some AWS consulting in here, and then they’ll leave after 90 days, and you guys run all the production systems up there in that whole new environment after 90 days of familiarization.” I don’t think too many companies would take that kind of a risk.

    So I think people get so carried away with thinking that reskilling can be effective, that people will come to embrace it. And, again, I hate to say this, but in my personal experience, if you reskill a population of people, 20% will be superstars, 20% won’t get it, and 60% will be good enough. But if one of the 60% left, you’d recruit somebody in with a higher skill level than the person that left. So they make forward progress. I’m not denigrating people’s commitment to new things. But you’ve gotta bring in that fresh talent that’s been there and done that. They know what it’s supposed to look like, right? And they can look around a corner and they can see the big fuzzy hole in the road that we’re all gonna fall into here in the next two months. 

    So that’s my thing.

    Shimel: Mitchell, you wanna bring it home?

    Ashley: Yeah. I’d like to just wrap with the human element, but maybe from a little different perspective. You know, people react to change in different ways. Your advocates – great, they’re all about it. Your resisters – love them ’cause you can actually work on that. You can help. You can help bring them along. It’s that passive unspoken middle ground, the folks that’re waiting to see: “Before I commit myself – I’m not gonna put myself, my job, my career at risk for this next thing. I don’t know if I can do it.” And the idea of bringing people in – I think one of the main purposes is to show the team, A, it can be done, and, B, they can learn it. So it isn’t: bring the consultants in for 30 days, hand over what they did, and now everybody goes, “Now what do I do?” Right? 

    So I think if you can de-risk, address the fear of what this means, that: “You’re gonna be able to do it and we’re gonna stick with you to help you get there, help everybody get there. And if there’s some folks that choose not to go along the journey, that’s okay too. But we’re all in this together.” I think you’ve gotta address the human element from a very personal: how does each person feel about this and whether they’re signed on to do it? And that’s gonna guide your success. That’s been my experience. 

    Shimel: Absolutely. Well, guys, we’re about outta time. Mark, Eveline, Louise, and of course Mitchell, thanks for joining us on this episode of DevOps Unbound. Many thanks to our friends at Tricentis for their sponsorship. Until next time, this is Alan Shimel for DevOps Unbound. Be well, be safe, and we’ll see you soon. Bye-bye.

  • Digital Transformation Efforts Hindered by Lack of Upskilling

    Digital Transformation Efforts Hindered by Lack of Upskilling

    There’s no digital transformation without a staff transformation. The people skills that helped bring successful enterprises to where they are today won’t be the skills that will make them successful tomorrow. Fortunately, Leadership Suite readers are well aware at how important it is for the success of their organizations to close the gaps between the skills their employees have today and the skills they need to carry the enterprise forward.

    According to the Upskilling 2020: Enterprise DevOps Skills Report from the DevOps Institute, based on 1,300 respondents, more than 50% of enterprises find challenges with all aspects associated with managing the people, processes and technologies that make DevOps possible.

    The report found 58% of enterprises have a tough time actually finding those with the right DevOps skills and 48% said it’s difficult to retain skilled DevOps professionals.

    With that in mind, it’s no surprise the report found DevOps salaries on the rise. According to the Robert Half Technology 2020 Salary Guide, salaries for experienced DevOps engineers can reach beyond $179,250. Survey respondents said that the skillsets necessary for DevOps practitioners skillsets should be multifaceted, including process skills and knowledge (69% of respondents), automation skills (67%) and interpersonal skills (61%). The 2019 survey found automation skills to be the top skill, followed by process skills and knowledge.

    The survey contends that successful DevOps professionals will have expertise that consists of both breadth and depth of knowledge, along with tangible and intangible skills that help them both dive into the details of a situation while also understanding the big picture. The 2020 Upskilling survey cited three highly sought horizontal skill categories: automation, functional knowledge and technical skills.

    A second grouping of skills—process and framework skills—is a vertical skillset which focuses on flow and understanding of different practices and methods such as scrum, agile development and value stream mapping. Another vertical skill category focuses on human skills such as collaboration and interpersonal skills.

    “People, process and technology have always been the trifecta needed to execute DevOps successfully,” stated Shawn Ahmed, senior vice president and general manager of the Software Delivery Automation business at CloudBees. “As we strive to enhance the culture needed to predictably deliver better software faster at CloudBees, it’s been important for us to identify which skills are considered ‘must-haves,’ which are ‘nice-to-haves’ and which are ‘not important’ across teams, roles and regions.”

    “As the report underscores, upskilling is now more important than ever to enable meaningful collaboration between all teams to truly deliver software at an elite level,” said Ahmed.

    The survey also found that adoption for Agile is at 81%, DevOps 75% and ITIL is at 25%. Organizations that employ SRE rose to 15% this year from 10% in 2018.

    — George V. Hulme

  • A Deep Dive Into AI for IT Operations

    A Deep Dive Into AI for IT Operations

    Traditional IT administration and management techniques are reforming. By employing artificial intelligence (AI), IT operations are taking an interesting turn in the field of advancements. The term “AIOps” stands for Artificial Intelligence for the IT Operations. AIOps uses AI techniques and algorithms to monitor the data as well as reduce the blackout times. The dominance of digital businesses is introducing technological changes in their operations to streamline them and eliminate the overhead of traditional operational management. 

    Digital companies are generating abundant and information-rich data whose analysis and monitoring do not demand delays. From data collection to storage and data processing to analysis, all operations need to be frictionless to deal with them in an efficient manner. In the last couple of years, the AIOps market has exploded which is ultimately achieving the goal of reducing delays in problem-solving and identification.

    Paving the Road to AIOps

    The story starts with the need of AIOps and digital transformations. Cloud adoption and the shift toward other digital technologies are revamping the IT industry. It also includes the adoption of innovative solutions in the IT operations to make them frictionless. The technologies that are widely used in IT operations vary from AI to machine learning, big data to Internet of Things (IoT) and Application Programming Interfaces (APIs) for various use-cases to edge computing. All these innovations are penetrating into IT operations making them more smooth and sleek.

     AIOps platforms enhance and automate IT operations, using the following different approaches:

    • Using machine learning algorithms and neural networks for better analysis of gathered data. The data is gathered using IoT devices and tools connected with the source and sending data to the cloud for storage. 
    • The system automatically interprets if something is wrong in the operations. The errors are detected and solved immediately without introducing delays in the operations that are dependent on each other to complete.
    • Reducing human power by automating the processes that include the effort of individuals. 

    Components of AIOps

    The two basic components of AIOps that accelerate innovation in IT operations are machine learning and big data. Instead of spending human effort and time into cleaning, processing and analysis of the raw data collected from different platforms, IT operations are able to do all the tasks by employing machine learning algorithms and techniques to judge the nature of data and deduce necessary information from it.

    Factors Boosting the Emergence of AIOps

    AI is a promising technology that holds the confidence of building applications that can help the IT community. AI provides options for reliability, scalability and generic tools that can be deployed to promote the IT operations and boost them without utilizing human power.

    Factors boosting digital transformation in the IT industry:

    • Complex IT Infrastructure: Its operations face many challenges regarding data management and infrastructure. Manual IT operations are becoming harder to handle such as data collection, processing, cloud management, database efficiency, third-party management tools and SaaS integrations. Complexity management is a task that needs proper attention and the environment to deal in a better way. 
    • Handling Abundant Data: IoT technology is penetrating rapidly at an industrial level. IoT devices produce an abundant amount of data. Handling this much data is not the job of individuals. Therefore, by using AI-based algorithms the data is interpreted and analyzed. The performance is monitored using efficient algorithms. 
    • Increased Computing Power: The networking infrastructure has become robust. Therefore the IT industry is in dire need to enhance the processing speed also. By deploying IT solutions that harness AI and machine learning technologies, the computational power of the system can be increased. 

    Enterprises Using AIOps

    The IT companies that are complex and large to which human power is not enough for overall operations are using AIOps to automate the tasks.

    The adoption of technology has a huge impact on the success of IT companies:

    • Development Teams: Companies that have a DevOps model and struggle to manage the roles between the organization are using AI and other innovative technologies to smoothen their processes. With this, developers increase the responsiveness, agility and clarity in the IT operations.
    • Cloud Computing: Cloud computing has a big future. The companies store their huge data in the cloud and all the operations related to cloud data management need to streamline, as it has its own challenges. Therefore, to make the processes flow without errors and monitor the access, there needs to be automation.
    • Digital Transformation: Companies around the world are all active in adopting technology solutions. Whether it is a fintech, travel, healthcare or e-commerce company, all businesses are automating their processing by first digitizing them and providing the user’s facility of utilizing applications based on newly emerged technologies. Information handling can be done by making operations handled by robotics and blockchain technology. AIOps removes friction from the IT operations.

    — James Efron

  • 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

  • Survey Finds IT Modernization Efforts Reap Significant Benefits

    Survey Finds IT Modernization Efforts Reap Significant Benefits

    When it comes to the state of IT, few questions weigh more substantially on the minds of CIOs and other business-technology leaders than the degree of success they see in their digital transformation efforts, and foundational to that their efforts to modernize their technology stack.

    In a survey recently released by market research firm IDG, and commissioned by services provider Insight, those enterprises that have managed to reach their initial modernization goals report (25% in this survey) success they say that they can quantify in such areas as cost efficiency, availability and customer experience. Sixty-seven percent of respondents said that their modernization efforts are essential to their digital transformations.

    There were 26% of respondents who said they are at the beginning of their modernization work. Even still, many reporting significant business benefits including improved quality of service (65%), better customer experience/satisfaction (52%), cost savings (50%), uptime (44%) and the creation of revenue-generating products and services (42%).

    The “The State of IT Modernization 2020” survey questioned 200 IT executives at organizations 29,000 employees on average and within a range of industries. The survey examined the maturity of efforts to mature IT operating environments, cloud strategies, applications and processes.

    Of those respondents who stated that they reached their initial modernization goals, 19% report having made moderate progress on those goals and 31% said their development has been significant. Twenty-five percent said they’ve hit their initial goals and are optimizing where possible.

    Despite 59% of respondents reporting moving forward with their modernization efforts, 41% said they have delayed or abandoned those efforts. According to the survey, they did so due to competing priorities (46%), poor roadmap (45%), concerns about data privacy and security (39%), lack of skills (38%), didn’t or couldn’t budget appropriately (30%), and unexpected challenges (30%).

    Not surprisingly, the vast majority of organizations cited cloud optimization as a central part of their modernization efforts and ranked nearly ubiquitous. These included application modification (93%), increasing public cloud workloads (92%) and private clouds (91%), and moving to multi-cloud (87%) or a hybrid-cloud model (89%).

    Further, and what highlights the difficulty some organizations have when finding the optimal home for all of their workloads, 84% said they transferred specific workloads from a public cloud to a non-cloud location. These transitions may have been driven, in part, by the 69% who found their cloud costs to be 62% higher than they expected. The underlying causes of those cost overruns range from “data egress charges for shared persistent data, unplanned cloud adoption, and mergers and acquisitions to failure to take advantage of vendor volume discounts, over-subscription and failure to optimize workloads to extract maximum value from cloud platforms,” Insight said in a statement.

    Finally, the survey found that 95% of respondents are outsourcing at least some facet of their operating environments to a managed services provider. Eighty-four percent said they are outsourcing cloud management.

    Going forward, the most commonly cited priorities include better managing workloads based on their use (39%), improved design to size services to need (38%) and the implementation of additional policies that will restrict the type and size of cloud services made available internally to their organization.

    — George V. Hulme

  • Why Enterprise Survival Depends on a Context Driven Approach to Data

    Why Enterprise Survival Depends on a Context Driven Approach to Data

    Enterprises are sitting on an enormous amount of data that could be fueling their automation journey. Much of the information needed to run a business is existing data. However, much of an organization’s data is inaccessible and unsearchable. This so-called “dark data” is hidden away in paper forms, spreadsheets, emails and literally billions of PDF documents. This dark data is locked away and mostly unusable by the systems and AI required to power the autonomous business of the future. Enterprises are trying to achieve 21st-century outcomes while being shackled to 20th-century data practices. 

    I recently read a report from NewVantage Partners on a survey they did concerning how big data and AI were driving digital transformation. While 92% of the survey respondents said they were increasing investment in big data and AI, there were some interesting findings that suggest organizations are not realizing the ROI they had hoped. For instance:

    • Only 31% have a data-driven organization.
    • Only 28% stated they have a data culture.
    • 53% are not treating data as a business asset.
    • 38% have not realized any measurable outcome from their investment.

    Now, there’s a whole list of reasons and hurdles that are preventing organizations from realizing better value and outcomes from their efforts to become data-driven. But, could the underlying approach to becoming data-driven be flawed? Could organizations be struggling because they continue to apply a legacy mindset and approach to data acquisition and storage? Could these challenges be a contributing factor in 70% of digital transformation projects failing?

    Just take a look at the growing number of stories, market reports and surveys on digital transformation and you’ll see a graveyard of failed projects, lack of success and high turnover rates. The current approach to digital transformation is not working. 

    In our push to become data-driven, we capture data and attempt to transform it into computable bits and then stuff the data into rigid structures. This legacy approach to capturing and representing information outside the human brain results in a proliferation of single-use data that doesn’t scale with the business. We always lose some of the meaning, relationships and context. Despite all the advancements in technology, we’re still trying to model the information based on how we’ve historically stored data. We’re still producing flat data.  

    In the autonomous enterprise of the future, and the digital workers that will run them will need rich, contextual data. The true power and value of digital transformation will only be unlocked by the adoption of a semantic data-driven approach. The future of work will be built on digital workers powered by machine learning, artificial intelligence and knowledge graphs. It’s not enough for an organization to be data-driven anymore–they need to become contextually-driven. We need to start capturing the meaning to achieve a better understanding of the data.

    “I liked the idea that a piece of information is really defined only by what it’s related to, and how it’s related. There really is little else to meaning,” said Sir Tim Berners-Lee, the inventor of the World Wide Web.

    Context is all about the meaning. Context is more than just a piece of data. Context is the background in which an event, task or process takes place. It is the deep, multi-dimensional understanding of data and the relationships between the entities. Understanding the context can lead to accelerated insight through AI and machine learning. To be competitive, enterprises need more than data; they need context to enhance productivity and efficiency. But our current approaches to capturing and storing data have historically failed to capture this valuable context. As the amount of data grows exponentially, organizations will realize semantic data is key to survival.

    — Kevin Harbauer