devopsy.kinsta.cloud

Author: Jay Chapel

  • Cloud Growth and Other 2020 Trends

    Cloud Growth and Other 2020 Trends

    Growth continued this year as even the COVID pandemic could not slow down the cloud

    The rise of COVID-19 defined 2020 for nearly every industry. Cloud computing is no exception, though growth in the sector continued this year. Gartner estimates that $257.9 billion will be spent on public cloud services in 2020, up 6.3% from 2019. IDC reports that almost half of IT spending is cloud-based, “reaching 60% of all IT infrastructure and 60% to 70% of all software, services and technology spending in 2020.” These projections came in mid-2020, which proves that cloud adoption and spending were not greatly impacted by the pandemic.

    You can make the argument that cloud computing itself is the trend of 2020. Blockchain, quantum computing, machine learning and AI all deservedly earn a lot of headlines in the tech press. But at a more basic level, cloud computing is changing the way we do business. Whether it is the way they store their data, improvements to agility and go-to-market for faster release of new products and services, or how they develop and operate services remotely in today’s “locked-down world,” cloud computing is benefitting all businesses in every sector.

    In short, cloud computing had a strong year in 2020 despite COVID-19 and appears to have a very bright future. Several key trends, perhaps overshadowed by the pandemic, helped define a dynamic year for the sector. These include the following:

    • Continued Dominance of ‘The Big Four’ – All of the big four cloud providers—AWS, Azure, Google Cloud and Alibaba Cloud—reported strong growth and collectively grew 40% in Q320. Together they still account for 63% of the entire cloud sector.
    • Rise of Managed Services – The global cloud managed services market, in particular, is growing rapidly and is expected to reach $116 billion by 2025, growing from $62.4 billion in 2020, according to a study conducted by Markets and Markets.
    • Serverless and Containers – There used to be some talk about serverless and containers replacing the use of traditional virtual machines (VM). But I mostly see customers realizing that VM infrastructure is not going to disappear anytime soon, though container use certainly rose over the last 12 months.
    • Automation – The push toward greater automation continued in 2020. I noticed users accepting greater automation in their infrastructure environments, and there was simply more demand for it across the board. This is great news as one of the major advantages of a DevOps approach is automating away the manual tasks that bog down critical projects.
    • Growth in home use – This may seem an obvious one, but with the COVID-19 pandemic leading companies across the globe to new “work from home” policies, virtual desk infrastructure (VDI) usage exploded.
    • Security – Especially with a remote workforce, cloud security faced new challenges this year. One example of this playing out is in Snowflake’s massive IPO.

    Other trends of note this year included the continued growth of hybrid and multi-cloud and desktop as a service (DaaS). So, while COVID-19 truly defined 2020 for most people, the cloud sector was busy with the trends discussed above. It will certainly be interesting to see how these trends play out in the year ahead. Whatever new trends arise, it seems likely that cloud computing will continue to transform the way we all do business.

  • The Cloud Is Booming — But so Is Cloud Waste

    The Cloud Is Booming — But so Is Cloud Waste

    Fueled by the growth in cloud spend, cloud waste will exceed $17.6 billion in 2020.

    Over 90% of organizations will use public cloud services this year. In fact, public cloud customers will spend more than $50 billion on Infrastructure as a Service (IaaS) from providers such as AWS, Azure and Google. This boom is, of course, due to the broader adoption of public cloud services. But, it is also caused by the expansion of infrastructure within existing accounts. Not surprisingly, the growth in spending often exceeds the growth in business. That’s because a huge portion of what companies are spending on cloud is wasted.

    Cloud Computing Is Expanding

    Before getting to the waste, let’s look a little closer at the growth in the cloud sector. Gartner recently predicted that cloud services spending will grow 17% in 2020 and will reach $266.4 billion. While Software as a Service (SaaS) makes up the largest market segment at $116 billion, the fastest growing portion of cloud spend will continue to be IaaS. This will increase 24% year-over-year and surpass $50 billion in 2020.

    Typically, I find that about two-thirds of the average enterprise public cloud bill is spent on compute, which means about $33.3 billion this year will be spent on compute resources. Unfortunately, this portion of a cloud bill is particularly vulnerable to wasted spend. 

    Cloud Waste Is Also Expanding

    As cloud computing growth continues and cloud users mature, we might hope that this $50 billion is being put to optimal use. While I personally do find that cloud customers are more aware of the potential for wasted spending than they were just a few years ago, this does not seem to be correlated with cost optimized infrastructure from the beginning. The fact is, it’s simply not a default human behavior. 

    I frequently run reports for companies having issues with cloud waste. Invariably, I find wasted spend in these accounts. For example, one healthcare IT provider was found to be wasting up to $5.24 million annually on their cloud spend—an average of more than $1,000 per resource per year.

    Below is where the total waste is coming from.

    Idle Resources: Idle resources are VMs and instances being paid for by the hour, minute or second, that are not actually being used 24/7. Typically, these are non-production resources being used for development, staging, testing and QA. Based on data collected from our users, about 44% of their compute spend is on non-production resources. Most non-production resources are only used during a 40-hour work week, and do not need to run 24/7. That means that for the other 128 hours of the week (76%), the resources sit idle, but are still paid for.

    So, I find the following wasted spend from idle resources: $33.3 billion in compute spend, times 0.44 non-production, times 0.76 of week idle, equals to $11 billion wasted on idle cloud resources in 2020.

    Overprovisioned Resources: Another source of wasted cloud spend is overprovisioned infrastructure—that is, paying for resources are larger in capacity than needed. That means you’re paying for resource capacity you’re rarely (or never) using. About 40% of instances are sized at least one size larger than needed for their workloads. Just by reducing an instance by one size, the cost is reduced by 50%. Downsizing by two sizes saves 75%.

    The data I see in client infrastructure confirms this—and the problem may well be even larger. Infrastructure I see has an average CPU utilization of 4.9%. Of course, this could be skewed by the fact that resources I deal with are more commonly for non-production resources. However, it still paints a picture of gross underutilization, ripe for rightsizing and optimization.

    To take a conservative estimate of 40% of resources oversized by just one size, we see the following: $33 billion dollars in compute spend, times 0.4 oversized, times 0.5 overspend per oversized resource, equals to $6.6 billion wasted on oversized resources in 2020.

    The Extent of Wasted Cloud Spend

    Between idle and overprovisioned resources alone, that’s $17.6 billion in cloud spend that will be completely wasted this year. In fact, it could well be higher. Other sources of waste include orphaned volumes, inefficient containerization, underutilized databases, instances running on legacy resource types, unused reserved instances and more. Some of these result in significant one-off savings (such as deleting unattached volumes and old snapshots) whereas others can deliver regular monthly savings. 

    That’s a minimum of about $5 million wasted per day, every day this year, that could be reallocated toward other areas of the business. 

    It’s time to end wasted cloud spend. Perhaps acknowledging the extent of this problem is a good first step.

    — Jay Chapel

  • The Top Six Cloud Computing Trends of 2019

    The Top Six Cloud Computing Trends of 2019

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

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

    Rise of the Enterprise Cloud Manager

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

    Consolidated Multi-Cloud Views

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

    Multi-Cloud Arrives

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

    More Automation

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

    More Abstraction

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

    Containers Became Mainstream

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

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

    — Jay Chapel

  • Using Automation to Control Cloud Costs

    Using Automation to Control Cloud Costs

    By building in cost control automation from the very beginning, you can keep your cloud costs low while encouraging innovation.

    Infrastructure automation has become vital for every modern sys admin and operations team. Applications and systems are evolving from single-host mainframes to distributed microservices architectures. This automation has gone from basic operating system installation and setup to full-blown multistep deployments of production code from a single developer’s commit. By automating these mundane processes and eliminating the element of human error, production systems are much more stabile than ever before.

    But why stop at automating deployments? There are other elements that need to be automated, too. One of the main ones is cost control.

    Continually rolling out new infrastructure without ever taking a step back to analyze the cost often leads to the panic-driven cloud-bill-based phone calls from your finance department. Instead, applying automation to your cloud costs can help you to save money, so you never have that unpleasant surprise of a major bill.

    Scaling Up Without Ever Spinning Down

    Developers and operations teams often use infrastructure automation early in application development and deployment processes to get servers and databases deployed and functioning. Modern automation tools aren’t just powerful, but they’re also quick to deploy and fit into your current workflow. This is fantastic, but the problem is the automation effort can taper off once the environments are running—too often, users and teams move on to the next project before figuring out a way to keep costs from getting out of control. Then it’s too late, and users simply accept that money needs to be dumped into the deployment pipeline to keep everything on task.

    Easy-to-use automation is the key to spinning these environments up efficiently. It also can be key for keeping the costs of these environments low. Sure, you may need to keep the production systems scaled up for maximum application performance and customer satisfaction, but what about the test lab, sandbox environment, dev systems, UAT servers, QA deployments, staging hosts and other pre-production workloads? Having giant environments with system sizes that match production can be useful for some testing, but leaving it all running can be easily doubling your cloud costs. This is true for each environment you have, including for elements that are only used for a fraction of the time.

    As your infrastructure automation toolkit grows and evolves, there are a few things you should start building into all of your applications and deployments. These include:

    As this list grows, there’s one more thing you need: continuous cost control.

    By building in cost control automation from the very beginning, you can keep your cloud costs low while maintaining the flexibility required to keep up the pace of innovation. Without this, your costs are destined to rise faster than you intended, which will then cause headaches (and endless meetings) in the future. It may not be coming out of your bank account directly, but saving money at an enterprise organization is everyone’s job. Automating this is the key.

    — Jay Chapel

  • Cloud Waste To Hit Over $14 Billion in 2019

    Cloud Waste To Hit Over $14 Billion in 2019

     The good news to start 2019 is that cloud adoption is growing rapidly. Most people realize this, but along with major growth comes some less welcome news. Wasted cloud spend is also up—often dramatically. Chances are, if you’re spending money on cloud, some of that money is being wasted. For some, a lot of that money is being wasted. Here are the numbers.

    Predicted Cloud Spending 2019

    The latest predictions from Gartner estimate that overall IT spending will reach $3.8 trillion this year, a growth of 3.2 percent over IT spending in 2018. Of this spend, public cloud spending is expected to reach $206.2 billion—of which, the fastest growing segment is infrastructure as a service (IaaS), which Gartner says will grow 27.6 percent in 2019 to reach $39.5 billion, up from $31 billion in 2018.

    Now we can subdivide the public cloud spend number further to look just at compute resources—typically two-thirds of cloud spend is on compute, or about $26.3 billion. This segment of spend is especially vulnerable to waste, particularly from idle resources and oversized resources.

    Wasted Cloud Spending from Idle Resources

    Let’s first look at idle resources. This includes resources that are being paid for by the hour or minute, but that are not actually being used. Typically, this kind of waste occurs in non-production environments; that is, those used for development, testing, staging and QA. According to internal data available to my company, ParkMyCloud, about 44 percent of compute spend is on non-production resources.

    Most non-production resources are only used during a 40-hour work week, and do not need to run 24/7. That means that for the other 128 hours of the week (76 percent), the resources sit idle, but are still paid for.

    What does all this add up to?

    $26.3 billion in compute spend x 0.44 non-production x 0.76 of week idle = $8.8 billion wasted on idle cloud resources.

    Wasted Cloud Spending from Oversized Resources

    The other source of wasted cloud spend is oversized infrastructure; that is, paying for resources at a larger capacity than needed.

    RightScale found that 40 percent of instances were sized at least one size larger than needed for their workloads. Just by reducing an instance by one size, the cost is reduced by 50 percent. Downsizing by two sizes saves 75 percent.

    The data we see in our users’ infrastructure confirms this, and in fact we find that it may even be a conservative estimate. Infrastructure managed in our platform has an average CPU utilization of 4.9 percent. Of course, this doesn’t take memory into account, and could be skewed by the fact that resources managed are more commonly used for non-production resources. However, it still paints a picture of gross underutilization, ripe for rightsizing and optimization.

    If we take a conservative estimate of 40 percent of resources oversized by just one size, we find the following:

    $26.3 billion in compute spend x 0.4 oversized x 0.5 overspend per oversized resource = $5.3 billion wasted on oversized resources.

    Total Cloud Spending to be Wasted in 2019

    So, between idle resources and overprovisioning, wasted cloud spend will exceed $14.1 billion in 2019. In fact, this estimation of wasted cloud spend is probably low. This calculation doesn’t even account for waste accumulated through orphaned resources, suboptimal pricing options, misuse of reserved instances and more.

    Fortunately, cloud cost control is becoming top-of-mind as the industry is able to leverage cloud computing growth statistics to calculate the massive scale of this problem. If you are involved in your organization’s cloud  infrastructure, why not make reducing cloud waste one of your 2019 objectives?

    — Jay Chapel

  • Can You Implement DevOps in Large Organizations?

    Can You Implement DevOps in Large Organizations?

    Trying to modernize workflows through DevOps can be a challenge for any company, but there are different challenges, risks and benefits for bigger companies

    It is now more or less standard procedure to implement DevOps principles in startups or smaller companies. But what if you’re trying to utilize DevOps in large organizations? This is a bit more challenging, but let’s take a look at how such enterprises might approach a DevOps transformation through a few of the core tenants of DevOps.

    Rapid Feedback

    There are different types of feedback that come with DevOps: automated feedback about specific code (typically through unit and integration testing software), personal feedback from other team members, consumer feedback from customers using your product and cross-team feedback throughout the organization. Startups and small companies may find it easier to have open lines of communication between individual team members as well as across teams.

    Large organizations will need to make a conscious effort to keep team communication open. On the other hand, they will have more resources available (both money and employees) to field customer and in-house feedback about individual services or larger products. They may also be able to better purchase and implement automated testing and CI/CD tools, which leads to …

    Automation

    One of the biggest tech benefits to a DevOps approach is automating away the manual tasks that bog down critical projects. Large organizations often have the time, money and people to set up automated tools, such as CI/CD pipelines, unit and integration test suites and config management systems. The biggest challenge in the enterprise world is trying to make everyone happy.

    One approach is to standardize on a single tool for each purpose, such as Jenkins or Chef. This can enable your IT staff to specialize in those tools but may make some users unhappy with being forced into a tool they may not prefer. The alternative is to allow each team or business unit to use their own preferred software, but this can turn into a “toolset hell” with a mashup of every combination of applications within your organization. Each approach has its pros and cons, and often comes down to a management decision.

    Eliminating Silos

    Having individual teams that handle their part of the puzzle and nothing else is the biggest hurdle that enterprises face when trying to apply DevOps principles. The combination of “dev” and “ops” (and other disciplines, such as “sec” and “fin”) is naturally split out in a large organization, so recombining them can be a huge undertaking. Then again, that gap is exactly the problem the DevOps approach seeks to solve.

    Some companies solve this by having a separate team that handles the cross-team support and communication. Other companies break down these silos by enabling employees to migrate seamlessly between teams depending on the project or application. The more “DevOpsy” method is to utilize ChatOps and centralized documentation repositories for open communication and collaboration, which can help break down unify the distinct teams.

    Holistic Thinking

    The idea of holistic thinking tends to come easier to larger organizations, as successful enterprises typically have a system in place for “big picture” thinking, either through a management or product team, or through a cross-functional committee. That said, communication of this vision down to the employees, along with communication up to that management team, is crucial for enabling outside-the-box thinking to get past any roadblocks and hurdles that are in the way of creating and deploying the end product. Sometimes, the hardest part is convincing programmers that not everything needs to be solved with code!

    DevOps in Large Organizations: Challenging but Rewarding

    Some folks think that DevOps only applies to startups and small companies, but we’re seeing more and more teams benefit from implementing DevOps in large organizations. The benefits of the above DevOps principles are numerous, but frequently come with a different set of challenges based on your organizational size. Once you are aware of those challenges and have a plan to overcome them, you can start to transform your enterprise to a DevOps shop.

    — Jay Chapel

  • Evaluating a Multi-Cloud Strategy: The Pros and Cons

    Evaluating a Multi-Cloud Strategy: The Pros and Cons

    First off, let’s define multi-cloud. Clearly, we’re talking about using one or more clouds, but clouds come in different flavors. For example, multi-cloud incorporates the idea of hybrid cloud—a mix of public and private clouds. But multi-cloud can also mean two or more public clouds or two or more private clouds.

    So, why is this important? Over the past year or so, I’ve seen a major increase in the amount of companies who use multiple public clouds. In fact, more than 20 percent of ParkMyCloud’s customers use multiple public clouds. With this trend in mind, I think it is time to take a look at the positives of a multi-cloud strategy. But I also want to mention the negatives—because, of course, there’s no “easy button.”

    According to the “RightScale 2018 State of the Cloud Report,” more than 80% percent of enterprises have a multi-cloud strategy:

    What are the Advantages of Multi-Cloud?

    So, why are businesses heading in this direction with their infrastructure? Simple reasons include the following:

    • Risk mitigation—create resilient architectures.
    • Managing vendor lock-in—get price protection.
    • Optimization—place your workloads to optimize for cost and performance.
    • Cloud providers’ unique capabilities—take advantage of offerings in AI, IOT, machine learning and more.

    When I asked our CTO what he sees as the advantages of a multi-cloud strategy, he highlighted risk management. Our own platform was born in the cloud, so we run on AWS. We also have a multi-region architecture with redundancy (let’s call this “multi-cloud light”) and if we went multi-cloud, we would leverage another public cloud for risk mitigation.

    Specifically, he mentioned risk management from the perspective of one vendor having an infrastructure meltdown or attack. AWS had an issue about 15 months ago year when S3 was offline in US-East-1 region for more than five hours, affecting many companies large and small. Software from web apps to smartphones apps were affected (including ours). Certain AWS regions also have been the target of DDoS attacks that have affected service availability.

    Having a backup to another cloud service provider (CSP) or private cloud in these cases could have ensured 100 percent uptime. In the case of Alibaba and other cloud vendors, they may have a much stronger presence in certain geographic regions due to a long-term presence. When any vendor gets a toe-hold in a region, its environment has minimal redundancy and safeguards in place that provide the desired high availability; in this case, another provider in the same region may be safer from an availability perspective.

    What are the Disadvantages of Multi-Cloud?

    Now let’s say you want to go multi-cloud: What does this mean to you? From our own experience integrating with AWS, Azure and Google Cloud, we’ve seen that each cloud has its own set of interfaces and own challenges. It is not a “write once, run everywhere” situation between the vendors, and any cloud or network management utility system must do the work to provide deep integration with each CSP.

    Further, the nuances of configuring and managing each CSP require both broad and deep knowledge, and it is rare to find employees with the essential expertise for multiple clouds, so more staff is needed to manage multi-cloud with confidence that it is being done in a way that is both secure and highly available. With everyone trying to play catch-up with AWS—and with AWS itself evolving at a breakneck pace—it is very difficult for an individual or organization to best utilize one CSP, let alone multiple clouds.

    A common container environment, for example, can help mitigate these issues somewhat by isolating engineers from the nuances of virtual machine management; however, the issues of network, infrastructure, cost optimization, security and availability remain very CSP-specific.

    On paper, there are advantages of having a multi-cloud strategy. In practice—like many things—it’s not as easy as it may seem.

    — Jay Chapel

  • Cloud Computing and the Concept of DevFinOps

    Cloud Computing and the Concept of DevFinOps

    The formation of DevOps brought together two distinct worlds, causing a shift in IT culture that can only be made better (and more cost-effective) by the integration of financial strategy. Enter DevFinOps. I say this only partially in jest. As long as the public cloud remains a utility, everyone should be responsible for controlling the cost of their cloud use, meaning “continuous cost control” should be integrated into the processes of continuous integration and delivery.

    Companies should at least start thinking of financial management as an element in the DevOps process. Time and time again, I see DevOps teams overspend and face major organizational challenges when inevitably the finance team (or the CTO) starts enforcing a stricter budget. Cost control becomes a project, derailing forward development motion by rerouting valuable resources toward implementing spend management processes.

    It doesn’t have to be this way. As financial resources are finite, they should be an integrated element from the very beginning when possible. There are a number of ways that finance can be integrated into DevOps, but one near and dear to my heart is with automated cloud cost control. A mental disconnect between cloud resources and their costs causes strain on budgets and top-down pressure to get spending under control.

    Changing the Mindset: Cloud is a Utility

    The reason for this disconnect is that as development and operations have moved to the cloud, the way we assess costs has changed profoundly in the same way that infrastructure has changed. A move to the cloud is a move to pay-as-you-go compute resources.

    This is due to the change in pricing structure and mindset that happened with the shift from traditional infrastructure to public cloud. As one of my customers put it:

    “It’s been a challenge educating our team on the cloud model. They’re learning that there’s a direct monetary impact for every hour that an idle instance is running. The world of physical servers was all CapEx-driven, requiring big up-front costs, and ending in systems running full-time. Now the model is OpEx, and getting our people to see the benefits of the new cost-per-hour model has been challenging but rewarding.”

    In a world where IT costs already tend to exceed budgets, there’s an added struggle to calculating long-term cost estimates for applications that are developed, built and run on a utility. But wasn’t the public cloud supposed to be more cost-effective? Yes, but only if every team and individual is aware of their usage, accountable for it and empowered with tools that will give them insight and control over what they use. The public cloud needs to be thought of like any other utility.

    Take your monthly electric bill, for example. If everyone in the office left the lights on 24 hours a day and 7 days a week, those costs would add up rather quickly. Meanwhile, you’d be wasting money on all those nights and weekends that your beautifully lit office is completely empty. But that doesn’t happen because in most cases, people understand that lights cost money, so people have automated this process in the office by using sensors either based on motion (usage) or time-based schedules. Now apply that same thinking to the cloud and it’s easy to see why cost-effectiveness goes down the drain when individuals and teams aren’t aware or accountable for the resources they’re using.

    Financial decisions regarding IT infrastructure fall into the category of IT asset management (ITAM), an area that merges the financial, contractual and inventory components of an IT project to support lifecycle management and strategic decision-making. That brings us back to DevFinOps: an expansion of ITAM, fixing financial cost and value of IT assets directly into IT infrastructure, updating calculations in real time and simplifying the budgeting process.

    Why This is Important Now That You’re on Cloud

    DevFinOps proposes that a more effective way to estimate costs is by breaking them down into smaller estimates over time as parts of the work get completed, integrating financial planning directly into IT and cloud development operations. To do this, the DevOps team needs visibility into how and when resources are being used and an understanding on opportunities for saving.

    As I have noted, the public cloud is a utility—you pay for what you use. And with that in mind, the easiest way to waste money is by leaving instances or VMs running 24 hours a day and 7 days a week. The easiest way to save money is just as simple: turn them off when they’re idle.

    — Jay Chapel

  • How the Cloud is Reshaping IT

    How the Cloud is Reshaping IT

    The cloud has been rapidly reshaping and redefining IT as we know it, from the language we use to describe it to the management models and infrastructure itself. Providers such as Amazon Web Services, Google Cloud Platform and Microsoft Azure have transformed cloud computing, giving businesses access to IT resources anytime, anywhere. At the same time, this rapid migration off-premises has been reshaping the needs and roles in the IT department.

    The Cloud and IT

    The following are four ways that the cloud is redefining IT roles and operations:

    Sysadmin vs. DevOps

    When you compare sysadmin vs. DevOps, you’ll find that they’re similar roles, but also distinct. A system administrator, or sysadmin, is the person responsible for configuring, operating and maintaining computer systems, servers in particular. This jack-of-all-trades IT role handles everything from installations and upgrades to security, troubleshooting, technical support and more.

    And then we have the evolution of DevOps, which could very well be the biggest game-changer to the IT process. Under the DevOps umbrella, a team of software developers, IT operations and product management people must combine strengths to effectively streamline and stabilize operations for rolling out new apps and updating code to support and improve the whole business.

    With the cloud taking over and without the need for physical, on-prem servers, a large portion of the sysadmin role has become lost to automation. As this change was occurring, sysadmins remained effective as their role shifted toward the support of developers, combining efforts and thus giving birth to the term DevOps. So, can you truly compare sysadmin vs. DevOps? Well, the roles are similar in the sense that sysadmins can do a lot of what DevOps guys do, but not the other way around, making DevOps the newer, bigger jack of all trades.

    IT Operations Management vs. Cloud Operations Management

    IT Operations Management is responsible for the efficiency and performance of IT processes, which can include anything from administrative processes to hardware and software support, and for both internal and external clients. IT management sets the standard policies and procedures for how service and support is carried out and how issues are resolved.

    Thanks to the cloud, IT management has also given way to automation and outsourcing. Cloud operational processes are now a more efficient way of using resources, providing services and meeting compliance requirements. In the same way IT operations and projects (ITOP) manages IT processes, cloud operations management is doing so in a cloud environment with resource capacity planning and analytics that provide vital intelligence into how to control resources and run them cost-effectively.

    IT Service Management vs. Cloud Service Management

    Traditional IT service management (ITSM) dealt with strategizing in the design, delivery, management and innovation of the way an organization is using IT. This involved developing, implementing, and monitoring IT governance and management using frameworks such as COBIT, Microsoft Operations Framework, Six Sigma and ITIL, for example.

    As the cloud became a better option for operational management, companies have turned to it to transform their business model via service providers including Amazon Web Services, Google Cloud Platform and Microsoft Azure to outsource IT for more efficient, scalable services.

    Since cloud computing resources are hosted as off-site VMs and managed externally, ITSM has grown more complex, introducing cloud service management (CSM) as an extension of ITSM, pushing in three core areas: automated service provisioning, DevOps and asset management. And as ITSM shifts toward CSM, the concerns lie in the adoption strategy and the approach for designing, deploying and running of cloud services.

    Finance and Operations vs. DevFinOps

    In a world where IT projects are known to exceed budgets and coming up with cost estimates is no easy feat, how can businesses break down a reasonable overall estimate for projects in which applications are developed, built and run on a utility? The answer is to make estimates little by little as parts of the work get completed, integrating financial planning directly into IT development operations. In other words: DevFinOps.

    IT asset management (ITAM) merges the financial, contractual and inventory components of an IT project to support lifecycle management and strategic decision-making. The strategy involves both software and hardware inventory and the decision-making process for purchases and redistribution. DevFinOps expands and builds upon ITAM by fixing financial cost and value of IT assets directly into IT infrastructure, updating calculations in real time and simplifying the budgeting process.

    What This Means For You

    Cellphones, self-driving cars, DevOps … cloud computing is yet another evolution in technology—albeit a huge one—and IT is simply going through a metamorphosis. The best way of looking it at is that cloud is not killing IT, it’s redefining IT. Enterprises are following suit as they make the shift and change or update traditional IT roles. As IT evolves, the cloud is paving the way for opportunities for those who adapt and evolve their roles with it.

    — Jay Chapel