devopsy.kinsta.cloud

Category: Cloud Management

  • Survey Surfaces Multi-Cloud Computing and Cost Challenges

    Survey Surfaces Multi-Cloud Computing and Cost Challenges

    A survey of 360 CIOs and IT leaders in the U.S. and the United Kingdom found that, as the number of cloud platforms an organization employs expands, the number of tools they are required to deploy and master does, too.

    The survey, published this week by Virtana, a provider of a platform for managing cloud migrations, found nearly two-thirds of respondents (63%) reported their organization relied on at least five separate tools for migration, cloud cost optimization, integrated performance monitoring, application performance management and cloud infrastructure monitoring. A full 83% are expending some level of manual effort to consolidate data from all of these tools, or are simply using them in isolation from one another. Only 17% said data integration is fully automated.

    Nearly three-quarters (73%) also noted that siloed efforts limit their ability to realize the full potential of the cloud.

    It appears that multi-cloud computing only makes managing IT more challenging. Not to mention the increased pressure a multi-cloud approach puts on DevOps and developers that already juggle an overwhelming number of tools for development, DevSecOps and more. And, of course, the risk of cloud misconfiguration grows alongside the number of cloud platforms an organization uses.

    According to the Virtana survey, a total of 82% of respondents have a multi-cloud strategy, with more than three-quarters (78%) deploying workloads in more than three public clouds. A full 59% now run more than half of their workloads on public clouds. More than half (51%) also plan to increase the number of public cloud instances they support this year, with more than a third (34%) planning on using five or more cloud platforms.

    More challenging still, more than three quarters (76%) are in the early stages of implementing serverless computing frameworks. Overall, more than half (52%) will continue to maintain a hybrid environment as part of their core IT strategy. A full 96% of respondents see value in workload portability, but only 71% are in the early stages of achieving that goal. Top benefits anticipated include maximized cost savings (58%), reduced cloud service provider risk (46%) and increased business agility (43%). However, nearly three-quarters (75%) have either no or few cloud governance capabilities (34%) or have stitched together disparate tools to achieve that goal (41%).

    Jonathan Cyr, vice president of product management for Virtana, said that as the global economy becomes more challenging, it’s only a matter of time before sensitivity to cloud costs start to rise. Each time the overall IT environment expands, increases in complexity drive the total cost of IT higher.

    It’s not clear to what degree that sensitivity to cloud cost might drive more IT organizations to centralize the management of IT environments. In theory, a single control plane could be employed to manage multiple cloud computing environments, but today most clouds are still managed in isolation from one another.

    IT teams also find themselves inadvertently locked into a cloud platform. The more developers invoke proprietary application programming interfaces (API), the more difficult it becomes to migrate a workload from one cloud platform to another.

    It’s all but certain there will be a cloud management reckoning in the months ahead. Development teams may prefer one cloud platform over another for many reasons but, as the cost of IT continues to increase, there will soon be tougher cloud cost questions emanating from the finance office.

  • CloudBolt Adds Modular Automation Framework to Tame Hybrid Clouds

    CloudBolt Adds Modular Automation Framework to Tame Hybrid Clouds

    CloudBolt Software this week added a framework consisting of eight modules that collectively make it simpler to automate, optimize and govern hybrid cloud computing environments.

    Jeff Kukowski, CloudBolt CEO, said the goal is to provide IT teams with a more modular approach to managing multiple clouds that they can employ as they gain additional expertise.

    The modules provided by CloudBolt address everything from providing a repository, dubbed Automation Exchange, through which reusable automation content can be shared to implementing governance policies and tracking cloud spending.

    Other modules address testing and assurance, integration, automated discovery and machine learning algorithms that can be used to automate processes.

    While most organizations employ multiple clouds alongside on-premises IT environments, the management of IT across an extended enterprise is far from unified. A recent survey published by CloudBolt found a full 88% of respondents needed a “manager of managers” that would enable them to unify the various silos that have multiplied across their IT environment. CloudBolt Software is making a case for an IT framework that provides a layer of abstraction through which the management of multiple clouds and on-premises IT environments can be unified.

    It’s not clear whether organizations are deliberately employing multiple clouds or if, because of simple inertia, they have found themselves managing multiple cloud platforms because of decisions made by various application development teams. Some IT organizations employ multiple clouds because they are concerned about either becoming locked in to a specific cloud computing service; others are concerned an outage on one platform might take all their applications offline. Others simply take advantage of services that are better provided by one cloud service provider than another. It’s also not uncommon for one organization to acquire another that relied on a completely different platform to deploy applications.

    Regardless of how IT organizations found themselves managing multiple clouds, the total cost of IT rises as each new platform is added to an IT environment. Just as challenging is the fact that each new platform exposes some type of automation framework. Before too long, IT teams find themselves having to navigate multiple islands of automation implemented across a highly distributed computing environment. In many cases, those automation instances are reinventing the same process that has already been automated on another platform using a completely different toolset.

    It is more a question of time and the degree to which IT organizations will eventually consolidate management of disparate IT environments under some type of unified control plane that enables true hybrid cloud computing. Once that capability is achieved, IT teams should find it simpler to migrate workloads from one platform to another.

    In the meantime, most organizations will be managing multiple IT environments for the foreseeable future. The only thing that is unclear is the volume of workloads that might be running on one of those platforms at any given time. The challenge—and the opportunity—is to regain control over computing environments increasingly more distributed.

  • BMC Integrates DevOps Mainframe Portfolio With Git

    BMC Integrates DevOps Mainframe Portfolio With Git

    BMC has expanded its efforts to bring DevOps best practices to the development of mainframe applications by integrating the BMC Compuware ISPW continuous integration/continuous delivery (CI/CD) platform with Git repositories.

    In addition, the company tightened integration between BMC Compuware ISPW and BMC AMI Ops platform and integrated BMC Compuware Topaz Workbench for building applications with code scanning tools from Vercacode.

    Finally, there is also now a BMC Enterprise Connector for Illumio that provides a bi-directional interface between the zero-trust segmentation platform from Illumio and the mainframe. In addition, the BMC AMI Command Center for Security system can now also surface malicious performance activity to accelerate incident response.

    John McKenny, senior vice president and general manager for intelligent Z optimization and transformation at BMC, said the overall goal is to make the mainframe just another platform where IT teams can apply DevOps best practices to build applications faster. That’s more critical than ever because mainframes are often at the core of digital business transformation initiatives and require integration with a wide range of distributed computing platforms. A recent survey published by BMC found two-thirds of respondents (66%) are investing in new technologies such as AIOps and artificial intelligence/machine learning (AI/ML), DevOps and integrations.

    That approach enables organizations to leverage existing mainframes in a way that minimizes technical debt rather than duplicating functionality, added McKenny.

    When it comes to DevOps in mainframe environments, the biggest challenge these days has more to do with culture than the maturity of the tools being provided, he said. Many of the IT teams building mainframe applications still rely on waterfall processes mainly because of simple inertia and a general fear of change, McKenny noted.

    There is, however, a new generation of IT professionals that have embraced modern development practices across all platforms to accelerate the rate at which applications are built and deployed, said McKenny. That shift is leading to the wider adoption of DevOps best practices within both mainframe and distributed computing environments, he added. In fact, as a result, enterprise IT has never been more hybrid, he noted.

    IBM continues to invest in mainframes, so the platform should remain relevant well through this decade and into the next. Though it’s been nearly 60 years since the venerable platform was introduced, it continues to host mission-critical applications for a broad range of enterprise IT organizations. Most recently, IBM added an IBM z16 edition of the mainframe that adds a dedicated on-chip AI accelerator in addition to quantum-safe cryptography. It’s not clear how quickly organizations that have mainframes will upgrade, but that level of investment suggests IBM is still investing heavily in mainframe research and development.

    Regardless of how—or even who—builds applications for the mainframe, tools such as Git repositories will be more widely used if for no other reason than to more easily share code. Now, the issue is improving the overall level of DevOps maturity within mainframe environments to keep up with the rapid pace at which applications are being built and updated across the rest of the enterprise.

  • Defining the Next Cycle of Technology

    Defining the Next Cycle of Technology

    We’re in the middle of what we at ScyllaDB dubbed The Next Tech Cycle. Not “The World of Tomorrow” nor “The Shape of Things to Come” nor “The Wave of the Future”—because it’s already here today. We’re right in the middle of it. It’s a wave that’s carrying us forward, but it began with trends that got their start earlier this century.

    Everything is co-evolving, simultaneously, from the hardware you run on to the languages and operating systems you work with to the operating methodologies you use day-to-day. All of those familiar technologies and business models are themselves undergoing revolutionary change.

    This Next Tech Cycle Goes far Beyond “Big Data”

    We’re talking about huge data. Welcome to the Zettabyte Era. This era, depending on who is defining it and what it is measuring, either started in 2010 (if you’re measuring total data stored on earth) or in 2016 (if you’re measuring total internet protocol traffic in a year).

    Right now, individual data-intensive corporations are generating information at the rate of petabytes per day and storing exabytes in total. There are some prognosticators who believe we’ll see humanity, our computing systems and our IoT-enabled machinery generating half a zettabyte of data per day by 2025.

    Yet, conversely, we’re also seeing the importance of small data. Look at the genomics revolution.

    Because the RNA gene sequence of, say, COVID-19 is actually not that big, data-wise—you can store it in less than 100kb; less than an ancient floppy. But it is increasingly important to understand every single byte of that information because vaccinating against this global pandemic requires understanding every change of that rapidly-evolving pathogen.

    So, this next tech cycle has to scale everything from huge data and small data systems. And the database you will use and the data analytics you perform need to align with the volume, variety and velocity of the data you have under management.

    “Great! Now Make it All Multi-Cloud!”

    Also, this next tech cycle is not just the “cloud computing cycle.” AWS launched in 2006. Google Cloud was launched in 2008. And Microsoft Azure was formally launched in 2010. So, we’re already well over a decade past the dawn of the public cloud. Yet this next tech cycle definitely builds on the ecosystems, methodologies and technologies these hyperscalers provide.

    The database you use also has to align with where you need to deploy it. Does it only work in the cloud, or can it be deployed on-premises far behind your firewall? Does it just work with one cloud vendor or is it deployable to any of them? Or all of them simultaneously? These are important questions.

    Just as we do not want to be locked into old ways of thinking and doing, the industry does not want to be locked into any one technology provider.

    If you’ve just been mastering the art of running stateful distributed databases on a single cloud using Kubernetes, that’s not good enough. Now you’re being asked to do it all over again; this time in a hybrid or multi-cloud environment using Anthos, OpenShift, Tanzu, EKS Anywhere or Azure Arc.

    Computing Beyond Moore’s Law

    It’s also not the basic broadband or wireless internet revolutions. We’re a full two decades into both of those. Yet the advent of gigabit broadband and the new diverse range of 5G services—also capable of scaling to a gigabit—enable incredible new opportunities in real-time data streaming services, IoT and more.

    So how does your database work when you need to connect to systems far and near? How important are the limitations of the speed of light to your latencies? How well do you deal with data ingested from hundreds of millions of endpoints at gigabit-per-second scale?

    And finally, underpinning all of this are the raw capabilities of silicon, summed up by the transistor and core counts of current generation CPUs. We’ve already reached 64-core CPUs. The next generation(s) will double that, to the point where a single CPU will have more than 100 processors. Fill a rack-based high-performance computer with those and you can easily get into thousands of cores per server.

    And all of this is just traditional CPU-based computing. You also have GPU advancements that are powering the world of distributed ledger technologies like blockchain. Plus, all of this is happening concurrently as IBM plans to deliver a 1,000 qubit quantum computer in 2023 and Google plans to deliver a computer with one million qubits by 2029.

    This next tech cycle is powered by all of these fundamentally revolutionary capabilities. It’s what’s enabling real-time full streaming data from anyone to anywhere. And this is just the infrastructure.

    If you dive deeper into that infrastructure, you know that each of the hardware architecture bottleneck points is undergoing its own revolution.

    We’ve already seen CPU densities growing. Yet vanilla standalone CPUs themselves are also giving way to full systems on a chip (or SoCs).

    And while they’ve been used in high-performance computing in the past, expect to see commonly-available server systems with greater than 1,000 CPUs. These will be the workhorses —or, more specifically, the warhorses—of this next generation: Huge beasts capable of carrying mighty workloads.

    Memory, another classic bottleneck, is getting a huge boost from DDR5 today and DDR6 in just a few years. Densities are going up, so you can expect to see warhorse systems with a full terabyte of RAM. These and larger scales are going to be increasingly common—and, for businesses, increasingly affordable.

    Storage is also seeing its own revolution with the recently-approved NVMe base and transport specifications, which will enable much easier implementation of NVMe over fabrics.

    Now, software will have to play catch-up to these capabilities. Just as it took time for kernels and then applications inside of a vertically scaled box to be made async everywhere, shared-nothing, sharded-per-core, and NUMA-aware, this next tech cycle is going to require systems to adapt to whole new methodologies of getting the most from these new hardware capabilities. We will need to reconsider many foundational software assumptions.

    Evolving Methodologies: Agile and Beyond

    Speaking of methodologies, just look at these from the dawn of the millennium and onward. As an industry, we’ve moved from batch operations and monolithic upgrades performed with multi-hour windows of downtime on the weekend to a world of streaming data and continuous software delivery performed 24 × 7 × 365 with zero downtime ever.

    And by migrating to the cloud (and this always-on world) we’ve exposed ourselves and our organizations to a world of random chaos and security threats. We now have to operate fleets of servers autonomously and orchestrate them across on-premises, edge and multiple public cloud vendor environments.

    While Scrum has been around since the 1980s, and continuous integration since 1991, in this century, the twelve principles of the Agile Manifesto in 2001 altered the very philosophy—never mind the methodologies—underlying the way software is developed.

    The Agile Manifesto’s very first line talks about the highest priority being “to satisfy the customer through early and continuous delivery of valuable software.”

    However, the specific term continuous delivery (CD), as we know it today, didn’t take hold until 2009. It was then joined to continuous integration and coincided with the birth of what we now know as DevOps.

    With that, you had a framework for defining change-oriented processes and software life cycles through a responsive developer culture that now, a decade or two into this revolution, everyone takes as a given.

    This graph shows how continuous integration (CI) and continuous delivery (CD) evolved independently. They were eventually conjoined by the term CI/CD, whose popularity as a search term only began to rise around 2016 and did not displace the two separate terms until early in 2020. It is now increasingly rare to refer to CI or CD separately, according to Google Trends.

    Onto that baseline were built tools and systems and philosophies that extended those fundamental principles. The Chaos Monkeys of the world, as well as the pentesters, want to break your system—or break into them—to uncover flaws and defects long before something stochastic and catastrophic or someone maliciously does it for you.

    Cloud-native technologies like Kubernetes and single-source-of-truth for infrastructure methodologies like GitOps were created out of sheer necessity to scale systems to the hundreds of thousands of production software deployments under management.

    DevSecOps

    And that’s still not enough. We’ve already seen software supply chain attacks like SolarWinds, low-level system attacks like Spectre, Meltdown and Zombieload, or human-factor threats like viral deep fakes and millions of fictitious social media accounts using profile images generated by generative adversarial networks, never mind millions of IoT-enabled devices being nefariously harnessed for distributed denial-of-service (DDoS) botnet attacks. Just recently, news broke of the Log4j vulnerability—our best wishes to anyone who was patching code this past holiday season.

    These are all just the bowshocks of what’s still to come.

    So now, your AI-powered security systems are locked in combat every day in real-time against the threat actors attempting to undermine your normal operations. We know this because a growing number of intrusion prevention and malware analysis systems are built at terabyte-and-beyond scale using distributed databases as their underlying storage engines.

    Hence, these days, rather than just DevOps, increasingly we talk about DevSecOps—because security cannot be an afterthought. Not even for your MVP. Not in 2022.

    And these methodologies are continuing to evolve.

    Summary

    This next tech cycle is already upon us. We’re in the thick of it. You can feel it in the same way you’d yearn for major life or career change. Maybe it’s a programming language rebase. Is it time to rewrite some of your core code as Rust? Or maybe it’s in the way you are considering repatriating certain cloud workloads or extending your favorite cloud services on-premises such as through an AWS Outpost. Or maybe you’re actually looking to move data to the edge? Planning for a massive fan-out? Whatever this sea change means to you, you’ll need rock-solid infrastructure that’s available today to take workloads into production right now, but flexible enough to keep growing with your emerging, evolving requirements.

  • Tackling the Complexities of Multi-Cloud With a New IT Model

    Tackling the Complexities of Multi-Cloud With a New IT Model

    The pandemic put incredible pressure on organizations to modernize and accelerate digital transformation efforts, with many businesses rushing to embrace cloud strategies in response. According to this year’s Enterprise Cloud Index from Nutanix, multi-cloud—an IT operating model that combines multiple clouds, public or private—is the most commonly deployed IT environment and the only IT model on an upward adoption trajectory. In fact, nearly two-thirds (64%) of organizations plan to operate a multi-cloud environment within three years.

    But there are complexities and challenges of managing across cloud borders that organizations are still grappling with, and concerns about security, data integration and cost remain. Enterprises will need to find ways to leverage existing cloud investments and redefine best practices and what it means to have agility and resilience in IT.

    Current Challenges

    Businesses have traditionally been designed around managing costs, increasing efficiency and streamlining operations, but lean IT teams find themselves under new pressures to support the challenges we’re facing today. The pandemic forced organizations to prioritize implementations and view the public cloud as a quick solution for everything without proper due diligence at the expense of optimization. This approach lacked focus on strategic business outcomes, and ultimately led to increased complexity, higher costs and less flexibility. According to the study, 87% of respondents agreed that multi-cloud success requires simpler management across mixed-cloud infrastructures.

    Enterprises also continue to rank improving security as a top IT priority, yet managing security was among the top multi-cloud challenges cited. Additionally, the majority of respondents (80%) say that moving apps can be time-consuming and costly, and 77% agree that workload portability is a significant challenge. This underscores the need for uniform management and operations across different cloud environments to avoid costly and time-consuming efforts to move applications.

    “Cloud-Smart” approach to IT

    Current cloud thinking is that there’s a “best” cloud environment for each workload or application, but there is no one-size-fits-all approach to the cloud. Organizations will start to move away from blanket cloud-first approaches to IT, and instead, be more thoughtful about which workloads run where. It is no longer a foregone conclusion that taking every app or workflow to the cloud permanently is the best course of action. The adoption of this “cloud-smart” approach, leveraging the most appropriate cloud environment for each use case, is likely a primary driver behind the proliferation of multi-cloud.

    The use of IT infrastructure by organizations is becoming more strategic over time. Nearly three-quarters of IT professionals (72%) feel that the IT function in their businesses is seen as more strategic now than it was a year ago. While businesses are now viewing and using IT more strategically than ever before, the complexity of multi-cloud is creating challenges that are standing in the way of cloud success. Despite challenges, a strong case is made for why the future of IT is hybrid multi-cloud, a model that enables more operational consistency across clouds. In fact, 83% consider it ideal.

    Multi-Cloud Supports New Ways of Working

    The pandemic has changed how nearly all organizations operate, and the top reasons cited by businesses for changing their infrastructure and deployment models are improving remote work and collaboration. While an organizations’ remote workforces may fluctuate, they are here to stay for the foreseeable future and IT will need to be nimble to support a remote, hybrid workforce and keep people productive and connected regardless of location.

    Over half (61%) of organizations are focused on offering more flexible work setups because of the pandemic, and multi-cloud supports this new way of working. It offers the most agile IT environment for supporting this kind of flexibility by distributing data and allowing remote access to business applications from diverse geolocations for user proximity and business continuity, and enabling organizations to implement technology that helps retain and attract talent.

    Multi-cloud is here to stay—and is the only operating model that is expected to increase in the coming years. 2022 will bring about a shift towards hybrid multi-cloud deployment as organizations look to take advantage of what each cloud has to offer while still having the flexibility and freedom of choice around their applications and data. This would deliver on the flexibility and agility that most organizations seek to compete in today’s digital world while enabling enterprises to significantly simplify operations. Future-proofing cloud strategies is the key to building IT resilience.

  • The Future of Cloud Strategy: Multi-Cloud

    The Future of Cloud Strategy: Multi-Cloud

    As Gartner’s Milind Govekar recently said, “There is no business strategy without a cloud strategy.” But in 2021, some of the world’s biggest brands suffered disruptions in their services due to outages from their cloud service providers, including Google, Slack, Venmo, Disney+, Facebook/Meta, Tinder, iRobot, The Washington Post and Sony.

    While the outages do not negate the overall benefits of moving to the cloud in the first place, they do make IT leaders think twice about putting all their eggs in one cloud provider’s basket. In this article, we will be exploring the multi-cloud strategy, its advantages and how to prepare for your multi-cloud future.

    Let’s Be Clear About Cloud

    The adoption of a cloud strategy was evidenced in a 2021 O’Reilly survey in which 48% of participants reported a plan to migrate more than half their applications to the cloud while 20% planned to migrate all their applications to the cloud.

    Cloud migration is a multi-factored decision made by business leaders to migrate electronic assets from local servers to the cloud. Cloud storage is rapidly overrunning on-premises data warehouses because of its many positive business impacts including scalability, speed, collaboration, continuity, security and rapid ROI. Although it is simple to select one provider, we’re seeing more and more organizations opt for multiple providers to avoid the negative impacts of outages.

    Multi-Cloud Strategy: The Dominant Choice

    Cloud revenue continues to reach new heights. Gartner predicted cloud revenues globally will reach $474 billion in 2022. That number represents a significant increase from $313 billion in 2020. 

    The challenge among many IT leaders is continually mapping the use of the cloud in relation to their business goals. This alignment is critical to the success of overall objectives as cloud solutions need to match business requirements, whether related to security, compliance or other issues. 

    Cloud-based solutions are highly sought after by businesses and IT leaders. In the quest for the “perfect” solution, multi-cloud options are highly appealing. Benefits of a muti-cloud system include: 

    • Avoiding vendor/provider lock-in
    • Allowing for scaling as business grows
    • Increasing security to thwart attacks
    • Harnessing unique capabilities of different providers

    Multi-cloud and hybrid cloud are often used interchangeably, but they actually refer to slightly different approaches. 

    Hybrid, strictly speaking, is the use of cloud infrastructure in conjunction with bare metal (aka traditional) data centers. As such, it has been an approach favored by enterprises migrating to the cloud in phases.

    Multi-cloud, as the name suggests, involves the use of more than one cloud provider to provision IT. Many would argue it’s also the future of operating as a cloud-first entity.

    Fast-Tracking Digital Transformation

    Digital transformation can be a long haul, however, businesses adopting multi-cloud solutions are navigating the digital services path more quickly.

    Why does the cloud present itself as the best solution for businesses?

    • Rapid advancement of cloud solutions
    • Apps are becoming more readily suited for development and deployment
    • Skepticism toward the cloud is now waning; businesses are porting databases and mission-critical apps to the cloud
    • Cloud is key to delivering AI services, an area of increased growth

    Flexibility meets Functionality

    Flexibility is undoubtedly a major attraction in relation to cloud choices. However, making the correct decisions is imperative to meeting strategic business objectives. The cloud proves beneficial to leaders as, in combination with data engineering, they can procure a comprehensive view of relevant data.

    The first critical component to selecting the correct cloud solution is market research. The necessity of this step is two-fold. Yes, it takes time to conduct research, but in the end, diligence can end up saving both time and money.

    Of course, businesses and providers want their relationships to be symbiotic. App migration may go well and all proper dynamics function at the onset, but what happens when a switch needs to be made? It can prove to be both burdensome and costly. With this reason in mind, it’s important to continually weigh both short-term advantages and longer-term flexibility. 

    Another essential component when assessing options is ensuring seamless interoperability between systems. Simply defined, interoperability is the ability of computerized systems to connect and communicate with one another without regard to their manufacturer or industry. 

    In a modern economy, IT leaders are called on to be increasingly conscientious about cloud services to alleviate any issues with future data portability.

    Edge Computing on the Rise

    Edge computing is a subset of a distributed computing topology in which information processing is located close to or at the location where that information is produced or consumed.

    With the trend of edge computing on the rise, the lines between edge and cloud computing continue to become more obscure. Cloud vendors need to use an edge strategy, and some already employ their own specific suite of services aimed at making data processing seamless.

    Data processing and transition should not be an arduous task. This factor alone influences leaders when making decisions on their cloud journey. Digital maturity is a competitive advantage for which all businesses should strive. 

    Adapting to Multi-Cloud

    A more complex cloud environment can be challenging, but the task is manageable. By dedicating the time and resources necessary, businesses can adapt to muti-cloud or hybrid systems with considerable ease.

    Whether through necessity or design, a multi-cloud or hybrid system has numerous benefits in relation to compliance, security, efficiency, scale, and performance. The multi-cloud strategy is here to stay.

  • Russian Dev Exodus | Puppet IPO FAIL | Intel 18A Ahead of Sched.

    Russian Dev Exodus | Puppet IPO FAIL | Intel 18A Ahead of Sched.

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

    This week: More than 100,000 tech workers leave Russia, Perforce buys Puppet, and Intel moves faster than planned. (more…)

  • Survey Shows Shift to SRE Principles to Automate IT Management

    Survey Shows Shift to SRE Principles to Automate IT Management

    A global survey of 1,500 IT decision-makers conducted by F5 found that, on average, organizations are managing more than 200 applications deployed across an extended enterprise as well as more than 20 different security and delivery technologies.

    Lori MacVittie, principal technical evangelist in the Office of the CTO for F5, said that level of complexity makes it apparent that IT teams will need to embrace higher levels of automation to manage the IT environments that are now at the core of a wide range of digital business transformation initiatives. The survey revealed that more than three-quarters of respondents (77%) were embracing site reliability engineering (SRE) principles to automate the management of IT.

    A full 95% of respondents also planned to mine operational data for insights they could use to improve the customer experience and drive business growth. However, 98% of respondents also said they are currently unable to extract those needed insights from their existing systems. A total of 90% said they planned to implement some form of artificial intelligence (AI) to achieve that goal. More than two-thirds of respondents said their organizations realized that creating superior digital interactions for customers will require modernizing business processes and back-office functions.

    As part of those efforts, the survey suggested that application workloads are being shifted across highly distributed computing environments. In addition to the 84% of respondents that are planning to move workloads to the edge, the survey found two-thirds of organizations (67%) are currently or planning to repatriate applications from the cloud to a data center environment in the next 12 months. A total of 93% of respondents reported using some type of as-a-service offering delivered via the cloud today.

    Naturally, securing that many platforms also represents a major challenge. However, despite inherent risks, more than three-quarters (76%) of respondents said, given the choice, they’d turn off security measures to improve performance. That lack of willingness to sacrifice performance suggests that attitudes to security may not have changed much despite all the breaches that now regularly occur, said MacVittie.

    It’s not clear to what degree managing enterprise IT environments has become untenable; however, it’s clear that legacy manual processes will need to become automated. Organizations can’t afford to keep hiring IT staff to manage IT platforms that span everything from the network edge to public clouds. In fact, the survey makes clear that DevOps practices—in the form of the SRE principles first defined by Google—are gaining traction. That doesn’t necessarily mean everyone managing IT is becoming an SRE or an engineer, but it does suggest that automation frameworks are being more widely used.

    It may be a while before those automation frameworks are ubiquitous. However, one way or another, many of the tasks that have historically conspired to make working in IT tedious are going to disappear. The issue, of course, is to not wind up with islands of disconnected automation that introduce more complexity.

  • Survey Shows Increased Focus on Modernizing IT, Retiring Apps

    Survey Shows Increased Focus on Modernizing IT, Retiring Apps

    A survey of 140 enterprise architects and IT leaders published today suggested that, while moving applications to the cloud remains a priority, more attention is being paid to reducing technical debt by retiring applications.

    Conducted by LeanIX, a provider of a platform for managing enterprise architecture and managing value stream management (VSM), the survey found 40% of respondents identified reducing technical debt created by legacy applications and modernizing legacy systems as their top IT priorities. A full 96% said their company has at least one project planned for this year aimed at reducing technical debt with more than half (52%) noting that retiring IT applications is the primary means they will employ to reduce technical debt.

    Nearly 60% considered migrating applications to the cloud to be a high priority, as well. However, less than a quarter of respondents (24%) identified cloud initiatives as a top IT priority. The second most important cloud initiative, identified by 41% of respondents, is to increase the number of SaaS applications being employed.

    Regardless of the approach to the cloud, nearly three-quarters (73%) of respondents said enterprise architects should form a closer connection with software development teams, with an almost equal percentage agreeing on the importance of tracking the business impact of software development.

    However, only 16% of those surveyed considered the evolution and improvement of their security posture a top priority, even though more than two-thirds considered security initiatives—such as improving risk assessment capabilities and adopting more zero-trust IT offerings—as important or highly important.

    Dominik Rose, vice president of product management for LeanIX, said enterprise architects—or someone within IT who assumes responsibility for enterprise architecture—are trying to minimize disruptions to the business as IT environments continue to expand and evolve. The challenge they encounter is there is usually a divide between software development teams and the rest of the business. The size of that divide will vary by organization; in general, though, digital business transformation initiatives should help bridge the gap—assuming enterprise architects can establish and maintain close connections with software development teams, noted Rose.

    LeanIX is making a case for an enterprise architecture management (EAM) platform that provides visibility into IT environments. The company also makes a VSM offering available on top of that platform that provides visibility into software delivery processes. The number of organizations that have adopted VSM platforms remains relatively small, but as organizations depend more on software to drive digital processes, the need for senior business and IT leaders to have more visibility into software delivery schedules is expected to increase.

    In the meantime, it remains to be seen just how aligned DevOps teams are with the strategic goals of the business. The ability to build and deploy software faster does not automatically equate to gaining a deeper understanding of the needs of the business. In fact, there may come a day when software is built and deployed faster than most organizations can effectively absorb unless they have some equivalent of a VSM platform in place.

  • Overcoming IT Complexity With Full-Stack Observability

    Overcoming IT Complexity With Full-Stack Observability

    Organizations embarking on digital transformation journeys tend to develop complex infrastructures. They update their legacy applications while adding multi-cloud, virtual and cloud-native capabilities. Eventually, IT pros find themselves managing diverse, complex and distributed networks including cloud, system, application and database infrastructures.

    To rein in the resulting complexity, organizations tend to amass monitoring and managing tools. The goal is to simplify systems oversight—but instead, silos tend to develop because teams use a wide variety of tools to manage their networks or infrastructures. 

    This piecemeal approach worsens operational blind spots and delays problem resolution. It also increases security exposures. Soon, overwhelmed IT pros can’t keep pace with app modernization or infrastructure dynamics because they’re awash in complexity.

    Though this scenario is common, it’s not inevitable. IT teams can ease their digital transformation journey by implementing an integrated and cost-effective full-stack, end-to-end monitoring service capable of overcoming complexity and silos. 

    Organizations require full-stack observability.

    How Observability Differs From Traditional Monitoring

    Observability goes beyond traditional monitoring. Traditional monitoring helps IT organizations understand the actual state of their infrastructure and applications. It captures and processes volumes of infrastructure and application telemetry data and notifications and displays which components are up, which ones are down and which ones have changed. 

    Usually, traditional monitoring focuses on a specific network, cloud or infrastructure. It tracks application and infrastructure elements so IT pros can identify anomalies and investigate problems as they arise.

    Monitoring relies on metrics-oriented dashboards built to assess telemetry data against manual or basic statistically relevant thresholds. Monitoring tools are invaluable, but they don’t offer cross-domain correlation, service delivery insight, operational dependencies, or predictability. Modern systems have complex multi-cloud environments and a deluge of telemetry data: This counts as a shortfall.

    Observability does more. It measures the internal states of systems by examining the outputs and looks at applications and systems in their entirety—from the end-user experience to server-side metrics and logs.

    But observability also includes monitoring as a critical element. To gain observability, you must first collect information through monitoring. Observability uses the insights and metrics generated through monitoring to understand what’s causing the issue at hand. 

    Monitoring aggregates and displays the data to determine whether the systems are operating as expected. The analysis of this information is compared with expected outcomes and objectives. This allows IT pros to understand the state of their infrastructure and applications. 

    Silos are thus avoided because complex environments are viewed in their entirety.

    Observability in Action

    Once in place, observability allows IT organizations to continuously improve performance, availability and digital experience across complex, diverse and distributed hybrid and cloud environments.

    With observability, organizations can quickly find and resolve anomalies. However, full-stack observability goes beyond monitoring and expedited problem resolution: It supplies insights, automated analytics and actionable intelligence through cross-domain data correlation, machine learning (ML) and artificial intelligence for IT operations (AIOps). It works across massive real-time and historical metrics, logs and trace data.

    Observability goes beyond the silos and the piecemeal approach associated with traditional monitoring. And when observability isn’t limited—when it includes ML and AIOps—it uses the large volume of gathered data and supplies insights, automated analytics and actionable intelligence to help IT staff expedite problem resolution. It also enables ITOps, DevOps and security organizations to achieve consistent, optimized and predictable business service delivery with continuously improved digital experience and IT productivity. 

    The result is customers and employees benefit from better-run systems. The technology provides organizations of all sizes and industries with comprehensive, integrated, and cost-effective functionality through cloud-connected on-premises or software as a service (SaaS) deployment flexibility.

    When embarking on digital transformation journeys, organizations don’t need further complexity—certainly not while they update legacy applications and add a plethora of modern services and capabilities to their stack. The key to reducing complexity is observability.

    Observability simplifies the transformation process. It reduces operational noise to benefit ITOps, DevOps and security teams. They can become more proactive in issue and anomaly detection to achieve optimum IT performance, compliance, and resilience. With full-stack observability, any organization—no matter its size or industry—can reduce IT complexity while readying itself for digital transformation.