Babble

At Cloud Field Day 9 Netapp presented some of its cloud solutions. This comes on the heels of NetApp Insight , the annual corporate event that should give its user base not just new products but also a general overview of the company strategy for the future. NetApp presented a lot of interesting news and projects around multi-cloud data and system management. The Transition to Data Fabric This is not the first time that NetApp radically changed its strategy. Do you remember when NetApp was the boring ONTAP-only company? Not that there is anything wrong with ONTAP of course (the storage OS originally designed by NetApp is still at the core of many of its storage appliances). It just can’t be the solution for everything, even if it does work pretty well. When ONTAP was the only answer to every question (even with StorageGrid and EF systems already part of the portfolio), the company started to look boring and, honestly, not very credible. The day the Data Fabric vision was announced...

Yes, much of the world may have moved on from email to social media and culturally dubious TikTok dances, yet traditional electronic mail remains a foundation of business communication. And sadly, it remains a prime vector for malware, data leakage, and phishing attacks that can undermine enterprise protections. It doesn’t have to be that way. In a just released report titled “ GigaOm Radar for Phishing Prevention and Detection ,” GigaOm Analyst Simon Gibson surveyed more than a dozen enterprise-focused email security solutions. He found a range of approaches to securing communications that often can be fitted together to provide critical, defense-in-depth protection against even determined attackers. Figure 1. GigaOm Radar for Email Phishing Prevention and Detection “When evaluating these vendors and their solutions, it is important to consider your own business and workflow,” Gibson writes in the report, stressing the need to deploy solutions that best address your organization’...

Could we be entering an era of hands-free data centers, where remote software and robotics handle tasks that until now have fallen to human technicians? That prospect may not be as far off as you think, according to a recent InformationWeek article by John Edwards that explores the push to make data centers autonomous. As Edwards reports, the COVID-19 pandemic has helped force the issue, with data centers worldwide operating at sharply reduced headcount. GigaOm Analyst Ned Bellavance was cited in the article. He urged IT managers to establish the proper foundation for an automation effort, cautioning that existing data center deployments may be difficult to transition to full hands-free operation. He stressed that a homogeneous and standardized environment is important to achieving success. As a case in point, Bellavance singles out Microsoft’s Project Natick, an effort to develop enclosed data centers that can be deployed in coastal waters on the seafloor. Microsoft in 2018 deploy...

DevOps’ general aim is to enable a more efficient process for producing software and technology solutions and bringing stakeholders together to speed up delivery. But we know from experience that this inherently creative, outcome-driven approach often forgets about one thing until too late in the process—security. Too often, security is brought into the timeline just before deployment, risking last minute headaches and major delays. The security team is pushed into being the Greek chorus of the process, “ruining everyone’s fun” by demanding changes and slowing things down. But as we know, in the complex, multi-cloud and containerized environment we find ourselves in, security is becoming more important and challenging than ever. And the costs of security failure are not only measured in slower deployment, but in compliance breaches and reputational damage. The term “DevSecOps” has been coined to characterize how security needs to be at the heart of the DevOps process. This is in part...

“If you can’t measure it, you can’t manage it.” It’s an old management saw, but one rooted in truth, especially in the arena of software development where establishing a common vision and language of success can be so important. DevOps practices have for years given organizations a model for linking and streamlining processes, enabling both continuous integration (CI) and continuous delivery (CD). But as GigaOm VP of Research Jon Collins explains, businesses still struggle with understanding the actual value derived from these processes. In his recent Strategy Considerations report, “ Driving Value Through Visibility ,” Jon emphasizes that delivering on innovation requires more than moving from a project to a product mindset. It hinges on the ability to measure success, across both the products you create and the processes you use to create them. “Across organizations today, we’re seeing DevOps have to up the ante—to move beyond simply doing things faster and towards enabling softw...

So-called legacy software gets that name for a reason—it’s done enough for the organization over the years to earn a legacy enabling the business. But as GigaOm Analyst Ned Bellavance notes in a recently published GigaOm benchmark report (“ Costs and Benefits of .NET Application Migration to the Cloud ”), aging on-premises applications and infrastructure can work against businesses as they seek to scale, innovate, and grow. A cloud modernization effort can change that. By migrating application logic and functionality to the cloud, enterprises avail themselves of the matchless scalability and managed services offered by major cloud providers. In the report, Bellevance lays out four options for organizations looking to cloudify their application portfolios. Figure 1: Cloud Application Modernization Spectrum Rehost: “Lift-and-shift” virtual machines running on on-premises servers to cloud-based servers. Simple and quick. Replatform: Migrate application logic (say, ASP.NET apps) t...

One of the most interesting and successful research projects I’ve worked on lately was the one about unstructured data management. Our clients loved the Key Criteria and Radar reports, and I had many fascinating conversations with vendors and users about what is coming next in this space. Why Unstructured Data Management First, let’s be clear here—explosive data growth is not something you can bargain with or avoid. You can’t stop it. Human-generated data has been joined by a growing host of sensors, cameras, and countless other devices that are capable of producing overwhelming amounts of data for an incredibly diverse range of use cases. Most of this data we are keeping in our on-premises and cloud storage systems. Some of this data is analyzed almost immediately and then lays dormant for quite a long time, sometimes forever. There are plenty of reasons to keep data around for long periods of time—internal policy, compliance, regulations, you name it. Traditional storage systems a...

Hyperconverged infrastructure (HCI) has quickly earned a place in the datacenter, mostly due to the promise of infrastructure simplification. HCI has already worked very well for virtualized infrastructures, but will this be the case with Kubernetes? There’s reason for optimism, and I offer a couple thoughts here as to why. HCI is one of many ways to build your computing stack. The idea is to virtualize and collapse several components of the stack, including storage and networking, alongside compute resources (virtual machines). The approach trades off some performance for enhanced flexibility and ease of use. In its early iterations, HCI was a good fit for mostly small-to-medium sized businesses (SMBs) and vertical applications such as virtual desktop infrastructure (VDI). Now the performance gap has narrowed and HCI can be leveraged across a broader range of applications. Some IT organizations have made HCI their go-to technology, with 90% of their data centers built around HCI! Ku...

Storage vendors, especially startups, are finally supporting new media types in their systems. In this article I want to talk about the impact that quad-level cell (QLC) NAND memory and Intel Optane have in the development of scale-out systems and how vendors like VAST Data are taking full advantage of them in their product design. In my recent GigaOm report about scale-out file storage ( Key Criteria for Evaluating Scale-Out File Storage ), I mentioned several key criteria that can help users evaluate this type of storage system. Today I want to explore specific solution functionality that can make a difference in a scale-out storage deployment, and how it should impact your thinking. Key Criteria, Considered Before I go further, however, I want to dive into the structure of our GigaOm Key Criteria reports and how they help inform decision making. For each sector we assess, the Key Criteria report explores three sets of criteria specific to that sector. They are: Table stakes are...

Enterprises of all sizes are embracing hybrid cloud strategies that are becoming more complex and structured. But they want the flexibility to choose where applications and data should run dynamically, depending on business, technical, and financial factors. The use of Kubernetes brings this vision within reach of most organizations, but you need the right integration with infrastructure layers, such as storage, to make it happen. How should organizations set up their storage infrastructure to make using Kubernetes—and the enterprise efficiencies it enables—achievable? Below, we look into what makes Kubernetes so powerful and important to today’s enterprises, and outline the structures and technology needed to create the perfect setup for this technology. Lock-In Danger Promotes Hybrid Solutions Every enterprise faces different challenges when deploying business-critical systems. A common problem is lock-in, where the selection of certain business systems creates conflicts with ot...

I had the chance to meet with storage startup Nebulon recently and have been thinking about the company’s solution and value proposition. It is very difficult to figure out where they belong in the market, but in the end I decided that their product should be included in the composable storage category. Here’s why. Nebulon’s product consists of two components: A hardware layer and a software system. Let’s explore these in turn. The hardware layer is called the services processing unit (SPU ), which is a disk controller on steroids that you install on a standard x86 server to provide sophisticated data protection and other services. This node can also be connected to other nodes and share resources to form a sort of virtual array called nPod. The controllers are PCI-based and connect through standard high-speed network interfaces. The storage resources in the back end, installed on the servers, can be all-flash or hybrid. This storage can be accessed directly from the servers themsel...

Robotic process automation (RPA) lets businesses quickly transition analog, human-led activities into automated digital actions. What differentiates RPA from tools that have complementary or overlapping capabilities is the ability to implement computer-initiated actions that would typically require human intervention. Examples of such actions include pulling information from an unstructured document, using a visual interface to enter or query data, extract information from printed forms, or evaluate voice input. Without this capability, digital automation is not possible and, therefore, neither are the benefits associated with such automation. RPA is democratizing automation—empowering employees and increasing efficiency within organizations. But the implementation of RPA processes within a business can be difficult—and often there are alternatives that are more cost-effective and better aligned with business needs. In this report, we lay out the questions and considerations an orga...

In a recent report, “ Key Criteria for Evaluating People Analytics ,” distinguished analyst Stowe Boyd looks at the emerging field of people analytics, and examines the platforms that focus on human resources and the criteria with which to best judge their capabilities. Stowe in the report outlines the table stakes criteria of People Analytics—the essential features and capabilities without which a platform can’t be considered relevant in this sector. These include basic analytic elements such as recording performance reviews, attendance monitoring, and integration with other HR tools. The report also defines the key criteria, or the features that actively differentiate products within the market and help organizations to choose an appropriate solution. These criteria include: Full employee life cycle tracking Support for different employee types (seasonal or freelance workers) Employee surveys Diversity and inclusion monitoring Stowe also looks at the rapid innovation and em...

In a new Key Criteria report, GigaOm analyst Enrico Signoretti looks at how file storage—one of the most popular ways to store data—has been adapted for modern scale-out systems, and how this helps large enterprises achieve their ends. “ Key Criteria for Evaluating Scale-Out File Storage ” examines the history of file storage and shows how its strengths—ease of use, cost-effectiveness, and its importance for legacy systems—allow it to maintain continued relevance in today’s crowded storage market. In the report, Enrico also explains how these systems work, including their structure and basic components, and the differences between scale-up and scale-out systems. In this Key Criteria report, Enrico defines the evaluation metrics that enterprises should use to judge the quality and relevance of file storage systems: Scalability Flexibility Performance System lifespan Usability TCO and ROI The report looks at the table stakes—the basic requirements—of a scale-out file storage ...

COVID-19 has created a new normal: knowledge workers setting up their offices at home, juggling child care, homeschooling, and household chores even as they try to maintain and develop business relationships over video links. All this comes following years marked by declining employee engagement and rising levels of stress in the workplace. Now the sudden and unexpected shift to home working has caused unprecedented levels of disruption to the lives of workers. No surprise, most organizations were caught cold by the pandemic. The question now becomes, how can they support their teams as the world structurally shifts to a work-from-home model? Supporting the Distributed Workplace The COVID-19 pandemic has forced a scramble to upgrade and align central IT infrastructures—from security approaches and software deployment models to the adoption of user-facing solutions like intranets and workplace technologies like chat, file sharing, and digital whiteboards. But those efforts won’t fr...

In his recent Key Criteria Report, respected analyst and author Chris Grundemann explores the criteria needed to understand and evaluate software-defined wide area network (SD-WAN) solutions and how they are transforming the performance of traditional wide area networks (WANs). The report, “ Key Criteria for Evaluating SD-WAN ,” explores this fast-developing area of network solutions. It outlines the key elements that define an SD-WAN, including centralized management, network virtualization with encryption, the use of multiple circuits, and path measurement. These features are the basic set of requirements for an SD-WAN and help give it the qualities that set it apart and make it a useful networking technique to simplify and improve WANs. Chris outlines how those looking to incorporate an SD-WAN solution into their organization can differentiate between solutions and how different features and criteria can boost the capabilities of a network. These features include: Routing and fo...

Data is the “new oil” for modern tech, transforming countless industries and providing invaluable insight as organizations leverage artificial intelligence (AI) and machine learning. But this data-rich future—where information once bound for cold storage becomes an actionable, strategic asset—comes with challenges. More data must be stored safely at reasonable cost over longer time spans, even as enterprises forge a data foundation layer to transform every type of data they own from a liability to be stored and defended into an asset to be leveraged. Enterprises need the right storage infrastructure to manage this transition and unlock the potential value in their data. In this blog post, we outline how storage has evolved to combat the challenges of AI, ML, and big data and how the new generation of data storage offers a better solution than traditional stacks. What ML and Big Data Need To make a successful data storage layer for AI and ML operations using large amounts of data, yo...

Do you remember the data center of the past? And by past, I mean 20 to 25 years ago, when there was this huge, almost philosophical debate about complex instruction set computer (CISC) and reduced instruction set computer (RISC) architectures, and between large symmetric multi-processing (SMP) servers and mainframes and smaller systems. There were even fights over some esoteric system designs. All of this was happening before there were co-processors, ASICs and other fancy accelerators to speed data access and optimize complex operations. You might think we are past the fighting, now that data centers have largely aligned around commoditized x86 (ahem, CISC) CPUs, small two-socket servers, and a general standardization of the components that make up the modern data center. But the reality is that an increasing number of companies are rethinking the data center in ways that remind me of the ideological tussles of the past, while introducing new paradigms and innovations based on recent...