devopsy.kinsta.cloud

Category: Infrastructure/Networking

  • Deploying OpenStack: Pick a Distribution With These 7 Qualities

    Deploying OpenStack: Pick a Distribution With These 7 Qualities

    OpenStack, which turns 10 years old in July, remains the leading open source infrastructure component in private clouds. But, there is a plethora of OpenStack distributions out there, and selecting the right one is vital to the success of every organization’s OpenStack project.

    How do you know which is best? It’s an important question because, despite OpenStack’s popularity, companies often face serious challenges when adopting and deploying it. Put simply, OpenStack can be time-consuming and skill-heavy in order to deploy it, unless the chosen distribution is equipped to overcome those challenges.

    Thus, anyone planning to deploy OpenStack should make sure the distribution they pick meets the following seven criteria.

    Strong Economics

    Cloud environments are supposed to be more cost-efficient than proprietary hardware. That’s why enterprises love the cloud, after all. Therefore, the number one priority when choosing an OpenStack distribution is to make sure it can indeed reduce costs. That means steering clear of OpenStack platforms that are hard to deploy, maintain, upgrade and force you to struggle with basic operations. It’s also important that the distribution’s pricing model be clear and predictable so that organizations can plan expenses accurately.

    Totally Open Source 

    While OpenStack itself is open source, the installers provided by the vendors as part of their distributions often are not. This can lead to additional costs being applied to the licenses and situations where organizations are forced to pay for the distribution before even trying it out. Furthermore, all types of environments in use—including staging and development—need to be covered by the license, too. These pitfalls are sidestepped with OpenStack distributions that are 100% open source, providing better economics and flexibility for organizations.

    Predictable Release Cadence 

    While the release cadence of OpenStack is predictable and well documented, not all distributions follow the upstream quickly enough. Making sure the OpenStack distribution you choose supports the latest stable upstream release as soon as possible is crucial for a few reasons. The upstream release may have features that are important for the organization. Or there may be bug fixes that they feel are critical. Picking a downstream distribution with a predictable release cadence that stays in sync with the upstream ensures transparency and allows organizations to plan the upgrade process. 

    Long Support Runway

    Support services are essential for OpenStack production environments, especially when service level agreements (SLAs) apply. But, how long vendors will support older versions of OpenStack can vary. Though there is always an option to upgrade or re-deploy, there are times when it may be beneficial for organizations to stay with the current version. Thus, how long the vendor will provide support services is a key factor in choosing a distribution.

    Upgrades Made Easy

    There inevitably comes a time for most organizations when they want to upgrade their upstream OpenStack. However, OpenStack upgrades are known to be complex, and many commercial distributions do not support them. Even if they do, the process is complex and must be executed manually. Thus, choosing an OpenStack distribution that provides support for fully automated upgrades is essential for the success of the cloud operations team.

    Simplified Operations 

    Even after an OpenStack cloud is deployed, consideration must be given to the ongoing operations that can become complex and fragile. Maintaining the cloud on a daily basis includes operations such as scaling the cluster out or recovering it from failure. While most OpenStack distributions don’t provide mechanisms to simplify these tasks—forcing users to execute them manually—some do. Organizations should look to distributions that do a good job automating complex operational tasks, saving time and money.

    Flexible Technology Choices 

    OpenStack is a flexible cloud platform, supporting various hypervisors, software-defined networking (SDN) solutions and storage plugins. But many distributions are tied to a single stack. That means an organization may need to re-platform or move to a heterogeneous environment in the future. Avoid that trap by selecting a distribution that can adapt to work with new technologies.

    By looking for these seven qualities, organizations can get the most out of their OpenStack distribution and optimize the cloud infrastructure on which they increasingly rely.

  • GigaSpaces Embraces Kubernetes Alternative for DataOps

    GigaSpaces Embraces Kubernetes Alternative for DataOps

    GigaSpaces has added a DataOps framework to its in-memory computing platform that provides an alternative to Kubernetes by employing Nomad software from HashiCorp as a scheduler.

    Yoav Einav, vice president of product for GigaSpaces, said many enterprise IT organizations aren’t in a position to adopt Kubernetes, yet they still need a means to embrace best DataOps practices to process massive amounts of data in real-time.

    Version 15.2 of the company’s namesake platform adds a GigaOps Stack module based on ElasticGrid, an alternative to Kubernetes; and Ops Manager; gsctl; and a monitoring tool. GigaSpaces already natively supports Kubernetes, but Einav said there is a significant number of IT teams that don’t have the skills required to deploy and manage Kubernetes clusters.

    DataOps has emerged as a corollary to DevOps in that it defines a set of practices for automating the provisioning of storage systems that makes data readily accessible to applications. The need to automate those processes has become more acute as organizations build and deploy applications infused with machine learning algorithms, noted Einav.

    ElasticGrid is designed to provide a more declarative alternative to achieve that goal without having to learn how to programmatically spin up Kubernetes clusters, Einav said. That approach makes ElasticGrid more accessible to the average IT administrator, he added.

    In addition to being able to support both virtual machines and containers, Einav said ElasticGrid is approximately 20% faster than Kubernetes.

    Other capabilities added to the latest release of GigaSpaces include a stream iterator optimization tool that increases throughput for read-intensive workloads by a factor of two and support for memory-level encryption and compression per property to better adhere to data privacy regulations.

    GigaSpaces is making the case for an in-memory computing platform that is optimized to run applications in near real-time. As organizations embrace a wide range of digital business applications, legacy IT infrastructure that was optimized to process applications in batch mode needs to be updated to support applications that need to process data in memory to support applications that are processing data in near real-time.

    It’s not clear to what degree organizations will be investing in new platforms during the economic downturn brought on by the COVID-19 pandemic. There is no doubt some organizations will pull back on those investments. However, a significant number of organizations are also accelerating the rate at which they are building digital business applications to drive a newly minted business continuity strategy. Recognizing the need for more resilient applications that can be accessed by customers and suppliers from anywhere, many organizations are accelerating the deadlines for delivering many of these applications in the wake of the pandemic.

    Of course, there are multiple options available when it comes to deploying an in-memory computing platform to support these applications. The challenge many organizations will encounter, however, is finding an in-memory computing platform that also addresses the inherent challenges associated with moving large amounts of data in and out of the platform on-demand.

  • Managing a New Kind of Complexity in Software-Defined Networking

    Managing a New Kind of Complexity in Software-Defined Networking

    Software-defined networking (SDN) has moved up the enterprise IT agenda in recent years. And it’s easy to see why–in theory, SDNs are far quicker and easier to control and alter than traditional networks. By using open protocols to apply controls from the network edge, SDNs enable network engineers to shape traffic from a single centralized console, rather than working with individual switches across the network.

    In turn, this makes software-defined networks far more agile than traditional networks, with opportunities for automatic load balancing, streamlined processes, on-demand provisioning of new applications and traffic flows–in short, a network that works much harder for the organization. So, it’s no surprise that organizations are embracing SDN. A 2019 Verizon study found that while just 15% of respondents said their companies had implemented SDN, 57% expected to do so within two years.

    However, deploying SDNs can introduce new challenges for network staff revolving around complexity–in particular, complexity in relation to managing network security. Let’s take a closer look at what this means.

    A Shift in Complexity

    Any organization that moves to a software-defined environment essentially moves from datacenter-focused firewalls into a model where its security policies are defined by software within its fabric. This requires a far more granular level of security policies, on a much larger scale and with far more agility, than in traditional networks. Why? Because security controls are much more diverse.

    In a traditional setup, network security policy is relatively monolithic. A set of servers is protected by a perimeter firewall, filtering so-called north-south traffic that enters the network from the outside. Traditionally, east-west traffic within the datacenter itself is not subject to any filtering, which introduces security risks–particularly in terms of enabling malicious parties to laterally explore the environment once they have compromised a single endpoint.

    By contrast, in an SDN environment, built-in firewalls are considered part of the infrastructure. It is likely that the organization will have multiple tenants, each containing a unique set of granular security policies dictating which assets can connect to which other assets within the SDN fabric. An SDN environment is likely, for example, to incorporate one contract with Cisco Application Centric Architecture (ACI), VMWare NSX distributed firewalls and so on. There is a lot of complexity to manage.

    Ultimately, the organization in question needs to identify which elements within the newly software-defined network need to connect to each other. Then, create granular security policies that enforce this, dividing the network into smaller zones to prevent lateral infiltration by malicious parties. In short, they need to introduce micro-segmentation. 

    Managing Micro-Segmentation

    There are two main challenges associated with micro-segmentation from a security point of view. First, the organization needs to define the micro-segmented zones, and second, it needs to enforce and maintain the security policies that enable that micro-segmentation.

    How do we define micro-segmentation zones? This is all about understanding the assets within your environment, which databases contain the most sensitive data and therefore need to be segmented off from each other, which assets are talking to each other and how traffic is flowing throughout the network. Crucially, all this should be contextualized in terms of business applications–in other words, you need to understand the traffic that makes business applications work. This enables you to design a micro-segmentation architecture–and the security roles to enable it–that are centered around your business-critical services. Solutions that automatically discover and map all of the traffic flows within and through a datacenter are invaluable at this point.

    Then we move onto enforcement and maintenance of those rules on an ongoing basis, and this is where a security policy management solution is truly critical. All this complexity and dynamism cannot be managed manually. Each time a new business application is introduced, or an existing one removed or amended, the security policies also need to change–and these changes could be happening on a daily or even an hourly basis in a large organization.

    Automating the Management Process

    So, given the flexibility and rapid changes that SDN enables, how should organizations approach managing and maintaining security policies across their entire enterprise network? The most effective way is with an automation solution that holistically supports the SDN environment and its security controls, alongside existing traditional on-premise firewall estates.

    It’s important to note that the SDN deployment will be subjected to the same compliance and auditing requirements as existing networks. The security management solution must be capable of providing visibility across both physical and virtual network functions so that the overall compliance status can be centrally monitored and logged for audit purposes.

    Automated security policy management solutions generate filtering policies based on enabling only the traffic required for every application in the datacenter. This is a way of approaching intent-based networking, which comes back to looking at the components of each individual application and how they are communicating with each other. Furthermore, automated security policy management solutions audit and record every single change that is made across the network, making it easier to demonstrate compliance continuously.

    With the right automation solution, IT and security teams can eliminate time-consuming, error-prone manual security processes, such as connectivity discovery and mapping, migrating and ongoing maintenance of their environments. This frees up the teams to strategically maximize the benefits of the SDN deployment, and reap its rewards of increased flexibility and enhanced network security.

  • Accelerating IoT by Switching Gears to 5G

    Accelerating IoT by Switching Gears to 5G

    Unprecedented breakthroughs in technology have often resulted in the emergence of disruptive technologies and outstanding innovations. A major development in one technology always fuels the growth and advancement of several other technology domains and industries that take advantage of it, resulting in a need to transform businesses to address new opportunities.

    The evolution and development of various generations of mobile wireless technologies—mobile phones, mobile application development, eCommerce, banking, transportation, hotels, etc.—have seen a cascading impact on the growth and advancement of various applications. We are about to witness a similar multi-dimensional growth in several industries with the advent of the 5G wireless technology. With speeds that could be at least 10 times faster than 4G networks, 5G is expected to create pathbreaking opportunities for innovation and development in a variety of domains including but not limited to education, IoT, artificial intelligence (AI) and health care.

    5G networks offer three major benefits, bigger channels, reduced latency and scalability, which allow the connection to a large number of sensors and devices. This combination will enable the government and other industries to introduce advanced digital initiatives involving AI, machine learning (ML), Industrial IoT (IIoT) and a variety of other data intensive applications.

    This article focuses on the effect of 5G networks on IoT, and the role that DevOps could play in this mix.

    Where Does 5G Fit with Regards to IoT?

    At a high level, the focus areas for the five generations of mobile network technologies can be summarized as: 1G, voice; 2G, voice and texting; 3G, voice, texting and data; 4G, everything as in 3G but much faster; and 5G is expected to be everything in 4G but extremely faster. 

    IoT devices employ a wide range of wireless technologies such as WiFi and Bluetooth, in addition to cellular technologies such as GSM, LTE, 4G and 5G. In the field of IoT, cellular technologies such as 4G, have helped a great deal with regards to device provisioning and device management. These technologies have also improved and ensured coverage, performance, reliability and security of IoT devices and applications.

    5G brings in a variety of other benefits that are not available with 4G. The speed, higher capacity and low latency of 5G will make it more ideal for simultaneously connecting a large number of devices. Further, additional enhancements made by some 5G service providers aim at expanding the frequencies for data transfer by digital cellular technologies. These features will also make 5G a major enabler in applications that use IoT where real-time performance and decision making are critical. Remote medical diagnosis and remote surgery are some examples where 5G’s ultra-low latency will help improve the virtual and augmented reality experience, making them more powerful tools in the medical industry—especially at a time of crisis like the currently prevalent COVID-19 pandemic. 

    The bandwidth reliability and resiliency offered by 5G will pave the way for several new applications for IIoT systems. For example, factors such as operator productivity in manufacturing, reduction in cost of quality management and enhanced quality through continuous monitoring and improvement, are some examples where IIoT can be made more effective with the use of 5G.

    The volume of real-time data exchanges with IIoT devices will be greatly increased with 5G. This helps with obtaining more frequent and reliable data on several KPIs in manufacturing, worker productivity, root-cause analysis, etc. Predictive maintenance, which is turning out to be a major use case for 5G and IIoT, aims at predicting failures before they occur by leveraging AI.

    The Difference that 5G Makes on IoT Data 

    Prior to the advent of 5G, technology required to offer a higher bandwidth and reliable network connectivity were quite limited and have further prevented from realizing the fullest potential of several edge devices. These devices can potentially generate and transmit large volumes of data that can be processed and analyzed by cloud-based applications. With 5G, there will be a sharp increase in the capture and use of valuable data from edge devices leading to greater insights and predictive analytics on IoT implementations.

    5G technology offers a significant increase in transmission bandwidth, theoretically up to 10 Gbps, as opposed to 4G which only offers 100 Mbps. This increase in bandwidth will result in significant growth in the volume and quality of IoT data and a proportional growth in AI applications leveraging ML and big data. The mass volumes of data created by IoT under the influence of 5G have the power to revolutionize everything, from education to healthcare to manufacturing and even autonomous vehicles.

    With 5G, there will be a surge in the volume of data generated by sensors, cameras, drones and edge IoT devices. Integration of data from different sources will lead to the development of several large data-intensive applications that help draw valuable insights regarding the domains in which they are implemented. The convergence of 5G technology, IoT and data analytics will also pave the way for innovation and several new business opportunities. IoT applications leveraging 5G technology will proliferate wearables, smart home appliances, industrial automation and also future self-driven vehicles.

    All Things Considered

    There is absolutely no doubt that IoT is already taking the world by storm. The power of IoT, when harnessed with the power of 5G technology, will certainly lead to several innovative approaches and open up new business opportunities. Overall, the speed, reliability and low-latency offered by 5G makes it ideal for connecting a large number of IoT devices.

    IIoT devices will find a great use for 5G as they can now collect and report large volumes of real-time data from manufacturing units and sensors, helping companies obtain valuable insights and take well informed decisions. The large bandwidth supported by 5G additionally provides edge devices the ability to transmit larger volumes of data more frequently to applications that can process and use the data effectively for AI and ML.

    We will definitely see the industry witness a sharp growth in IoT, AI and ML applications relatively soon, given the fast growth of 5G and the enhancements that several service providers are already making in this technology.

  • AWS Adds GUI to Snow Edge Computing Family

    AWS Adds GUI to Snow Edge Computing Family

    Amazon Web Services (AWS) this week announced it has added a graphical user interface (GUI) tool dubbed AWS OpsHub for Snow Family to provide an alternative to the command-line interface (CLI) tool it makes available to manage its family of Snow appliances deployed in on-premises environments.

    At the same time, AWS announced it is making available additional Snowball storage appliances that are 25% faster than previous generations thanks to additional memory, support for more virtual CPUs and 100GB networking.

    Finally, AWS is also making it possible to control access to Snow appliance via AWS Identity and Access Management (IAM) and the ability to automate tasks using AWS Systems Manager.

    Bill Vass, vice president of technology for AWS, said organizations can now build storage clusters that are now as large as 1.4PB using Snow appliances.

    AWS originally rolled out Snow appliances to provide an easier way to upload massive amounts of the data to a public cloud. Once an organization loads data on to an appliance, it is physically shipped to AWS. Once there, AWS personnel transfer that data on to the AWS cloud.

    However, with the rise of edge computing, AWS is now also employing Snowball appliances to drive hybrid applications in internet of things (IoT) and other environments. AWS now makes available a Greengrass framework for building hybrid cloud applications. The Snow appliance family provides a more efficient and secure alternative to the rival edge computing platform from Dell Technologies, said Vass.

    The GUI from AWS is intended to make it easier for the average IT administrator to provision Snow appliances, which previously would have been accessible only to IT professionals who had mastered the Snow CLI. AWS is even going so far as to include cartoons that demonstrate how to provision its appliances.

    While AWS clearly dominates the public cloud, it is not clear to what degree it will be able to extend that dominance to edge computing. AWS is counting on the fact that large numbers of edge computing applications will need to be tightly integrated with application workloads running on its public cloud. Providers of traditional data center platforms are also vying to become the providers of those same platforms, all of which now can be centrally managed via the cloud.

    Edge computing platforms will, of course, vary widely in size depending on the use case. However, there may come a day soon when the total number of workloads deployed at the edge exceeds the number of workloads in the cloud. The amount of compute and storage horsepower at the edge will be crucial as organizations look to deliver next-generation applications that process and analyze data real-time, especially as 5G wireless computing networks simultaneously make more network bandwidth available.

    AWS may not be the first IT vendor that comes to mind when it comes to edge computing platforms, but it is signaling its intention to be a lot more than just a provider of cloud computing services.

  • Embracing the Journey to Public Cloud

    Embracing the Journey to Public Cloud

    One of the fascinating competitions in today’s business world is the one between the digital disruptors—companies whose business vision is rooted in technology and driven by the cloud—and the so-called incumbents.

    One sector where this competition is particularly intense is financial services. In this sector, the digital-first companies typically don’t compete with banks and other financial institutions directly. Instead, they target specific functions based on a clear—and often data-driven—understanding of what customers want. This strategy has proven particularly successful with millennials. For example, until recently the norm for giving money to a friend or family member was to write a check. Now, almost two-thirds of 20- and 30-year-olds use payment apps, such as Venmo.

    In healthcare, a different pattern is emerging, one where digital-first giants either buy or innovate their way into the sector. Examples include Amazon’s billion-dollar acquisition of the online pharmacy PillPack and the new Apple Watch, which is capable of taking electrocardiograms.

    Whatever the sector, digital disruptors have one characteristic in common. They leverage the capabilities of the cloud to the maximum extent possible. A shift in power toward digital-first companies is underway, and the cloud plays a major role in helping these companies establish themselves.

    Many incumbents are just now taking their first steps on the journey to the cloud, and still working on the challenges involved in migrating their existing legacy applications to more scalable and agile public cloud environments. While they’re engaged in this process, digital insurgents are already exploiting the full potential of the cloud to deliver solutions that meet emerging customer needs associated with today’s evolving lifestyles.

    In highly regulated industries, such as financial services and healthcare, major brands will not necessarily see an immediate decline in their customer base, nor profits. Nonetheless, digital-first companies are capturing millions of customers annually, and this growth poses a considerable challenge over time. Embracing the journey to public cloud is crucial for legacy enterprises.

    The most successful cloud-based disruptors use experimental sandboxes as a critical component of development. The public cloud can drive progress toward almost any business goal involving IT—operational transformation, new market penetration, new product launches, automation.

    Digital transformation to the public cloud is also the only way companies can leverage storage scalability and the essential innovations of the open-source community. There are still lingering concerns among executives in highly regulated, data-sensitive industries concerning privacy and regulatory compliance, and these can lead to hesitation. The face is, public clouds have been in place for over two decades now, and their security is often superior to older on-premise security. Incumbents can, therefore, tap into the public cloud to ensure safety for mission critical workloads.

    To accelerate the transition to the public cloud, consider the following best practices.

    Learning to Fail Fast and Learn from Experience More Quickly

    The Silicon Valley maxim to fail fast may run counter to incumbent corporate culture, but it is the best path to success in the new digital reality. The key is being able to learn from failures quickly and adjust accordingly.

    Partnering for Progress

    A digital native approach to business is often lacking in the corporate culture of incumbents. Cloud partners that have a digital disruption in their DNA can play an important role in driving cultural renewal at every level of the organization. A reliable cloud service partnership can accelerate concepts, pilots, staffing and other mechanisms designed to deliver value quickly and securely.

    Re-Examining Compliance Processes

    Operations should be streamlined to transform enterprise IT to be well-suited for the cloud. Companies can apply artificial intelligence to supplement human intervention, and encourage cloud adoption among employees. First, building a solid foundation, then working your way up, enables businesses to make important changes that transform the enterprise into an environment that is compliant by design.

    Successfully competing with digital natives means using the cloud to find new opportunities to streamline and better comprehend customer needs and behaviors. It also means being unafraid to change time-honored business practices. At the same time, in highly regulated and data-sensitive industries, compliance and security must be prioritized. Cloud transformation has quickly become vital for companies in all sectors and represents an essential foundation for future business success.

  • LF Edge Moves Open Networking Push Forward

    LF Edge Moves Open Networking Push Forward

    A vendor-neutral initiative dubbed the State of the Edge was acquired this week by LF Edge, an arm of The Linux Foundation focused on defining an open source stack of software for edge computing applications.

    The State of the Edge project will be merged with the existing Open Glossary of Edge Computing initiative that LF Edge already had in place. That combined initiative will now be known as the State of the Edge project within the larger umbrella of LF Edge projects.

    State of the Edge was launched by Vapor IO, Arm, Rafay Systems, Packet by Equinix and Edge Gravity by Ericsson to provide free research reports. Arpit Joshipura, general manager for networking, edge and Internet of Things (IoT) for The Linux Foundation, said that mission will continue as part of a larger effort to advance open software-defined networking software.

    The goal is to define stacks of software and implementation blueprints that will make it simpler for both telecommunications carriers and enterprise IT organizations to implement open source networking software both at the edge and in the cloud, said Joshipura.

    That’s critical because as IoT continues to evolve it’s apparent that IT and operations technology (OT) teams will converge, he added, noting the challenge is enabling organizations to achieve that goal around using a suite of programmable open source platforms that are truly interoperable with one another.

    Existing LF Edge projects include Akraino Edge Stack, an edge computing platform; Baetyl, a cloud-based management platform; EdgeX Foundry; a framework for sharing data between devices; Fledge, a set of application programming interfaces (APIs) for common administrative tasks; Home Edge, a platform for deploying consumer applications; and Project EVE, a virtualization engine.

    Interest in building and deploying applications at the network edge is on the rise in anticipation of 5G wireless networking services becoming widely available. Most of the organizations building those applications will be relying on best DevOps practices to achieve that goal. Less clear for now is the degree to which traditional network operations will be rolled up into those DevOps practices. The more programmable the networking environment becomes the more control each developer theoretically can have over the network services being accessed by their applications. However, network bandwidth is often a finite resource; there most likely will need to be some governing mechanism that determines how much network bandwidth any one application would be allowed to access at any given time.

    Of course, the open source community is not the only entity eyeing the rise of edge computing. Providers of commercial networking platforms ranging from Cisco Systems to VMware are all focused on enabling edge computing applications. Historically, open source platforms such as OpenStack have been embraced by carriers. However, within enterprise IT environments open source networking platforms have not gained much traction. The open source community will need to galvanize around a set of platforms and blueprints for edge computing platforms quickly. Otherwise, many organizations will most likely turn once again to commercial networking platforms to provide services to edge computing applications.

    — Mike Vizard

  • VMware Extends Network Virtualization Reach

    VMware Extends Network Virtualization Reach

    VMware today announced the general availability of an update to its NSX-T network virtualization software that adds support for NSX Federation, which enables IT teams to apply global policies and isolate domains to contain problems to a single zone. Other capabilities being added via NSX-T 3.0 include support for Level 3 Ethernet virtual private networks (L3 EVPN), multicast routing and improved data plane performance.

    In addition, VMware revealed that next month it will make available an update to VMware vRealize Network Insight that employs machine learning algorithms and statistics to discover application flows across a virtual network.

    VMware is also making generally available intrusion detection and prevention (IDS/IPS) capabilities to a previously announced software-defined firewall, along with support for AWS Direct Connect, VMware SD-WAN application and business policy statistics; enhanced Kubernetes visibility, integrations with the VMware Tanzu cloud service for managing containers; the latest release of VMware Cloud Foundation; and VMware NSX-T 3.0.

    Finally, VMware announced that VMware SD-WAN by VeloCloud software has now been integrated with the Microsoft Azure Zones portal to simplify provisioning on that public cloud.

    Tom Gillis, senior vice president and general manager for the Networking and Security Business Unit at VMware, said as part of the overall effort to reduce costs in the wake of the sudden downturn in the economy as a result of the COVID-19 pandemic, VMware expects many organizations will accelerate the rate at which they are transitioning to network virtualization to replace many of the hardware appliances they currently rely on. For the amount many organizations are paying for software and support for those appliances, they could be transitioning to a much more flexible approach to networking that provides a cloud experience spanning on-premises and public cloud computing platforms, he said.

    Gillis also noted it is now only a matter of time before VMware extends the control plane of its network virtualization software to the physical network underlay on which NSX-T is deployed. That capability will enable IT organizations to further reduce costs by eliminating the need to deploy multiple control planes, he said.

    According to VMware, the number of customers that are consuming some element of its Virtual Cloud Network portfolio now exceeds 15,000, which represents on average a 50% growth rate each fiscal year since May 2018.

    Gillis made it clear that in the months ahead a much larger swath of networking will become automated to drive down costs. Most organizations have adopted some level of network automation. However, Gillis said partial automation is an “oxymoron”—once most organizations start down the automation path the network becomes just as programmable as other IT infrastructure that is now managed as code.

    It may take a while for networks to come fully automated at a time when many network engineers still prefer to use command-line interfaces (CLIs) to manage network infrastructure. However, as networking continues to become more complex in the age of the cloud, it’s not so much a question of whether organizations will automate networking as it is to what degree and using which platform.

    — Mike Vizard

  • GigaSpaces to Provide Free Go-Live Services

    GigaSpaces to Provide Free Go-Live Services

    GigaSpaces, a provider of a platform for processing analytics data in real-time, will be making available professional services for free during the duration of the COVID-19 pandemic as part of a Go Live initiative to reduce the total cost of acquiring and implementing its platform.

    Yoav Einav, vice president of product for GigaSpaces, said the economic impact of the COVID-19 pandemic shows it’s apparent organizations of all sizes will need to reduce their IT costs. At the same time, many organizations will need to keep IT projects moving forward as nascent digital business strategies now become business continuity strategies, he said. Most of those business continuity plans will be contingent on providing a better digital customer experience based on real-time analytics.

    GigaSpaces has been building up its professional services capability for the past several months and plans to tap into the expertise of third-party IT services providers to make sure there is enough available expertise in the right place to meet anticipated Go Live demand.

    GigaSpacesIt’s still unclear to what degree IT projects will be impacted by the COVID-19 pandemic. Undoubtedly, many IT projects are being paused or outright canceled, especially in vertical industry segments that have been among the hardest hit. Organizations that are moving IT projects forward, however, should expect to IT vendors to help reduce the total cost of implementing those projects by providing free additional services, as in the case of GigaSpaces, or at the very least much more flexible payment terms.

    There are, of course, some vertical industry segments where organizations are building new applications that are highly relevant. One GigaSpaces customer, for example, is racing to build an application that will make it easier to find critical healthcare supplies that are frequently out of stock when needed most, noted Einav. Other organizations are simply moving to reduce costs by offloading queries from traditional databases.

    In many cases, organizations will be evaluating which platforms to employ to build these applications not just on the raw performance attributes of the platform but also how quickly those platforms can be implemented. As such, the robustness of the IT services ecosystem, including its overall DevOps acumen, will become a more critical evaluation criterion.

    In the meantime, a major transition away from legacy batch-oriented applications toward applications that process data in near real-time that has been gaining momentum now for several years should continue. Most organizations are now going to require the sub-second performance of a financial services application. However, visibility into supply chains in near real-time is becoming a bigger requirement, especially when many of the organizations that make up the supply chain are potentially not as economically resilient as they once were.

    Less clear is the rate at which the transition to near real-time applications will now occur. However, at a time when competition between organizations is about to become more fierce than at any time in recent memory, many organizations are about to discover how big a difference modern applications can really make.

    — Mike Vizard

  • Laying the Foundation for a Successful Digital Future

    Laying the Foundation for a Successful Digital Future

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

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

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

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

    The Issues of Network Modernization Raise Some Big Questions

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

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

    Meeting the Challenge 1: SD-WANs

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

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

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

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

    Meeting the Challenge 2: NFV

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

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

    Modernizing Your Network for Digital Transformation

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

    — Michael Cabra