Benefits of Monitoring Networks Proactively

February 7, 2019 | 46 views

To avoid events that end up adding cost in your daily IT operations, network teams stay on top of their toes, keeping a hawk eye on every ongoing network activity. And, why not? Network performance after all, is quantifiable, measurable and every CTO is responsible to show its impact on the bottom line. By extending the same monitoring capabilities into a mobile app, Lavelle Networks announced the world’s first mobile app to monitor SD-WAN networks – The CloudStation mobile Application.

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EXILANT is a leading provider of Information Technology (IT) Services and Custom products using various distributed models to clients worldwide. Our sphere of operations includes Application Lifecycle Management, Infrastructure Lifecycle Management & Product Lifecycle Management.

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SOFTWARE

AI's Impact on Improving Customer Experience

Article | July 14, 2022

To enhance the consumer experience, businesses all over the world are experimenting with artificial intelligenace (AI), machine learning, and advanced analytics. Artificial intelligence (AI) is becoming increasingly popular among marketers and salespeople, and it has become a vital tool for businesses that want to offer their customers a hyper-personalized, outstanding experience. Customer relationship management (CRM) and customer data platform (CDP) software that has been upgraded with AI has made AI accessible to businesses without the exorbitant expenses previously associated with the technology. When AI and machine learning are used in conjunction for collecting and analyzing social, historical, and behavioral data, brands may develop a much more thorough understanding of their customers. In addition, AI can predict client behavior because it continuously learns from the data it analyzes, in contrast to traditional data analytics tools. As a result, businesses may deliver highly pertinent content, boost sales, and enhance the customer experience. Predictive Behavior Analysis and Real-time Decision Making Real-time decisioning is the capacity to act quickly and based on the most up-to-date information available, such as information from a customer's most recent encounter with a company. For instance, Precognitive's Decision-AI uses a combination of AI and machine learning to assess any event in real-time with a response time of less than 200 milliseconds. Precognitive's fraud prevention product includes Decision-AI, which can be implemented using an API on a website. Marketing to customers can be done more successfully by using real-time decisioning. For example, brands may display highly tailored, pertinent content and offer to clients by utilizing AI and real-time decisioning to discover and comprehend a customer's purpose from the data they produce in real-time. By providing deeper insights into what has already happened and what can be done to facilitate a sale through suggestions for related products and accessories, AI and predictive analytics are able to go further than historical data alone. This increases the relevance of the customer experience, increases the likelihood that a sale will be made, and increases the emotional connection that the customer has with a brand.

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AI TECH

The Evolution of Quantum Computing and What its Future Beholds

Article | July 11, 2022

The mechanism of quantum computers will be entirely different from anything we humans have ever created or constructed in the past. Quantum computers, like classical computers, are designed to address problems in the real world. They process data in a unique way, though, which makes them a much more effective machine than any computer in use today. Superposition and entanglement, two fundamental ideas in quantum mechanics, could be used to explain what makes quantum computers unique. The goal of quantum computing research is to find a technique to accelerate the execution of lengthy chains of computer instructions. This method of execution would take advantage of a quantum physics event that is frequently observed but does not appear to make much sense when written out. When this fundamental objective of quantum computing is accomplished, and all theorists are confident works in practice, computing will undoubtedly undergo a revolution. Quantum computing promises that it will enable us to address specific issues that current classical computers cannot resolve in a timely manner. While not a cure-all for all computer issues, quantum computing is adequate for most "needle in a haystack" search and optimization issues. Quantum Computing and Its Deployment Only the big hyperscalers and a few hardware vendors offer quantum computer emulators and limited-sized quantum computers as a cloud service. Quantum computers are used for compute-intensive, non-latency-sensitive issues. Quantum computer architectures can't handle massive data sizes yet. In many circumstances, a hybrid quantum-classical computer is used. Quantum computers don't use much electricity to compute but need cryogenic refrigerators to sustain superconducting temperatures. Networking and Quantum Software Stacks Many quantum computing software stacks virtualize the hardware and build a virtual layer of logical qubits. Software stacks provide compilers that transform high-level programming structures into low-level assembly commands that operate on logical qubits. In addition, software stack suppliers are designing domain-specific application-level templates for quantum computing. The software layer hides complexity without affecting quantum computing hardware performance or mobility.

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SOFTWARE

Language Models: Emerging Types and Why They Matter

Article | August 8, 2022

Language model systems, often known as text understanding and generation systems, are the newest trend in business. However, not every language model is made equal. A few are starting to take center stage, including massive general-purpose models like OpenAI's GPT-3 and models tailored for specific jobs. There is a third type of model at the edge that is intended to run on Internet of Things devices and workstations but is typically very compressed in size and has few functionalities. Large Language Models Large language models, which can reach tens of petabytes in size, are trained on vast volumes of text data. As a result, they rank among the models with the highest number of parameters, where a "parameter" is a value the model can alter on its own as it gains knowledge. The model's parameters, which are made of components learned from prior training data, fundamentally describe the model's aptitude for solving a particular task, like producing text. Fine-tuned Language Models Compared to their massive language model siblings, fine-tuned models are typically smaller. Examples include OpenAI's Codex, a version of GPT-3 that is specifically tailored for programming jobs. Codex is both smaller than OpenAI and more effective at creating and completing strings of computer code, although it still has billions of parameters. The performance of a model, like its capacity to generate protein sequences or respond to queries, can be improved through fine-tuning. Edge Language Models Edge models, which are intentionally small in size, occasionally take the shape of finely tuned models. To work within certain hardware limits, they are occasionally trained from scratch on modest data sets. In any event, edge models provide several advantages that massive language models simply cannot match, notwithstanding their limitations in some areas. The main factor is cost. There are no cloud usage fees with an edge approach that operates locally and offline. As significant, fine-tuned, and edge language models grow in response to new research, they are likely to encounter hurdles on their way to wider use. For example, compared to training a model from the start, fine-tuning requires less data, but fine-tuning still requires a dataset.

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SOFTWARE

Low-code and No-code: A Business' New Best Friend

Article | July 5, 2022

Businesses are starting to integrate artificial intelligence (AI) into their workflow in greater numbers as a result of the growth of digital transformation and developments in machine learning (ML). As a result, platforms that need no coding, as well as their low-code counterparts, are becoming more popular. This development is a step toward computer science's long-term objective of automating manual coding. Low-code/no-code AI platforms will be beneficial to businesses in more data-driven industries like marketing, sales, and finance. AI can assist in a variety of ways, including automating invoicing, evaluating reports, making intelligent suggestions, and anticipating churn rates. How Does an Organization Look at Low-code/No-code as the Future? Developers and other tech-related positions are in high demand, particularly in the fields of AI and data science. Organizations have the chance to close the gap with the aid of citizen data scientists who don't require an AI professional to design unique AI solutions for many scenarios, thanks to low-code and no-code AI technologies. The demand for technological solutions and AI technologies is rising significantly as the technological landscape rapidly changes. AI systems, for example, require complex software that uses a lot of code, a variety of frameworks, and the Internet of Things (IoT). One person's capacity to comprehend every technical detail is strained by the array of complicated technology. Software delivery must be timely, effective, and secure while maintaining high standards. Conclusion Low-code AI solutions offer the speed, ease of use, and adaptability of ready-made software solutions while also drastically reducing the time to market for AI solutions and the cost of recruiting software and computer vision engineers. Organizations are free to construct the architecture, functionality, or pipeline that best suits their project, the sky being the limit. However, creating such unique models may be both costly and time-consuming. Therefore, employing low-code/no-code platforms would apply to particular pipeline actions that would streamline and accelerate the processes.

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EXILANT Technologies Private Limited

EXILANT is a leading provider of Information Technology (IT) Services and Custom products using various distributed models to clients worldwide. Our sphere of operations includes Application Lifecycle Management, Infrastructure Lifecycle Management & Product Lifecycle Management.

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A10 Networks DDoS Threat Intelligence Finds IoT Devices a Growing Part of Global DDoS Weapon Arsenals

IoT Business News | March 10, 2019

New Report Shows IoT Devices Using Machine-to-Machine Communications Protocol Are Increasingly Exploitable in Attacks. A10 Networks today announced the findings of a new report into the state of Distributed Denial of Service (DDoS) attack weapons and targets, showcasing the growing use of IoT devices in synchronised attacks on targets globally. The report describes the significant potential for attackers to use an IoT-related protocol, the Constrained Application Protocol (CoAP), deployed on IoT devices to marshal attacks. The A10 Networks report on the state of DDoS weapons in the first quarter of 2019 examines the types of weapons and attacks being used and where they are coming from. While the most prevalent types of weapons leverage other more established technologies and internet protocols, such as the Network Time Protocol (NTP), Domain Name System (DNS) resolvers, and the Simple Services Discovery Protocol (SSDP), CoAP-based devices represent a fast-emerging new weapon type in botnet arsenals, according to the report. The most common type of attack utilising many of these weapons is a reflective amplification attack through which attackers spoof a target’s IP address and send out requests for information to vulnerable servers that then send amplified responses back to the victim’s IP address overwhelming the capacity of the target’s servers.

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Veriflow Gives Enterprises Visibility Into Their Public Cloud Networks

eWeek | February 28, 2019

The company’s CloudPredict SaaS service enables businesses to be more proactive as their multicloud environments get more complex. Veriflow officials are rolling out a new service designed to give enterprises greater visibility and assurance into their network deployments into the public cloud, addressing a growing challenge as organizations continue to migrate more workloads into the cloud and adopt multicloud and hybrid cloud strategies. The vendor’s CloudPredict SaaS offering is aimed at giving enterprise network teams a clearer view of what’s happening in their public cloud networking environments, enabling them to more quickly detect and find problems and resolve any vulnerabilities or outages. As the use of public clouds continues to grow, being able to rapidly address problems along the network becomes crucial, according to Veriflow officials. “Although public cloud helps make it easy to rapidly spin up compute instances, it has made networking more difficult in several ways,” Brighten Godfrey, Veriflow co-founder and CTO, told eWEEK. “It’s important to understand what the cloud does for you, and what it doesn’t. Public cloud makes it easy to utilize resources on-demand, so you don’t have to deal with the physical hardware, but how to use it to get the job done—and done securely—is up to you.” Cloud deployments tend to start simply, often being spun up by a DevOps or cloud team, Godfrey said. However, “as cloud adoption has expanded, these deployments have become more complex and more integrated into the enterprise, often with many VPCs [virtual private clouds], critical security requirements and interconnection with hybrid and multicloud infrastructure.

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Service assurance challenges in virtualized, multi-cloud networks

RCRWireless News | February 20, 2019

What are the challenges for service assurance — and visibility and observability — as networks evolve toward virtualization, multi-cloud environments and edge computing? Network and service assurance needs are evolving rapidly, as more applications — both network functions that support telecom network operations, and enterprise applications — are becoming virtualized. SNS Research estimates that service provider SDN and NFV investments will have a compound annual growth rate of about 45% through 2020. Such deployments need assurance for both the underlying infrastructure as well as service assurance for the applications they are handling. RCR Wireless News asked a number of companies from around the service assurance space to weigh in on the topic, answering the question: What do you see as the biggest challenges for service assurance in an increasingly virtualized, multi-cloud network? Responses have been lightly edited. John English, senior marketing manager, NETSCOUT Systems: “I’ll talk about three, but I think there are more. Service assurance … has to be cloud-optimized, and by cloud-optimized, I mean that it’s built for the cloud. The most important piece of that is that it’s efficient and cost-effective in how it uses cloud resources. The compute and storage resources that are in the cloud — that’s not free, and that’s one of the realities I think that carriers are learning in the real world: that they have to deploy service assurance on cloud resources efficiently, or else it’s just expending revenues, and maybe more more expensive than the traditional physical world.

Read More

A10 Networks DDoS Threat Intelligence Finds IoT Devices a Growing Part of Global DDoS Weapon Arsenals

IoT Business News | March 10, 2019

New Report Shows IoT Devices Using Machine-to-Machine Communications Protocol Are Increasingly Exploitable in Attacks. A10 Networks today announced the findings of a new report into the state of Distributed Denial of Service (DDoS) attack weapons and targets, showcasing the growing use of IoT devices in synchronised attacks on targets globally. The report describes the significant potential for attackers to use an IoT-related protocol, the Constrained Application Protocol (CoAP), deployed on IoT devices to marshal attacks. The A10 Networks report on the state of DDoS weapons in the first quarter of 2019 examines the types of weapons and attacks being used and where they are coming from. While the most prevalent types of weapons leverage other more established technologies and internet protocols, such as the Network Time Protocol (NTP), Domain Name System (DNS) resolvers, and the Simple Services Discovery Protocol (SSDP), CoAP-based devices represent a fast-emerging new weapon type in botnet arsenals, according to the report. The most common type of attack utilising many of these weapons is a reflective amplification attack through which attackers spoof a target’s IP address and send out requests for information to vulnerable servers that then send amplified responses back to the victim’s IP address overwhelming the capacity of the target’s servers.

Read More

Veriflow Gives Enterprises Visibility Into Their Public Cloud Networks

eWeek | February 28, 2019

The company’s CloudPredict SaaS service enables businesses to be more proactive as their multicloud environments get more complex. Veriflow officials are rolling out a new service designed to give enterprises greater visibility and assurance into their network deployments into the public cloud, addressing a growing challenge as organizations continue to migrate more workloads into the cloud and adopt multicloud and hybrid cloud strategies. The vendor’s CloudPredict SaaS offering is aimed at giving enterprise network teams a clearer view of what’s happening in their public cloud networking environments, enabling them to more quickly detect and find problems and resolve any vulnerabilities or outages. As the use of public clouds continues to grow, being able to rapidly address problems along the network becomes crucial, according to Veriflow officials. “Although public cloud helps make it easy to rapidly spin up compute instances, it has made networking more difficult in several ways,” Brighten Godfrey, Veriflow co-founder and CTO, told eWEEK. “It’s important to understand what the cloud does for you, and what it doesn’t. Public cloud makes it easy to utilize resources on-demand, so you don’t have to deal with the physical hardware, but how to use it to get the job done—and done securely—is up to you.” Cloud deployments tend to start simply, often being spun up by a DevOps or cloud team, Godfrey said. However, “as cloud adoption has expanded, these deployments have become more complex and more integrated into the enterprise, often with many VPCs [virtual private clouds], critical security requirements and interconnection with hybrid and multicloud infrastructure.

Read More

Service assurance challenges in virtualized, multi-cloud networks

RCRWireless News | February 20, 2019

What are the challenges for service assurance — and visibility and observability — as networks evolve toward virtualization, multi-cloud environments and edge computing? Network and service assurance needs are evolving rapidly, as more applications — both network functions that support telecom network operations, and enterprise applications — are becoming virtualized. SNS Research estimates that service provider SDN and NFV investments will have a compound annual growth rate of about 45% through 2020. Such deployments need assurance for both the underlying infrastructure as well as service assurance for the applications they are handling. RCR Wireless News asked a number of companies from around the service assurance space to weigh in on the topic, answering the question: What do you see as the biggest challenges for service assurance in an increasingly virtualized, multi-cloud network? Responses have been lightly edited. John English, senior marketing manager, NETSCOUT Systems: “I’ll talk about three, but I think there are more. Service assurance … has to be cloud-optimized, and by cloud-optimized, I mean that it’s built for the cloud. The most important piece of that is that it’s efficient and cost-effective in how it uses cloud resources. The compute and storage resources that are in the cloud — that’s not free, and that’s one of the realities I think that carriers are learning in the real world: that they have to deploy service assurance on cloud resources efficiently, or else it’s just expending revenues, and maybe more more expensive than the traditional physical world.

Read More

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