GBI discusses their SD-WAN service and the selection of Nuage Networks VNS

| June 5, 2018

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In this video, Fahd Suleman, VP Pre-sales, Product and Services at GBI, provides an overview of GBI's business, the challenges they face and why they looked at SD-WAN. Fahd also shares GBI's technology evaluation process and why they chose Nuage Networks VNS as their SD-WAN solution.

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Mitoc Group

Mitoc Group is a technology company focusing on automation using cloud native services. Our track record includes helping Fortune 500 companies migrate to public clouds, as well as establish devops and dataops processes using cloud native services and industry best practices. We deliver automations and business results in weeks instead of months.

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Artificial Intelligence Applications: Is Your Business Implementing AI Smartly?

Article | March 12, 2020

The book Design, Launch, and Scale IoT Services classifies the components of IoT services into technical modules. One of the most important of these is Artificial Intelligence (AI). This article is intended to supplement the book by providing insight into AI and its applications for IoT. After many years in the wilderness, AI is back on the hype curve and will change the world again. Or, will it? AI has always been interesting, but what has changed to justify the current hype?

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AI TECH

How safe is our quantum future?

Article | March 12, 2020

If you're my age, you will remember the critical premise of the 1992 classic "Sneakers" premise, starring Robert Redford and Ben Kingsley - a top-secret black box that can break the encryption of any computer system. Quantum computing is that "black box." In the next 2-7 years, quantum computers could change the face of cybersecurity. Once they can factor products of large prime numbers (the basis of current cryptography) (expected between 2024 and 2030) – existing cyber-defense mechanisms will be rendered obsolete. We need to plan for encryption in the quantum future. What is Quantum Computing? Classical computers use binary arithmetic - all numbers are a sequence of bits - either a 1 or a 0. However, a quantum bit (qubit) exists not as a 0 or 1 but as a superposition of the two (think Schrödinger's cat). Every additional qubit doubles the processing power of a quantum computer, allowing it to execute multiple computational paths simultaneously. Similarly, as per Grover’s algorithm, it is a known fact that quantum computing divides the key space of symmetric cryptography algorithms by two, meaning that their key sizes have to be doubled to keep the safety margin of today. In October 2019, Google demonstrated quantum supremacy with Sycamore. It performed a series of operations in 200 seconds that Google claimed would take a supercomputer about 10,000 years to complete. In December 2020, physicists from the University of Science and Technology of China in Shanghai performed a Gaussian boson sampling technique with their photon-based quantum computer, named Jiuzhang. They declared that Sunway TaihuLight (the fourth fastest supercomputer in the world) would require 2.5 billion years (approx. half the age of the Earth) to finish the computations done by their quantum computer in a mere 200 seconds. Cryptography: The gatekeepers of security As the wise Spider-Man said – "With great power comes great responsibility. And great risk.” Much of the world's encrypted data is protected using mathematical equations with millions of reasonable solutions. These encryption models are too complicated for even supercomputers to solve within an acceptable period, which quantum systems can quickly solve. Modern cryptography relies on symmetric and asymmetric standards. The significant difference is that symmetric cryptography is based on substitution and permutation (there is no underlying mathematical assumption) and uses a single key for encryption and decryption. In contrast, asymmetric key / public key cryptography uses two different keys for encryption and decryption. Since the mid-90s, researchers have theorized that quantum computers can break current public-key cryptographic (PKC) systems. Their ability to concurrently test multiple hypotheses (using Shor's factorization OR Grover's exhaustive search) at unprecedented speeds will make both asymmetric and symmetric cryptosystems redundant. Understanding 5G 5G is one of the most eagerly awaited technologies in the digital world, and with good reason. In the years ahead, 5G coupled with IoT, could revolutionize the integration of digital and physical worlds. What sets it apart from its predecessor? 5G speed - it is nearly 20x faster than 4G. An average-length movie takes 6 minutes to download on 4G and less than 20 seconds on 5G. 5G supports 10x more devices per sq. km. It will seamlessly handle many more devices within the same area – a boost for IoT infrastructure. 5G latency is 25x less than 4G. According to McKinsey, 5G will speed up the mainstream adoption of IoT across multiple industries: Transport, Manufacturing, Healthcare, to name a few. 5G and Quantum – the Perfect Storm While quantum systems provide the compute, 5G provides the channel to connect more than just mobile networks (self-driving cars, personal medical tech), thus expanding the 'threat surface.' In a 5G world, secured communications are a critical component of connectivity, and post-quantum cryptography will play a key role. Researchers globally are devising ways to embed quantum-safe cryptography into 5G networks without compromising QoS. I even came across a patent for a quantum-resistant 5G SIM card by a Swiss company that set an industry best practice in ITU-T X.1811 for quantum-safe 5G. Cryptocurrency Wallets: A prime candidate for Quantum hacking Imagine you forget the password of your Bitcoin wallet, which in theory had millions of dollars in the balance. With a quantum computer, you could unlock your wallet and save yourself many worries, which worries all cryptographers. If malicious players had a quantum computer, the first thing they would try and break is the Elliptic Curve digital signature algorithm, reverse-engineer your private key, forge your digital signature, and subsequently empty your wallet. Thankfully, we are still years away from that scenario, yet that is a telling tale for designing national digital currencies that are supposed to withstand the test of time. Likewise, this vital subject – including applications with legal consequences such as smart contracts enabled by blockchain technologies, which share the same technical basis and, therefore, vulnerabilities to quantum IT -, would need a dedicated article, hopefully soon as time enables it! The real question is: when will quantum computers become a threat to public-key cryptography? As of December 2020, IBM claims to have a 65 qubit quantum computer and already delivering a 53-qubit model to a client (it would take around 1500 qubits to hack Bitcoin private keys). Quantum computers could achieve the required processing power range from as soon as 2024 to as far as 2040 per estimate. How do we solve it? Public Key Cryptography enables over 4.5 billion users to securely access over 200 million websites and engage in over $3 trillion of e-commerce transactions. Further, an estimated 20% of all IT applications rely on PKC and an even higher percentage on symmetric cryptography. According to Prof. Davor Pavuna of the École Polytechnique Fédérale de Lausanne, "several quantum prototypes might already become functional in 2023 (specifically in China)," and that potentially poses a severe protection challenge much earlier!" Many companies are developing "post-quantum cryptography" (PQC) or "quantum-safe cryptography" (QSC) – algorithms whose security is not degraded by any known quantum computing algorithms. Typical ones are McEliece cryptosystem, Lattice-based cryptosystems, Code-based Cryptography, and Hash-based cryptography. While these developments promise 'quantum resistance,' they only reflect our current knowledge of quantum computing capabilities and have a relatively low benchmark set for their security. These methods aim to create mathematical problems that are too difficult for even a quantum computer to solve, with the US National Institute of Standards and Technology (NIST) planning to recommend a PQC standard by 2022-23 and already having done so specifically for hash-based signatures. Similarly, German BSI issued official guidance for using post-quantum key exchange mechanisms, somewhat differing from NIST, and the IETF standardized two hash-based signature schemes, LMS and XMSS, independently, also with differences. Last but not least, the ITU-T issued without much publicity an amended recommendation on IPTV security X.1197 Amd1 that provides comprehensive guidance on state-of-the-art standard PQC options available as of late 2019, for use in multimedia transmission, with a corrigendum issued in early 2020. Applying the Solution Post Quantum cryptography is a developing field. Although these algorithms are quantum-resistant in theory, there is an unpredictability about their efficacy. Secondly, these algorithms are heavy on memory and compute requirements, making it challenging to apply them universally. On the other hand, symmetric cryptography is more efficient and shows more resilience to quantum IT, yet needs an upgrade to accommodate larger key sizes. One such system I came across was a patent of the aforementioned Swiss company is eAES®, which enhances AES’s quantum resistance. It makes safely increasing the key size a reality (as per NIST’s IR 8105 guidance), a claim confirmed in a report by their competitor Kudelski Security on the former’s implementation for Intel® processors. The transition to PQC standards requires a staged approach. To successfully navigate the impending cryptographic change, companies and governments must embrace crypto-agility - the ability to rapidly adapt and switch between multiple cryptographic standards at varying levels. We must support algorithms from different standardization bodies such as NIST, ETSI, the ITU-T, ISO/IEC, and the IEEE in a connected world with fractured standards. Building a global quantum security alliance We are just laying the foundations of this new security ecosystem; however, more work is needed to drive broader adoption. While the academic, innovation labs, and specialist technical communities are making some progress, cha

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A Guide to Technical Debt Management

Article | March 12, 2020

In the ‘new normal’ world, digitalization is the core reason to drive businesses to success. As a result, these emerging technologies have given rise to technical debt. Of course, technical debt has always been a part of every IT and non-IT organization. But the evolution of the IT world has made companies invest more time to think about reducing tech debt. As the term consists of the word- debt, it gives a picture of being negative. Thus, technical debt is more or less like financial debt, but it also has good aspects. In this article, we will talk all about technical debt management and ways to deal with it. What Is Technical Debt? When a code design is not neat, has disjointed data structures, and is of poor quality, it gives rise to technical debt. If a code is designed in a hurry to meet strict deadlines, it may be written clumsily. For that particular period, the software may work perfectly well, but it starts bugging and stops working with time. And it becomes a difficult task to decode the coding and understand the problem as the code was not written neatly. The accumulation of work due to short-term decisions, unrealistic deadlines, shortage of resources, or just ‘lazy work’ leads to technical debt. Every organization has technical debt. Take note that this debt can never be zero. But the important part is to deal with technical debt management. It cannot be ‘paid off’ entirely but can be minimized and managed. Types of Technical Debt Various reasons lead to technical debt. Some are deliberate, and some are accidental. Whatever is the reason, if you notice any of the below actions implemented in your organization, consider it as a red flag. Then, identify the reasons for technical debt for precise technical debt management. Complex Architecture This is one primary reason that leads to technical debt. Of course, the coding should be precise and straightforward. But sometimes, due to limited time and resources, a complex architecture is created even for the simplest code. And if not mended with time, this leads to various problems along with technical debt. Thus complexity in products, processes, and applications should be simplified with time. Software Entropy This is also known as bit-rot. Software entropy occurs when developers write codes for the updates of the same software. As a result, the coding gains maximum complexity. And after a point, it gets unsolvable. Thus the software quality deteriorates, leading to errors and reduced usability. The solution to this is refactoring, which we will discuss later in the article. Accidental Tech Debt This type of tech debt occurs when there is sudden evolution in technology. For example, if the code was simple and precise but not meant to be adapted or updated with the changing scenario, accidental technical debt occurs. It leads to a wastage of time and resources in the future. Thus, this debt is resolved by dedicating time to update the code and system quickly. Ways to Handle Technical Debt Management When the engineering or developer’s team takes shortcuts to meet deadlines or finish the project early, it leads to more work in the long run. We understand that sometimes these demands are unavoidable, but the team needs to come back and resolve the issues to save the organization from technical debt. For starters, an organization must identify the causes of technical debt and deal with them accordingly. Here are some of the ways of technical debt management and how to manage them in the future. Identify the Source The best way to avoid and tackle technical debt is to identify the source. This can be done by having a conversation with the team as to why this debt occurred? For example, if the IT team was asked to design healthcare software within two months due to the project's urgency, the team will say that the reason for complex coding was the time constraints. As a result, you are identifying technical debt sources. They may have occurred due to time, resources, or system constraints. Once you identify the root cause, there is always a way to go back and solve the issue to avoid getting buried in technical debt. This is the first step towards technical debt management. Track Technical Debt You will be appalled to know that 7% of organizations track technical debt to minimize them. And they are a significant success. Tracking technical debt is as important as identifying it. When a team keeps track of technical debt, it is easy for them to forecast the time and resources required to pay it off. Digital Documentation This is building a roadmap while writing code. It makes sure that the entire team is on the same page while developing the software. The benefit of this documentation is that whenever there is an update or an error wherein the entire code requires to be reworked, it gets easier for any developer to work on it. This is a precise way to prevent the tech-debt burden. Maintain Agility & Testing This technique is paving the way for technical debt management. However, developing agile software and maintaining its agility through time are two different things. To reduce the technical debt, you need to maintain software agility by updating it on a timely basis. But be sure to make this update process clean and qualitative. Try not to skip testing of the software for whatsoever reasons. Testing of the software is essential to stop the build-up of technical debt. However, do not substitute manual testing for automated testing. It can prove to be a significant hurdle in the team’s agile process. Refactoring Dedicate time to understand and pay off technical debt. Even when you avoid errors and follow all the suitable approaches, there are chances of technical debt. Sometimes these may happen due to the client’s urgent demands or limited bandwidth to perform tasks. Whenever this happens, take out time and treat technical debt as a business problem and not a technical one. This is an intelligent way of handling technical debt management. Refactoring means going back to the developed codes in haste for many reasons and cleansing them. This does not affect the external working of the code but cleans the code and makes it future-ready. Furthermore, such timely cleaning of codes reduces technical debt significantly. How Is Technical Debt Good? Technical debt is not always bad. Sometimes the code building is done in haste and works precisely the way it should. The updating of codes is also seamless. At such times technical debt is regarded as a good thing. This usually happens in applications that have simple processes. Technical debt is also good in software that requires timely development and not bug fixes. The Conclusion Technical debt is required to stay ahead in the competition. But see to it that it is tackled and minimized in the best possible way. Procrastination is the enemy of success. And this is highly true in the case of technical debt. It will get more expensive the longer you hold it. So ensure that your team takes out regular time from their schedule for minimizing technical debt. Technical debt management will help your team to perform better, improve agility and deliver exceptional results. Frequently Asked Questions What drives tech debt? Tech debt occurs when the team cannot write a clean code due to deadlines or limited resources. The tech debt worsens if the team does not go back and dedicate time to clean the code. How do you handle tech debt? There are specific ways to handle technical debt. These include: Identifying the reasons that led to technical debt Integrate metrics in your strategy Digital documentation Refactoring Knowing that tech debt is not always bad What are the types of technical debt? There are majorly three main types of technical debt. Deliberate creation of complex software Software entropy Accidental tech debt { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "What drives tech debt?", "acceptedAnswer": { "@type": "Answer", "text": "Tech debt occurs when the team cannot write a clean code due to deadlines or limited resources. The tech debt worsens if the team does not go back and dedicate time to clean the code." } },{ "@type": "Question", "name": "How do you handle tech debt?", "acceptedAnswer": { "@type": "Answer", "text": "There are specific ways to handle technical debt. These include: Identifying the reasons that led to technical debt Integrate metrics in your strategy Digital documentation Refactoring Knowing that tech debt is not always bad" } },{ "@type": "Question", "name": "What are the types of technical debt?", "acceptedAnswer": { "@type": "Answer", "text": "There are majorly three main types of technical debt. Deliberate creation of complex software Software entropy Accidental tech debt" } }] }

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AI, ML explosion will be the game changer

Article | March 12, 2020

Technologies like Artificial Intelligence and Machine Learning will enable wider audience to get access to space analytics and insights. Assisted processes through software created by Machine Learning will enable users to run sophisticated models on their data. That is what I see happening in the next few years. It’s not about replacing, it’s about assisting new types of users to get access to the type of analysis that wasn’t accessible before. Automated Machine Learning is what we are going to be seeing in the coming years. It will expand the customer/ user base of spatial analytics by making it more accessible.

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Spotlight

Mitoc Group

Mitoc Group is a technology company focusing on automation using cloud native services. Our track record includes helping Fortune 500 companies migrate to public clouds, as well as establish devops and dataops processes using cloud native services and industry best practices. We deliver automations and business results in weeks instead of months.

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