Daily Tech Digest - July 23, 2023

Sustainable Computing - With An Eye On The Cloud

There are two parts to sustainable goals: 1. How do cloud service providers make their data centers more sustainable?; 2. What practices can cloud service customers practice to better align with the cloud and make their workloads more sustainable? Let us first look at the question of how businesses should be planning for sustainability. How should they bake in sustainability aspects as part of their migration to the cloud? The first aspect to consider, of course, is choosing the right cloud service provider. It is essential to select a carbon-thoughtful provider based on its commitment to sustainability as well as how it plans, builds, powers, operates, and eventually retires its physical data centers. The next aspect to consider is the process of migrating services to an infrastructure-as-a-service deployment model. Organizations should carry out such migrations without re-engineering for the cloud, as this can help to drastically reduce energy and carbon emissions as compared to doing so through an on-premise data center. 

The Intersection of AI and Data Stewardship: A New Era in Data Management

In addition to improving data quality, AI can also play a crucial role in enhancing data security and privacy. With the increasing number of data breaches and growing concerns around data privacy, organizations must ensure that their data is protected from unauthorized access and misuse. AI can help organizations identify potential security risks and vulnerabilities in their data infrastructure and implement appropriate measures to safeguard their data. Furthermore, AI can assist in ensuring compliance with various data protection regulations, such as the General Data Protection Regulation (GDPR), by automating the process of identifying and managing sensitive data. Another area where AI and data stewardship intersect is in data governance. Data governance refers to the set of processes, policies, and standards that organizations use to ensure the proper management of their data assets. AI can help organizations establish and maintain robust data governance practices by automating the process of creating, updating, and enforcing data policies and rules. 

Saga Pattern With NServiceBus in C#

In its simplest form, a saga is a sequence of local transactions. Each transaction updates data within a single service, and each service publishes an event to trigger the next transaction in the saga. If any transaction fails, the saga executes compensating transactions to undo the impact of the failed transaction. The Saga Pattern is ideal for long-running, distributed transactions where each step needs to be reliable and reversible. It allows us to maintain data consistency across services without the need for distributed locks or two-phase commit protocols, which can add significant complexity and performance overhead. ... The Saga Pattern is a powerful tool in our distributed systems toolbox, allowing us to manage complex business transactions in a reliable, scalable, and maintainable way. Additionally, when we merge the Saga Pattern with the Event Sourcing Pattern, we significantly enhance traceability by constructing a comprehensive sequence of events that can be analyzed to comprehend the transaction flow in-depth.

Efficiency and sustainability in legacy data centers

A recent analyst report found a “wave of technological trends” is driving change throughout the data center sector at an unprecedented pace, with “rapidly diversifying business applications generating terabytes of data.” All that data has to go somewhere, and as hyperscale cloud providers push some of their workloads away from large, CapEx-intensive centralized hubs into Tier II and Tier III colocation markets — it’s looking like colos may be in greater demand than ever before. However, these circumstances pose a serious challenge for the colocation sector, as “the resulting workloads have exploded onto legacy data center infrastructures”, many of which may be “ill-equipped to handle them.” Now, the colocation market finds itself caught between two conflicting macroeconomic forces. On one hand, the growth in demand puts greater pressure on operators in Tier II and III markets to build more facilities, faster, to accommodate larger and more complex workloads; on the other, the existential need to reduce carbon emissions and slash energy consumption is vital.

A quantum computer that can’t be simulated on classical hardware could be a reality next year

The current-generation machines are still very much in the noisy era of quantum computing, Ilyas Khan, who founded Cambridge Quantum out of the University of Cambridge in 2014 and now works as chief product officer, told Tech Monitor that we’re moving into the “mid-stage NISQ” where the machines are still noisy but we’re seeing signs of logical qubits and utility. Thanks to error correction, detection and mitigation techniques, even on noisy error-prone qubits, many companies have been able to produce usable outcomes. But at this stage, the structure and performance of the quantum circuits could still be simulated using classical hardware. That will change next year, says Khan. “We think it’s important for quantum computers to be useful in real-life problem solving,” he says. “Our current system model, H2, has 32 qubits in its current instantiation, all to all connected with mid-circuit measurement.”

Protecting your business through test automation

The inadequate pre-launch testing forces teams to then scramble post-launch to fix faulty software applications with renewed urgency, with the added pressure of managing the potential loss of revenue and damaged brand reputation caused by the defect. When the faulty software reaches end users, dissatisfied customers are a problem that could have far longer-reaching effects as users pass on their negative experiences to others. The negative feedback could also prevent potential new customers from ever trying the software in the first place. So why is software not being tested properly? Changing customer behaviours in the financial services sector, as well as increased competition from digital-native fintech start-ups, have led many organisations to invest in a huge amount of digital transformation in recent years. With companies coming under more pressure than ever to respond to market demands and user experience trends through increasingly frequent software releases, the sheer volume of software needing testing has skyrocketed, placing a further burden on resources already stretched to breaking point.

Implementing zero trust with the Internet of Things (IoT)

There’s a strongly held view that it simply isn’t possible to trust any IoT device, even if it’s equipped with automatic security updating. “As a former CIO, my guidance is that preparation is the best defense,” Archundia tells ITPro. IoT devices are often just too much of a risk; they’re too much of a soft entry point into the organization to overlook them. It’s best to assume each device is a hole in an enterprise’s defenses. Perhaps each device won’t be a hole at all times, but some may be for at least some of the times. So long as the hole isn’t plugged, it can be found and exploited. That’s actually fine in a zero trust environment, because it assumes every single act, by a human or a device, could be malicious. ... “Because zero trust focuses on continuously verifying and placing security as close to each asset as possible, a cyber attack need not have far-reaching consequences in the organization,” he says. “By relying on techniques such as secured zones, the organization can effectively limit the blast radius of an attack, ensuring that a successful attack will have limited benefits for the threat agent.”

US Data Privacy Relationship Status: It’s Complicated

The American Data Privacy and Protection Act (ADPPA) is a bill that if passed would become the first set of federal privacy regulations that would supersede state laws. While it passed a House of Representatives commerce committee vote by a 53-2 margin in July 2022, the bill is still waiting on a full House vote and then a Senate vote. In the US, 10 states have enacted comprehensive privacy laws, including California, Colorado, Connecticut, Indiana, Iowa, Montana, Tennessee, Texas, Utah, and Virginia. More than a dozen other states have proposed bills in various states of activity. The absence of an overarching federal law means companies must pick and choose based on where they happen to be doing business. Some businesses opt to start with the most stringent law and model their own data privacy standards accordingly. The current global standard for privacy is Europe’s 2018 General Data Protection Regulation (GDPR) and has become the model for other data privacy proposals. Since many large US companies do business globally, they are very familiar with GDPR. 

KillNet DDoS Attacks Further Moscow's Psychological Agenda

Mandiant's assessment of the 500 DDoS attacks launched by KillNet and associated groups from Jan. 1 through June 20 offers further evidence that the collective isn't some grassroots assembly of independent, patriotic hackers. "KillNet's targeting has consistently aligned with established and emerging Russian geopolitical priorities, which suggests that at least part of the influence component of this hacktivist activity is intended to directly promote Russia's interests within perceived adversary nations vis-a-vis the invasion of Ukraine," Mandiant said. Researchers said KillNet and its affiliates often attack technology, social media and transportation firms, as well as NATO. ... To hear KillNet's recounting of its attacks via its Telegram channel, these hacktivists are nothing short of devastating. The same goes for other past and present members of the KillNet collective, including KillMilk, Tesla Botnet, Anonymous Russia and Zarya. Recent attacks by Anonymous Sudan have involved paid cloud infrastructure and had a greater impact, although it's unclear if this will become the norm.

Agile vs. Waterfall: Choosing the Right Project Methodology

Choosing the right project management methodology lays the foundation for effective planning, collaboration, and delivery. Failure to select the appropriate methodology can lead to many challenges and setbacks that can hinder project progress and ultimately impact overall success. Let's delve into why it's crucial to choose the right project management methodology and explore in-depth what can go wrong if an unsuitable methodology is employed. ... The right methodology enables effective resource allocation and utilization. Projects require a myriad of resources, including human, financial, and technological. If you select an inappropriate methodology, you can experience inefficient resource management, causing budget overruns, underutilization of skills, and time delays. For instance, an Agile methodology that relies heavily on frequent collaboration and iterative development may not be suitable for projects with limited resources and a hierarchical team structure.

Quote for the day:

"People leave companies for two reasons. One, they don't feel appreciated. And two, they don't get along with their boss." -- Adam Bryant

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