September 17, 2024

Dedicated Cloud: What It’s For and How It’s Different From Public Cloud

While dedicated cloud services give you a level of architectural control you will not get from public clouds, using them comes with trade-offs, the biggest one being the amount of infrastructure engineering ability needed. But if your team has concluded that a public cloud isn’t a good fit, you probably know that already and have at least some of that ability on hand. ... Ultimately, dedicated cloud is about keeping control and giving yourself options. You can quickly deploy different combinations of resources, interconnecting dedicated infrastructure with public cloud services, and keep fine-tuning and refining as you go. You get full control of your data and your architecture with the freedom to change your mind. The trade-off is that you must be ready to roll up your sleeves and manage operating systems, deploy storage servers, tinker with traffic routing and do whatever else you need to do to get your architecture just right. But again, if you already know that you need more knobs than you can turn using a typical public cloud provider, you are probably ready anyway.

Building a More Sustainable Data Center: Challenges and Opportunities in the AI Era

Sustainability is not just a compliance exercise on reducing the negative impact on the environment, it also can bring financial benefits to an organization. According to Gartner’s Unlock the Business Benefits of Sustainable IT Infrastructure report, “[Infrastructure and operations’] contribution to sustainability strategies tends to focus on environmental impact, but sustainability also can have a significant positive impact on non-environmental factors, such as brand, innovation, resilience and attracting talent.” As a result, boards should embrace the financial opportunities of companies’ Environmental, Sustainability, and Governance (ESG) compliance rather than consider it just another unavoidable compliance expense without a discernable return on investment (ROI). ... To improve data center resilience, Gartner recommends that organizations expand use of renewable energy using a long-term power purchase agreement to contain costs, generate their own power where feasible, and reuse and redeploy equipment as much as possible to maximize the value of the resource.

Data Business Evaluation

Why data businesses? Because they can be phenomenal businesses with extremely high gross margins — as good or better than software-as-a-service (SaaS). Often data businesses can be the best businesses within the industries that they serve. ... Data aggregation can be a valuable way to assemble a data asset as well, but the value typically hinges on the difficulty of assembling the data…if it is too easy to do, others will do it as well and create price competition. Often the value comes in aggregating a long tail of data that is costly to do more than once either for the suppliers or a competitive aggregator. ... The most stable data businesses tend to employ a subscription business model in which customers subscribe to a data set for an extended period of time. Subscriptions models are clearly better when the subscriptions are long term or, at least, auto-renewing. Not surprisingly, the best data businesses are generally syndicated subscription models. On the other end, custom data businesses that produce data for clients in a one-off or project-based manner generally struggle to attain high margins and predictability, but can be solid businesses if the data manufacturing processes are optimized?

Leveraging AI for water management

AI is reshaping the landscape of water management by providing predictive insights, optimising operations, and enabling real-time decision-making. One of AI’s key contributions is its ability to forecast water usage patterns. AI models can accurately predict water demand by analysing historical data and considering variables like weather conditions, population trends, and industrial activities. This helps water utilities allocate resources more effectively, minimising waste while ensuring consistent supply to communities. Water utilities can also integrate AI systems to monitor and optimise their supply networks. ... One of the most critical applications of AI is in water quality monitoring. Traditional methods of detecting water contaminants are labour-intensive and involve periodic testing, which can result in delayed responses to contamination events. AI, on the other hand, can process continuous data streams from IoT-enabled sensors installed in water distribution systems. These sensors monitor variables like pH levels, temperature, and turbidity, detecting changes in water quality in real time. AI algorithms analyse the data, triggering immediate alerts when contaminants or irregularities are detected.

History of Cybersecurity: Key Changes Since the 1990s and Lessons for Today

Most cyber attackers hadn’t considered using the internet to pursue financial gain or cause serious harm to organizations. To be sure, financial crimes based on computer hacking took place in the '90s and early 2000s. But they didn't dominate the news in an endless stream of cautionary tales, and most people thought the 1995 movie Hackers was a realistic depiction of how hacking worked. ... By the mid-2000s, however, internet-based attacks became more harmful and frequent. This was the era when threat actors realized they could build massive botnets and then use them to distribute spam or send scam emails. These attacks could have caused real financial harm, but they weren't exactly original types of criminal activity. They merely conducted traditional criminal activity, like scams, using a new medium: the internet. ... The 2010s were also a time of massive technological change. The advent of cloud computing, widespread adoption of mobile devices, and rollout of Internet of Things (IoT) hardware meant businesses could no longer define clear network perimeters or ensure that sensitive data always remained in their data centers.?

Gateways to havoc: Overprivileged dormant service accounts

Dormant accounts go unnoticed, leaving organizations unaware of their access privileges, the systems they connect to, how to access them, and even of their purpose of existence. Their elevated privileges, lax security measures, and invisibility, make dormant service accounts prime targets for infiltration. By compromising such an account, attackers can gain significant access to systems and sensitive data, often without raising immediate suspicion for extended periods of time. During that time, cyber criminals can elevate privileges, exfiltrate data, disrupt operations, and install malware and backdoors, causing total mayhem completely undetected until it’s too late. The weaknesses that plague dormant accounts make them open doors into an organization’s system. If compromised, an overprivileged dormant account can give way to sensitive data such as customer PII, PHI, intellectual property, and financial records, leading to costly and damaging data breaches. Even without being breached, dormant accounts are significant liabilities, potentially causing operational disruptions and regulatory compliance violations.

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