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Quote for the day:

"Listen with curiosity, speak with honesty act with integrity." -- Roy T Bennett

What does aligning security to the business really mean?

“Alignment to me means that information security supports the strategy of the organization,” says Sattler, who also serves as a board director with the governance association . ... “It’s not enough to say it; you actually have to do it,” she explains. “There is a contingent of cybersecurity that sees itself as an island, implementing defense in depth in every corner of the organization, adopting all these frameworks and standards, but there is diminishing returns in doing that. So instead of saying, ‘This is our cybersecurity discipline and we’re doing all these things because the benchmarks tell us to,’ have to align their efforts to their organization’s business model.” ... To align, she says, security leaders must “know the objectives the business has and use those to shape strategy, whether it’s cost containment, going into new markets, adopting cloud. The playbook starts from understanding the organizational priorities and then layering in what threat actors are doing in that industry and what could go wrong, what is the risk we can live with, and understanding and articulating the business impact of security incidents.” ... “When security is not aligned, security is reacting to changes rather than shaping changes,” says . “But when security isn’t chasing the business it’s because it’s at the table from the beginning and is saying, ‘Here’s how I can help the business grow and grow securely.’”

CISO Burnout – Epidemic, Endemic, or Simply Inevitable?

“Burnout and are different conditions, though they can coexist and share some symptoms,” says . “The constant hypervigilance required in our roles can mirror PTSD symptoms, and some cyber security professionals do experience what could be considered from constantly dealing with the aftermath of cyber-attacks.” Experiencing trauma can make you more susceptible to burnout, and burnout can exacerbate existing trauma responses. “Both conditions are serious and treatable, but they require different approaches,” she suggests. And both are further complicated by , a characteristic that is particularly prevalent in cybersecurity, and especially among CISOs. ... “From my experience working with senior cyber security leaders,” she continues, “burnout also affects their ability to lead their teams effectively. They become less empathetic, more prone to micromanaging, and, ironically, more likely to create the very conditions that lead to burnout in their staff. The strategic thinking that makes a great CISO (the ability to see the big picture, anticipate threats, and balance risk with business needs) gets clouded by exhaustion and cynicism. Perhaps most dangerously, burned-out CISOs often develop tunnel vision, focusing obsessively on certain threats while missing others entirely. When the person responsible for an organization’s entire security posture is running on empty, everyone is at risk.”

Uncovering the risks of unmanaged identities

often operate independently, making it difficult to track and monitor their activities without a centralized management system. These agents can adapt and change their behavior autonomously, which complicates efforts to predict and control their actions. While performing their duties, AI agents can even spin up other models and agents that have access to valuable data. ... Unmanaged identities significantly expand the attack surface, providing more entry points for attackers. They are prime targets for credential theft, which can lead to lateral movement within an organization’s network. Forgotten or over-permissioned accounts can facilitate privilege escalation, allowing attackers to gain unauthorized access to sensitive data. have been linked to unmanaged identities, underscoring the critical need for effective identity management. ... Inefficient access management due to unmanaged identities increases IT overhead and complexity. Unauthorized access or accidental deletions can disrupt business operations, leading to breaches, financial losses, and diminished customer trust. ... Unmanaged identities present a clear and present danger to organizations. They increase the risk of security breaches, compliance failures, and operational disruptions. It is imperative for organizations to prioritize identity discovery and management as a core security practice.

Empowering Teams: Decentralizing Architectural Decision-Making

Decisions form the core of software architecture, and practicing software architecture means working with decisions. Software development itself represents a constant stream of decisions. In a decentralized decision-making process, everyone contributes to architectural decisions, from developers to architects. For this approach, identifying whether a decision is architecturally significant and will impact the system now or in the future matters more than who made the decision or how long it took. Recording architectural decisions captures the why behind every what, creating valuable context for future learning and shared understanding. ... Timing for seeking feedback or advice depends on the nature of the decision. For impactful decisions affecting multiple system parts, or when lacking business or technical knowledge, seeking advice during the decision-making process yields better results. ADRs are immutable documents; once marked as adopted, they cannot be changed. If a decision needs revision, the previous ADR is superseded and a new one created. ... From the program leadership perspective, watching teams make independent decisions felt like being the first test driver in a Tesla using autopilot and hoping to avoid crashing. Staying out of decisions required conscious effort to avoid undermining the advice process and resorting back to make the decisions for the team.

The Fractured Cloud: How CIOs Can Navigate Geopolitical and Regulatory Complexity

Initially, cloud environments were largely interchangeable from a governance, compliance, and security perspective. It didn't really matter exactly which cloud data center hosted an organization's workloads, or which jurisdiction the data center was located in. IT leaders had the luxury of choosing cloud platforms and regions based primarily on factors such as pricing and latency, without having to consider geopolitics or the global regulatory environment. Fast forward to the present, however, and planning a cloud architecture -- let alone evolving an existing cloud strategy in response to changing needs -- has become much more complex. ... During the past decade or so, a host of regulations have emerged that apply to specific jurisdictions, including the and California Public Records Act (CPRA). Regulations dealing with AI, which are just now coming online, are likely to add even more diversity as different states or countries introduce varying laws. ... A related issue is the increasing pressure organizations face surrounding , which refers to the practice of keeping data within a certain country or jurisdiction. Regulations require this in some cases. Even if they don't, businesses may voluntarily choose to ensure data localization for the purposes of improving workload performance, or to assure customers that their data never leaves their home region.

Let's Get Physical: A New Convergence for Electrical Grid Security

Power plants and transmission/distribution system operators () have long focused on maintaining uptime and enhancing the resilience of their services; keeping the lights on is always the goal. That's especially true as the past few years have seen the rise of OT/OT convergence, wherein formerly siloed equipment that runs physical processes for critical infrastructure (operational technology, or OT) has been hooked up to the IT network and the Internet in some cases, exposing it to more cyberthreats. Now, another type of convergence been forcing a new conversation. ... In this new world, both industry regulators and analysts, like those at Black & Veatch, are arguing the same point: that where once keeping the lights on might have just meant maintaining equipment and avoiding fallen trees, today's grid operators need a robust, integrated physical and cybersecurity strategy to maintain continuous service. ... an IT operation might primarily concern itself with firewalls, or network monitoring; but "in many cases, cyberattacks can often involve physical access to sites, whether by malicious insiders or unwitting employees and contractors. Understanding who is present on-site, when and why, is critical to investigating and mitigating attacks on operations," Bramson explains.

Was data mesh just a fad?

Data mesh architecture promised to solve these problems. A polar opposite approach from a , a data mesh gives the source team ownership of the data and the responsibility to distribute the dataset. Other teams access the data from the source system directly, rather than from a centralized data lake. The data mesh was designed to be everything that the data lake system wasn’t. ... But the excitement around data mesh didn’t last. Many users became frustrated. Beneath the surface, almost every bottleneck between data providers and data consumers became an implementation challenge. The thing is, the data mesh approach isn’t a once-and-done change, but a long-term commitment to prepare a data schema in a certain way. Although every source team owns their dataset, they must maintain a schema that allows downstream systems to read the data, rather than replicating it. ... No, data mesh is not a fad, nor is it the next big thing that will solve all of your data challenges. But data mesh can dramatically reduce data management overhead, and at the same time improve data quality, for many companies. In essence, data mesh is a shift in mindset, one that completely changes the way you view data. Teams must envision data as a product, continuously showing commitment for the source team to own the data set and discouraging duplication.

8 ways to make responsible AI part of your company's DNA

" is a team sport," the report's authors explain. "Clear roles and tight hand-offs are now essential to scale safely and confidently as AI adoption accelerates." To leverage the advantages of responsible AI, recommends rolling out AI applications within an operating structure with three "lines of defense." First line: Builds and operates responsibly. Second line: Reviews and governs. Third line: Assures and audits. ... "For tech leaders and managers, making sure AI is responsible starts with how it's built," Rohan Sen, principal for cyber, data, and tech risk with PwC US. "To build trust and scale AI safely, focus on embedding responsible AI into every stage of the AI development lifecycle, and involve key functions like cyber, data governance, privacy, and regulatory compliance," said Sen. ... "Start with a value statement around ethical use," said Logan. "From here, prioritize periodic audits and consider a steering committee that spans privacy, security, legal, IT, and procurement. Ongoing transparency and open communication are paramount so users know what's approved, what's pending, and what's prohibited. Additionally, investing in training can help reinforce compliance and ethical usage." ... Make it a priority to "continually discuss how to responsibly use AI to increase value for clients while ensuring that both data security and IP concerns are addressed," said Tony Morgan, senior engineer at Priority Designs.

Context Engineering: The Next Frontier in AI-Driven DevOps

Context Engineering represents a significant evolution from the early days of , which focused on crafting the perfect, isolated instruction for an AI model. Context engineering, in contrast, is about orchestrating the entire information ecosystem around the AI. It’s the difference between giving someone a map (prompt engineering) and providing them with a real-time GPS that has traffic updates, road closures, and understands your personal driving preferences. ... The core components of context engineering in a DevOps environment include: Dynamic Information Assembly: Aggregating data from a multitude of DevOps tools, including monitoring platforms, , and infrastructure as code (IaC) repositories. Multi-Source Integration: Connecting to APIs, databases, and internal documentation to create a comprehensive view of the entire system. Temporal Awareness: Understanding the history of changes, incidents, and performance to identify patterns and predict future outcomes. ... In a traditional setup, the CI/CD pipeline would run a standard set of tests. But with context engineering, a context-aware AI agent analyzes the change. It recognizes the high-risk nature of the code, cross-references it with a recent security audit that flagged a related library, and automatically triggers an extended security testing suite. It also notifies the security team for a priority review. This is a far cry from the old days of one-size-fits-all pipelines.

Drowning in Data? Here’s Why You Need to Ditch the Rowboat for an Aircraft Carrier

In an effort to stay afloat, many enterprises are trying to patch their systems with incremental upgrades. They add more cloud instances. They layer on external tools. They spin up new teams to manage increasingly fragmented stacks. But scaling up a fragile system doesn’t make it strong. It just makes the cracks bigger. ... The deeper issue is this: the dominant architecture most enterprises still rely on was designed over a decade ago. It served a world where workloads operated in gigabytes or single-digit terabytes. Today, companies are navigating hundreds of petabytes, yet many are still using infrastructure built for a far smaller scale. It’s no wonder the systems are buckling under the weight. ... As organizations reevaluate their data architectures, several priorities are coming into sharper focus: Reducing fragmentation by moving toward more unified environments, where systems work in concert rather than in silos. Improving performance and cost-efficiency not just through hardware, but through smarter architecture and workload optimization. Lowering latency for high-demand workloads like , AI, and real-time analytics, where speed directly impacts decision-making. Managing the energy consumption bottleneck in ways that align with both financial and sustainability goals. Ultimately, this shift is about enabling teams to go from playing defense (maintaining systems and containing cost) to playing offense with faster, more actionable insights.

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Daily Tech Digest - November 04, 2025