Technical Debt: An enterprise’s self-inflicted cyber risk
Technical debt issues vary in risk level depending on the scope and blast radius
of the issue. Unaddressed high-risk technical debt issues create inefficiency
and security exposure while diminishing network reliability and performance.
There’s the obvious financial risk that comes from wasted time, inefficiencies,
and maintenance costs. Adding tools potentially introduces new vulnerabilities,
increasing the attack surface for cyber threats. A lot of the literature around
technical debt focuses on obsolete technology on desktops. While this does
present some risk, desktops have a limited blast radius when compromised.
Outdated hardware and unattended software vulnerabilities within network
infrastructure pose a much more imminent and severe risk as they serve as a
convenient entry point for malicious actors with a much wider potential reach.
An unpatched or end-of-life router, switch, or firewall, riddled with documented
vulnerabilities, creates a clear path to infiltrating the network. By
methodically addressing technical debt, enterprises can significantly mitigate
cyber risks, enhance operational preparedness, and minimize unforeseen
infrastructure disruptions.
Why Your AI Will Never Take Off Without Better Data Accessibility
Data management and security challenges cast a long shadow over efforts to
modernize infrastructures in support of AI and cloud strategies. The survey
results reveal that while CIOs prioritize streamlining business processes
through cloud infrastructures, improving data security and business resilience
is a close second. Security is a persistent challenge for companies managing
large volumes of file data and it continues to complicate efforts to enhance
data accessibility. Nasuni’s research highlights that 49% of firms (rising to
54% in the UK) view security as their biggest problem when managing file data
infrastructures. This issue ranks ahead of concerns such as rapid recovery from
cyberattacks and ensuring data compliance. As companies attempt to move their
file data to the cloud, security is again the primary obstacle, with 45% of all
respondents—and 55% in the DACH region—citing it as the leading barrier, far
outstripping concerns over cost control, upskilling employees and data migration
challenges. These security concerns are not just theoretical. Over half of the
companies surveyed admitted that they had experienced a cyber incident from
which they struggled to recover. Alarmingly, only one in five said they managed
to recover from such incidents easily.
Exploring DORA: How to manage ICT incidents and minimize cyber threat risks
The SOC must be able to quickly detect and manage ICT incidents. This involves
proactive, around-the-clock monitoring of IT infrastructure to identify
anomalies and potential threats early on. Security teams can employ advanced
tools such as security automation, orchestration and response (SOAR), extended
detection and response (XDR), and security information and event management
(SIEM) systems, as well as threat analysis platforms, to accomplish this.
Through this monitoring, incidents can be identified before they escalate and
cause greater damage. ... DORA introduces a harmonized reporting system for
serious ICT incidents and significant cyber threats. The aim of this reporting
system is to ensure that relevant information is quickly communicated to all
responsible authorities, enabling them to assess the impact of an incident on
the company and the financial market in a timely manner and respond accordingly.
... One of the tasks of SOC analysts is to ensure effective communication with
relevant stakeholders, such as senior management, specialized departments and
responsible authorities. This also includes the creation and submission of the
necessary DORA reports.
What is Cyber Resilience? Insurance, Recovery, and Layered Defenses
While cyber insurance can provide financial protection against the fallout of
ransomware, it’s important to understand that it’s not a silver bullet.
Insurance alone won’t save your business from downtime, data loss, or reputation
damage. As we’ve seen with other types of insurance, such as property or health
insurance, simply holding a policy doesn’t mean you’re immune to risks. While
cyber insurance is designed to mitigate financial risks, insurers are becoming
increasingly discerning, often requiring businesses to demonstrate adequate
cybersecurity controls before providing coverage. Gone are the days when
businesses could simply “purchase” cyber insurance without robust cyber hygiene
in place. Today’s insurers require businesses to have key controls such as
multi-factor authentication (MFA), incident response plans, and regular
vulnerability assessments. Moreover, insurance alone doesn’t address the
critical issue of data recovery. While an insurance payout can help with
financial recovery, it can’t restore lost data or rebuild your reputation. This
is where a comprehensive cybersecurity strategy comes in — one that encompasses
both proactive and reactive measures, involving components like third-party data
recovery software.
Integrating Legacy Systems with Modern Data Solutions
Many legacy systems were not designed to share data across platforms or
departments, leading to the creation of data silos. Critical information gets
trapped in isolated systems, preventing a holistic view of the organization’s
data and hindering comprehensive analysis and decision-making. ... Modern
solutions are designed to scale dynamically, whether it’s accommodating more
users, handling larger datasets, or managing more complex computations. In
contrast, legacy systems are often constrained by outdated infrastructure,
making it difficult to scale operations efficiently. Addressing this requires
refactoring old code and updating the system architecture to manage accumulated
technical debt. ... Older systems typically lack the robust security features of
modern solutions, making them more vulnerable to cyber-attacks. Integrating
these systems without upgrading security protocols can expose sensitive data to
threats. Ensuring robust security measures during integration is critical to
protect data integrity and privacy. ... Maintaining legacy systems can be costly
due to outdated hardware, limited vendor support, and the need for specialized
expertise. Integrating them with modern solutions can add to this complexity and
expense.
The challenges of hybrid IT in the age of cloud repatriation
The story of cloud repatriation is often one of regaining operational control. A
recent report found that 25% of organizations surveyed are already moving some
cloud workloads back on-premises. Repatriation offers an opportunity to address
these issues like rising costs, data privacy concerns, and security issues.
Depending on their circumstances, managing IT resources internally can allow
some organizations to customize their infrastructure to meet these specific
needs while providing direct oversight over performance and security. With
rising regulations surrounding data privacy and protection, enhanced control
over on-prem data storage and management provides significant advantages by
simplifying compliance efforts. ... However, cloud repatriation can often create
challenges of its own. The costs associated with moving services back on-prem
can be significant: new hardware, increased maintenance, and energy expenses
should all be factored in. Yet, for some, the financial trade-off for
repatriation is worth it, especially if cloud expenses become unsustainable or
if significant savings can be achieved by managing resources partially on-prem.
Cloud repatriation is a calculated risk that, if done for the right reasons and
executed successfully, can lead to efficiency and peace of mind for many
companies.
IT Cost Reduction Strategies: 3 Unexpected Ways Enterprise Architecture Can Help
Easier said than done with the traditional process of manual follow-ups hampered
by inconsistent documentation often scattered across many teams. The issue with
documentation also often means that maintenance efforts are duplicated, wasting
resources that could have been better deployed elsewhere. The result is the
equivalent of around 3 hours of a dedicated employee’s focus per application per
year spent on documentation, governance, and maintenance. Not so for the
organization that has a digital-native EA platform that leverages your data to
enable scalability and automation in workflows and messaging so you can reach
out to the most relevant people in your organization when it's most needed.
Features like these can save an immense amount of time otherwise spent
identifying the right people to talk to and when to reach out to them, making a
company's Enterprise Architecture the single source of truth and a solid
foundation for effective governance. The result is a reduction of approximately
a third of the time usually needed to achieve this. That valuable time can then
be reallocated toward other, more strategic work within the organization. We
have seen that a mid-sized company can save approximately $70 thousand annually
by reducing its documentation and governance time.
How Rules Can Foster Creativity: The Design System of Reykjavík
Design systems have already gained significant traction, but many are still in
their early stages, lacking atomic design structures. While this approach may
seem daunting at first, as more designers and developers grow accustomed to
working systematically, I believe atomic design will become the norm. Today,
most teams create their own design systems, but I foresee a shift toward
subscription-based or open-source systems that can be customized at the atomic
level. We already see this with systems like Google’s Material UI, IBM’s Carbon,
Shopify’s Polaris, and Atlassian’s design system. Adopting a pre-built,
well-supported design system makes sense for many organizations. Custom systems
are expensive and time-consuming to build, and maintaining them requires ongoing
resources, as we learned in Reykjavík. By leveraging a tried-and-tested design
system, teams can focus on customization rather than starting from scratch.
ontrary to popular belief, this shift won’t stifle creativity. For public
services, there is little need for extreme creativity regarding core
functionality - these products simply need to work as expected. AI will also
play a significant role in evolving design systems.
Eyes on Data: A Data Governance Study Bridging Industry and Academia
The researcher, Tony Mazzarella, is a seasoned data management professional and
has extensive experience in data governance within large organizations. His
professional and research observations have identified key motivations for this
work: Data Governance has a knowledge problem. Existing literature and
publications are overly theoretical and lack empirical guidance on practical
implementation. The conceptual and practical entanglement of governance and
management concepts and activities exacerbates this issue, leading to divergent
definitions and perceptions that data governance is overly theoretical. The
“people” challenges in data management are often overlooked. Culture is core to
data governance, but its institutionalization as a business function coincided
first in the financial services industry with a shift towards regulatory
compliance in response to the 2008 financial crisis. “Data culture” has
re-emerged in all industries, but it implies the governance function is tasked
with fostering culture change rather than emphasizing that data governance
requires a culture change, which is a management challenge. Data Management’s
industry-driven nature and reactive ethos result in unnecessary change as the
macroenvironment changes, undermining process resilience and sustainability.
The future of data center maintenance
Condition-based maintenance and advanced monitoring services provide operators
with more information about the condition and behavior of assets within the
system, including insights into how environmental factors, controls, and usage
drive service needs. The ability to recommend actions for preventing downtime
and extending asset life allows a focus on high-impact items instead of tasks
that don't immediately affect asset reliability or lifespan. These items include
lifecycle parts replacement, optimizing preventive maintenance schedules,
managing parts inventories, and optimizing control logic. The effectiveness of a
service visit can subsequently be validated as the actions taken are reflected
in asset health analyses. ... Condition-based maintenance and advanced
monitoring services include a customer portal for efficient equipment health
reporting. Detailed dashboards display site health scores, critical events, and
degradation patterns. ... The future of data center maintenance is here –
smarter, more efficient, and more reliable than ever. With condition-based
maintenance and advanced monitoring services, data centers can anticipate risks
and benchmark assets, leading to improved risk management and enhanced
availability.
Quote for the day:
"It's not about how smart you are--it's
about capturing minds." -- Richie Norton