Quote for the day:
"Whatever you can do, or dream you can, begin it. Boldness has genius, power and magic in it." -- Johann Wolfgang von Goethe
The incredibly shrinking shelf life of IT solutions
“Technology cycles are spinning faster and faster, and some solutions are
evolving so fast, that they’re now a year-long bet, not a three- or five-year
bet for CIOs,” says Craig Kane ... “We are living in a period of high
user expectations. Every day is a newly hyped technology, and CIOs are
constantly being asked how can we, the company, take advantage of this new
solution,” says Boston Dynamics CIO Chad Wright. “Technology providers can
move quicker today with better development tools and practices, and this feeds
the demand that customers are creating.” ... Not every CIO is switching out
software as quickly as that, and Taffet, Irish, and others say they’re certainly
not seeing the shelf life for all software and solutions in their enterprise
shrink. Indeed, many vendors are updated their applications with new
features and functions to keep pace with business and market demands — updates
that help extend the life of their solutions. And core solutions generally
aren’t turning over any more quickly today than they did five or 10 years ago,
Kearney’s Kane says. ... Montgomery says CIOs and business colleagues sometimes
think the solutions they have in place are falling behind market innovations
and, as a result, their business will fall behind, too. That may be the case,
but they may just be falling for marketing hype, she says. Montgomery also
cites the fast pace of executive turnover as contributing to the increasingly
short shelf life of IT solutions.
Resiliency in Fintech: Why System Design Matters More Than Ever
Cloud computing has transformed fintech. What once took months to provision can now be spun up in hours. Auto-scaling, serverless computing, and global distribution have enabled firms to grow without massive upfront infrastructure costs. Yet, cloud also changes the resilience equation. Outages at major CSPs — rare but not impossible — can cascade across entire industries. The Financial Stability Board (FSB) has repeatedly warned about “cloud concentration risk.” Regulators are exploring frameworks for oversight, including requirements for firms to maintain exit strategies or multi-cloud approaches. For fintech leaders, the lesson is clear: cloud-first doesn’t mean resilience-last. Building systems that are cloud-resilient (and in some cases cloud-agnostic) is becoming a strategic priority. ... Recent high-profile outages underline the stakes. Trading platforms freezing during volatile markets, digital banks leaving customers without access to funds, and payment networks faltering during peak shopping days all illustrate the cost of insufficient resilience. ... Innovation remains the lifeblood of fintech. But as the industry matures, resilience has become the new competitive differentiator. The firms that win will be those that treat system design as risk management, embedding high availability, regulatory compliance, and cloud resilience into their DNA. In a world where customer trust can be lost in minutes, resilience is not just good engineering.AI cost pressures fuelling cloud repatriation
IBM thinks AI will present a bigger challenge than the cloud because it will be
more pervasive with more new applications being built on it. Consequently, IT
leaders are already nervous about the cost and value implications and are
looking for ways to get ahead of the curve. Repeating the experience of cloud
adoption, AI is being driven by business teams, not by back-office IT. AI is
becoming a significant driver for shifting workloads back to private, on-premise
systems. This is because data becomes the most critical asset, and Patel
believes few enterprises are ready to give up their data to a third party at
this stage. ... The cloud is an excellent platform for many workloads, just as
there are certain workloads that run extremely well on a mainframe. The key is
to understand workload placement: is my application best placed on a mainframe,
on a private cloud or on a public cloud? As they start their AI journey, some of
Apptio’s customers are not ready for their models, learning and intelligence –
their strategic intellectual property – to sit in a public cloud. There are
consequences when things go wrong with data, and those consequences can be
severe for the executives concerned. So, when a third party suggests putting all
of the customer, operational and financial data in one place to gain wonderful
insights, some organisations are unwilling to do this if the data is outside
their direct control. Finding connection and resilience as a CISO
To create stronger networks among CISOs, security leaders can join trusted peer groups like industry ISACs (Information Sharing and Analysis Centers) or associations within shared technology / compliance spaces like cloud, GRC, and regulatory. The protocols and procedures in these groups ensure members can have meaningful conversations without putting them or their organization at risk. ... Information sharing operates in tiers, each with specific protocols for data protection. Top tiers, involving entities like ISACs, the FBI, and DHS, have established protocols to properly share and safeguard confidential data. Other tiers may involve information and intelligence already made public, such as CVEs or other security disclosures. CISOs and their teams may seek assistance from industry groups, partnerships, or vendors to interpret current Indicators of Compromise (IOCs) and other remediation elements, even when public. Continuously improving vendor partnerships is crucial for managing platforms and programs, as strong partners will be familiar with internal operations while protecting sensitive information. ... Additionally, encouraging a culture of continuous learning and development, not just with the security team but broader technology and product teams, will empower employees, distribute expertise, and grow a more resilient and adaptable workforce.Geopolitics is forcing the data sovereignty issue and it might just be a good thing
At London Tech Week recently UK Prime Minister Keir Starmer said that the way
that war is being fought “has changed profoundly,” adding that technology and AI
are now “hard wired” into national defense. It was a stark reminder that IT
infrastructure management must now be viewed through a security lens and that
businesses need to re-evaluate data management technologies and practices to
ensure they are not left out in the cold. ... For many, public cloud services
have created a false sense of flexibility. Moving fast is not the same as moving
safely. Data localization, jurisdictional control, and security policy alignment
are now critical to long-term strategy, not barriers to short-term scale. So
where does that leave enterprise IT? Essentially, it leaves us with a choice -
design for agility with control, or face disruption when the rules change. ...
Sovereignty-aware infrastructure isn’t about isolation. It’s about knowing where
your data is, who can access it, how it moves, and what policies govern it at
each stage. That means visibility, auditability, and the ability to adjust
without rebuilding every time a new compliance rule appears. A hybrid multicloud
approach gives organizations the flexibility while keeping data governance
central. It’s not about locking into one cloud provider or building everything
on-prem.
Recalibrating Hybrid Cloud Security in the Age of AI: The Need for Deep Observability
As AI further fuels digital transformation, the security landscape of hybrid cloud infrastructures is becoming more strained. As such, security leaders are confronting a paradox. Cloud environments are essential for scaling operations, but they also present new attack vectors. ... Amid these challenges, some organisations are realising that their traditional security tools are insufficient. The lack of visibility into hybrid cloud environments is identified as a core issue, with 60 percent of Australian leaders expressing a lack of confidence in their current tools to detect breaches effectively. The call for "deep observability" has never been louder. The research underscores the the need for having a comprehensive, real-time view into all data in motion across the enterprise to improve threat detection and response. Deep observability, combining metadata, network packets, and flow data has become a cornerstone of hybrid cloud security strategies. It provides security teams with actionable insights into their environments, allowing them to spot potential threats in real time. In fact, 89 percent of survey respondents agree that deep observability is critical to securing AI workloads and managing complex hybrid cloud infrastructures. Being proactive with this approach is seen as a vital way to bridge the visibility gap and ensure comprehensive security coverage across hybrid cloud environments.Financial fraud is widening its clutches—Can AI stay ahead?
Today, organised crime groups are running call centres staffed with human
trafficking victims. These victims execute “romance baiting” schemes that
combine emotional manipulation with investment fraud. The content they use?
AI-generated. The payments they request? ... Fraud attempts rose significantly
in a single quarter after COVID hit, and the traditional detection methods fell
apart. This is why modern fraud detection systems had to evolve. Now, these
systems can analyse thousands of transactions per minute, assigning risk scores
that update in real-time. There was no choice. Staying in the old regime of
anti-fraud systems was no longer an option when static rules became obsolete
almost overnight. ... The real problem isn’t the technology itself. It’s the
pace of adoption by bad actors. Stop Scams UK found something telling: While
banks have limited evidence of large-scale AI fraud today, technology companies
are already seeing fake AI-generated content and profiles flooding their
platforms. ... When AI systems learn from historical data that reflects societal
inequalities, they can perpetuate discrimination under the guise of objective
analysis. Banks using biased training data have inadvertently created systems
that disproportionately flag certain communities for additional scrutiny. This
creates moral problems alongside operational and legal risks.
Data security and compliance are non-negotiable in any cloud transformation journey
Enterprises today operate in a data-intensive environment that demands modern infrastructure, built for speed, intelligence, and alignment with business outcomes. Data modernisation is essential to this shift. It enables real-time processing, improves data integrity, and accelerates decision-making. When executed with purpose, it becomes a catalyst for innovation and long-term growth. ... The rise of generative AI has transformed industries by enhancing automation, streamlining processes, and fostering innovation. According to a recent NASSCOM report, around 27% of companies already have AI agents in production, while another 31% are running pilots. ... Cloud has become the foundation of digital transformation in India, driving agility, resilience, and continuous innovation across sectors. Kyndryl is expanding its capabilities in the market to support this momentum. This includes strengthening our cloud delivery centres and expanding local expertise across hyperscaler platforms. ... Strategic partnerships are central to how we co-innovate and deliver differentiated outcomes for our clients. We collaborate closely with a broad ecosystem of technology leaders to co-create solutions that are rooted in real business needs. ... Enterprises in India are accelerating their cloud journeys, demanding solutions that combine hyperscaler innovation with deep enterprise expertise.Digital Transformation Strategies for Enterprise Architects
Customer experience must be deliberately architected to deliver relevance,
consistency, and responsiveness across all digital channels. Enterprise
architects enable this by building composable service layers that allow
marketing, commerce, and support platforms to act on a unified view of the
customer. Event-driven architectures detect behavior signals and trigger
automated, context-aware experiences. APIs must be designed to support edge
responsiveness while enforcing standards for security and governance. ...
Handling large datasets at the enterprise level requires infrastructure that
treats metadata, lineage, and ownership as first-class citizens. Enterprise
architects design data platforms that surface reliable, actionable insights,
built on contracts that define how data is created, consumed, and governed
across domains. Domain-oriented ownership via data mesh ensures accountability,
while catalogs and contracts maintain enterprise-wide discoverability. ...
Architectural resilience starts at the design level. Modular systems that use
container orchestration, distributed tracing, and standardized service contracts
allow for elasticity under pressure and graceful degradation during failure.
Architects embed durability into operations through chaos engineering,
auto-remediation policies, and blue-green or canary deployments.
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