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Consumer Goods and Services
'The search is soul-destroying': Young jobseekers on the struggle to find work
2026-02-17 17:37:08| BBC News | Business | UK Edition
Young people are bearing the brunt of a weak jobs market, the latest figures show.
Category: Consumer Goods and Services
Ex-Carillion boss fined for 'reckless' actions
2026-02-17 16:58:27| BBC News | Business | UK Edition
Ex-chief executive Richard Howson acted "recklessly" and misled others, a watchdog says.
Category: Consumer Goods and Services
Dual nationals face scramble for UK passports as new rules come into force
2026-02-17 15:17:16| BBC News | Business | UK Edition
Entry requirements to the UK for dual nationals are being overhauled as part of sweeping changes to the immigration system.
Category: Consumer Goods and Services
Telecommunications
Turning AI into Measurable Outcomes with Private Cloud
2026-02-10 18:59:26| The Webmail Blog
Turning AI into Measurable Outcomes with Private Cloud jord4473 Tue, 02/10/2026 - 11:59 AI Insights Turning AI into Measurable Outcomes with Private Cloud February 12, 2026 By Amine Badaoui, Senior Manager AI/HPC Product Engineering, Rackspace Technology Link Copied! Recent Posts Turning AI into Measurable Outcomes with Private Cloud February 12th, 2026 How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 Getting Started With AI: A Practical Path Forward February 5th, 2026 Effective Housekeeping With Rackspace Managed Snapshot Cleanup January 29th, 2026 Redefining Detection Engineering and Threat Hunting with RAIDER January 27th, 2026 Related Posts AI Insights Turning AI into Measurable Outcomes with Private Cloud February 12th, 2026 Cloud Insights How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 AI Insights Getting Started With AI: A Practical Path Forward February 5th, 2026 Cloud Insights Effective Housekeeping With Rackspace Managed Snapshot Cleanup January 29th, 2026 AI Insights Redefining Detection Engineering and Threat Hunting with RAIDER January 27th, 2026 As AI moves from pilots to production, outcomes matter more than models. This article explores how private cloud supports governed, cost-predictable AI at enterprise scale. Every board is now asking, What is our AI strategy? Far fewer can answer the harder question: What has AI actually delivered for our margins, growth, risk profile and customer experience? Most enterprises have accumulated pilots and proofs of concept, yet only a small number translate those efforts into measurable P&L impact. The difference is not who has the most advanced model. It is who treats AI as a business outcome engine, supported by an operating and infrastructure model they control. Increasingly, private cloud is emerging as that control plane, enabling organizations to scale AI with more predictable cost, stronger governance and clearer business impact. The value gap: lots of AI, little business impact Across industries, AI initiatives often begin with curiosity and technology. Someone wants to do something with generative AI, build a chatbot or experiment with copilots. Teams spin up environments, connect a model and produce an impressive demo. Then the project stalls. The issue is usually straightforward: the effort started with tools, not outcomes. No KPI was defined, no accountable owner was assigned, and no core process was redesigned. When budgets tighten or priorities shift, these initiatives are often the first to be deprioritized because leadership cannot clearly connect them to growth, cost efficiency or risk reduction. At the same time, senior leaders are becoming more deliberate about where AI runs. Public cloudonly deployment models can introduce data sovereignty challenges, regulatory complexity and unpredictable cost. For workloads tied to critical data, revenue streams or compliance obligations, many organizations are increasingly turning to private cloud and private AI not as legacy patterns, but as strategic control planes for delivering measurable outcomes. Why serious AI is moving to private cloud For business-critical AI, where it runs is often as important as what it does. Private cloud gives organizations greater control where it matters most: Data control: Sensitive customer, financial, health and operational data remains within a defined perimeter, aligned with residency and sovereignty requirements. Risk control: Identity, access and audit controls are enforced consistently across workloads, making AI-driven decisions easier to explain to regulators, customers and internal audit teams. Economic control: Capacity can be shaped and rightsized, helping to avoid the surprise invoice problem that can emerge during unconstrained AI experimentation. This allows AI to be embedded directly into day-to-day workflows such as claims, onboarding, underwriting, care management and shop-floor operations, rather than operating as a disconnected sidecar. For C-suite and line-of-business leaders, private AI on private cloud is increasingly viewed as a governance and value-creation strategy, not simply an infrastructure choice. From pilots to an AI outcome portfolio A more useful way for leaders to think about AI is as a portfolio of outcome bets aligned to the levers they already manage. At a high level, this portfolio tends to cluster around three themes: Protect the downside Reduce leakage, strengthen compliance and improve safety and resilience. Improve the run Increase productivity, lower cost to serve, reduce errors and shorten cycle times. Grow the business Launch new AI-enabled products, personalize experiences and open new revenue streams. Private cloud helps by giving this portfolio a consistent foundation. The same platform defines who can access which data, which models are approved, how workloads are monitored and how cost is tracked. Leaders establish a clear view of which AI initiatives exist, which are delivering value and where to double down or divest. A four-step framework for outcome-first private AI Executives do not need to become AI engineers. They need a simple way to connect business priorities, processes and AI capabilities. A practical framework can be expressed in four steps. 1. Start with the outcome, then the process Begin every AI conversation with a business outcome: What are we trying to change? Which KPI will show that we have succeeded? Over what timeframe? Examples might include Cut onboarding time from 10 days to three, or Increase cross-sell conversion in our top two segments. Once the outcome is clear, map the process that drives it today. Where does time, friction or error accumulate? Which steps depend heavily on reading, writing or routing information? These are often the areas where AI can realistically provide assistance. 2. Choose the right private AI pattern With outcome and process in view, the focus shifts to the pattern of AI required. At a business level, three patterns cover most use cases: Smarter decisions Models that score, predict or classify fraud detection, risk scoring, demand forecasting or next-best-offer selection. Smarter content and interactions Generative models that draft responses, summarize documents or support agents and employees as copilots. Smarter workflows Agent-like systems that stitch together multiple steps: retrieving information, invoking systems and proposing or executing actions. All of these patterns can run on a private cloud AI platform, close to the systems and data they depend on. The technical details matter to architects; what matters to leaders is whether the pattern fits the process, the risk tolerance and the available data. 3. Build governance and trust from day one Governance cannot be bolted on at the end. For private AI to earn the right to scale, three elements must be designed upfront: Data and access Which data sources are in scope? Who can use them? How are permissions granted and revoked? Private cloud allows these rules to be enforced centrally. Guardrails and responsibility What decisions can AI make or automate, and where must a human remain in the loop? How will bias, hallucination and other failure modes be monitored and addressed? Transparency and auditability How will AI-assisted decisions be explained to regulators, customers and employees? Can you show who did what, when and using which model? When these questions are addressed early, AI initiatives are far more likely to clear risk, legal and compliance hurdles and to survive first contact with real-world complexity. 4. Measure value in short, sharp loops Finally, value must be measured as systematically as cost. For each use case, teams should be able to articulate: The baseline: Current cost, cycle time, error rate, revenue or satisfaction score The target: The improvement expected over a defined period The feedback loop: How performance will be tracked and how quickly the team can respond Short, time-boxed experiments, measured in weeks and months instead of years, allow leadership to make clear decisions. If a private AI initiative moves a KPI in the right direction, invest and scale it. If it does not, adjust the approach or stop it and learn. Because this work runs on a shared private cloud platform, components, patterns and learnings can be reused across the portfolio, compounding value over time. Outcomefirst stories: what good looks like Three brief examples below illustrate how an outcome-first approach to private AI plays out in pratice. Customer service: A service organization deploys AI copilots for agents and virtual assistants for customers, all running on a private cloud platform. Routine queries are handled automatically, while agents receive suggested replies and next-best actions informed by the full history of the relationship. Average handling time declines, first-contact resolution improves and sensitive interaction data remains within the organizations environment. Operations and risk: A financial or insurance organization builds private AI models to scan transactions and documents for anomalies and potential issues. Cases are automatically prioritized and routed to specialists, with full traceability for every recommendation. Investigation time shrinks, losses are reduced and regulatory reviews become more straightforward because decisions are explainable. Product and innovation: A product team uses a standardized private AI platform to experiment with new capabilities such as intelligent search, personalized offers and document automation. Because data, models and guardrails already operate within a governed environment, teams can move from idea to pilot to production more efficiently. Time to market shortens, and multiple business units reuse the same platform and patterns. In each case, the headline is not the model or the technology. It is the business metric that moved, and the fact that the organization retained control over data, risk and cost. A call to action for Csuite and lineofbusiness leaders The question for leadership is no longer Should we use AI? It is, How do we turn AI into measurable, durable business value on our terms? Three moves can help shift the conversation: Set a 1224-month AI outcome agenda: Identify a small set of enterprise-level KPIs cost to serve, churn, time to market, loss ratio, patient outcomes and frame AI initiatives against them. Create a cross-functional AI value council: Bring together business, technology, data, risk and operations leaders who jointly own both the upside and the downside of AI. Treat private AI on private cloud as a strategic capability: Invest, govern and report on it the way you would any core platform, from ERP to CRM with clear ownership, clear metrics and clear accountability. Done well, AI stops being a scatter of pilots and becomes a disciplined, outcome-driven program. Private cloud becomes the control plane that allows organizations to decide where and how that value is created securely, predictably and on their terms. Learn how Rackspace Private Cloud AI supports outcome-driven AI initiatives with predictable performance and governance. Tags: AI Insights
Category: Telecommunications
How Proactive Threat Hunting Stopped INC Ransom Before the Alert
2026-02-06 20:15:19| The Webmail Blog
How Proactive Threat Hunting Stopped INC Ransom Before the Alert jord4473 Fri, 02/06/2026 - 13:15 Cloud Insights How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9, 2026 by Craig Fretwell, Global Head of Cybersecurity Operations, Rackspace Technology Link Copied! Recent Posts How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 Getting Started With AI: A Practical Path Forward February 5th, 2026 Effective Housekeeping With Rackspace Managed Snapshot Cleanup January 29th, 2026 Redefining Detection Engineering and Threat Hunting with RAIDER January 27th, 2026 How to Keep Azure Cloud Costs Under Control with Continuous Optimization January 26th, 2026 Related Posts Cloud Insights How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 AI Insights Getting Started With AI: A Practical Path Forward February 5th, 2026 Cloud Insights Effective Housekeeping With Rackspace Managed Snapshot Cleanup January 29th, 2026 AI Insights Redefining Detection Engineering and Threat Hunting with RAIDER January 27th, 2026 Cloud Insights How to Keep Azure Cloud Costs Under Control with Continuous Optimization January 26th, 2026 A real-world threat hunting engagement shows how INC Ransom activity was uncovered early, before alerts fired and before ransomware could take hold. Modern security operations rely heavily on automated detection. Alerts, analytics and automated responses play a critical role in identifying known threats and responding at speed. But even the most mature security operations center cannot account for every possible adversary behavior. That gap is where proactive threat hunting becomes essential. Threat hunting is designed to surface malicious activity that does not yet meet the threshold of an incident. This is the kind of activity that blends into normal operations, avoids known detection logic or unfolds slowly over time. If you rely only on alerts, this behavior is easy to miss. A recent threat hunting engagement conducted by the Rackspace Cyber Defense Center demonstrates exactly why this capability matters. Safeguarding critical emergency communications The environment in question belonged to a government services organization that supports critical emergency communications. Availability, reliability and trust were non-negotiable. Any service disruption, particularly one caused by ransomware, would have had immediate operational and public safety implications. Like many organizations operating critical services, this environment relied on standard preventative controls and alerting to identify known threats. At the time of the engagement, there were no active incidents, no high-severity alerts and no visible signs of compromise. That was precisely the point. The absence of alerts did not indicate the absence of risk. It created an opportunity to look deeper for adversary behavior that had not yet reached an alerting threshold. A proactive, analyst-led threat hunt As part of a scheduled, analyst-led threat hunting exercise, the Rackspace Cyber Defense Center conducted a focused review of identity, endpoint and network telemetry collected over the prior month. The hunt assumed potential compromise and intentionally looked beyond alert-based detections. If youre responsible for a mature security environment, this type of threat hunt may feel counterintuitive. There was no incident to respond to and no alert demanding investigation. Instead, analysts worked from the premise that not all adversary activity announces itself. The goal was to identify behaviors that should not exist, even when controls appear to be working as expected. Rather than responding to known indicators, analysts searched for adversary behaviors aligned to the MITRE ATT&CK framework. This included techniques commonly associated with ransomware activity, such as credential abuse, unauthorized remote access, lateral movement and early-stage prepositioning. This hunt was not driven by an incident. Instead, it was driven by intent and the understanding that early-stage adversary behavior is often easiest to find before it becomes an alert. Focusing on the INC Ransom threat group The threat hunt focused on tradecraft associated with INC Ransom, a globally active ransomware and data extortion group that has been operating since at least mid-2023. The group has been linked to attacks against public sector organizations and critical services, often relying on credential compromise, Living off the Land techniques and the abuse of legitimate remote access tools before moving to encryption or extortion. If you are responsible for defending a complex environment, this kind of activity may sound familiar. These techniques are designed to blend in. They rely on tools and access patterns that can appear legitimate, especially in environments with diverse users and administrative workflows. At the time of the hunt, there were no dedicated detections in place tuned specifically to INC Ransoms early-stage behaviors. That gap proved critical. It meant adversary activity could progress quietly, without triggering alerts, unless someone was actively looking for it. What the hunt uncovered before impact The threat hunt did not surface a single obvious indicator. Instead, it revealed a pattern of early-stage adversary behavior unfolding across identity, endpoint and network telemetry. Individually, each signal was subtle. Taken together, they pointed to an active intrusion progressing toward ransomware execution. Because analysts werent constrained by alert thresholds, they were able to identify these behaviors early, before encryption, data exfiltration or service disruption occurred. The findings fell into several key areas. Identity and authentication abuse Analysis of authentication telemetry revealed cleartext authentication events associated with a legitimate user account. This activity deviated from established baselines and suggested potential credential exposure. Correlation with logon timing and source infrastructure elevated the risk assessment. Unauthorized account activity and RDP access Threat hunting analysis identified unauthorized RDP logon activity tied to an unapproved user account. The account did not align with documented access requirements or operational usage patterns. Session attributes and originating infrastructure were inconsistent with normal administrative behavior. Unauthorized remote access tooling Endpoint execution telemetry revealed the presence of an unapproved remote access tool, AnyDesk.exe. Installation and execution context indicated unauthorized use rather than sanctioned administrative activity. The organization confirmed that only approved remote access tools were permitted within the environment. Network-based pre-impact indicators Proactive network analysis identified multiple malicious external IP addresses generating high-volume inbound traffic that was initially permitted at the application layer. In addition, ransomware-related artifacts, including README.txt and README.html files, were observed originating from suspicious external infrastructure. While encryption had not yet occurred, these indicators aligned with known INC Ransom pre-impact behavior. Viewed in isolation, none of these findings would necessarily indicate an active ransomware event. Together, they revealed a clear trajectory toward impact. This is where proactive threat hunting proved decisive. By identifying low-signal behaviors early and connecting them across telemetry sources, analysts were able to surface attacker intent before the environment reached an incident threshold. Containment before disruption Once the activity was identified, containment actions were taken quickly and in close coordination with the customer. The focus was on stopping adversary progression without disrupting normal operations. Key actions included: Disabling unauthorized user accounts associated with suspicious authentication and RDP activity Blocking malicious external IP addresses at perimeter and cloud security layers Removing unauthorized remote access tooling after customer validation Sharing confirmed Indicators of Compromise to strengthen environment-wide prevention and monitoring Following containment, analysts conducted a review of subsequent telemetry to validate remediation. No continued malicious activity was observed. Most importantly, the threat was stopped before it reached impact. No ransomware encryption occurred. No data was exfiltrated. No service disruption was experienced. Closing the gaps between alerts This engagement highlights a practical reality of modern security operations. Not all malicious activity generates alerts, and not all compromises begin with a clear incident. Ransomware groups increasingly rely on low-noise techniques that unfold gradually. They abuse legitimate credentials, use approved tools and blend into normal operational workflows. In environments that depend primarily on automated detection, this activity can persist unnoticed unil attackers reach later stages such as encryption or extortion. Proactive threat hunting is designed to close these gaps. By looking for behavior that falls outside expected patterns, analysts can identify adversary activity earlier, validate whether controls are working as intended and uncover blind spots that automated detections do not address. In this case, threat hunting surfaced adversary behavior that would likely have remained invisible until the environment reached an incident threshold. How Rackspace helps Threat hunting is a core part of Rackspace Managed XDR and is delivered through the Rackspace Cyber Defense Center powered by Microsoft Sentinel. It is not treated as a one-off exercise or an escalation step. It is an ongoing, analyst-led capability designed to work alongside detection and response. If you rely primarily on alerts to understand risk in your environment, threat hunting provides a necessary counterbalance. Analysts actively search for emerging adversary behavior that automated logic may miss, using evidence drawn from identity, endpoint and network telemetry. By combining deep security expertise with continuous analysis across these data sources, Rackspace helps you identify risk earlier, validate whether controls are operating as intended and strengthen cyber resilience without waiting for an alert to fire. Take the next step with a Microsoft Sentinel Visibility & Resilience Check to identify detection gaps and improve visibility between alerts. Tags: Cloud Insights
Category: Telecommunications
Rackspace Technology at ViVE 2026
2026-02-06 19:19:08| The Webmail Blog
Rackspace Technology at ViVE 2026 jord4473 Fri, 02/06/2026 - 12:19 Cloud Insights Rackspace Technology at ViVE 2026 February 17, 2026 by Rich Fletcher, Global Healthcare Marketing Director, Rackspace Technology Link Copied! Recent Posts Rackspace Technology at ViVE 2026 February 17th, 2026 Rethinking Security in the Face of the Skills Gap February 16th, 2026 Community Impact 2025: A Global Year of Giving Back February 13th, 2026 Turning AI into Measurable Outcomes with Private Cloud February 12th, 2026 How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 Related Posts Cloud Insights Rackspace Technology at ViVE 2026 February 17th, 2026 Cloud Insights Rethinking Security in the Face of the Skills Gap February 16th, 2026 Culture & Talent Community Impact 2025: A Global Year of Giving Back February 13th, 2026 AI Insights Turning AI into Measurable Outcomes with Private Cloud February 12th, 2026 Cloud Insights How Proactive Threat Hunting Stopped INC Ransom Before the Alert February 9th, 2026 At ViVE 2026, Rackspace Technology explores cyber resilience in healthcare and how minimum viable hospital strategies help organizations sustain care during disruption. Moving beyond cybersecurity to enable the minimum viable hospital Healthcare leaders know cybersecurity is no longer just an IT concern. When systems go down, care delivery is at risk. That reality is driving a broader shift from traditional prevention-only security models toward cyber resilience. At ViVE 2026, Rackspace Technology will be on site to engage with healthcare executives and IT leaders navigating this shift. Our team will join industry peers to explore how resilient cloud foundations help organizations protect patient trust, meet regulatory demands and keep clinical operations running when it matters most. Cyber resilience as a healthcare imperative Hospitals are complex digital ecosystems. Clinical systems are only one part of the picture. Core operations such as facilities, staffing, supply chains and administrative services are just as essential to patient outcomes. As cyber threats increase, resilience becomes the true indicator of readiness. Cyber resilience is about maintaining a minimum viable hospital. By connecting security, cloud architecture and operations, healthcare organizations can sustain essential care and hospital-wide operations during disruption. This reduces impact to patients, protects operational continuity and reputation and ultimately helps prevent loss of life, transforming cybersecurity from a reactive function into an operational imperative. ViVE 2026 speaking session Melissa Pettigrew, Product Director, Healthcare, Rackspace Technology, will take the ViVE stage to explore this topic alongside Rubrik, sharing practical insights on how healthcare organizations can operationalize resilience without slowing innovation. Session details Title: Beyond Cybersecurity: Enabling the Minimum Viable Hospital Through Cyber Resilience Event: ViVE 2026 Location: Live from the CHiME Theater, Los Angeles Convention Center Date & time: Tuesday, February 24, 2026 | 12:50 PM1:20 PM Speakers Melissa Pettigrew, Product Director, Healthcare, Rackspace Technology Nathan Bahls, Sales Engineering Manager, Rubrik Calli Dretke, EVP, Chief Digital and Marketing Officer, CHIME The session will examine how cyber resilience strategies support continuity of care, align security with operations and help healthcare leaders rethink preparedness through the lens of patient impact. Meet the Rackspace team at ViVE Rackspace Technology will be sending a team of healthcare sales and product leaders to ViVE 2026. We will be hosting onsite meetings throughout the event in Meeting Room MC-655, located in the Meeting Cube Complex on the show floor. If you are attending ViVE and want to discuss cyber resilience, cloud modernization or healthcare-specific security challenges, we would welcome the conversation. Attend the session Tags: Private Cloud Cloud Insights Healthcare
Category: Telecommunications