IT Infrastructure Management Strategies

🚨NSA Releases Guidance on Hybrid and Multi-Cloud Environments🚨 The National Security Agency (NSA) recently published an important Cybersecurity Information Sheet (CSI): "Account for Complexities Introduced by Hybrid Cloud and Multi-Cloud Environments." As organizations increasingly adopt hybrid and multi-cloud strategies to enhance flexibility and scalability, understanding the complexities of these environments is crucial for securing digital assets. This CSI provides a comprehensive overview of the unique challenges presented by hybrid and multi-cloud setups. Key Insights Include: 🛠️ Operational Complexities: Addressing the knowledge and skill gaps that arise from managing diverse cloud environments and the potential for security gaps due to operational siloes. 🔗 Network Protections: Implementing Zero Trust principles to minimize data flows and secure communications across cloud environments. 🔑 Identity and Access Management (IAM): Ensuring robust identity management and access control across cloud platforms, adhering to the principle of least privilege. 📊 Logging and Monitoring: Centralizing log management for improved visibility and threat detection across hybrid and multi-cloud infrastructures. 🚑 Disaster Recovery: Utilizing multi-cloud strategies to ensure redundancy and resilience, facilitating rapid recovery from outages or cyber incidents. 📜 Compliance: Applying policy as code to ensure uniform security and compliance practices across all cloud environments. The guide also emphasizes the strategic use of Infrastructure as Code (IaC) to streamline cloud deployments and the importance of continuous education to keep pace with evolving cloud technologies. As organizations navigate the complexities of hybrid and multi-cloud strategies, this CSI provides valuable insights into securing cloud infrastructures against the backdrop of increasing cyber threats. Embracing these practices not only fortifies defenses but also ensures a scalable, compliant, and efficient cloud ecosystem. Read NSA's full guidance here: https://lnkd.in/eFfCSq5R #cybersecurity #innovation #ZeroTrust #cloudcomputing #programming #future #bigdata #softwareengineering

Since the ’90s I’ve built, shipped, and occasionally exploited just about every kind of identity control. We’re now pretty good at building gates around privilege, but not nearly as good at removing it once the job is done. This hurts in 2025. Privileged access no longer lives only with well-defined admin accounts. It threads through every developer workflow, CI/CD script, SaaS connector, and microservice. The result: standing privilege is inevitable, an orphaned token here, a break-glass account there, quietly turning into “forever creds.” Here’s what’s working in the field: → One JIT policy engine that spans cloud, SaaS, and on-prem - no more cloud-specific silos.  ↳ Same approval workflow everywhere, so nobody bypasses “the one tricky platform.”  ↳ Central log stream = single source of truth for auditors and threat hunters. → Bundle-based access: server + DB + repo granted (and revoked) as one unit.  ↳ Devs get everything they need in one click - no shadow roles spun up on the side.  ↳ When the bundle expires, all linked privileges disappear, killing stragglers. → Continuous discovery & auto-kill for any threat that slips through #1 or #2.  ↳ Scan surfaces for compromised creds, role drifts, and partially off-boarded accounts.  ↳ Privilege paths are ranked by risk so teams can cut off the dangerous ones first. Killing standing privilege isn’t a tech mystery anymore, it’s an operational discipline.  What else would you put on the “modern PAM” checklist?

As a Global Capability Center(GCC) Leader, the Onus Is on You—Will You Drive AI Transformation or Get Left Behind? Most GCCs were not designed with AI at their core. Yet, AI is reshaping industries at an unprecedented pace. If your GCC remains focused on traditional service delivery, it risks becoming obsolete. The responsibility to drive this transformation does not sit with IT teams or innovation labs alone—it starts with you. As a GCC leader, you must push beyond cost efficiencies and position your center as a strategic AI hub that delivers business impact. How to Transform an Existing GCC into an AI-Native GCC This shift requires clear, measurable objectives. Here are five critical OKRs (Objectives & Key Results) to guide your AI transformation. 1. Embed AI in Core Business Processes Objective: Move beyond AI pilots and integrate AI into everyday decision-making. Key Results: • Automate 20 percent or more of manual workflows within 12 months. • Deploy AI-powered analytics in at least three business-critical functions. • Reduce operational decision-making time by 30 percent using AI insights. 2. Reskill and Upskill Talent for AI Readiness Objective: Develop an AI-fluent workforce that can build, deploy, and manage AI solutions. Key Results: • Train 100 percent of employees on AI fundamentals. • Upskill at least 30 percent of engineers in MLOps and GenAI development. • Establish an internal AI guild to drive AI innovation and best practices. 3. Build AI Infrastructure and MLOps Capabilities Objective: Create a scalable AI backbone for your organization. Key Results: • Implement MLOps pipelines to reduce AI model deployment time by 50 percent. • Establish a centralized AI data lake for enterprise-wide AI applications. • Deploy at least five AI use cases in production over the next year. 4. Shift from AI as an Experiment to AI as a Business Strategy Objective: Ensure AI initiatives drive measurable business value. Key Results: • Ensure 50 percent of AI projects are directly linked to revenue growth or cost savings. • Develop an AI governance framework to ensure responsible AI use. • Integrate AI-driven customer experience enhancements in at least three markets. 5. Change the Operating Model: From Service Delivery to Co-Ownership Objective: Position the GCC as a leader in AI-driven transformation, not just an execution arm. Key Results: • Rebrand the GCC internally as a center of AI-driven innovation. • Secure C-level sponsorship for AI-driven initiatives. • Establish at least three AI innovation partnerships with startups or universities. The question is not whether AI will reshape your GCC. It will. The time to act is now. Are you ready to drive the AI transformation? Let’s discuss how to accelerate your GCC’s AI journey. Zinnov Mohammed Faraz Khan Namita Dipanwita ieswariya Mohammad Mujahid Karthik Komal Hani Amita Rohit Amaresh

AI development comes with real challenges. Here's a practical overview of three ways AWS AI infrastructure solves common problems developers face when scaling AI projects: accelerating innovation, enhancing security, and optimizing performance. Let's break down the key tools for each: 1️⃣ Accelerate Development with Sustainable Capabilities: • Amazon SageMaker: Build, train, and deploy ML models at scale • Amazon EKS: Run distributed training on GPU-powered instances, deploy with Kubeflow • EC2 Instances:   - Trn1: High-performance, cost-effective for deep learning and generative AI training   - Inf1: Optimized for deep learning inference   - P5: Highest performance GPU-based instances for deep learning and HPC   - G5: High-performance for graphics-intensive ML inference • Capacity Blocks: Reserve GPU instances in EC2 UltraClusters for ML workloads • AWS Neuron: Optimize ML on AWS Trainium and AWS Inferentia 2️⃣ Enhance Security: • AWS Nitro System: Hardware-enhanced security and performance • Nitro Enclaves: Create additional isolation for highly sensitive data • KMS: Create, manage, and control cryptographic keys across your applications 3️⃣ Optimize Performance: • Networking:   - Elastic Fabric Adapter: Ultra-fast networking for distributed AI/ML workloads   - Direct Connect: Create private connections with advanced encryption options   - EC2 UltraClusters: Scale to thousands of GPUs or purpose-built ML accelerators • Storage:   - FSx for Lustre: High-throughput, low-latency file storage   - S3: Retrieve any amount of data with industry-leading scalability and performance   - S3 Express One Zone: High-performance storage ideal for ML inference Want to dive deeper into AI infrastructure? Check out 🔗 https://lnkd.in/erKgAv39 You'll find resources to help you choose the right cloud services for your AI/ML projects, plus opportunities to gain hands-on experience with Amazon SageMaker. What AI challenges are you tackling in your projects? Share your experiences in the comments! 📍 save + share! 👩🏻💻 follow me (Brooke Jamieson) for the latest AWS + AI tips 🏷️  Amazon Web Services (AWS), AWS AI, AWS Developers #AI #AWS #Infrastructure #CloudComputing #LIVideo

Key Secrets for Multicloud Success From “An Insider’s Guide to Cloud Computing” With voiceover and commentary by the author. Now that we understand the challenges of deploying and operating a multicloud, and some of the approaches that will likely overcome these challenges, let’s dig deeper into specific approaches to a multicloud deployment that will optimize its use. The goal is to leverage a multicloud deployment using approaches and technologies that minimize risk and cost and maximize the return of value back to the business. Everyone will eventually move to a multicloud deployment, and most have no idea how to do this in an optimized way. In other words, the deployment won’t be successful. Again, the concepts presented in this chapter are perhaps the most important in this book. Applied correctly, they will lead to successful multicloud deployments. Remember that most enterprises won’t increase their operations budget to support a multicloud. The key themes are to not replicate operational services for each cloud provider, which is the way teams typically approach multicloud today. That architecture won’t scale, and you will just make the complexity worse. Eventually, you’ll run into complexity issues such as security misconfigurations that lead to breaches or outages due to systems that aren’t proactively monitored. If these issues go unresolved, chances are good that your multicloud deployment will be considered a failure in the eyes of the business, or more trouble than the cost to deploy it. So, do not replicate operational processes such as security, operations, data integration, governance, and other systems within each cloud. This replication creates excess complexity. Here are some additional basic tenets to follow: Consolidate operationally oriented services so they work across clouds, not within a single cloud. This usually includes operations, security, and governance that you want to span all clouds in your multicloud deployment. Because it can include anything a multicloud leverages, it works across all clouds within a multicloud deployment. Leverage technologies and architectures that support abstraction and automation. This removes most of the complexity by abstracting native cloud resources and services to view and manage those services via common mechanisms. For instance, there should be one way to view cloud storage that could map down to 20–25 different native instances of cloud storage. Because humans do not need to deal with differences in native cross-cloud operations (security, governance, and so on), abstraction and automation avoid excess complexity. Isolate volatility to accommodate growth and changes, such as adding and removing public cloud providers, or adding and removing specific services. When possible, place volatility into a configurable domain (see Figure 6-10) where major or minor clouds and cloud services can be added or …

7 Cloud Migration Strategies Every Cloud Engineer Should Know (with scenario questions for interviews) Cloud migration can originate from on-premises infrastructure or from another cloud provider. And it goes beyond just moving data. It's about strategically deciding the best approach for each application and workload. The goal is to optimize performance, cost, and long-term viability in the cloud. Here’s a simple breakdown of the key strategies you should focus on: 1/ Retain (Revisit later) ↳ Keep workloads on-prem if they aren’t cloud-ready or are still needed locally. Scenario : You have a critical legacy application with custom hardware dependencies. How would you initially approach its cloud migration? 2/ Retire (Decommission) ↳ Eliminate outdated or unused parts to reduce cost and simplify the system. Scenario : During an assessment, you identify an old reporting tool used by only a few employees once a month. What's your recommendation? 3/ Repurchase (Drop & Shop) ↳ Replace legacy apps with SaaS alternatives, a fast and cost-effective solution. Scenario : Your company's on-premise CRM system (example) is outdated and costly to maintain. What quick cloud solution might you consider? 4/ Rehost (Lift & Shift) ↳ Move your application to the cloud as-is, with no code changes needed. Scenario : A non-critical internal application needs to move to the cloud quickly with minimal disruption. What strategy would you prioritize? 5/ Replatform (Lift, Tinker & Shift) ↳ Make light optimizations before migration, for better performance with minimal effort. Scenario : You're migrating a web application, and a small change to its database will significantly improve cloud performance. What strategy does this align with? 6/ Relocate (Many Providers) ↳ Change the hosting provider without modifying the app, a quick and simple approach. Scenario : Your current cloud provider is increasing prices significantly for a specific set of VMs. How might you address this without rewriting applications? 7/ Refactor (Re-architect) ↳ Redesign your application for cloud-native capabilities, making it scalable and future-ready. Scenario : A monolithic, highly scalable customer-facing application is experiencing performance bottlenecks on-prem. What long-term cloud strategy would you propose?. Beyond these strategies themselves, successful cloud migration also focuses on: - thorough assessment, - understanding dependencies, - meticulous planning, - and continuous optimization Just remember: successful migration isn't just about the tools, but the approach. Very important to understands the "why" behind each strategy — not just the "how." Dropping a newsletter this Thursday with detailed scenario based questions (and example answers) for each of these patterns — subscribe now to get it -> https://lnkd.in/dBNJPv9U • • • If you found this useful.. 🔔 Follow me (Vishakha) for more Cloud & DevOps insights ♻️ Share so others can learn as well

Communication is the glue that holds teams together, but even the smallest cracks can lead to major fractures if left unaddressed. Imagine trying to build a strong, sturdy wall without noticing the hairline cracks forming—those tiny issues eventually compromise the whole structure. The same is true for communication within teams. Here’s why communication cracks happen and how to address them before they break the team dynamic: 1️⃣ Clarity Over Assumptions One of the biggest causes of communication cracks is the assumption that everyone is on the same page. Leaders often believe their instructions are clear, while team members interpret them differently. The solution? Prioritize clarity. Spell things out, confirm understanding, ask for play backs from your audience and encourage team members to ask questions. It’s far better to over-communicate to get it wrong. 2️⃣ Build a Culture of Openness Fear of speaking up is a silent communication killer. If team members feel like they can’t ask questions, provide feedback, or share concerns, cracks start forming. Leaders must actively create an environment where openness is celebrated. Foster trust by inviting feedback regularly and responding with empathy and action. 3️⃣ Don’t Let Digital Overwhelm Human Connections In today’s workplace, we rely heavily on emails, chats, and virtual meetings. While these tools are convenient, they can dilute the human element of communication. Misinterpretations happen, and nuances are lost. Incorporate more face-to-face (or virtual face-to-face) conversations for clarity and connection. Sometimes, a 5-minute chat can fix what a dozen emails cannot. 4️⃣ Active Listening is Non-Negotiable Effective communication isn’t just about talking—it’s about listening. Leaders and team members alike need to practice active listening. This means not just hearing words but understanding intent, emotions, and the bigger picture. Active listening makes people feel valued and prevents misunderstandings from growing into bigger issues. 5️⃣ Address Conflict Early Unresolved conflict is one of the most visible cracks in team communication. When issues are ignored, they fester and grow, creating divides that are hard to repair. Address conflicts as soon as they arise. Create an environment where disagreements can be discussed constructively and lead to solutions, not resentment. Take Action Before It’s Too Late Communication cracks, if ignored, don’t just affect a single project or conversation—they compromise trust, productivity, and the overall health of the team. Proactively addressing them ensures your team remains aligned, resilient, and effective. What’s one step you’ll take this week to strengthen communication within your team? Let’s start the conversation below. 👇 #CommunicationMatters #TeamSuccess #ConflictResolution #Leadership #WorkplaceCulture #RuthOnLeadership

Yesterday, the National Security Agency Artificial Intelligence Security Center published the joint Cybersecurity Information Sheet Deploying AI Systems Securely in collaboration with the Cybersecurity and Infrastructure Security Agency, the Federal Bureau of Investigation (FBI), the Australian Signals Directorate’s Australian Cyber Security Centre, the Canadian Centre for Cyber Security, the New Zealand National Cyber Security Centre, and the United Kingdom’s National Cyber Security Centre. Deploying AI securely demands a strategy that tackles AI-specific and traditional IT vulnerabilities, especially in high-risk environments like on-premises or private clouds. Authored by international security experts, the guidelines stress the need for ongoing updates and tailored mitigation strategies to meet unique organizational needs. 🔒 Secure Deployment Environment: * Establish robust IT infrastructure. * Align governance with organizational standards. * Use threat models to enhance security. 🏗️ Robust Architecture: * Protect AI-IT interfaces. * Guard against data poisoning. * Implement Zero Trust architectures. 🔧 Hardened Configurations: * Apply sandboxing and secure settings. * Regularly update hardware and software. 🛡️ Network Protection: * Anticipate breaches; focus on detection and quick response. * Use advanced cybersecurity solutions. 🔍 AI System Protection: * Regularly validate and test AI models. * Encrypt and control access to AI data. 👮 Operation and Maintenance: * Enforce strict access controls. * Continuously educate users and monitor systems. 🔄 Updates and Testing: * Conduct security audits and penetration tests. * Regularly update systems to address new threats. 🚨 Emergency Preparedness: * Develop disaster recovery plans and immutable backups. 🔐 API Security: * Secure exposed APIs with strong authentication and encryption. This framework helps reduce risks and protect sensitive data, ensuring the success and security of AI systems in a dynamic digital ecosystem. #cybersecurity #CISO #leadership

𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧 1: 𝐓𝐡𝐞 𝐃𝐚𝐰𝐧 𝐨𝐟 𝐒𝐦𝐚𝐫𝐭 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐁𝐞𝐭𝐰𝐞𝐞𝐧 𝐭𝐡𝐞 𝐄𝐝𝐠𝐞 𝐚𝐧𝐝 𝐭𝐡𝐞 𝐂𝐥𝐨𝐮𝐝 In 2024, the spotlight is on smart connectivity, a critical evolution that promises to redefine IoT by enhancing the synergy between device intelligence at the Edge and cloud capabilities. This transformative approach is set to impact organizations across industries by enabling more efficient, secure, and intelligent operations. 𝐈𝐦𝐩𝐚𝐜𝐭 𝐨𝐧 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬: 📌𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐝 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐌𝐚𝐤𝐢𝐧𝐠: With the acceleration of Edge processing, organizations can leverage local data analysis for quicker, more autonomous decision-making. This reduces dependency on cloud processing, thereby minimizing latency and enhancing real-time responses. 📌𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲: Full-stack integration means that IoT devices will be more self-reliant, requiring less intervention and manual oversight. This leads to streamlined operations, lower operational costs, and reduced potential for human error. 📌𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐥𝐢𝐚𝐧𝐜𝐞: The emphasis on secure, resilient connectivity ensures that data is protected from endpoint to cloud. This is crucial for organizations dealing with sensitive information, helping them meet regulatory compliance standards like GDPR and HIPAA more effectively. 📌𝐂𝐨𝐬𝐭 𝐚𝐧𝐝 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Intelligent connectivity allows devices to select the most cost-effective and efficient network paths. This adaptability can lead to significant savings on data transmission costs and optimize network resource usage. 📢 𝐌𝐲 𝐓𝐡𝐨𝐮𝐠𝐡𝐭𝐬 The prediction of smart connectivity as a cornerstone for IoT in 2024 resonates with a growing trend toward distributed intelligence and the need for more agile, secure, and efficient operations. From an organizational perspective, this shift is not merely technological but strategic, offering a pathway to transform how businesses interact with digital infrastructure, manage data, and deliver services. 📌𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞: Organizations that embrace smart connectivity will gain a competitive edge through enhanced operational agility, improved customer experiences, and a stronger posture on security and compliance. 📌𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬: This new paradigm opens doors for innovative applications and services that leverage Edge intelligence, from advanced predictive maintenance to dynamic supply chain management and beyond. 📌𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐚𝐧𝐝 𝐂𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬: While the benefits are clear, organizations must also navigate the complexities of integrating this technology. This includes ensuring interoperability across diverse devices and platforms, managing the increased complexity of decentralized data processing, and addressing the security vulnerabilities that come with expanded IoT ecosystems.

The 2025 Honeywell Cyber Threat Report reveals a stark reality: the industrial sector is facing a cybersecurity reckoning. Cyberattacks on operational technology (OT) environments have intensified—ransomware surged 46% in six months, while attacks on water systems, transportation networks, and manufacturing plants have caused real-world disruptions. Threat actors are no longer simply infiltrating; they are interrupting critical services and endangering safety and continuity. One notable trend is the rise in USB-based malware and credential-stealing Trojans like Win32.Worm.Ramnit, which surged 3,000% in frequency. In parallel, over 1,800 distinct threats were detected through Honeywell’s Secure Media Exchange (SMX), with alarming infiltration routes observed across removable media, remote access exploits, and compromised credentials. What’s driving this escalation? • Legacy systems with limited security controls remain widely deployed. • Converged IT/OT environments increase the attack surface. • Regulatory pressure, such as the SEC’s cybersecurity disclosure rule, is raising the stakes for leadership teams. The implication is clear: defending the industrial enterprise requires more than traditional cybersecurity postures. It demands a shift toward cyber resilience—a proactive, integrated approach that embeds security into the DNA of operations. At a minimum, organizations must act on five imperatives: 1. Adopt Zero Trust principles—no device, user, or process should be implicitly trusted. 2. Implement strict segmentation between IT and OT networks. 3. Elevate threat visibility with continuous monitoring, detection, and response tools. 4. Enforce multi-factor authentication and access governance. 5. Ensure secure USB/media handling and endpoint control at every entry point. This is not a technology problem alone—it is an operational and leadership mandate. Every breach is now a business risk. Boards, CISOs, and plant leaders must align around a single objective: operational continuity through cyber integrity. Honeywell remains committed to advancing industrial cyber maturity through our ecosystem of threat detection, monitoring, and managed response capabilities. But securing the future will require collective effort—from regulators, vendors, operators, and industry consortia. As the report concludes, it’s not a matter of if your OT environment will be targeted. The question is—will you be ready?