Cloud Computing Solutions

7 Critical Networking Protocols Every Technology Professional Must Know As a technology professional, understanding core networking protocols is crucial for building  reliable and efficient systems. Let’s break it down into what, how, and where these protocols are used: 1. 𝗧𝗖𝗣/𝗜𝗣   𝗪𝗵𝗮𝘁: The backbone of the internet, combining the Transmission Control Protocol (TCP) and Internet Protocol (IP).   𝗛𝗼𝘄:   - TCP ensures reliable data delivery with error checking and flow control.   - IP manages addressing and routing across networks.   𝗪𝗵𝗲𝗿𝗲:   - Web services like HTTP (port 80) and HTTPS (port 443) rely on TCP/IP for communication.  2. 𝗗𝗡𝗦   𝗪𝗵𝗮𝘁: Domain Name System translates human-readable domain names into IP addresses.   𝗛𝗼𝘄:   - Uses a hierarchical structure: root servers, TLD servers, and authoritative name servers.   - Supports record types like A, AAAA, MX, and CNAME.   𝗪𝗵𝗲𝗿𝗲:   - Vital for web infrastructure and email routing.  3. 𝗛𝗧𝗧𝗣/𝗛𝗧𝗧𝗣𝗦   𝗪𝗵𝗮𝘁: Protocols that power web communication and data transfer.   𝗛𝗼𝘄:   - Implements RESTful methods like GET, POST, PUT, and DELETE.   - Status codes (e.g., 200, 404) indicate request outcomes.   - HTTPS adds encryption via SSL/TLS for secure data transfer.   𝗪𝗵𝗲𝗿𝗲:   - Used by websites, APIs, and modern web applications.  4. 𝗦𝗠𝗧𝗣   𝗪𝗵𝗮𝘁: Simple Mail Transfer Protocol enables email transmission.   𝗛𝗼𝘄:   - Works alongside POP3 and IMAP for email delivery and retrieval.   - Implements security features like SPF, DKIM, and DMARC.   𝗪𝗵𝗲𝗿𝗲:   - Operates on ports 25 (standard) and 587 (TLS) for secure email communication.  5. 𝗙𝗧𝗣   𝗪𝗵𝗮𝘁: File Transfer Protocol for transferring files over a network.   𝗛𝗼𝘄:   - Supports active and passive modes for connections.   - Secure alternatives include SFTP (SSH-based) and FTPS (SSL/TLS-based).   𝗪𝗵𝗲𝗿𝗲:   - Ideal for large file transfers, especially between servers.  6. 𝗨𝗗𝗣   𝗪𝗵𝗮𝘁: User Datagram Protocol prioritizes speed over reliability.   𝗛𝗼𝘄:   - Offers minimal overhead, making it faster but less reliable than TCP.   - Commonly used for real-time applications like VoIP and streaming.   𝗪𝗵𝗲𝗿𝗲:   - Frequently paired with DNS and DHCP for network services.  7. 𝗗𝗛𝗖𝗣   𝗪𝗵𝗮𝘁: Dynamic Host Configuration Protocol automates IP address management.   𝗛𝗼𝘄:   - Uses the DORA process (Discover, Offer, Request, Acknowledge) for IP assignment.   - Configures network parameters like subnet mask and default gateway.   𝗪𝗵𝗲𝗿𝗲:   - Critical for scaling networks and managing devices dynamically.  Why These Protocols Matter   These networking protocols form the foundation of modern systems. Mastering them enables better system design, faster troubleshooting, and improved performance. What tools do you use for network diagnostics?   Personally, I rely on 𝗖𝗵𝗿𝗼𝗺𝗲 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿 𝗧𝗼𝗼𝗹𝘀 for web debugging. What’s your go-to tool?

The next era of datacenters is here. The demand for AI is growing rapidly, and with it comes the need to grow the cloud’s physical footprint. Historically, datacenters have been water-intensive and require using large amounts of higher carbon materials like steel. At Microsoft, we're building datacenters with sustainability in mind, and we're constantly innovating to find new ways to reduce our environmental impact. This includes: 🤝 A first-of-its-kind agreement with Stegra, backed by an investment from Microsoft’s Climate Innovation Fund (CIF) in 2024, to procure near zero-emissions steel from Stegra’s new plant in Boden, Sweden, for use in our datacenters. Powered by renewable energy and green hydrogen, Stegra's facility reduces CO2 emissions by up to 95% versus conventional steel production. By committing to purchase this green steel before it rolls off the line, Microsoft is sending a clear market signal, driving demand for cleaner materials and supporting Stegra’s growth. 💧 We also announced a major breakthrough to make our datacenters more sustainable: microfluidic in-chip cooling technology. Unlike traditional cold plates that sit atop chips, microfluidics brings cooling right inside the silicon itself. Engineers carve microscopic channels directly into the chip, letting liquid coolant flow through and absorb heat exactly where it’s generated. This approach is up to three times more effective than current methods. More efficient cooling allows datacenters to support powerful next-gen AI chips without ramping up energy use or investing in costly new gear. 💵 Through our CIF investments, we’ve catalyzed billions in follow-on capital for breakthrough solutions in low-carbon materials, sustainable fuels, carbon removal, and more. We just released a new whitepaper – Building Markets for Sustainable Growth – that distills five key lessons on how catalytic investment and partnership can move markets and accelerate a global transition in energy, waste, water, and ecosystems. Our journey toward sustainable datacenters is only beginning, and we recognize true progress requires collective action and investment. Read more from Building Markets for Sustainable Growth: https://msft.it/6041sq9xD

A few months ago, I was juggling Terraform deployments on AWS and Azure across dev, test, and prod environments. As the project grew, managing separate states, avoiding drift, and keeping the code clean became a real challenge. This happens when you handle multi-cloud and multi-environment code without a proper configuration structure. Messy state files, deployment errors, and overwritten environments can follow. In my latest blog, I share tips to manage multi-cloud (AWS + Azure) and multi-environments (dev, test, prod): • Project structure • Variables & modules • State file • Best practices for running Terraform • Common pitfalls in multi-cloud Terraform 🔗 Find the blog link in the comments. 💬 I would love to know how you are managing your Terraform projects?

Legacy systems are holding HR leaders back. 61% of HR leaders cite outdated tech as a barrier to business goals (McKinsey). And tools like Workday and SAP SuccessFactors, that were once revolutionary, now face challenges like inefficiency, poor integration, and outdated user experiences. The time for transformation is now. 2025 offers HR Directors the chance to reimagine their tech strategies: > AI & Automation: Automate tasks like payroll and onboarding, allowing HR teams to focus on strategic initiatives. > Integrated Platforms: Cloud-based systems streamline operations, improving efficiency by 20% and cutting costs by 15% (Forbes). > Enhanced Employee Experience: Personalised tools and feedback systems boost engagement and retention. > Data-Driven Insights: Advanced analytics provide actionable insights into workforce trends and decision-making. 4 key considerations to make when evaluating HR Tech: 1) Focus on Scalability: Choose solutions that integrate well and grow with your organisation. 2) Embrace Automation: Free up time for strategic HR work. 3) Prioritise Employee Experience: Invest in tools that enhance learning, wellbeing, and communication. 4) Leverage Analytics: Use data to drive smarter talent and business decisions. 2025 is the time for HR leaders to modernise their tech infrastructure. Outdated systems no longer meet the demands of a dynamic, data-driven workforce. By embracing advancements in technology, HR departments can deliver greater efficiency, employee satisfaction, and business outcomes. What HR tech changes are you looking to make in 2025? #FutureOfHR #HRTech #HRInnovation #FutureOfWork P.S. This is 1 of 9 trends featured in our new report, Shaping the Future of HR. Find all 9 on the TalentMapper website 🔍 (1/9)

🚨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

“Should we move to the cloud?” is no longer the question businesses are asking. Today, the question is, how do we make the cloud work smarter for us? The better approach depends on an organization’s maturity, goals, and industry: * Cloud-First is ideal for startups or companies looking to modernize quickly and embrace innovation at scale. * Cloud-Smart works best for enterprises with diverse workloads, legacy systems, or complex regulatory needs—where a one-size-fits-all approach doesn’t always fit.   In practice, a cloud-smart strategy often wins in the long run, striking a balance between agility, cost-effectiveness, and operational control. It reflects a more thoughtful understanding of the cloud’s role in achieving business outcomes, beyond simply adopting it for its own sake. In India, we see both approaches shaping businesses—from startups scaling with cloud-native solutions to established organizations optimizing their workloads to meet unique needs like data sovereignty and cost efficiency.   So, what’s your perspective? Are you leaning toward one approach, or navigating a mix of both?   #CloudStrategy #DigitalTransformation #BusinessTechnology #PegaIndia

😮 5% of people are responsible for 35% of the valuable collaboration in your organization.   One of the highlights of my time at the Tulsa Remote Plugged In Conference was meeting Rebecca Hinds, PhD, Head of Asana's Work Innovation Lab. Onstage she gave a presentation jam-packed with great insights about what it takes for effective team collaboration. Offstage we got to share stories about how what her research shows is what I see on a daily basis as we work with cross-functional distributed and hybrid teams. And how teaching teams to create their team charters / team working agreements to codify goals, roles, and ways of working leads to more effective collaboration and more teammate connection. Key takeaways from her presentation, "5 Research-Backed Strategies to Drive Better Collaboration": 1. Collaboration equity 52% of employees say their teams rely on a few high performers to get work done. When Asana provided a dashboard to show how collaboration was distributed across the team, 93% made meaningful changes when it was visible who needed to step back and others needed to step up 2. Cross-functional collaboration The most innovative firms have 30-50% of their ties established cross-functionally. Example: for tech companies the top predictor of innovation is strength of collaboration between marketing and engineering 3. Collaboration across physical space Asana research shows that the current behavior is for people to do more cross functional collaboration on in-office workdays than on remote workdays. [My 2 cents → this is why building what I call "Omni-modal" leadership skills is so critical, so that people are equally skilled at collaborating in a remote or hybrid setting as they are in an in-person setting. Especially since many people need to switch between these modes even within the same day. ] 4. Collaboration across work The connection between tasks and goals is a massive driver of employee engagement. Only 55% of workers in remote and hybrid orgs are clear on how their work helps their company reach its goal. For every 10 pieces of work related to goals there is + 7% increase in engagement. For every 100 pieces there is a +101% increase in engagement. 5. Collaboration with AI Treat it like a teammate, not just a tool. When used daily, 89% of people say they get productivity gains. But AI needs cross-functional context to enable the best collaboration. P.S. a big thanks to Justin Harlan and Betsy Slagle for pulling together a well-crafted event with a great line-up of speakers! #tulsaremote #virtualleadership #hybridteams

There’s more to AI than ChatGPT and DeepSeek… Here are 6 AI productivity tools I can’t stop using: 1. Perplexity (Personal Researcher) When I want in-depth answers to urgent questions, I use Perplexity more than Google these days. It’s like having your own 24/7 research assistant — I use it to do industry research, competitor analysis, fact-finding, and much more. https://www.perplexity.ai/ 2. Substrata (Dealmaking Assistant) High-stakes dealmaking can get complex, making it hard to have a clear understanding of how things are going. Substrata solves this by carefully evaluating all the signals (across your calls and emails) to understand who has the upper hand in a deal — and how to get it if you don’t. My company closed two massive deals this year (both Fortune 500 firms), and I used this tool a ton. https://www.substrata.me/ 3. Gamma (AI-Powered Presentations) Create infinite presentations, websites, and more in seconds with AI. It’s saved me hundreds of hours already, and the end results always look great. https://gamma.app/ 4. Claude (Idea Generator) I use Claude 90% of the time, and ChatGPT just 10%. Why? Claude’s writing sounds more human and is really good at giving easy-to-understand concepts. I use it to get ideas for carousels/infographics and improve my LinkedIn content. https://claude.ai/ 5. NotebookLM (Infinite Knowledgebase) This is the most underrated AI tool right now… You can combine all of your knowledge (PDFs, recordings, blog posts, etc) on a given subject in a single place and get instant hallucination-free answers when you search it. The best part? It’s 100% free (from Google). https://lnkd.in/gAfYp_Kb 6. Tango (Easy SOPs) Creating walkthroughs and SOPs for new hires is incredibly important—but equally tedious and time-consuming. This is by far the best tool for doing that (and creating any kind of how-to) that I’ve found. https://www.tango.ai/ … Those are my favorites. Which would you add?

“𝗦𝟯, 𝗔𝗗𝗟𝗦, 𝗚𝗖𝗦? 𝗝𝘂𝘀𝘁 𝘀𝘁𝗼𝗿𝗮𝗴𝗲, 𝗿𝗶𝗴𝗵𝘁?” Not quite. Here’s a better way to think about it 👇 𝗖𝗹𝗼𝘂𝗱 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 — 𝗠𝗼𝗿𝗲 𝗧𝗵𝗮𝗻 𝗝𝘂𝘀𝘁 𝗮 𝗙𝗶𝗹𝗲 𝗗𝘂𝗺𝗽 Cloud storage is like a hotel for your data. It checks in from various sources — APIs, apps, pipelines. Some stay temporarily (like staging or temp files) Others are long-term guests (like audit logs or historical records) You control who can access it (IAM), what they can do (read/write), and how long it stays (retention policies) There’s even housekeeping involved — with lifecycle rules, versioning, deduplication, and cost optimization. ⚠️ 𝗪𝗵𝗮𝘁 𝗣𝗲𝗼𝗽𝗹𝗲 𝗧𝗵𝗶𝗻𝗸 𝗗𝗘𝘀 𝗗𝗼: "Just dump the data to S3 and move on." ✅ 𝗪𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗛𝗮𝗽𝗽𝗲𝗻𝘀:   • Design folder structures for efficient querying and partitioning   • Choose the right storage class (Standard, Infrequent Access, Glacier)   • Use optimal file formats (Parquet, ORC) and compression (Snappy, Zstandard)   • Set access controls, encryption, and auditing (IAM roles, KMS, logging)   • Enable direct querying (Athena, Synapse, BigQuery on GCS)   • Integrate storage across cloud platforms (multi-cloud architectures)   • Automate lifecycle management to control cost and reduce clutter   • Leverage features like S3 Select, signed URLs, and Delta format for smart access 📌 Takeaway: Cloud storage isn’t where data ends up — it’s where the journey begins. How you design and manage it defines the performance, scalability, and reliability of everything downstream. #data #engineering #reeltorealdata #python #sql #cloud

Amidst the #AI dominance of boardroom discussions and headlines, there is one factor, whose catalyzing importance often goes under the radar: the #cloud. Let’s take a look. There is a two-way critical interdependence between AI and the cloud: —     Cloud computing is AI’s critical infrastructure. AI is literally running on the cloud. —     AI is a tremendous added value for the cloud, enhancing its functionality (i.e. automation, data analytics, security) and scalability. It might be going against public belief, but it’s not AI driving #innovation but the synergy between AI and the cloud. Which is why building an AI-native cloud is becoming the name of the game. There is no better justification for this twist than the emphasis that leading infrastructure companies are putting on cloud native #technology. Huawei with its Cloud Native 2.0 approach is a very good example: —     Introduced as early as the end of 2020, Cloud Native 2.0 features a new technical architecture: distributed cloud, application-driven infrastructure, hybrid deployment, unified scheduling, decoupled compute-storage, automated data governance, trusted DevOps, serverless, heterogeneous integration based on soft bus, multi-modal iterative industry AI, and all-round security. —     The new architecture translates to visible benefits in enterprise digital transformation: efficient resources, agile applications, Internet of Things, ultimate experience, service intelligence, security and trustworthiness, and industry enablement. One of the most notable aspects of Huawei’s Cloud Native 2.0 #strategy is the way that it connects AI and the cloud, via a parallel bi-polar focus in 2 directions: —     AI for Cloud —     Cloud for AI Via this dual strategy, Huawei is using AI to optimize cloud infrastructure ("AI for Cloud"), while simultaneously leveraging cloud resources to enhance AI development and deployment ("Cloud for AI"). The extent to which this dual play is critical is reflected in corporate spend. According to Huawei’s Intelligent World 2030 report: —     By 2030, cloud services will account for 87% of enterprises’ application expenditure, while —     AI computing will account for 7% of a company’s total IT investment Companies of all kinds are realizing that no matter the industry they are in and their role in the value chain, they are fast becoming software companies. In the sense that their ability to effectively deploy software can be a critical make or break factor. In turn, this ability depends on adopting cloud native technologies. For one main reason: because cloud native technologies mean fast delivery, which is a critical go-to-market component. This is a play in progress. Choosing the right cloud infrastructure (and provider) is becoming one of the main decisions companies will have to make, greatly influencing their ability to make good use of AI and to innovate. Opinions: my own; Graphic sources: Panagiotis Kriaris, Huawei  #HuaweiConnect