• Container Network Interface Kubernetes

    The Kubernetes Networking Model: Simplicity by Design Kubernetes begins with a deceptively simple promise that every pod gets its own IP address, and every pod can communicate with every other pod directly, without NAT. From the perspective of an application running inside a pod, the network should feel flat and predictable, regardless of which node…

  • Cloud Portability Drives Business Flexibility

    What makes cloud portability more than just a technical preference? Why Cloud Portability is Essential Hybrid Cloud Models and Their Role Sector Applications The Technical Layer Business Value of Cloud Portability1. Avoiding Vendor Lock-In2. Smarter Cost Management3. Compliance Without Compromise4. Future-Proofing Technology Investments Role of Providers in Cloud Portability enterprise AI platform’s Place in This…

  • Build vs Buy AI Platform: Finding the Right Balance

    Why Every AI Ambition Breaks on the Build vs Buy Question What Building an AI Platform Actually MeansThe Benefits of BuildingThe Challenges of BuildingIndustry Examples The Case for Buying an AI PlatformThe Benefits of BuyingThe Trade-Offs of BuyingIndustry Examples The Trade-Off Matrix: Build vs Buy AI Platform Comparing the Two Paths Beyond Cost and Speed…

  • The Infrastructure Gap Stalling BFSI

    Volume was never the real problem, variability is. This is also why more teams are shifting to an AI GPU cloud when real-time systems start seeing unpredictable spikes. For a long time, scaling financial systems was pretty straightforward. More users, more transactions, more data, but the shape stayed the same. Growth was predictable. You could…

  • B300 in Production: What 18 Benchmark Runs Actually Showed

    For a while now, the B300 conversation has been mostly spec sheets. 268 GiB of HBM3e per GPU, Blackwell Ultra architecture, numbers that look almost too clean on paper. The question engineers actually ask is – ‘whether a 400-billion parameter model can run on four GPUs without falling apart under real concurrency’, and ‘whether the throughput…

  • The Economics of Running AI Inference on AMD MI350X

    Every time someone uses an AI model, it runs inference, reading the request and producing an answer, token by token, and you pay for every token. It runs every day the model is live, and grows with every user. There are two forces pulling against each other, when it comes to tokens – Tokens keep…

  • AMD MI300X: Specs and Performance for AI/ML Workloads

    If you’re someone working in AI research, data science, or cloud computing, you need the best hardware. It must handle massive datasets, complex AI models, and high-speed computations. The AMD MI300X is designed to deliver exactly that. This GPU has groundbreaking memory capacity (192GB HBM3). It boasts high-performance architecture. Efficiency optimisations further enhance its capabilities.…

  • Will Your AI run on AMD?

    More teams are taking a hard look at AMD chips this year, and the reason is simple: there aren’t enough NVIDIA GPUs to go around. The newest ones are sold out into late-2026, with a backlog in the millions of units, and most of what’s available has already been committed. You can get AMD chips…

  • Winning with AI: Identifying Use Cases and Running POCs

    Introduction to AI Use Cases to POCs: Thinking Like A Quarterback wins with strategic bets. Understanding the AI Playbook Mapping the AI Field: Exploring Business Challenges Choosing The Right Plays: Common AI Use Cases Playbook to Practise: Building AI Proof of Concept (POC) Winning with AI: Industry Examples Retail: Mercari Healthcare: Bupa APAC Financial Services: JPMorgan Chase Conclusion…

  • AI training on Cloud Platforms: leveraging infrastructure for next-gen models

    Introduction Why Train AI Models in the Cloud?ScalabilityCost EfficiencyCollaborationSpecialised Hardware Dominant Players in AI Cloud Training AI Cloud Use Cases Across IndustriesManufacturingBFSIHealthcare Conclusion FAQs Scalability Cost Efficiency Collaboration Specialised Hardware Manufacturing BFSI Healthcare Introduction Not too long ago, creating an artificial intelligence (AI) model was something only extremely well-funded research laboratories or Big Tech could…