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The latest News and Information on Cloud monitoring, security and related technologies.

Track the performance of your HPC workloads with Datadog's AWS PCS integration

AWS Parallel Computing Service (AWS PCS) is a managed service that helps users run and scale their high performance computing (HPC) workloads. AWS PCS uses Slurm, an open source workload manager, for scheduling and orchestrating simulations, which enables users to build their scientific and engineering models in a familiar HPC environment.

Beyond the Horizon: Cloud Security Realities MSPs Can't Ignore

In this episode of Beyond the Horizon, N-able Head Nerd Joe Ferla sits down with Lewis Pope, Head Security and Compliance Nerd, to unpack the evolving landscape of cloud security for MSPs. As MSPs shift from physical environments to cloud-first operations, Lewis shares hard-earned insights on what it takes to secure cloud workloads, manage identity, and navigate the growing complexity of cloud infrastructure.

5 Key Azure FinOps Principles for Ultimate Cost Control.

Seeking ways to slash Azure costs? This video breaks down the challenges and reveals how FinOps can be the strategic answer to optimizing your Azure resources that can help you maximize Azure cost savings. Furthermore, learn how the Azure Cost Management Tool from Turbo360 (formerly Serverless360) perfectly aligns with the five essential FinOps principles, enabling you to boost your Azure savings by up to 30%.

Mastering the User Off-Boarding Process

When someone leaves your organisation — whether they resign, retire, or are let go — it’s easy to think the hard work is over. But the moment an employee’s last day arrives, a new risk window opens. If their access isn’t revoked properly or their data isn’t captured, organisations face security breaches, data loss, compliance issues, and rising costs. This is why a well-designed user off-boarding process is just as important as onboarding.

AI's False Efficiency Curve: How To Save And Protect Your Margins

The popular narrative around AI economics is changing. At one time, Moore’s Law conditioned us to expect that smarter, faster computing would steadily get cheaper. When it comes to AI, that expectation holds true at the unit level. Per-token costs are indeed declining. But the number of tokens consumed per task is growing exponentially, making total costs spike. The tension here is important: on paper, inference is getting cheaper.

Exploring cloud analytics solutions for efficient data processing

In the ever-evolving digital landscape, organisations are increasingly turning to sophisticated systems that can handle their growing data needs efficiently. Cloud analytics solutions have emerged as a powerful approach for businesses looking to extract value from their information without overwhelming technical complexity or excessive costs. These platforms combine the flexibility of cloud computing with powerful analytical capabilities, creating an environment where data can truly drive decision-making.

I Tested MIG in Real-Life Azure - Did It Feel Like a Stuffed Cubicle?

I carved one Azure H100 into virtual “cubicles” using MIG (Multi-Instance GPU), compared it to an A100, ran Triton inference workloads, and captured both latency and cost. The verdict – The H100 with MIG delivers better latency and consistency, while the A100 is more cost-effective at scale, depending on your workload.