Operations | Monitoring | ITSM | DevOps | Cloud

The Command Center Shift: Why the Future of Middleware is Unified, Predictive, and Transaction-Centric

Middleware is evolving beyond invisible plumbing into a strategic Command Center. The future demands unified management, predictive intelligence, and transaction-centric operations to move from reactive firefighting to operational mastery in 2026.

Enable end-to-end visibility into your Java apps with a single command

Achieving end-to-end observability for applications is a top priority for organizations today, but instrumenting for both frontend and backend monitoring can be a significant hurdle. What complicates matters is that the SREs and DevOps teams responsible for deploying monitoring tools typically don’t own frontend code or have the context needed to safely modify it.

Powering Security Innovation: Executive Q&A on Splunk Joining AWS Security Hub Extended

To succeed in the AI era, customers need fast, easy access to security solutions that can harness the power of agentic AI and deliver business outcomes. They need seamless access to their data for faster threat detection, simpler incident response, and reduced risk. They need technology vendors to work together and not in silos.

Inside the architecture: How Upsun delivers 99.99% uptime for AI

For a CTO, "four nines" represents a commitment to keeping production revenue live with less than 0.01% of total downtime per year. As AI workloads move from pilot projects into core production services, the reliability requirements for infrastructure have shifted. AI agents, RAG pipelines, and automated LLM workflows depend on a consistent platform state.

Build a Unified Operational Ecosystem with ServiceNow and Coralogix

During high-priority incidents, SRE teams frequently lose critical time switching between monitoring platforms and ticketing systems. Context switching like this forces engineers to manually update incident states by copying and pasting data. The inevitable result is increased risk of information gaps and slower Mean Time to Recovery (MTTR).

Unmasking the Resolute Raccoon

You’ve almost certainly seen them… In the forest, rummaging through a dumpster, in poorly aging millennial memes. Raccoons are ubiquitous and endlessly entertaining creatures. YouTube and TikTok are full of videos documenting their clever antics and escapades. One such intrepid raccoon gained fame for making their way to the most unlikely places, from liquor stores to karate studios.

How to Debug Code You Didn't Write (your AI did)

I was looking at a customer’s error report last week. A TypeError buried three callbacks deep in a checkout flow that made no sense. The code around it was clean, well-structured, and completely wrong about how the Stripe API actually works. Turns out it was vibe-coded. Someone prompted their way through the integration, it passed code review because it looked reasonable, and it worked fine right up until a customer’s card got declined for the first time. That’s the new normal.

Managing AI Models and Datasets with Harness Artifact Registry | AI/ML Artifact Management

Building AI applications often means juggling multiple models, scattered datasets, and version chaos across local systems. But what if you could bring it all together — securely and efficiently — in one place? In this walkthrough, Shibam Dhar, DevRel Engineer at Harness, demonstrates how Harness Artifact Registry makes it easy to manage and govern your AI/ML assets — from models and datasets to prompts and agents — with built-in support like Hugging Face and generic registry types.