Operations | Monitoring | ITSM | DevOps | Cloud

The HaloPSA plugin is a new addition to SquaredUp, and helps you create live dashboards that surface the important metrics – giving you and your team a single pane of glass for help desk performance, asset visibility, and client reporting. Why it matters: If your team uses HaloPSA to manage tickets, assets, and clients, then you already know how vital that data is for running smooth operations.

There’s a common misconception in IT operations that mastering DevOps, AIOps, or MLOps means you’re “fully modern.” But these aren’t checkpoints on a single journey to automation. DevOps, MLOps, and AIOps solve different problems for different teams—and they operate on different layers of the technology stack. They’re not stages of maturity. They’re parallel areas that sometimes interact, but serve separate needs.

You’ve probably felt the pain: data pouring in from every corner of your stack, tools choking on volume, dashboards lagging behind reality, alerts firing (or worse, not firing) without context. If that sounds familiar, it’s time to get serious about telemetry pipelines. Whether you're an SRE trying to stabilize a flapping service or a developer navigating multi-cloud chaos, a telemetry pipeline helps you take control of the data firehose.

We are exploring how we can help on-call engineers troubleshoot incidents more effectively by providing the OpenAI Codex agent with access to real-time observability data in terminals. We've developed an integration and new tool visualizations that connect OpenAI's Codex CLI to the new Datadog MCP server. In this post, we'll share what we've been experimenting with: enabling an AI agent to retrieve production metrics, logs, and incidents from Datadog in real time and act on that context.

For decades, PHP has powered the web using a simple model: process a request, send a response, then shut down. This model, especially in the form of CGI and PHP-FPM, is easy to understand but increasingly inefficient for modern web demands.

Today, we’re announcing the general availability of Lumigo Copilot, the most intelligent AI-powered observability assistant on the market, built for the complexities of modern microservices. Copilot emerged from a simple realization: Distributed systems produce too much fragmented data across too many layers, making troubleshooting slow, reactive, and deeply manual. Copilot changes that.

Your organization has a bold modernization roadmap. Cloud migration. Application updates. Enhanced customer experiences. New revenue streams. The business case is compelling, the stakeholders are aligned, and the budget is approved. Yet six months in, progress feels sluggish. The cloud migration is behind schedule due to performance issues no one anticipated. Application modernization stalled when the team discovered integration complexities that weren’t apparent during planning.