Operations | Monitoring | ITSM | DevOps | Cloud

The Rise of Generative Engine Optimisation Services and What Businesses Need to Know

Search is changing in a way that feels subtle on the surface but significant underneath. People still type questions into Google, but they are also asking ChatGPT, Perplexity, Gemini, and other AI tools for direct answers, recommendations, summaries, and comparisons. In many cases, they are not clicking through a list of ten blue links first. They are reading a synthesised response and making decisions from there.

Tier 1 SOC Automation Options Explained

In 2026, like in every other year, tier 1 is the front line of the SOC. It's where alerts land, where triage happens, and where most of the repetitive work lives. Unsurprisingly, it is also where automation is moving fastest. There is a lot of skepticism around how much of tier 1 can be reliably automated. If you want to see some, just have a look on Reddit or other forums. But there is definitely a growing market and capability for AI-enabled tools to learn, guide and automate tier 1 workflows.

How AI for Short-Term Rentals Is Reshaping Property Operations

Running a short-term rental used to mean juggling a dozen different tasks by hand. Checking messages, updating calendars, adjusting prices, coordinating cleaners, and answering the same guest questions over and over. Anyone who has managed even a single listing knows how much time this takes, and anyone managing multiple properties knows how quickly it becomes overwhelming.

Integrating AI Into a System You Don't Fully Trust Yet: A Staged Rollout Framework

Many businesses want to introduce intelligent software to improve efficiency and reduce manual work. The challenge begins when it needs access to systems that manage customer data, financial records, inventory, or other business-critical operations. A single mistake in these environments can disrupt operations, create compliance risks, lead to financial losses, or damage customer trust.

What is a remote MCP server?

As development shifts toward agentic workflows, an AI agent is only as capable as the systems it can reach. Local MCP servers allow desktop CLI and IDE agents to execute multi-step tasks on your machine. But remote MCP servers (also called hosted MCP servers) extend that reach to cloud-based and background agents, allowing an agent running in a web browser, a CI runner, or a backend service to access external tools over HTTP without needing a developer’s machine running local child processes.

Agentic AI in the Data Center: What It Really Means, and Why Security Has to Come First

Agentic AI means a system that acts on behalf of a specific person, within that person’s exact role and access permissions — not a general term for “smart” software. In data center infrastructure, agentic AI only becomes safe to deploy once three things already exist: a complete monitoring pipeline, an analytics pipeline, and a control pipeline governed by strict role-based access control.

AssemblyAI scales production Voice AI with Datadog's unified observability

AssemblyAI is a leading Voice AI platform that provides speech-to-text models and AI infrastructure developers use to build real-time voice applications. AssemblyAI uses Datadog to unify observability across its AI inference pipelines and multi-cloud GPU infrastructure, enabling the team to optimize performance and costs, accelerate model releases, and confidently deliver fast, reliable AI experiences at scale.

Building with AI: Our Approach to Responsible Agentic Development in Open Source

The tech world has been building up towards the shift to a fully agentic development life cycle for a few years now. AI is changing how software gets built. Across the Puppet ecosystem, we’re seeing a shift toward more agentic engineering workflows. AI helps generate code, shape documentation, and accelerate how Puppet modules evolve.

Agentic Pipelines | Bitbucket Blitz | Atlassian

Most CI/CD pipelines are fragile bash scripts that break when things change. What if your pipeline could think? Agentic Pipelines lets you add AI agents as steps in Bitbucket Pipelines. In this video, I show an agent that reads a design spec from Confluence, generates frontend code, runs tests, and opens a PR, all inside a pipeline. With Agentic Pipelines, Bitbucket goes from a CI/CD platform to a full workflow and automation engine you can use far beyond builds and deploys.