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Introducing the AI Pulse Report

Join us for Introducing the AI Pulse Report, a concise, insight-driven webinar that breaks down the findings and implications of Octopus Deploy’s AI Pulse Report: AI adoption and its impact on developer productivity. The 2026 report combines global survey data from technology professionals with industry research to reveal how AI is reshaping software delivery workflows, hiring trends, and long-term talent dynamics.

The future of Search is here: Faster, simpler, AI-driven

Do more with less. That’s the mandate we’re all hearing. AI has fundamentally changed how we work. Modern AI workloads generate 10-100x more queries than humans ever could, pushing legacy architectures past performance limits. And the audacity of it all? Legacy logging vendors continue to raise costs without delivering meaningful innovation. IT and security teams are still forced to choose between speed and retention. Investigations are still slow. Data onboarding is still painful.

Why Your NOC Will Ignore AI

Imagine you are driving to work and a yellow check engine light flickers on your dashboard. The car feels fine. It accelerates normally, there is no strange noise, and the temperature gauge is steady. What do you do? If you are like most people, you keep driving. You might make a mental note to look at it later, but you don't pull over on the highway and call a tow truck.

The bare metal problem in AI Factories

As AI platforms grow in scale, many of the limiting factors are no longer related to model design or algorithmic performance, but to the operation of the underlying infrastructure. GPU accelerators are key components and are responsible for a large part of the total system cost, which makes their continuous availability and stable operation critical to the output and efficiency of the entire AI platform.

What is Ambient AI in Healthcare? Revolutionizing Clinical Care, Efficiency, and Outcomes

You probably use ambient AI every day without even knowing it. When your Apple Watch is telling you to stand up after sitting too long, your CGM recommends you eat a snack, or even when your smart home lights dim around the time you go to bed, every night…that’s ambient AI. Among other things, ambient AI is there to help you stay healthy, tracking what you do in the background and making decisions based on your previous actions and preferences.

The Rise of AI App Builders in Agile Development Environments

Modern software development moves quickly. Businesses need to test ideas, release updates, and respond to customer feedback faster than ever before. Agile development methods were created to support this need for speed and flexibility. In recent years, a new type of tool has begun to support these processes even more. An AI app builder helps teams create applications with less manual coding by using artificial intelligence to assist with design, development, and testing tasks.

The Evolution of Vocal Removal Technology in Music Production

Music production has always been shaped by technological innovation. From the early days of analog recording to the modern era of digital audio workstations, every advancement has changed the way artists create, edit, and experience music. One particularly fascinating development in this journey is the evolution of AI Music Generator vocal removal technology. Once a complicated and imperfect process, removing vocals from a track has gradually transformed into a highly accurate and accessible capability used by producers, DJs, musicians, and even casual music enthusiasts.

How Techdome accelerates AI-led product delivery with Civo Kubernetes

Accessing cloud infrastructure shouldn’t slow down product innovation. Yet for many engineering teams building AI-driven platforms, traditional hyperscalers often introduce unnecessary complexity, high costs, and slow provisioning cycles. At Civo, we’ve seen a different approach emerge. Our cloud platform enables teams to move faster with Kubernetes, compute, and networking designed for simplicity and speed.

The data context gap: an evaluation guide for agent-ready infrastructure

Why do AI agents that look brilliant in a sandbox fail the moment they hit production? For platform leaders, the answer is a lack of environmental parity: the ability to interact with the exact data state and service topology where the actual bugs live. When an agent attempts to modify a schema, optimize a query, or reproduce a bug without access to the real-world data state, it hits the Data Context Gap.

When Your Plant Talks Back: Conversational AI with InfluxDB 3

No one wants to stare at a plant and guess if it needs water. It’s much easier if the plant can say, “I’m thirsty.” A few years ago, we built Plant Buddy using InfluxDB Cloud 2.0. The linked article is still a great guide for cloud-first IoT prototyping as it shows how quickly you can connect devices, store time series data, and build dashboards in the cloud with the previous version of InfluxDB. But this time, the goal was different.