Operations | Monitoring | ITSM | DevOps | Cloud

Refactor your codebase with CircleCI Chunk AI agent

d function there, and before long you’re navigating a codebase full of inconsistent patterns, repeated logic, and code that’s harder to maintain than it should be. Refactoring is essential, but finding the time to clean up code while shipping features is a constant challenge. The rise of AI-assisted development has accelerated this tension. AI coding assistants help teams ship features faster, but they don’t always produce consistent code.

Can We Still Trust the Code? #speedscale #qualityassurance #digitaltwin #trust #devops

The "Velocity Gap" is real. AI like Claude and GitHub Copilot are pumping out code faster than ever, but there’s a catch: Engineers don't trust it yet. We’re moving away from the old days of "clicking around" in a test environment, but how do we verify code at the speed of light? Ken breaks down why the future of QA isn't just "testing," it’s simulation. Video collab with @ScottMooreConsultingLLC Learn More: speedscale.com.

The 4 pillars of AI in 2026: Agents, cost, observability & sovereignty

AI is no longer just about "one-shot" prompts. In this session from our "From Idea to Agent" webinar, Ben Norris (AI Engineer at Civo) breaks down the four key priorities dominating the enterprise space in 2026. From the 130x explosion in token usage to the "vibe-coding" revolution, learn why businesses are turning away from US hyperscalers in favor of democratized, secure, and UK-sovereign AI infrastructure. We explore how autonomous agents are solving multi-step problems and why "Chain of Thought" reasoning is unlocking AI for heavily regulated industries like finance and healthcare.

Agentic IT operations, powered by BigPanda

BigPanda delivers the next evolution in AIOps solutions, featuring agentic automation for ITOps and ITSM teams, all in a single platform. Agentic IT operations from BigPanda keep the digital world running by transforming reactive, manual IT processes into proactive, intelligent automation. Our platform uses AI to detect, respond to, and prevent IT incidents at machine speed.

Actionable Network Device Monitoring with Automated Anomaly Detection and AI Troubleshooting

Network device monitoring is often a mess of polling, graphs, and alerts that don't lead to answers. In this webinar, we'll show how to monitor routers, switches, and firewalls in a way that quickly surfaces what matters: interface health, errors, drops, saturation, latency signals, and performance regressions—without drowning in noise. You'll learn how Netdata turns raw SNMP metrics into high-signal insights using automated anomaly detection and AI-assisted troubleshooting, so your team can move from 'something is wrong' to 'here's the root cause' faster.

AI SRE in Practice: Resolving Node Termination Events at Scale

When a node terminates unexpectedly in a Kubernetes cluster, the immediate symptoms are obvious. Workloads restart elsewhere, services experience partial outages, and alerts fire across multiple systems. The harder question is why it happened and how to prevent it from recurring. This scenario walks through a node termination event where the entire node pool was affected, requiring investigation across infrastructure layers to identify root cause and implement lasting remediation.

GenAI Observability in Grafana Cloud: End-to-End Agent Debugging (Demo)

From Observability for GenAI Applications (Grafana OpenTelemetry Community Call) We drill into traces to see which agents called which tools, where errors occurred, how long each LLM call took, and how costs and tokens are distributed. The walkthrough also covers using AI assistance to summarize long traces and identify optimization opportunities in real time..

AI Hosting: The Colocation vs. Cloud Dilemma for Your Next Project

Organisations running AI workloads, like banks training fraud detection models, hospitals testing diagnostic tools, or manufacturers using predictive analytics, all face the same problem: hosting them is costly and resource-intensive. They require dedicated GPUs running non-stop, vast amounts of data moving in and out, and far more power and cooling than a typical IT system.