Operations | Monitoring | ITSM | DevOps | Cloud

Learn more at speedscale.com or check out https://docs.speedscale.com/proxymock/how-it-works/mcp/

Learn more at speedscale.com or visit https://docs.speedscale.com/proxymock/how-it-works/mcp/

Are your LLM coding agents (like Cursor or Claude Code) hallucinating fixes because they don't know what's actually happening in production? In this video, Matt from Speedscale shows you how to bridge the gap between your local IDE and live production traffic using the Model Context Protocol (MCP). Most observability tools just give you telemetry. Speedscale’s MCP server gives your agent the "inner workings" of actual API calls and payloads, so it can check its assumptions against reality. No more "vibe-coding" and hoping it works; let your agent find the 500 errors and rate limits for you.

Run your AI workloads like a boss ᕕ( ᐛ )ᕗ.

Intermittent production bugs are hard to debug and rarely reproduce locally. Teams fall into a loop of adding logs, and every rollback slows them down. In this demo, R&D team leads Maor Yaffe and Or Golan show how an AI assistant can verify production issues using real runtime data, without redeploying. By connecting Cursor to Lightrun MCP, the agent inspects live production behavior, collects real variable values, and confirms the root cause with evidence instead of assumptions.

What if your dev team loved their workflows? Jason Gates from Sandia National Labs joins GitKraken’s VP of Developer Research, Jeremy Castile, to unpack the real-world challenges and powerful benefits of developer workflow standardization. In this candid conversation, Jason shares lessons from helping dozens of teams improve their software delivery — from reducing friction and boosting velocity, to creating joyful, productive developer experiences. They dive into.

Get instant visibility into Windows event logs, system_state, process events and AD logs. the Cribl Search pack for Windows highlights performance and security signals at a glance, helping teams quickly spot anomalies.

In this video, we go over getting started with InfluxDB, including downloading, installing, writing, and reading data with a couple different clients.

Is Kubernetes actually hard, or are we just using the wrong tools? In 2026, the Kubernetes ecosystem has become a "dependency jungle." Between GitOps, YAML configuration, kubectl mastery, and complex CI/CD pipelines, developers are spending more time managing infrastructure than writing code. In this video, Ken breaks down the "hard parts" of K8s and introduces a more efficient workflow using Speedscale. Learn how to gain instant visibility into your cluster, pull logs without the headache, and turn real-world traffic into actionable load tests.

Thinking about learning Kubernetes in 2026? You’ll need GitOps, kubectl, and CI/CD pipelines... OR you can just use Speedscale. See how a single operator replaces a million dependencies and gives you the traffic insights you actually need to survive production.