Operations | Monitoring | ITSM | DevOps | Cloud

Debugging and logging in Laravel applications

Logic errors, failed HTTP requests, background jobs that ghost silently—software breaks in all kinds of fun ways. The difference between resilient systems and fragile ones isn’t about avoiding errors altogether. It’s about how fast and clearly you can see what went wrong, and fix it. Laravel gives you a solid foundation: structured logging, real-time introspection, and built-in performance monitoring.

APM for Kubernetes: Monitor Distributed Applications at Scale

When a payment service runs across 12 pods — each serving different customer segments — and an authentication layer spans three namespaces, performance issues can originate in both the application code and the orchestration layer. The challenge is linking request-level performance data with what’s happening inside the cluster: container CPU limits, pod scheduling decisions, and node-level events.

It broke... lets fix it with Sentry MCP and Seer

Real debugging starts in the editor where you're probably digging through the last commits wondering what random thing changed. Fortunately, you're probably using Sentry and it's going to give you that information. Sentry's MCP is the best way to bring all that context of what broke and how, into your editor so you can fix broken things faster. With Seer, you can bring in the root cause, and solution, and have tools like Cursor or Claude Code go fix it. We'll show you how.

Introducing Anomaly Detection: Your Early Warning System for Service Health

Modern engineering teams face a persistent challenge: knowing when something goes wrong before their customers do. With microservices architectures sprawling across dozens or hundreds of services, creating comprehensive alerting becomes an overwhelming task. You're left playing whack-a-mole with manual alert configurations, often missing critical issues or drowning in false positives.

Full-Stack Observability with VictoriaMetrics in the OTel Demo

The OpenTelemetry Astronomy Shop is a widely used demonstration environment designed to illustrate the concepts and practical implementation of observability in distributed systems. Built as a microservice-based e-commerce application, the demo provides developers with a near real-world environment where they can explore how telemetry data—metrics, logs, and traces—can be collected, processed, and visualized.

AI Wrote Your Bugs, AI Will Fix Your Bugs

There’s a lot of JavaScript developers these days not actually writing code. They whisper sweet prompts to our AI tools and hope for the best. Is it really any worse than copy-pasting from StackOverflow? Welcome to the era of vibe coding, where understanding your code is optional and “it works on my machine” has evolved into “the AI said it would work.”

Granular Allocation, Accurate Unit Costs: The New Standard For FinOps In The Outcome Era

If you’re struggling to contain cloud costs in this suddenly volatile AI-fixated environment, it might be time to consider FinOps as an exercise in granular allocation and unit economics, with a focus on outcome.