Best of Monitoring — November 2025

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   Article

   A Java geek·26w

   My first real Rust project

   A developer shares their experience building their first production Rust project: a health monitoring component that polls sensors and sends email alerts. The post covers the technical rationale for choosing Rust over JVM languages (short-lived processes, cross-compilation, memory efficiency), selecting appropriate crates (reqwest, config, lettre), leveraging Rust's derive macros for trait implementation, and troubleshooting Windows compilation issues with the GNU toolchain.

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2. 2
   Article

   Charity·26w

   From Cloudwashing to O11ywashing

   The term 'observability' has been co-opted by vendors to mean traditional monitoring tools that only track system uptime, losing its original meaning of understanding service quality from each customer's perspective. This 'o11ywashing' mirrors the 'cloudwashing' phenomenon where vendors rebrand existing products with trendy terminology. True observability requires unified telemetry combining app, business, and system data to slice by customer ID and other dimensions, not just separate metrics, logs, and traces. Engineering executives need better education on this distinction to avoid investing in rebranded monitoring tools that can't solve their actual problems.

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3. 3
   Article

   Product Hunt·29w

   Helicone AI: Open-source LLM Observability for Developers

   Helicone is an open-source platform that provides observability and monitoring for AI applications using large language models. It offers a unified API gateway that consolidates access to 100+ models from multiple providers through a single API key, with zero markup fees. Key features include automatic failover, built-in caching, custom rate limits, real-time analytics, and OpenAI SDK compatibility. The platform addresses common challenges like provider outages, rate limiting, and managing multiple API integrations while providing full visibility into performance and costs.

   28
4. 4
   Article

   Anton Zhiyanov·26w

   Go proposal: Goroutine metrics

   Go 1.26 introduces new runtime metrics for goroutine monitoring, including per-state goroutine counts (waiting, runnable, running, not-in-go) and active thread counts. These metrics help identify production issues like lock contention, syscall bottlenecks, and CPU saturation by tracking goroutine behavior through the runtime/metrics package. The counters enable observability systems to detect scheduler problems and performance regressions without requiring full tracing.

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5. 5
   Article

   FREEK.DEV·28w

   Introducing Flare’s next big feature: performance monitoring

   Flare launches performance monitoring capabilities for Laravel applications. The new feature provides comprehensive tracking of HTTP routes, queued jobs, Artisan commands, and database queries through a unified dashboard, giving developers visibility into application performance metrics.

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