Scout Monitoring

AcuBliss is a booking platform with a small engineering team. No dedicated ops. When something slowed down, engineers stopped building and started digging through logs. After adding Scout, they caught a production slowdown before users noticed. One endpoint was firing 418 SQL queries per request. Three N+1 patterns in a single serializer. The fix was straightforward once they could see it. The interesting part: they used Claude Code with Scout's MCP server to do the investigation. Claude Code pulled the slow traces, identified the patterns, ranked fixes by impact, and pointed to the exact file. The whole loop took under 3 minutes. Small teams can't afford to spend Friday afternoons chasing vague performance complaints. That's the real cost of flying blind. https://lnkd.in/eCkXSEsc #APM #Monitoring #DevTools #ClaudeCode

AI coding assistants made it possible for a single developer to build and ship a production application in a weekend. This is exciting. It is also dangerous if you ship without monitoring. The AI does not know the query it wrote loads 10,000 records without pagination. It does not know the background job it created retries indefinitely on failure. These are the problems monitoring catches every day. AI just creates them faster. We wrote about why monitoring is critical path for AI-built apps, including the self-improving flywheel where agents detect, diagnose, and fix errors autonomously. Also: what the Ruby twiddle-wakka teaches us about trusting new dependencies. https://lnkd.in/edshnrwa #AIDev #Monitoring #APM #DevTools

Most APM tools were built for organizations with dedicated platform teams, SRE rotations, and DevOps budgets. If your developers also handle deploys, on-call, and production debugging between writing features, you need monitoring that gives you answers, not a project. We compared Scout, Sentry, Honeybadger, AppSignal, New Relic, and Datadog through the lens of what small teams actually need: fast setup, automatic problem detection, predictable pricing, and AI-native access so your coding assistants can help fix what they find. https://lnkd.in/e-muFfgf #APM #DevTools #Monitoring #SmallTeams

Sentry is a good error monitoring tool. But in an agentic development world, the question is not just how well a tool shows errors to your team. It is how well it exposes errors to the agents writing and fixing your code. When an AI agent can query your monitoring via MCP, read the trace, and open a fix without human triage, platform complexity becomes friction. The simpler and more developer-centric the tool, the better it works for agents too. We compared Scout, Honeybadger, Bugsnag, Rollbar, New Relic, and Datadog as Sentry alternatives, each framed by what it does better and where the tradeoffs are. https://lnkd.in/e6PYGqB3 #Sentry #APM #AIDev #ErrorMonitoring #DevTools

We rewrote our error monitoring tools guide from scratch. The 2021 version listed JavaScript-only trackers. The 2026 version covers Scout, Sentry, Bugsnag, Rollbar, Honeybadger, and Raygun. The biggest change in error monitoring is not the tools themselves. It is who is using them. When AI agents can query your errors via MCP or API, understand the trace, and open a PR without a human triaging first, your monitoring tool becomes part of a self-improving development loop. The tools built for developers turn out to be the same tools that work best for agents. https://lnkd.in/e8U-rjCh #ErrorMonitoring #APM #AIDev #Monitoring #DevTools

PHP powers a huge share of the web, but the monitoring tools available to PHP teams vary wildly in how deeply they understand the ecosystem. We rewrote our PHP monitoring roundup from scratch for 2026. It now covers Scout, Tideways, New Relic, Datadog, and Sentry with the details that actually matter for PHP teams: Eloquent N+1 detection, memory management in PHP-FPM and Octane, Laravel Horizon and queue worker visibility, and CMS-specific support for WordPress, Magento, and Drupal. https://lnkd.in/ejFwBVpn #PHP #Laravel #APM #Monitoring #Observability #DevTools #WebDev #SoftwareEngineering

We migrated our marketing site off a modern CMS platform to a file-based Git workflow. SEO results have been overwhelmingly better. Pages are faster, AI can actually edit them, and I'm not fighting combo class overrides at midnight anymore. Not a knock on visual CMS tools. Ours served us well. But for a small team where we are all de facto marketing engineers and also the SEO people, Git won.

Elixir applications have performance characteristics that are genuinely different from Ruby or Python. The BEAM VM, supervision trees, and Phoenix Channels mean the problems you hit in production are different from what most APM tools were built to detect. We wrote a practical comparison of the main APM options for Elixir teams in 2026: Scout, AppSignal, New Relic, Datadog, and the PromEx/Prometheus/Grafana stack. The guide covers what actually matters for Elixir: Ecto N+1 query detection, BEAM VM metrics (process counts, scheduler utilization, message queues), LiveView and Channel monitoring, and Oban job visibility. https://lnkd.in/e8NPYjhj #ElixirLang #Phoenix #APM #Monitoring #Observability #BEAM #DevTools #SoftwareEngineering

A lot shipped this month in Scout. More Python support (Redis Cluster, Starlette 1.0, 3.13+) A major version release for the Elixir agent. If you're on Phoenix, it's worth the upgrade. New CLI usage insights MCP updates so you can monitor background jobs and usage from your AI assistant Scout is now available on AWS Marketplace. Also worth a read: BackerKit moved from Datadog to Scout and shifted from hunting issues to a clear list of what to fix. We'll be at Blue Ridge Ruby this week and PHPverse in June if you're around. https://lnkd.in/eA5ydqHz

Our guide to application performance monitoring: what it is, what it tracks, and how modern teams use it to go from "something is slow" to a fix. Production apps today touch a database, a cache layer, and several third-party APIs on every request. AI-generated traffic is making that even less predictable. When something breaks, guessing is not a strategy. If you are newer to observability or evaluating APM tooling, worth a read: https://lnkd.in/eM7FpjND