---
title: "Monitoring"
description: "199 posts about Monitoring, summarised, each linking to the original."
---

# Monitoring
> 199 posts about Monitoring, summarised, each linking to the original.

## Articles

### [From vibe code to production-ready: observability for Next.js and Supabase apps](https://yomu.fyi/post/from-vibe-code-to-production-ready-observability-for-next-js-and-supab.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Sergiy Dybskiy
- Published: May 11, 2026
- Type: Problem & solution

AI-assisted software development often generates functional code that lacks proper instrumentation, leading to unindexed database queries, N+1 patterns, and fragmented connection strategies. While Supabase provides built-in query analytics, security advisors, and subsystem logs, it cannot trace distributed requests across the entire application stack. Integrating Sentry bridges this visibility gap by establishing distributed traces across Next.js frontends, Deno-based Supabase Edge Functions, and Postgres databases. Teams can forward Supabase logs into dedicated Sentry projects and configure runtime integrations to automatically detect performance bottlenecks such as slow spans and Web Vitals regressions. Furthermore, integrating Model Context Protocol servers allows Sentry's Seer debugger to identify root causes and generate automated fixes for emerging issues.


### [Monitor Unreal Engine Game Performance with Application Metrics](https://yomu.fyi/post/monitor-unreal-engine-game-performance-with-application-metrics.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Ivan Tustanivskyi
- Published: May 8, 2026
- Type: Announcement

Unreal Engine games frequently experience performance issues such as frame-rate drops, hitches, and network degradation that do not register as application crashes. To address the lack of live production telemetry, the Sentry Unreal SDK introduces automatic performance metrics. The integration periodically samples frame times, network health, active UObject counts, physical memory usage, and garbage collection pause durations across desktop, console, and Android platforms. Telemetry entries attach contextual hardware and environment attributes alongside trace IDs to connect aggregate latency spikes directly to underlying traces and spans. Enabled by default in Unreal SDK version 1.11.0, this telemetry provides developers with fleet-wide visibility into hardware-specific bottlenecks across game releases.


### [Introducing Postgres Query Insights in ClickHouse Cloud](https://yomu.fyi/post/introducing-postgres-query-insights-in-clickhouse-cloud.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Amog Iska
- Published: May 7, 2026
- Type: Announcement

ClickHouse Cloud introduced Query Insights in preview for Managed Postgres to help teams diagnose slow database queries. Powered by the open-source extension pg\_stat\_ch, the tool streams per-statement telemetry directly into ClickHouse to enable fast aggregations across billions of execution rows. Postgres normalizes query literals into placeholders during the parse-analyze phase before telemetry leaves the database, preventing sensitive data exposure. Telemetry emission maintains around three percent producer overhead by utilizing a non-blocking try-lock on a shared-memory ring buffer. Users can examine high-level database health metrics, rank query patterns by runtime or latency percentiles, and inspect execution flyouts detailing disk spills, cache hits, and parallel worker behavior.


### [Fixing JavaScript observability, one library at a time](https://yomu.fyi/post/fixing-javascript-observability-one-library-at-a-time.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Abdelrahman Awad
- Published: May 7, 2026
- Type: Problem & solution

JavaScript application performance monitoring tools rely on monkey-patching via require-in-the-middle and import-in-the-middle, which breaks with ECMAScript Modules, bundlers, and non-Node runtimes. To solve this, an initiative is replacing monkey-patching with Node's built-in diagnostics\_channel TracingChannel API across server-side JavaScript libraries. Under this pattern, libraries publish structured events while monitoring vendors subscribe to them with zero overhead when unlistened. The author leveraged Claude Code workflows alongside direct maintainer communication to draft proposals, implement code, and manage reviews across 44 target packages. Ten libraries including mysql2, node-redis, ioredis, and unjs modules have merged support, while active efforts continue on shared OpenTelemetry mapper registries and remaining ecosystem packages.


### [Improved debugging for Expo apps with the React Native SDK](https://yomu.fyi/post/improved-debugging-for-expo-apps-with-the-react-native-sdk.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Aleksandr Pantiukhov
- Published: May 6, 2026
- Type: Announcement

Expo applications generate approximately 75% of the total event volume received from React Native applications in Sentry. In response, Sentry updated its React Native SDK starting in version 8.10 to improve Expo debugging and performance monitoring workflows. The update automatically enriches events with Expo constants and over-the-air update context, including channels, runtime versions, and emergency launch warnings when an OTA update fails. Developers can track remote EAS Build lifecycle failures and successes using dedicated hooks configured in package.json. Performance instrumentation now supports span generation for Expo Router route prefetching as well as asset and image loading through wrapper functions around expo-image and expo-asset.


### [Stop guessing in production: Full fidelity tracing at scale with ClickHouse and Odigos](https://yomu.fyi/post/stop-guessing-in-production-full-fidelity-tracing-at-scale-with-clickh.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Will Searle
- Published: May 5, 2026
- Type: Problem & solution

Distributed tracing frequently suffers from visibility gaps, broken context across asynchronous boundaries like Kafka, and high operational overhead from manually configuring OpenTelemetry SDKs and collectors. To resolve these issues, Odigos provides zero-code instrumentation via eBPF probes that dynamically attach to running workloads without modifying application code. An intelligent control plane within Odigos dynamically adjusts trace sampling and attribute enrichment based on real-time latency and error rates. The resulting telemetry exports over OTLP into ClickStack, an all-in-one backend featuring an OpenTelemetry Collector, ClickHouse storage, and the HyperDX query interface. This unified pipeline preserves end-to-end trace continuity, captures deep application and database context, and enables fast SQL-based trace analysis.


### [Introducing Application Metrics: Track the signal, see the spike, jump to the trace](https://yomu.fyi/post/introducing-application-metrics-track-the-signal-see-the-spike-jump-to.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Ben Coe
- Published: May 5, 2026
- Type: Announcement

Sentry launched Application Metrics to capture application signals without pre-aggregating counters or discarding high-cardinality attributes like user IDs, project IDs, and regions. The system supports counters, distributions, and gauges within the existing SDK while linking each metric event directly to trace IDs for integrated debugging. Engineers demonstrated the feature by troubleshooting a Session Replay failure that triggered silently when sessions exceeded 1,000 video segments. By instrumenting distributions for replay event counts with project and replay attributes, the team isolated seven affected occurrences, navigated to connected traces and log lines, and reproduced the issue. Application Metrics comes enabled in recent SDK versions with 5GB included per plan.


### [MLOps vs DevOps: A Practical Guide for Data Scientists and IT Teams](https://yomu.fyi/post/mlops-vs-devops-a-practical-guide-for-data-scientists-and-it-teams.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: May 1, 2026
- Type: Explainer

The guide compares DevOps and MLOps, framing both as practices for reliable production systems but distinguishing traditional application code from machine-learning systems involving data and models. DevOps uses source control, automated testing, staging, and CI/CD, while MLOps governs the “holy trinity” of code, data, and models through separate versioning, quality checks, lineage, and access controls. Its central operational difference is Continuous Training: MLOps pipelines can validate model quality, monitor drift, and trigger retraining when data distributions shift, alongside testing model-serving infrastructure and promoting models through a registry. The guide also assigns responsibilities across data scientists, ML engineers, data engineers, and IT operations, and recommends dedicated MLOps for business-critical, frequently retrained models, DevOps for applications without ML, and split pipelines for hybrid products.


### [Two commands to Sentry: now on Stripe Projects](https://yomu.fyi/post/two-commands-to-sentry-now-on-stripe-projects.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Burak Yiğit Kaya
- Published: Apr 29, 2026
- Type: Announcement

Sentry is now integrated into Stripe Projects, enabling developers and coding agents to discover, provision, and manage Sentry services directly through the command-line interface. Running initialization and addition commands automatically sets up accounts, generates necessary environment variables like auth tokens and DSNs, and scaffolds agent skill files for tools such as Claude Code and Cursor. The integration supports plan upgrades, downgrades, and the addition of the Seer AI debugging assistant with billing handled through existing Stripe payment methods. Additional CLI capabilities include minting single-use magic login URLs for the Sentry dashboard, managing multi-member team collaboration tied to Stripe organizations, and rotating project credentials directly into local environment files.


### [What is operational analytics?](https://yomu.fyi/post/what-is-operational-analytics.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Databricks Staff
- Published: Apr 15, 2026
- Type: Explainer

Operational analytics uses real-time or near-real-time data to monitor day-to-day operations and support immediate decisions, unlike traditional analytics, which generally relies on batch data to explain past performance. Its workflow collects logs, events, clickstreams, telemetry, transactions, and other signals; streams them into a unified platform for cleaning, transformation, and enrichment; analyzes incoming data with rules, models, or anomaly detection; and sends results to dashboards, alerts, or operational applications. This can help teams detect issues earlier, reduce mean time to detect (MTTD) and mean time to respond (MTTR), improve forecasting, coordinate across departments, and act on inventory, customer, or system changes. The approach also requires integrating heterogeneous systems, maintaining data quality and schemas, embedding insights into existing workflows, and building reliable low-latency pipelines, with tools such as Lakeflow, Databricks SQL, and AI and machine learning capabilities presented as examples.


### [Our vision for the ClickHouse Grafana plugin](https://yomu.fyi/post/our-vision-for-the-clickhouse-grafana-plugin.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Alex Fedotyev
- Published: Apr 15, 2026
- Type: Problem & solution

ClickHouse is widely used with Grafana for observability and real-time analytics, but requiring users to write raw SQL creates onboarding and exploration friction. To simplify the user experience, planned updates to the ClickHouse Grafana plugin introduce native interfaces such as click-to-filter actions, categorized OpenTelemetry attribute displays, and guided variable editors. A new compact search mode leverages the hasToken function for fast log filtering, while a visual metrics builder simplifies aggregating OpenTelemetry and Kubernetes metrics without manual queries. Prebuilt dashboards for logs and traces will accelerate initial setup alongside automated annotations derived from service version changes and Kubernetes lifecycle events. Future prototypes also explore bidirectional SQL AST parsing for seamless query editing, JWT user identity forwarding for fine-grained access control, and conversational query generation.


### [What's new in ClickStack - March 2026](https://yomu.fyi/post/what-s-new-in-clickstack-march-2026.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: The ClickStack Team
- Published: Apr 14, 2026
- Type: Announcement

ClickStack announced several observability updates in its March 2026 release to improve root cause analysis, dashboard organization, and local development. The Event Deltas tool now displays baseline span distributions immediately, uses deterministic cityHash64 sampling for trace heatmaps, and applies proportional comparison scoring to accurately evaluate attributes across uneven sample sizes. Furthermore, users can directly include or exclude values from attribute comparison bars to streamline query creation during incident investigations. Dashboard capabilities expanded with a curated OpenTelemetry template gallery, multi-value filtering with optional lookup WHERE clauses, and broadened metric display units. Finally, local mode introduces browser localStorage persistence through createEntityStore, allowing developers to save dashboards and favorites without a running backend API.


### [Announcing Role Based Access Control in ClickStack](https://yomu.fyi/post/announcing-role-based-access-control-in-clickstack.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Mike Shi
- Published: Apr 1, 2026
- Type: Announcement

Managed ClickStack has introduced Role-Based Access Control (RBAC) to replace a legacy model where all users shared identical instance-wide permissions or required duplicate HyperDX instances for isolation. Integrated with ClickHouse Cloud for identity management, the new system allows administrators to assign users to roles governed by three access tiers: no access, read, and manage. Permissions apply across platform resources including dashboards, saved searches, sources, alerts, webhooks, and notebooks, with support for fine-grained rules matching names, IDs, or tags. While table-level source restrictions work through ClickStack, row-level access currently depends on separate ClickHouse SQL console roles, which the team intends to unify directly inside ClickStack in future releases.


### [We taught ClickStack to read your logs like a detective novel](https://yomu.fyi/post/we-taught-clickstack-to-read-your-logs-like-a-detective-novel.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: The ClickStack Team
- Published: Apr 1, 2026
- Type: Announcement

HyperDX introduced AI Summarize, a feature designed to translate raw logs, traces, and log patterns into narrative summaries directly within its observability interface. Instead of relying on backend large language models, the tool runs entirely client-side using OpenTelemetry-aware data extraction combined with hand-written phrase pools. The generation logic inspects Kubernetes and OpenTelemetry attributes—such as service names, endpoints, exception details, and query durations—to tailor tone across detective noir, Shakespearean drama, and nature documentary themes. Because processing occurs inside the browser tab without external API calls, the system avoids third-party latency, token expenses, model hallucinations, and data privacy risks. Users can access summaries across logs, spans, and pattern drawers or re-enable the interface toggle via URL parameter through April 2026.


### [From Custom to Open: Scalable Network Probing and HTTP/3 Readiness with Prometheus](https://yomu.fyi/post/from-custom-to-open-scalable-network-probing-and-http-3-readiness-with.md)
- Company: [Slack](https://yomu.fyi/company/slack.md)
- Author: Carlo Preciado
- Published: Mar 31, 2026
- Type: Problem & solution

Slack encountered a lack of client-side observability when introducing HTTP/3 at its edge. Because HTTP/3 runs over QUIC on UDP instead of TCP, neither existing commercial SaaS tools nor the internal Prometheus Blackbox Exporter could probe the new endpoints. To address this gap, an engineering intern integrated the open-source quic-go library into Prometheus Blackbox Exporter to build a native, configurable HTTP/3 probe. Slack deployed an internal implementation using the upstream functionality while waiting for pull request reviews, ultimately landing the contribution upstream. The resulting setup provides a unified view of HTTP/1.1, HTTP/2, and HTTP/3 metrics within Grafana, enabling reliable alerting and faster correlation with other telemetry.


### [More Visibility, Less Guesswork: ClickHouse Cloud's New Monitoring Capabilities](https://yomu.fyi/post/more-visibility-less-guesswork-clickhouse-cloud-s-new-monitoring-capab.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Mihir Gokhale
- Published: Mar 25, 2026
- Type: Announcement

ClickHouse Cloud released new monitoring capabilities and dashboards to give platform administrators deeper visibility into deployment health and server behavior. A newly introduced Overview page consolidates critical signals into a unified view for rapid health checks. Additionally, an updated Infrastructure page tracks service scaling over time, presenting CPU and memory utilization with new aggregation options alongside modals explaining automatic scaling decisions. The platform now sends automated email and Slack notifications when deployments encounter risks such as excessive parts, failed mutations, or query concurrency saturation. These additions allow administrators to proactively identify operational bottlenecks and configure scaling limits without spending excessive time searching for telemetry data.


### [Announcing Monitors: Opening the AI black box](https://yomu.fyi/post/announcing-monitors-opening-the-ai-black-box.md)
- Company: [Intercom](https://yomu.fyi/company/intercom.md)
- Author: Alissa Tyrangiel
- Published: Mar 25, 2026
- Type: Announcement

Intercom announced Monitors, a new Fin product area intended to complete its observability suite alongside Insights and Recommendations. It addresses the limits of random sampling, CSAT, and spreadsheet-driven quality assurance by letting teams select conversations with filters or natural-language criteria, including risk signals, and maintain repeatable samples. Custom Scorecards then define business-specific evaluation criteria, weighting, and critical failures, with scoring performed by AI, humans, or both to produce an overall quality score. Flagged conversations enter a Review Queue for assignment, notes, status tracking, and follow-up fixes, while reporting compares scores with CX Score, resolution rate, Monitors, and Scorecards over time. Monitors for Fin conversations is live, with human-agent QA, real-time alerts, and knowledge-base evaluation identified as planned additions.


### [Introducing AI observability notebooks for Managed ClickStack in Private Preview](https://yomu.fyi/post/introducing-ai-observability-notebooks-for-managed-clickstack-in-priva.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Author: Mike Shi
- Published: Mar 18, 2026
- Type: Announcement

ClickHouse has launched AI Notebooks for Managed ClickStack in private preview to assist site reliability engineers during system investigations. Instead of isolating interactions in a standard chat window, the platform embeds Anthropic's Claude models directly into a cell-based notebook canvas. The system connects the model to internal ClickStack APIs, translating natural language questions into structured queries that leverage ClickHouse optimizations like materialized views and query chunking. Engineers can inspect reasoning, edit generated SQL queries, add manual visualizations, and branch investigations to evaluate multiple hypotheses independently. While currently utilizing a last-write-wins model for shared canvases, the roadmap includes true concurrent editing, customizable context, and external tool integration via an MCP server.


### [From Fragmented Logs to Full-Stack Visibility with SolarWinds Papertrail](https://yomu.fyi/post/from-fragmented-logs-to-full-stack-visibility-with-solarwinds-papertra.md)
- Company: [Heroku](https://yomu.fyi/company/heroku.md)
- Author: Rachel Revoy
- Published: Mar 12, 2026
- Type: Announcement

Heroku applications combine dynos, databases, third-party APIs, and user interactions, making fragmented logs, metrics, and dashboards costly to correlate during production incidents. The expanded SolarWinds Papertrail add-on addresses this “swivel-chair” workflow by unifying real-time log management, metrics dashboards, and alerting in one interface. It supports live tailing and contextual search through the web, CLI, or API, while ingesting native Heroku metrics for dyno CPU, memory, load averages, application throughput, response times, error rates, and database performance. Custom thresholds based on minimum, maximum, average, or summary values can filter transient-noise alerts, with notifications sent to Slack, PagerDuty, and Microsoft Teams. The post’s incident example correlates a response-time spike with R14 “Out of Memory” errors from Dyno worker.1, identifying an oversized batch job; Librato and AppOptics were deprecated at the end of January 2026.


### [Observability and OpenTelemetry: Introducing MongoDB Atlas Log Integration](https://yomu.fyi/post/observability-and-opentelemetry-introducing-mongodb-atlas-log-integrat.md)
- Company: [MongoDB](https://yomu.fyi/company/mongodb.md)
- Author: Sabina Bates
- Published: Mar 12, 2026
- Type: Announcement

During database latency spikes or unexpected outages, operations teams frequently waste valuable time downloading compressed archives and manually inspecting log files to isolate root causes. MongoDB Atlas resolves this operational friction by introducing a direct log integration feature for dedicated M10+ clusters. The system routes mongod, mongos, and audit logs directly to third-party tools such as Datadog, Splunk, Amazon S3, Google Cloud Storage, and Azure Blob Storage. Furthermore, built-in support for the OpenTelemetry standard enables teams to pipe database logs into any OTel-compatible logging backend. This setup eliminates operational silos, streamlines security auditing, and correlates database query diagnostics with application traces and infrastructure metrics in real time.


[Newer posts](https://yomu.fyi/topic/monitoring/page/5.md) · [Older posts](https://yomu.fyi/topic/monitoring/page/7.md)