---
title: "Observability"
description: "250 posts about Observability, summarised, each linking to the original."
---

# Observability
> 250 posts about Observability, summarised, each linking to the original.

## Articles

### [Unlocking the Power of the TPU Stack: Introducing our new Developer Hub](https://yomu.fyi/post/unlocking-the-power-of-the-tpu-stack-introducing-our-new-developer-hub.md)
- Company: [Google](https://yomu.fyi/company/google.md)
- Author: Keelin McDonell
- Published: Jun 16, 2026
- Type: Announcement

Google Cloud has launched the TPU Developer Hub, an educational resource for model builders, optimizers, and developers working with TPU infrastructure and its supporting software stack. It organizes guidance across the developer lifecycle, covering pre-training, post-training, and inference, with material on hardware architecture, infrastructure consumption modes, and software capabilities including specialized compiler technology and XLA. Resources also address PyTorch migration and deployment, XProf-based tracing and observability, multi-chip parallelism, Pallas kernels, KV cache offloading, networking, and security for distributed workloads. The hub combines interactive Colabs, open-source code recipes, and deep-dive documentation, with content intended for both manual browsing and AI-assisted development. Its stated purpose is to help users select appropriate TPU infrastructure, diagnose bottlenecks, optimize model performance, and move from concepts toward production through practical, regularly updated guidance.


### [ClickHouse achieves AWS Retail Competency](https://yomu.fyi/post/clickhouse-achieves-aws-retail-competency.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 12, 2026
- Type: Announcement

ClickHouse has achieved the AWS Retail Competency in the Advanced Data Insights category, a designation recognizing validated technical expertise and demonstrated customer success in retail real-time analytics. Retail workloads described here combine high-volume, high-cardinality, high-concurrency data with hard freshness requirements, including inventory, pricing, personalization, and peak seasonal demand. The post attributes the platform's fit to compressed columnar storage, parallel queries, continuous Kafka and Amazon S3 ingestion through ClickPipes, compute-compute separation, and AWS support for private networking, multi-region deployment, and Marketplace billing. Examples include Mercado Libre's 90-TB-per-day observability ingestion and trace lookups reduced from 15–20 minutes to about two seconds, while other customers report cost, speed, and analyst-efficiency gains.


### [Better, faster, less wrong: Enhancing issue grouping](https://yomu.fyi/post/better-faster-less-wrong-enhancing-issue-grouping.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Kush Dubey, Yuval Mandelboum
- Published: Jun 12, 2026
- Type: Problem & solution

Sentry upgraded its AI-driven issue grouping system to better prevent duplicate issues without merging distinct application errors. The team trained lightonai/modernbert-embed-large using Matryoshka Representation Learning on hundreds of thousands of stacktrace pairs labeled by Claude Sonnet 4.5. To optimize the high-throughput ingestion pipeline, embeddings were truncated from 768 to 64 dimensions, combined with bfloat16 precision, PyTorch SDPA, and CUDA graph compilation. A phased live rollout used threshold-gated index backfilling and automatic fallback to prevent issue spikes during migration. In production, the v2 model cuts the overgrouping rate from 8% to 4%, increases prevented duplicate issues to 70%, and delivers 6x faster inference.


### [From Chaos to Clarity: How We Built a Unified, Self-Routing Support Ops Ticketing System at Lyft](https://yomu.fyi/post/from-chaos-to-clarity-how-we-built-a-unified-self-routing-support-ops.md)
- Company: [Lyft](https://yomu.fyi/company/lyft.md)
- Author: Atulgupta
- Published: Jun 9, 2026
- Type: Problem & solution

Lyft Urban Solutions' Support Ops team faced fragmented ticketing across four Jira Help Centers with duplicate intake forms, lack of routing logic, and no dashboards. Over five years, the team redesigned the intake architecture by replacing redundant forms with dynamic Jira Proforma forms featuring conditional branching. Automated Jira rules were introduced to assign tickets, apply a taxonomy of over 30 labels, and trigger PagerDuty alerts for P0 incidents. To unify operations across disparate backend projects, the system automatically clones and links tickets from a single portal to downstream project boards. Jira Structures and a Jira-to-Mode ETL pipeline provided cross-project rollups and business analytics before an upcoming Jira Cloud migration required dashboard rebuilds.


### [Monitor SLAs and scale ClickHouse Cloud with clickhousectl and agents](https://yomu.fyi/post/monitor-slas-and-scale-clickhouse-cloud-with-clickhousectl-and-agents.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 5, 2026
- Type: Tutorial

ClickHouse Cloud can automatically scale infrastructure up and down, but teams may need to monitor latency SLAs for specific workloads such as a frontend dashboard requiring p99 under 200 ms. The guide tags queries with log\_comment, reads system.query\_log through clickhousectl, and aggregates query\_duration\_ms over a defined window to measure the SLA. When it is breached, operators compare query volume and latency with Prometheus-compatible CPU, memory, and concurrency metrics to distinguish increased concurrency from resource contention, then choose horizontal replica scaling or vertical replica sizing. A cron-based script can scale out when p99 exceeds a threshold, while an agent can inspect evidence and apply one scaling action using clickhousectl; actions are recorded in the ClickHouse Cloud activity log.


### [Errors, traces, logs, metrics: when to reach for what](https://yomu.fyi/post/errors-traces-logs-metrics-when-to-reach-for-what.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Sergiy Dybskiy
- Published: Jun 5, 2026
- Type: Explainer

Modern application telemetry relies on four overlapping signals: errors, traces, logs, and metrics. Each telemetry type addresses distinct engineering questions and powers specific debugging workflows. Errors track grouped, actionable application crashes, whereas traces map timing and execution paths across dependency waterfalls. Metrics aggregate numerical measurements across historical deployments, and logs preserve complete state and decision-making context at specific moments in execution. Emitting telemetry directly into the format needed for a given workflow proves superior to relying on a single wide event, as tools like AI coding agents require structured spans to optimize execution paths while human debuggers rely on unsampled logs and metrics to pinpoint silent failures.


### [Canvas Design Mode and Context Usage Report](https://yomu.fyi/post/canvas-design-mode-and-context-usage-report.md)
- Company: [Cursor](https://yomu.fyi/company/cursor.md)
- Published: Jun 4, 2026
- Type: Announcement

Cursor’s canvas release adds Design Mode, enabling users to select and annotate UI elements directly while guiding edits. The update also turns agent context usage into an interactive canvas report, breaking token consumption across the system prompt, tool definitions, rules, skills, and more. Because the report is interactive, users can ask follow-up questions, customize its answers, or use an embedded Debug with Agent button to seek opportunities to reduce context usage in a new conversation. Other changes include full-screen browser access for shared canvases, prompt-triggering buttons, improved handling of canvas type errors, better component styling, and more chart customization options.


### [Click-a-thon 2026: 24 hours, Bengaluru, and the fastest analytical database on the planet](https://yomu.fyi/post/click-a-thon-2026-24-hours-bengaluru-and-the-fastest-analytical-databa.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 4, 2026
- Type: Announcement

ClickHouse announces Click-a-thon 2026, its first in-person hackathon in India, scheduled for Bengaluru on August 1–2, 2026. The event invites working tech professionals to form teams of two to four for a 24-hour build with four tracks—Real-Time Analytics, Observability, Data Warehousing, and Agentic AI and Analytics—and a ₹10,00,000 prize pool. Its stated purpose is to bring developers together to build practical systems under tight constraints and experiment with ClickHouse alongside modern open-source tools. The post points to ClickStack for observability, Langfuse for LLM tracing and evaluation, and LibreChat for model and agent interfaces, while describing combinations such as streaming ingestion, materialized views, projections, analytical queries, and tool-using agents over data. Applications close June 25, with shortlists planned for the first week of July; the team captain applies on behalf of the team.


### [Logging, Metrics, and Distributed Tracing in .NET with OpenTelemetry and ClickStack](https://yomu.fyi/post/logging-metrics-and-distributed-tracing-in-net-with-opentelemetry-and.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 3, 2026
- Type: Tutorial

The post presents a walkthrough of instrumenting two ASP.NET services—an Order API and a Payment Service—with OpenTelemetry and sending traces, logs, and metrics to ClickStack. The demo uses SQLite for persistence, with Entity Framework Core instrumentation capturing database operations without manually creating spans. The configuration adds ASP.NET, HTTP client, and EF Core instrumentation, custom sources and meters, OpenTelemetry logging, and OTLP/gRPC exporters directed by OTEL\_EXPORTER\_OTLP\_ENDPOINT. In ClickStack, the signals are correlated so a request can be followed across service boundaries, application work, and database calls, while the UI and ClickHouse SQL provide exploration options. The conclusion is that a relatively small ASP.NET setup replaces isolated timeout logs with an end-to-end view of timing, errors, logs, and database activity.


### [Building a .NET API Gateway with ClickHouse and Aspire](https://yomu.fyi/post/building-a-net-api-gateway-with-clickhouse-and-aspire.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: Jun 2, 2026
- Type: Tutorial

The tutorial builds a .NET distributed application around a YARP API gateway, two backend APIs, an analytics API, a Blazor dashboard, a load generator, and ClickHouse. Aspire’s AppHost coordinates these resources, injects connection strings and service endpoints, orders startup with dependency health checks, and exposes selected services through stable or external endpoints. The gateway records proxied requests in ClickHouse while emitting OpenTelemetry metrics for request counts, duration, and backend failures. A bounded queue and background ingestion keep request logging off the hot path, while a narrow schema and materialized view precompute minute-level aggregates for volume, p95 latency, error rates, and route comparisons. Aspire supplies live telemetry, whereas ClickHouse retains request history for analytical queries and drill-down into slow requests.


### [Beyond LLMs: Why Scalable Enterprise AI Adoption Depends on Agent Logic](https://yomu.fyi/post/beyond-llms-why-scalable-enterprise-ai-adoption-depends-on-agent-logic.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Nicholas Fuller
- Published: Jun 1, 2026
- Type: Explainer

Enterprise workflows are dynamic, long-running, API- and data-rich, and constrained by policies or regulations, creating challenges that an LLM alone may not handle efficiently. The article defines agent logic as software primitives—including knowledge graphs, algorithms, and program-analysis libraries—within an agent harness that steer models toward relevant workflow context. Examples span legacy COBOL and PL/1 understanding, automated test generation, incident investigation and code remediation, and compliance modernization; reported results include ~30× lower token consumption for application understanding, 20–45% higher test coverage, and up to 4.0× better incident-investigation performance than a ReAct baseline. A Condition Insights example reports 57% fewer unsupported claims and 77% lower average token usage, supporting the conclusion that structured guidance can improve quality, cost, and rule adherence.


### [Profiling in PyTorch (Part 1): A Beginner's Guide to torch.profiler](https://yomu.fyi/post/profiling-in-pytorch-part-1-a-beginner-s-guide-to-torch-profiler.md)
- Company: [Hugging Face](https://yomu.fyi/company/hugging-face.md)
- Author: Aritra Roy Gosthipaty, Sayak Paul, Sergio Paniego, Rémi Ouazan Reboul, Pedro Cuenca
- Published: May 29, 2026
- Type: Tutorial

The post introduces torch.profiler through a beginner-oriented walkthrough of profiling a matrix multiplication and addition, explaining how to configure the profiler and interpret its outputs. It uses a small function with torch.matmul and torch.add, annotates it with record\_function, captures CPU and CUDA activities after warm-up iterations, and exports a profiler table plus a Chrome trace. The table summarizes event counts and CPU or GPU time, while the trace shows execution order, call hierarchy, CPU-GPU gaps, kernel launches, and overlap. Comparing 64x64 and 4096x4096 matrices demonstrates a shift from overhead-bound behavior to compute-bound behavior; the guide also covers dispatch chains, hidden device-to-device copies, profiler buffer activity, and torch.compile's runtime and caching behavior.


### [Open House 2026 Day 2: 10 years of open source and what the ecosystem is building next](https://yomu.fyi/post/open-house-2026-day-2-10-years-of-open-source-and-what-the-ecosystem-i.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: May 28, 2026
- Type: Announcement

Open House 2026 Day 2 recaps ClickHouse’s tenth year as an open-source project and the ecosystem forming around its data platform. The event reported more than 2,600 contributors, nearly 48,000 GitHub stars, over 200 integrations, and the launch of the House Mates partner program. Announcements included Fivetran’s generally available ClickHouse Cloud destination, a Google Cloud Dataflow Pub/Sub template, Sigma’s public-beta connector and ETL Cache Layer, and a ClickHouse dbt Fusion adapter available in alpha through the CLI. The recap also describes MCP and agent-oriented observability work, including a ClickStack MCP server that translates investigations into optimized ClickHouse queries. Internal testing reported up to 25% fewer tool calls, 2.5 times greater consistency, and nearly 20% better evaluation results.


### [Thank you for building with us](https://yomu.fyi/post/thank-you-for-building-with-us.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: May 27, 2026
- Type: Announcement

At its 2026 user conference in San Francisco, ClickHouse reports surpassing 4,000 customers and $250 million in annual run-rate revenue, while marking nearly ten years since Alexey Milovidov open-sourced the database. The company attributes its growth to a community of contributors and describes use across AI products, financial services, observability, analytics, and infrastructure. New offerings include ClickHouse Agents, a fully managed agentic analytics service powered by Anthropic’s Claude; CostBench, an open benchmark using each warehouse’s real billing model; and House Mates, a partner program launching with more than 50 partners across six continents. Additional updates include Managed Postgres in public beta, Managed ClickStack and Langfuse for AI-era observability, generally available full-text search, and automatic JOIN optimization, with cost-performance identified as the central constraint for high-concurrency, low-latency workloads.


### [ClickHouse tops $250M ARR and 4,000 customers, launches Claude-powered agents at Open House 2026](https://yomu.fyi/post/clickhouse-tops-250m-arr-and-4-000-customers-launches-claude-powered-a.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: May 27, 2026
- Type: Announcement

At Open House 2026, ClickHouse announced that its serverless cloud offering exceeded $250 million in annual run-rate revenue and reached 4,000 customers, with ARR more than tripling year-over-year and more than 1,000 net new customers added since January. The company launched ClickHouse Agents, a fully managed, no-code agentic analytics service powered by Anthropic’s Claude, with a chat interface, sandboxed code interpreter, artifacts, skills, memory, multi-agent workflows, and MCP-compatible integrations. It also published CostBench, an open benchmark applying each vendor’s real compute billing model to the same workload; ClickHouse Cloud was reported to have 23x better cost-performance than the nearest cloud data warehouse. Other announcements included Managed Postgres in public beta, managed ClickStack, generally available full-text search, cross-region replication, and the House Mates partner program.


### [Open House 2026 Day 1: Real-time data without lock-in and what teams can build next](https://yomu.fyi/post/open-house-2026-day-1-real-time-data-without-lock-in-and-what-teams-ca.md)
- Company: [Clickhouse](https://yomu.fyi/company/clickhouse.md)
- Published: May 27, 2026
- Type: Announcement

ClickHouse’s Open House 2026 Day 1 announced updates spanning ClickHouse Cloud, Postgres, distributed query execution, observability, AI agents, and lakehouse interoperability. ClickHouse Postgres entered public beta with local NVMe storage, high availability, S3-backed point-in-time recovery, and a native CDC path into ClickHouse; early benchmarks reported more than 5x the transactions per second of AWS RDS. Multi-stage distributed queries repartition intermediate data between stages to scale joins and high-cardinality aggregations, reducing TPC-H SF100 runtime from 117.6 seconds on one node to 54.7 seconds on eight nodes. Additional launches included a Claude-powered ClickHouse Agents public beta, an AI-enhanced query builder, Monitoring v2, and Langfuse V4’s reported 200x query performance improvement, while the wrap-up framed the releases around real-time systems without lock-in.


### [You don’t need to pick one: how Sentry and OpenTelemetry work together](https://yomu.fyi/post/you-don-t-need-to-pick-one-how-sentry-and-opentelemetry-work-together.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Lazar Nikolov
- Published: May 27, 2026
- Type: Explainer

Integrating Sentry into systems already instrumented with OpenTelemetry does not require replacing existing backend SDKs or rewriting service instrumentation. A hybrid architecture pairs the Sentry SDK on the frontend for browser tracing, Session Replay, and logs with existing OpenTelemetry configurations across backend services. Frontend requests propagate W3C traceparent headers to backend endpoints, which then export traces and logs over OTLP directly to Sentry endpoints or through an intermediate OpenTelemetry Collector. Ingested telemetry attaches backend spans and standard Python logs to the initial frontend user actions, establishing a unified distributed trace across the entire request path. Although Sentry's OTLP ingest currently supports logs and traces rather than metrics, dedicated backend Sentry SDKs remain an optional addition later for backend exception tracking and profiling.


### [Your agent can't fix what it can't see](https://yomu.fyi/post/your-agent-can-t-fix-what-it-can-t-see.md)
- Company: [Sentry](https://yomu.fyi/company/sentry.md)
- Author: Sergiy Dybskiy
- Published: May 26, 2026
- Type: Announcement

Coding agents frequently fail to resolve production bugs when restricted to source code alone, as they lack critical runtime context such as stack traces, breadcrumbs, and environment data. To bridge this gap, Sentry introduces Sentry MCP and the Sentry CLI to supply agents and developers with structured production telemetry. The Model Context Protocol integration supports clients like Claude Code, Cursor, and VS Code, while the CLI enables scripted workflows. When an alert triggers, an agent uses trace and commit metadata to diagnose root causes across service boundaries, generate regression tests, and open draft pull requests. Over six months, the Autofix pull request merge rate increased from 41% to 46%.


### [Observability for any agent, anywhere: Production-ready tracing with OpenTelemetry & Unity Catalog on Databricks](https://yomu.fyi/post/observability-for-any-agent-anywhere-production-ready-tracing-with-ope.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Firas Farah, Bruno Faria, Anoop Sunke
- Published: May 22, 2026
- Type: Tutorial

Databricks supports writing OpenTelemetry (OTel) traces directly to Unity Catalog, where real-time telemetry is stored in Delta tables for governed analytics and retention. AI traces capture prompts, tool calls, responses, latency, and execution paths, enabling debugging, evaluation, and monitoring, while lakehouse storage also allows SQL queries, dashboards, joins with business data, and PII controls. The managed, serverless ingestion layer uses Zerobus Ingest to accept OTLP over gRPC from collectors and REST integrations, streaming spans, logs, and metrics to Unity Catalog without intermediate message buses. A LangGraph support manager assistant demonstrates instrumentation with mlflow.langchain.autolog() and an @MLflow.trace root span, while Genie is invoked through MCP for data-driven questions. The resulting traces can be searched in MLflow, evaluated at scale, and monitored continuously, with FAQ details stating 200 QPS starting throughput, no storage limit, and Unity Catalog governance options for access control, masking, and filtering.


### [Using observability data to prevent incidents](https://yomu.fyi/post/using-observability-data-to-prevent-incidents.md)
- Company: [Databricks](https://yomu.fyi/company/databricks.md)
- Author: Madelyn Mullen
- Published: May 22, 2026
- Type: Problem & solution

Engineering teams often remain reactive not because they lack telemetry, but because metrics, logs, traces, error budgets, and SLO burn rates are difficult to query at decision speed. The post frames reliability intelligence as trend analysis that identifies accumulating risk before a user-facing incident, contrasting it with observability focused on current system state. It proposes unified telemetry access and natural-language self-service, using Databricks Genie to examine p99 latency, error-budget burn, deployment frequency, incident rates, dependencies, and capacity across services. The Trade Desk’s Genie Router handles questions across more than 10,000 tables, while the post says ad-hoc analysis runs five times faster with Genie and can support mitigation before a page fires.


[Newer posts](https://yomu.fyi/topic/observability/page/6.md) · [Older posts](https://yomu.fyi/topic/observability/page/8.md)