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News

DEV Community
dev.to > zephyr_77 > agentatc-93g

AgentATC

1+ hour, 39+ min ago   (758+ words) Track 3: AI & Agent Observability — "Agents of SigNoz" Hackathon (WeMakeDevs × SigNoz, July 2026) Every team at a hackathon like this is going to show you an agent that's slow, or an agent that errors. Tasks bounce endlessly between an Executor and a…...

DEV Community
dev.to > animaregem > my-ai-agent-refunded-a-customer-twice-and-every-status-code-was-200-2d2k

My AI Agent Refunded a Customer Twice, and Every Status Code Was 200

4+ hour, 42+ min ago   (1482+ words) Last weekend, during the Agents of SigNoz hackathon, I wanted to avoid building yet another self-healing agent or a demo that simply detected an error and retried the same workflow. I was more interested in a harder class of failure:…...

DEV Community
dev.to > machadomichael > although-we-are-in-the-dark-not-all-information-will-be-useful-267j

Although we are in the dark, not all information will be useful.

6+ hour, 3+ min ago   (263+ words) Last week I came across some log issues and it helped me to understand the importance to set good logs. Sometimes (read many times) the code creator wasn't be there anymore. It impact directly when you faced an issue in…...

DEV Community
dev.to > emmanuel_joshua_b3935fe49 > we-asked-signoz-how-to-flag-a-hallucinating-agent-they-said-we-havent-figured-that-out-so-we-105c

We Asked SigNoz How to Flag a Hallucinating Agent. They Said "We Haven't Figured That Out." So We Did.

8+ hour, 57+ min ago   (397+ words) By Team ThunderBoltz · Agents of SigNoz Hackathon · Track 1: AI & Agent Observability In the... Tagged with ai, opentelemetry, signoz, observability....

Medium
medium.com > @saneekadam1326 > my-lcp-was-11-3-seconds-8-angular-fixes-that-brought-it-under-2-4958e4b5a522

My LCP Was 11.3 Seconds: 8 Angular Fixes That Brought It Under 2

13+ hour, 22+ min ago   (36+ words) Eleven point three seconds. That is how long my users stared at a white screen before the most important element on my dashboard …...

DEV Community
dev.to > saheliroycommits > from-zero-docker-experience-to-tracing-every-llm-call-building-an-observable-ai-assistant-with-1741

From Zero Docker Experience to Tracing Every LLM Call: Building an Observable AI Assistant with SigNoz

16+ hour, 2+ min ago   (557+ words) This trace is precisely why I am writing this article right now. Three days back, I hadn't even interacted with Docker, OpenTelemetry, or SigNoz yet. As a 2nd year of AI and Data Science student, and for the Agents of SigNoz…...

Google News
docs.tenbi.ai > troubleshooting

Troubleshooting | Tenbi Docs

23+ hour, 45+ min ago   (1749+ words) Your First Run & Costs Every section below follows the same shape: symptom → what it means → what to check, in order. Failures in the app link straight to the matching section where a code is known. If you fix something mid-run,…...

DEV Community
dev.to > kanishga_subramani_49ad73 > day-99-efficient-random-sampling-with-systemnumbersmt-parallel-number-generation-in-4eil

Day 99 - Efficient Random Sampling with system.numbers_mt: Parallel Number Generation in ClickHouse® 26.3

16+ hour, 24+ min ago   (599+ words) One such change in ClickHouse® 26.3 is the removal of the experimental Hypothesis Skip Index (TYPE hypothesis). If you experimented with this index type in earlier versions, you'll need to update your schema before upgrading to ClickHouse® 26.3. Otherwise, table creation or…...

Dataobservability
dataobservability.ai > solutions > dbt

dbt Data Observability: Auto-Monitors From Your Manifest

1+ day, 1+ hour ago   (606+ words) Point us at your dbt project and we generate monitors and lineage from your manifest, adding always-on coverage that dbt tests alone cannot give you. orders is 47 min late, past the 5-min SLA. Alerted #data-eng 0.8s ago. Downstream impact · 3 consumers at…...

Medium
medium.com > @jubileehappy > adding-a-third-kind-of-judge-what-cross-llm-evaluation-changed-about-the-winner-8c99addf239c

Adding a Third Kind of Judge: What Cross-LLM Evaluation Changed About the Winner

17+ hour, 54+ min ago   (123+ words) Adding cross-LLM judging and weighted Cohen's Kappa to a Jira backlog grooming pipeline: Claude and GPT-5.5 judge each other's work, then a human-weighted composite score decides the final winner...