Agents creating and editing dashboard panels on SigNoz 👇 Plus the new dashboard manager.
SigNoz
Software Development
San Francisco, CA 9,461 followers
Open Source Observability | OpenTelemetry Native | Hiring in US & India
About us
SigNoz simplifies observability for engineering teams. Instead of juggling multiple monitoring tools, get metrics, traces, and logs in a single open-source platform. Built with OpenTelemetry-native architecture and designed for cloud-native environments. Trusted by developers worldwide with 24,000+ GitHub stars and backed by Y Combinator.
- Website
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https://signoz.io
External link for SigNoz
- Industry
- Software Development
- Company size
- 11-50 employees
- Headquarters
- San Francisco, CA
- Type
- Privately Held
- Specialties
- Observability, Application Monitoring, Log Management, and DevOps
Locations
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Primary
Get directions
San Francisco, CA 94114, US
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Get directions
Bangalore, Karnataka 560001, IN
Employees at SigNoz
Updates
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We've updated SigNoz Cloud dashboards to be agent-native. Since we launched MCP and NozAI, agents are creating and editing more dashboards on SigNoz Cloud. So we rebuilt the dashboard schema around a strict, validated hierarchy based on the CNCF Perses specification. Agent-driven operations on dashboards are now faster, more reliable, and more token-efficient. Plus, we added custom views and DSL search to the dashboard manager. Finding and organizing a growing collection of dashboards is now much easier.
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Six times out of 10, Appvia’s agent workflow gets from an alert to the actual fix. Not just the diagnosis. The line of code. We spoke with Lewis Marshall and Mark Hughes about how Appvia uses SigNoz Cloud + SigNoz MCP to give coding agents the telemetry context behind alerts. That’s agent-native observability in the wild 🚀 Full story in first comment 👇
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“You cannot just all the time set up triggers and focus on everything.” That line from Sandijs Jercums sums up the Docupace story really well. Docupace runs a multi-tenant platform across many customer environments. Some issues show up as incidents. Others stay quieter: repeated errors, soft failures, noisy services, missing fields during log migration. We spoke with Sandijs, Infrastructure Manager at Docupace, about how their team uses SigNoz MCP with SigNoz Cloud to ask broader questions across logs before they know exactly what to search for. - What keeps repeating? - Which service looks noisy? - What happened before the node crash? - Is new log ingestion flowing correctly? During incidents, Sandijs said the workflow has increased diagnostics “tenfold or even more” in many cases. Full story in the first comment 👇
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We rebuilt the Trace Detail View for high-volume traces. AI-native teams generate around 2.4x more telemetry on SigNoz, and LLM workloads are making individual traces larger and denser. That means more spans to load and investigate. The new trace view handles both: it loads dense traces faster and makes it frictionless to zero in on the span that matters. What changed: - Flame graph renders 100K spans in a single load - Faster waterfall shows every span, even in very large traces - One-click filters highlight errors, LLM calls, database spans, and more - Query-based search finds spans across multiple attribute values - Span details panel now docks or floats, with a structured attributes view Live now.
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SigNoz reposted this
We're still buzzing from the WeMakeDevs Zero Downtime Hackathon we co-hosted over the weekend along with Bright Data and SigNoz. The challenge for the 38 teams was to NOT focus on building an app, but instead to build the factory that builds, operates, and repairs it. Port was central to every single project, serving as the place teams stored context for their agents, ran agents and workflows, built event-driven systems to detect and fix issues, and incorporated human in the loop approval flows. So who won? 2 teams went home with NVIDIA DGX Sparks. Working solor was Nitish Mane who built an app that makes sure you don't miss your favorite TV shows and movies. But, since we emphasized focusing on the factory, not the app, Nitish built a system in Port to detect drift and fix it autonomously. And Gracelyn N, Ben O'Connor, and Hugh Hoford built an app that turns new AI papers into runnable code. Naturally, Port was used as the context layer and orchestration engine. And some honorable mentions: - Voice-of-Customer Factory: Sales calls become a living PRD that dynamically staffs its own Port AI agent team. - DriftForge: Tracks external vendor/API changes and turns them into internal migration work via Port. Elijah Umana - ALWAYSUP: Reusable factory taking a brief from plan to build to release, fully governed by Port. Kushaan Naskar - Daisy: Software+hardware factory with strict Port-enforced gates Rishith Chennupati Huge thank you to Kunal Kushwaha and the WeMakeDevs team, Bright Data, SigNoz, our incredible judges and partners, 🎩 Baruch Sadogursky, and everyone who built with us. See you at the next hackathon!
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Some slowdowns are one bad call. Some are extra work hiding in the flow. At MSI, a sales-order workflow was running checks on user actions that did not need them. Taylor surfaced 20 unnecessary operations from that pattern. We spoke with Taylor Mattison and Thang Syle from MSI about how their team debugs API-heavy workflows with SigNoz. Thang goes straight to SigNoz when something breaks across APIs. Taylor connected SigNoz through MCP to bring more trace context into the debugging process and compare patterns faster. Their take is worth the swipe 👉
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SF, we’ll see you at Zero Downtime Hackathon on August 22 🚀 A day to build reliable AI systems, with SigNoz powering observability. Bring an idea, build something cool, and come say hi. Registration NOW 👉 https://lnkd.in/gVrWNnqZ
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