Observability

Docupace uses SigNoz MCP to move from manual log search to daily operational reports, broad system overviews, and faster incident diagnostics across many customer environments.

MSI's sales-order workflow runs across the UI, APIs, database, and its ERP. Engineers already used SigNoz Cloud for API traces and logs. Here's how Taylor Mattison uses SigNoz MCP with Claude to compare traces at scale, connect telemetry to code, and get to a clear answer for where slowdowns actually live.

Kathleen Xue at Shaped used a coding agent with SigNoz Cloud and the SigNoz MCP server to fix a Redis latency bug that had persisted in production for almost a year.

Learn how the SigNoz MCP server lets you investigate logs and traces from plain English - whether you're starting from a vague symptom or a known failure.

Learn how to collect logs from .NET 8 applications using OpenTelemetry, from the OTLP exporter setup to shipping logs to a backend.

Discover the best distributed tracing tools for microservices in 2026. Compare features, benefits, and use cases to optimize your application performance.

Redis monitoring in 2026: key metrics (memory, hit rate, ops/sec, replication), dashboards, and alerts in SigNoz, via the OpenTelemetry redis receiver.

Learn how to set up OpenTelemetry Django auto-instrumentation using opentelemetry-instrumentation-django to monitor traces, metrics, and logs.

Observability vs monitoring in 2026: monitoring watches known signals; observability explains the unknown. See how they differ and complement, plus SigNoz.

Compare the 7 best Grafana alternatives for 2026, side-by-side on pricing, features, open source vs SaaS, and best-fit use cases.

Learn what OpenTelemetry (OTel) is, how its architecture, Collector, and OTLP work, plus the benefits, challenges, and how to get started with SigNoz.

A comprehensive guide to the OpenTelemetry Collector Contrib distribution. Learn how it differs from Core, its architecture, and how to build your own.

A case study of how Alien Intelligence built an AI SRE workflow on SigNoz Cloud to triage alerts, reduce noise, and keep humans in the loop.

Learn how the SigNoz MCP server automates the full on-call lifecycle — from creating alerts for new services to generating handoff briefs, auditing alert fatigue, and compiling postmortem evidence packs.

Learn how the SigNoz MCP server lets you investigate incidents faster — tracing errors to their origin, identifying latency bottlenecks, and determining whether multiple alerts represent one incident or several.

Learn how the SigNoz MCP server lets you create and spin up dashboards from plain English. Whether you're onboarding a new service or responding to an active incident.

Learn how the SigNoz MCP server brings observability into the development and release lifecycle — catching performance problems during development and validating deployments the moment they go out.

How SigNoz rebuilt its internal observability system to monitor its own cloud platform, ingesting 21 billion metric points, 14 TB of logs, and 10 TB of traces every day across six regions.

SREcon26 Americas has no way to filter talks by topic. Here's the observability-focused guide to the schedule, covering the talks worth your time if you're there to learn about monitoring, OpenTelemetry, metrics costs, and LLM observability.

When AI handles 95% of your incident response, do you get worse at handling the 5% that actually matters? Exploring the ironies of automation applied to SREs and the growing deskilling risk.

Explore five lesser-known trace sampling strategies beyond head and tail-based sampling that can help you reduce observability costs while maintaining visibility.

Understand OpenTelemetry Resource Attributes - Learn how to set standard keys, manage precedence between sources, and enforce data quality across teams.

Learn what OpenTelemetry (OTel) Environment Variables are, and how you can use them to manage application behaviour through this practical guide.

Learn how to reduce telemetry volume by 40% with SigNoz

Understand OpenTelemetry Baggage - Learn what it is and how it enables cross-signal context propagation, and its usage via a hands-on demo.

High cardinality crashes Prometheus servers and inflates cloud bills. Learn what causes cardinality explosion, how different databases handle it, and strategies to manage it.

A comprehensive guide to OTLP - the vendor-neutral protocol unifying traces, metrics, and logs transmission. Learn about its goals, architecture, and how it helps solve observability fragmentation.

We recently overhauled how we store JSON logs in ClickHouse to improve query performance and enable filtering of nested dot-notation keys, which was previously not possible. What started as an investigation into filtering inconsistent dot-key notation in JSON logs ended up optimising our query performance by 30%.

Tired of unpredictable Datadog bills? We analyze cost-effective Datadog alternatives like Grafana, New Relic, and ELK, and show why SigNoz Cloud is the best managed choice.

This blog is an attempt for anyone lost to find their way into observability and a wake-up call for devs to they should think about observability more actively today than ever before.

MCP Servers are the new hotness in the Observability space. But are they really? This is an unhyped take filled with facts and figures.

Current observability tooling significantly lags behind user expectations by failing to support a critical capability - querying across different telemetry signals. This limitation turns what should be powerful correlation capabilities into mere “correlation theater” – a superficial simulation of insights rather than true analytical power.

Learn how to set up `logspout-signoz` for effective log collection, labeling, and forwarding from Docker containers to SigNoz. Simplify your log management and improve observability.

Learn the essentials of O11y (Observability) in this beginner's guide. Discover how to implement it effectively to improve system performance and reliability.

OpenTelemetry round for 2023 and what to expect in 2024

When you think about observability? Do you just think of it as an insurance? Or do you think of it as a growth driver? In this article, we will discuss how observability can be a growth driver for your business.

I’d like to write a bit about how Observability costs are significant, how these costs tend to be justified, and how precise amount a company spends on *anything* tends to be more subjective than you’d think. This article is not about how to reduce or control these costs, but rather how the costs are justified.

With your help, we can destroy observability in our lifetime.

We believe the aim of observability is to solve customer issues quickly. Creating monitoring dashboards is useless if it can’t help engineering teams quickly identify the root causes of performance issues...

Not 3 pillars but a single whole to help customers solve issues faster