Fireship·1yGrafana is the goat... Let's deploy the LGTM stack
Learn how to deploy the LGTM stack to collect and visualize telemetry data from your server using open Telemetry. The stack includes Grafana for visualization, Prometheus for metric storage, Tempo for traces, and Loki for logs, all hosted on a Linux virtual private server. This guide simplifies the setup process using Docker, making it accessible for those new to these technologies.
Trendyol Tech·47wEverything Looked Fine Until Memory Ran Out in Our Node.js App
An unexpected memory leak in a Node.js application was discovered during a code freeze, with symptoms including crashing services and unusual memory patterns. The issue was traced back to incorrect file permissions preventing log flushing to disk, causing logs to accumulate in memory. The team used tools like Chrome DevTools and heap snapshots to diagnose and resolve the leak, leading to stabilized memory usage and improved system stability.
Grafana Labs·49wDashboards and detergent: How two students monitor laundry machines in a college dorm with Grafana
Two college students developed a system using Grafana and TimescaleDB to track laundry machine usage in dorms. They used internet-connected laundry machines' data, building a real-time dashboard that also records metrics like machine popularity and usage times. This creative approach demonstrates Grafana's versatility beyond typical network monitoring and hints at future integration possibilities with weather data or gamification.
Grafana Labs·1yKubernetes Monitoring Helm chart 2.0: a simpler, more predictable experience
Version 2.0 of the Kubernetes Monitoring Helm chart improves ease of use and flexibility in collecting telemetry data from Kubernetes clusters. Key updates include user-focused feature design, multiple data destinations, built-in integrations for popular services, and compatibility with Fleet Management. Simplified migration from version 1.x is supported by a detailed guide and migration utility.
freeCodeCamp·44wHow to Debug CI/CD Pipelines: A Handbook on Troubleshooting with Observability Tools
A comprehensive guide to implementing observability in CI/CD pipelines using free and open-source tools. Covers setting up Grafana Loki and lightweight ELK stacks for log aggregation, creating unified logging strategies with correlation IDs, writing advanced LogQL and KQL queries for troubleshooting, integrating Prometheus metrics with logs, and building Grafana dashboards. Includes practical examples for debugging common pipeline failures like build errors, dependency issues, and flaky tests across GitHub Actions, Jenkins, and GitLab.
Hacker News·23wThe Grafana trust problem
An experienced engineer shares their journey with Grafana's observability stack, detailing how frequent architectural changes, deprecations, and increasing complexity have eroded trust. Starting with simple Loki/Prometheus setups, they've witnessed rapid product churn—Grafana Agent deprecated within 2-3 years, OnCall discontinued, and Mimir 3.0 now requiring Kafka. The constant restructuring, incompatibilities with Prometheus Operator standards, and career-driven development pace make it difficult to maintain stable monitoring infrastructure. While acknowledging the technical quality of Grafana products, the author questions their long-term viability and considers alternatives like the kube-prometheus-stack with Thanos.
Grafana Labs·23wA Star Wars dashboard deep dive: How to build your next visualization in less than 12 parsecs
A detailed walkthrough of building a Star Wars-themed Grafana dashboard, covering practical techniques like using stat panels for custom text styling, TestData plugin for simulating dynamic data, canvas panels for creating custom visualizations with animations, and styling approaches for visual consistency. Demonstrates how to create gauges, charts, maps, and custom layouts while explaining the technical implementation behind each component.
Grafana Labs·23wUnderstand, diagnose, and optimize SQL queries: Introducing Grafana Cloud Database Observability
Grafana Cloud Database Observability is now in public preview, offering developers, SREs, and DBAs tools to understand, diagnose, and optimize SQL queries. The solution addresses the visibility gap in database performance by providing query-level insights, execution plans, wait event analysis, and AI-powered optimization suggestions. It supports MySQL and PostgreSQL, integrates with Grafana Alloy for telemetry collection, and correlates database metrics with application and infrastructure data for comprehensive system-wide performance analysis.
Grafana Labs·29wTaylor Swift (Grafana’s Version): How to track and visualize data related to pop’s biggest superstar
Grafana Labs built a comprehensive dashboard using Grafana Assistant to visualize Taylor Swift's career data, including album characteristics, Eras Tour analytics, and career milestones. The project demonstrates how Grafana Assistant's AI-powered natural language interface enables users of varying skill levels to create complex dashboards by querying data from sources like BigQuery and Kaggle datasets. The dashboard features four tabs covering profile stats, musical analysis with Spotify API data, tour attendance metrics with geomaps, and album details.
Grafana Labs·24wGrafana Mimir 3.0 release: performance improvements, a new query engine, and more
Grafana Mimir 3.0 introduces a redesigned architecture that separates read and write operations using Apache Kafka as an asynchronous buffer, eliminating performance bottlenecks between ingestion and queries. The release features the Mimir Query Engine (MQE), which processes queries in a streaming fashion rather than bulk loading, reducing peak memory usage by up to 92%. These improvements deliver 15% lower resource usage in large clusters while maintaining faster query execution and higher reliability. The new ingest storage component ensures query spikes won't slow down data ingestion and vice versa, enabling independent scaling of each path.
Grafana Labs·50wNew in Grafana 12: Dynamic dashboards that are smarter, easier to edit, and can be customized for teams
Grafana 12 introduces dynamic dashboards designed to enhance ease of navigation, editability, and customization. Key features include tabs for segmenting data by context, a dashboard outline for quick navigation, and conditional rendering to reduce visual clutter. The release also features a new schema inspired by Kubernetes CRD to improve dashboard management, and a context-aware editing interface to streamline user workflows. These enhancements aim to address scalability challenges in large organizations and improve overall user experience.
Milan Jovanović·44wMonitoring .NET Applications with OpenTelemetry and Grafana
Learn how to implement comprehensive observability for .NET applications using OpenTelemetry and Grafana Cloud. The guide covers installing OpenTelemetry packages, configuring automatic instrumentation for ASP.NET Core, Entity Framework, and other libraries, setting up OTLP export to Grafana Cloud, and viewing traces and logs in unified dashboards. This setup provides distributed tracing, log correlation, and monitoring capabilities that scale from single services to complex microservice architectures.
Grafana Labs·1yThe latest in Kubernetes Monitoring: new features to track persistent storage, simplify alerting, and more
Grafana Cloud has introduced several new features in Kubernetes Monitoring, including enhanced storage observability, easier alert creation, and improved Fleet Management. Key updates include tracking persistent volumes, seamless navigation, streamlined troubleshooting with historical data, and advanced cost management tools. Version 2.0 of the Kubernetes Monitoring Helm chart simplifies data collection and configuration, supporting multiple telemetry destinations and built-in integrations.
Devtron·39wSetting up Prometheus Stack on Kubernetes
Kubernetes monitoring is essential for maintaining application health in dynamic containerized environments. Prometheus collects and stores time-series metrics while Grafana provides visualization through dashboards. The kube-prometheus-stack offers a complete monitoring solution with service discovery, alerting, and predefined dashboards. Devtron simplifies the setup process by providing integrated monitoring capabilities - users can install Grafana via Stack Manager, deploy Prometheus using Helm charts, and configure endpoints to get real-time application metrics including CPU usage, throughput, and latency directly in the Devtron dashboard.
Grafana Labs·1yGrafana Drilldown: first-class OpenTelemetry support now available for metrics
Grafana Labs has added first-class support for OpenTelemetry in its Metrics Drilldown tool. This integration allows users to seamlessly explore and filter metrics using OpenTelemetry resource attributes alongside Prometheus labels. The new features include automatic query writing, context-aware filtering, and a consolidated interface, significantly simplifying the process of gaining insights into distributed system performance.
codeHeim·1y#79 Golang - Observability: Logging with Loki, Promtail & Grafana
Enhance observability in Golang applications by setting up logging using Loki, Promtail, and Grafana. Learn how to collect and send logs to Loki with Promtail and visualize them in Grafana. The post explains the setup process, configuring a Go application to write logs, using Promtail for log collection, and using Grafana to visualize and analyze logs.
Grafana Labs·1yHow CERN uses Grafana and Mimir to monitor the world's largest computer grid
CERN operates the world's largest computing grid to support its particle accelerator research. To monitor this massive infrastructure, which includes 1.4 million computing cores and 1.5 exabytes of storage, CERN uses Grafana and Grafana Mimir. These tools provide essential dashboards and alerting functions, integrating various data sources into a unified system. Grafana has become key to ensuring 12,000 physicists can access and analyze the data they need, while Mimir addresses long-term storage challenges for Prometheus metrics.
Grafana Labs·26wGrafana Tempo 2.9 release: MCP server support, TraceQL metrics sampling, and more
Grafana Tempo 2.9 introduces MCP server support enabling LLMs like Claude to query and analyze distributed tracing data through TraceQL. The release adds query sampling hints to speed up metrics queries by returning approximate results, particularly useful for high-volume environments. New operational improvements include metrics for monitoring query I/O and span timestamp distances, plus enhanced cost-attribution tracking with resource and span-level scoping for multi-tenant deployments. The team is also working on vParquet5 block format and Project Rhythm architecture to improve scalability and reduce operational costs.
Grafana Labs·30wGrafana 12.2 release: LLM-powered SQL expressions, updates to canvas and table visualizations, simplified reporting, and more
Grafana 12.2 introduces LLM-powered SQL expressions for natural language query generation, enhanced table visualizations with new cell types and formatting options, improved canvas visualization with flexible pan/zoom capabilities, enhanced ad hoc filtering support for SQL data sources, and simplified one-page reporting. The release also includes updates to Drilldown apps for queryless data exploration, a new Jenkins Enterprise data source for CI/CD metrics, and authentication support for visualization actions with the Infinity data source.
Grafana Labs·34wOptimize application performance at the network layer: introducing HTTP Performance Insights in Frontend Observability
Grafana Cloud Frontend Observability introduces HTTP Performance Insights, a new feature that helps frontend engineers monitor HTTP requests and identify performance bottlenecks in real time. The tool provides comprehensive dashboards with health indicators, error tracking, and drill-down capabilities for specific endpoints. It automatically analyzes existing HTTP request data without requiring additional instrumentation, offering actionable insights to optimize application performance at the network layer. Future enhancements will include Page Performance Insights, Resource Loading Intelligence, and Integrated User Experience Views.
Grafana Labs·1yMetrics, logs, and literature: Inside The National Library of the Netherlands’ observability stack
The National Library of the Netherlands uses Grafana for their observability stack, ensuring seamless access to a vast collection of digital literature. The library's choice of Grafana over Splunk was driven by ease of use, cost reduction, and native Prometheus support. They deployed Grafana Mimir for metrics and Grafana Loki for logs, empowering developers with simplified infrastructure setup. Future plans include implementing Grafana Alerting, Grafana Tempo, and Grafana Faro to enhance performance monitoring.
Programmers are also human·40wSenior DevOps engineer
A humorous and satirical take on the daily struggles of senior DevOps engineers, highlighting common pain points like unreliable cloud infrastructure, complex monitoring systems, infrastructure-as-code challenges, multi-region deployments, and the gap between development practices and operational reality. The piece touches on familiar DevOps frustrations including Terraform unpredictability, monitoring alert fatigue, dependency management, and the complexity of modern CI/CD pipelines.
Grafana Labs·44wConfigure and customize Kubernetes Monitoring easier with Alloy Operator
Grafana Labs introduces version 3.0 of the Kubernetes Monitoring Helm chart featuring Alloy Operator, which simplifies configuration by dynamically setting up telemetry data collection based on selected features. The new approach reduces the massive values.yaml file from nearly 3,000 lines and eliminates complex subchart management. Key improvements include automatic configuration of Alloy collectors when features are enabled, built-in tail sampling support for distributed tracing, and dynamic deployment of required Alloy instances. The operator uses Helm-based architecture to manage Alloy objects while maintaining security through proper encapsulation and minimal permissions.
Grafana Labs·1yKubernetes Monitoring: One view for observing all your storage volumes
Grafana Cloud has introduced a new Storage tab in its Kubernetes Monitoring solution, providing users with a single view to track volume usage over time, conduct data forensics, and troubleshoot volume provisioning. The tab includes prebuilt panels for tracking various storage metrics, reducing context switching, and making it easier to spot issues with new alert overlays. The view is available at different levels, from pod to cluster, helping users visualize storage metrics comprehensively and make informed decisions about their storage infrastructure.
codeHeim·1y#81 Golang - Observability: Logging with Loki, Alloy & Grafana
Enhance observability in Golang applications by setting up logging using Loki and Grafana. Use Alloy to collect logs and send them to Loki, then visualize and analyze logs in Grafana. Details on setting up Grafana, configuring SLOG for logging, and steps to integrate logs from Alloy to Loki are provided along with some basic operations you can perform in Grafana.