Grafana Labs vs Langfuse

Tempo 3.1 release: new features for Kafka, TraceQL metrics updates, trace redaction, and more

Grafana Labs blog features a new post on Tempo 3.1 release with new features for Kafka, TraceQL metrics updates, trace redaction, and more.

Observability Stack: Prometheus, Node Exporter, Grafana

A technical how-to explaining the three-piece observability stack: Prometheus (time-series database that scrapes metrics), Node Exporter (exposes OS-level metrics at a /metrics HTTP endpoint), and Grafana (visualizes Prometheus data as dashboards). The article describes the pull-based model Prometheus uses, the role of Node Exporter as a translator of OS stats, how Grafana queries Prometheus, default ports (Prometheus 9090, Node Exporter 9100, Grafana 3000), basic install commands, a sample prometheus.yml with scrape_interval and job_name, and next steps such as adding scrape targets, writing PromQL queries, and adding Alertmanager for notifications.

• Prometheus is a time-series database and monitoring system that scrapes metrics from HTTP endpoints and exposes its own metrics on port 9090.
• Node Exporter exposes hardware and OS-level metrics at a /metrics endpoint (default port 9100) and is typically installed one-per-machine.
• Grafana queries Prometheus (e.g., via PromQL) to render dashboards and runs by default on port 3000; it stores no metrics itself.

Building an Internal Developer Platform on Azure AKS

This technical article explains how to create an Internal Developer Platform (IDP) using Azure Kubernetes Service (AKS). It outlines core components including AKS as the managed Kubernetes backbone, a service mesh (e.g., Istio or Linkerd) for microservice communication, CI/CD pipelines (Azure DevOps, GitHub Actions, Jenkins) for automated build and deployment, monitoring and logging tools (Azure Monitor, Prometheus, Grafana, Azure Log Analytics), and security/compliance controls (RBAC, Pod Security Policies, Azure Policy, Azure Security Center). The piece describes an example developer workflow from code push to production and summarizes benefits such as increased efficiency, scalability, security, and consistency.

• An Internal Developer Platform (IDP) is a set of tools, processes, and automations that simplifies development, testing, and deployment for developers.
• Azure Kubernetes Service (AKS) is presented as the central managed Kubernetes environment where containerized applications run.
• Service meshes such as Istio or Linkerd are recommended to manage microservice communication, including load balancing, traffic management, and security policies.

See which projects drive your usage

A new chart shows your organization's units over time, grouped by project or type, with a CSV export. On Langfuse Cloud it is on the Billing page; self-hosted deployments get a new Usage page.

Langfuse CLI 1.0 and new evaluator features

Langfuse CLI 1.0 released, along with new evaluator template gallery and reusable evaluators for production evaluations.

Deploying Langfuse Open-Source LLM Observability

This technical guide explains how to deploy Langfuse, an open-source observability platform for LLM applications, using Docker Compose. The deployment uses PostgreSQL for metadata, ClickHouse for trace and metrics analytics, Redis for cache/queueing, and S3-compatible object storage for media/exports, with Traefik and Let's Encrypt providing TLS. The article includes required prerequisites (Linux server 4 vCPU / 16GB RAM, Docker + Docker Compose, domain A record), step-by-step environment and docker-compose configuration, first-run setup (create organization/project and API keys), and a test-trace example using the Langfuse SDK and an OpenAI-compatible client. Publication date: 2026-08-12.

• Langfuse is an open-source observability platform for LLM applications that traces prompts/responses, tracks token usage and cost, and provides debugging analytics.
• The guide deploys Langfuse via Docker Compose using Traefik (TLS), PostgreSQL (metadata), ClickHouse (trace/metrics analytics), Redis (cache/queue), and S3-compatible object storage.
• Container images and versions shown include traefik:v3.7.0, postgres:17, clickhouse/clickhouse-server:26.5.1-alpine, and redis:7-alpine; Langfuse images used are langfuse/langfuse:3 and langfuse/langfuse-worker:3.