Join us

ContentUpdates and recent posts about Grafana Tempo..
Link
@varbear shared a link, 4 months, 2 weeks ago
FAUN.dev()

Measuring Engineering Productivity

A former engineering leader lays out a no-nonsense framework for tracking team output without turning into Big Brother. Think:daily Slack updates,weekly GitHub changelogs,tight 1:1s,demo-fueled All-Hands, andauto-verified deploys. It leans onpublic artifacts, not peeking over shoulders - and puts th.. read more  

Measuring Engineering Productivity
Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

Debugging container image creation with a Dockerfile

Docker just made debugging Dockerfiles inVS Codefeel like real development. With the latest Docker extension and Docker Desktop update, you can now set breakpoints, step through builds with F10/F11, poke at variables, and mess with the container’s file system mid-build... read more  

Debugging container image creation with a Dockerfile
Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

Kubernetes Gateway API in action

The Kubernetes Gateway API leveled up - unifying North-South, East-West, and egress traffic with standard CRDs likeGRPCRoute,HTTPRoute, andReferenceGrant. In a Linkerd world, that means clean, declarative canary releases, granular egress control to outside APIs (say, Mistral AI), and clearer lines b.. read more  

Kubernetes Gateway API in action
Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

Bootstrapping Rancher’s RKE2 Kubernetes Cluster on a Podman VM with Cilium CNI and MetalLB LoadBalancer

Running RKE2 with Cilium and MetalLB in a lightweight Podman VM on macOS enables experimentation with Kubernetes. Unique network challenges require SSH port forwarding for service exposure... read more  

Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

How to manage EKS Pod Identities at scale using Argo CD and AWS ACK

AWS shows how to wire upArgo CDwithAWS Controllers for Kubernetes (ACK)to automateEKS Pod Identityfor IAM roles - GitOps-style. The catch? The Pod Identity API has a lag. So they bolt on apre-deployment validation jobto wait-and-confirm that the IAM role's actually bound before app pods come online... read more  

Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

Spotlight on Policy Working Group

The Kubernetes Policy Working Group got busy turning good intentions into real specs. They rolled out thePolicy Reports API, dropped best-practice docs worth reading, and helped steerValidatingAdmissionPolicyandMutatingAdmissionPolicytoward GA. Their work pulled inSIG Auth,SIG Security, and anyone e.. read more  

Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

Replaying massive data in a non-production environment using Pekko Streams and Kubernetes Pekko Cluster

DoubleVerify built a traffic replay tool that actually scales. It runs onPekko StreamsandPekko Cluster, pumping real production-like traffic into non-prod setups. Throttlenails the RPS with precision for functional tests.Distributed datasyncs stressful loads across cluster nodes without breaking a s.. read more  

Replaying massive data in a non-production environment using Pekko Streams and Kubernetes Pekko Cluster
Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

Exposing Kubernetes Services Without Cloud LoadBalancers: A Practical Guide

Bare-metal Kubernetes just got a cloud-style glow-up. By wiring upMetalLBin layer2 mode with theNGINX ingress controller, the setup exposesLoadBalancer-typeservices—no cloud provider in sight. MetalLB dishes out static, LAN-routable IPs. NGINX funnels external traffic to internalClusterIPservices th.. read more  

Exposing Kubernetes Services Without Cloud LoadBalancers: A Practical Guide
Link
@kaptain shared a link, 4 months, 2 weeks ago
FAUN.dev()

7 Common Kubernetes Pitfalls (and How I Learned to Avoid Them)

Seven ways folks trip over Kubernetes - each more avoidable than the last. Top offenses: skippingresource requests/limits, forgettinghealth probes, trustingephemeral logsthat vanish when you need them. Reusing configs across dev and prod? Still a bad idea. Pushing off observability until it’s on fir.. read more  

Link
@kala shared a link, 4 months, 2 weeks ago
FAUN.dev()

Why open source may not survive the rise of generative AI

Generative AI is snapping the attribution chain thatcopyleft licenseslike theGNU GPLrely on. Without clear provenance, license terms get lost. Compliance? Forget it. The give-and-take that powersFOSSstops giving - or taking... read more  

Why open source may not survive the rise of generative AI
Grafana Tempo is a distributed tracing backend built for massive scale and low operational overhead. Unlike traditional tracing systems that depend on complex databases, Tempo uses object storage—such as S3, GCS, or Azure Blob Storage—to store trace data, making it highly cost-effective and resilient. Tempo is part of the Grafana observability stack and integrates natively with Grafana, Prometheus, and Loki, enabling unified visualization and correlation across metrics, logs, and traces.

Technically, Tempo supports ingestion from major tracing protocols including Jaeger, Zipkin, OpenCensus, and OpenTelemetry, ensuring easy interoperability. It features TraceQL, a domain-specific query language for traces inspired by PromQL and LogQL, allowing developers to perform targeted searches and complex trace-based analytics. The newer TraceQL Metrics capability even lets users derive metrics directly from trace data, bridging the gap between tracing and performance analysis.

Tempo’s Traces Drilldown UI further enhances usability by providing intuitive, queryless analysis of latency, errors, and performance bottlenecks. Combined with the tempo-cli and tempo-vulture tools, it delivers a full suite for trace collection, verification, and debugging.

Built in Go and following OpenTelemetry standards, Grafana Tempo is ideal for organizations seeking scalable, vendor-neutral distributed tracing to power observability at cloud scale.