Updates and recent posts about Grafana Tempo..

Posts
Description

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

How Zapier runs isolated tasks on AWS Lambda and upgrades functions at scale

Zapier snaps each customer Zap into its ownAWS Lambda, cradled inside leanFirecracker microVMs. It wrangles 100k+ functions under anEKScontrol plane and inventory DB. When runtimes retire, Zapier swings into action: a set ofTerraform modulespaired with a customLambda canary tool. Traffic trickles in.. read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

How GitHub engineers tackle platform problems

Product engineersare like builders ofGundam models, construcing the final product, whileplatform engineerssupply the tools needed to build these kits. Understanding theGundam analogyhelps differentiate engineering roles at GitHub... read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

10 Best API Monitoring Tools in 2025

API monitoring tracks latency, errors and uptime. Tools tag real-time metrics. They fire alerts. They map traces. They automate tests. They crunch analytics. Examples span OSS starsPrometheus,Graphiteand SaaS champsAppDynamics,Postman. Each hooks into CI/CD pipelines and plants global synthetic prob.. read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

Building a Secure, Scalable, and Automated Cloud-Native Platform on AWS with EKS, GitOps, and…

The blueprint carves out production-grade AWS infra. Terraform orchestrates VPCs with public and private subnets, deploys a Bastion host, spins up private EKS clusters, and stands up an internet-facing ALB armed with SSL/TLS. Argo CD drives GitOps. The CI pipeline runs SAST, builds Docker images, hu.. read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

The Art of Azure RBAC for Kubernetes: A Complete Guide to Access Control Mastery

This article dives into Azure RBAC for Kubernetes. It maps each persona to pinpoint roles per namespace. Permissions stay minimal from the get-go. It ties role bindings toAzure AD groups, splits dev and prod, and flips on audit logs. Quarterly reviews, crisp docs keep RBAC lean and current... read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

MCP Catalog: Finding the Right AI Tools for Your Project

Docker Desktop hatches a betaMCP CatalogandToolkit. It unleashes 100+ containerized Model Context Protocol servers loaded with metadata and use-case filters. Teams fire them via GUI or CLI. The catalog carvesDocker-builtimages from community builds, runs supply-chain scans, and seals isolation. Cust.. read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

We Added Chaos to Our CI/CD Pipelines — It Made Everything More Stable.

Wix’sMREteam injectsAI-drivenchaosintoCI/CDpipelines. Mobile releases gain speed and rock-solid stability. They harness hackathon-born prompt tests to bulletproof builds and deployments. Signal: AI resilience trials in pipelines mark a shift from rigid builds to probabilistic validation... read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

Critical VMware Tools VGAuth Vulnerabilities Enable Full System Access for Attackers

Two CVE-2025 vulns in VMware Tools allow SYSTEM access via named pipe hijacking and path traversal. Upgrade to 12.5.1+ ASAP for fixes. Administrators must upgrade... read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

Serverless: The Illusion of Choice

A LinkedIn thread exposes a hack around AWS EventBridge’s256KBlimit. Someone chains Lambdas tocompressthendecompressevents. Serverless traps lurk: blown-upIAMpermissions. Triggers with zero validation. Wide-openegress. Unscanned packages fueling supply chain bombs... read more

Link

@faun shared a link, 10 months, 4 weeks ago

FAUN.dev()

GitHub Spark in public preview for Copilot Pro+ subscribers

GitHub Spark spins natural-language prompts into full-stack AI apps in minutes. It tapsClaude Sonnet 4to scaffold UI and server logic. It hooks updata storage,LLM inference, hosting,GitHub Actions,Dependabot, plus multi-LLM smarts from OpenAI, Meta, DeepSeek and xAI—zero config. Trend to watch: AI .. read more

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.