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@laura_garcia shared a post, 1 day, 16 hours ago

Software Developer, RELIANOID

Network Load Balancer

🌐 𝘎𝘳𝘦𝘢𝘵 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘴𝘵𝘢𝘳𝘵𝘴 𝘸𝘪𝘵𝘩 𝘪𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘵 𝘵𝘳𝘢𝘧𝘧𝘪𝘤 𝘥𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯. A 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗿 helps organizations maximize availability, eliminate bottlenecks, and keep critical applications running smoothly—even under heavy traffic or unexpected failures. In our latest article, we explain how Layer 4 l..

Story

@laura_garcia shared a post, 2 days, 12 hours ago

Software Developer, RELIANOID

SOC2 compliance

🔐 𝗦𝗢𝗖 𝟮 alignment is about trust, resilience, and doing security right by design. At 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗, our load balancing and application delivery platform is aligned with the 𝗦𝗢𝗖 𝟮 𝗧𝗿𝘂𝘀𝘁 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀 𝗖𝗿𝗶𝘁𝗲𝗿𝗶𝗮—𝗰𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆, 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆, 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗶𝗮𝗹𝗶𝘁𝘆, 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗜𝗻𝘁𝗲𝗴𝗿𝗶𝘁𝘆, 𝗮𝗻𝗱 𝗣𝗿𝗶𝘃𝗮𝗰𝘆. From encryption ..

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@kevin-faun started using tool BOOM , 2 days, 15 hours ago.

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@goutham-annem started using tool vLLM , 2 days, 21 hours ago.

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@goutham-annem started using tool Kubernetes , 2 days, 21 hours ago.

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@goutham-annem started using tool Istio , 2 days, 21 hours ago.

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@goutham-annem started using tool GPT-5.3-Codex , 2 days, 21 hours ago.

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@goutham-annem started using tool Google Kubernetes Engine (GKE) , 2 days, 21 hours ago.

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@goutham-annem started using tool Claude Code , 2 days, 21 hours ago.

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@goutham-annem started using tool Azure Kubernetes Service (AKS) , 2 days, 21 hours ago.

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.