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        <tabi:current_section>distributed tracing</tabi:current_section>
    </tabi:metadata><link rel="extra-stylesheet" href="https://idle-ti.me/skins/lowcontrast_orange.css?h=43aaccb17d8ec616ace4" /><title>idle-ti.me - distributed tracing</title>
        <subtitle>Performance engineering &amp; observability — articles, curated tools, and projects by Jérôme Ramette.</subtitle>
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    <generator uri="https://www.getzola.org/">Zola</generator><updated>2026-05-05T00:00:00+00:00</updated><id>https://idle-ti.me/tags/distributed-tracing/atom.xml</id><entry xml:lang="en">
        <title>Reading Observability by Intent</title>
        <published>2026-05-05T00:00:00+00:00</published>
        <updated>2026-05-05T00:00:00+00:00</updated>
        <author>
            <name>Jérôme Ramette</name>
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        <summary type="html">Tool taxonomies organise observability by metrics, traces, logs, and profiles. Practitioners organise it by intent: what am I trying to understand, debug, or prove? This article reframes the observability stack around six common intents — Golden Signals, latency propagation, high-cardinality debugging, low-overhead profiling, black-box, and cost-efficient at scale — with the workflows, the right tool combinations, the anti-patterns to avoid, and a dedicated treatment of how unified APM platforms (Datadog, New Relic, Dynatrace) fit in the intent-routing framing.</summary>
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