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ClickHouse engineering resources

  • What is shadow AI? The governance gap in AI adoption

    Shadow AI is the use of AI tools and models inside an organization without IT or governance approval. It drives data leakage, unbudgeted spend, and compliance exposure, and detecting it is an observability problem.

    Last updated: 28 de jul. de 2026

  • What is real user monitoring (RUM)?

    Real user monitoring (RUM) passively collects performance and experience telemetry from real user sessions. How it works, what it captures, and how to store it at scale.

    Last updated: 28 de jul. de 2026

  • What is platform engineering?

    Platform engineering is the discipline of building internal developer platforms (IDPs) that give product teams self-service infrastructure through golden paths, reducing cognitive load.

    Last updated: 28 de jul. de 2026

  • What is MELT? Metrics, events, logs, and traces explained

    MELT groups telemetry into metrics, events, logs, and traces. What each type captures, how events differ from logs, and how MELT relates to the three pillars of observability.

    Last updated: 28 de jul. de 2026

  • What is log management? Lifecycle, retention, and tooling

    Log management is the discipline of handling logs across their full lifecycle: generation, collection, parsing, storage, retention, query, and deletion.

    Last updated: 28 de jul. de 2026

  • What is log analytics? Querying logs at scale

    Log analytics runs aggregations, time series, and pattern detection over centralized logs, turning billions of log lines into answers about system behavior.

    Last updated: 28 de jul. de 2026

  • What is log aggregation? Centralizing logs from every service

    Log aggregation collects log data from every service, host, and container into one queryable store, so engineers can search and correlate events across a whole system.

    Last updated: 28 de jul. de 2026

  • What is eBPF? Kernel-level observability without code changes

    eBPF runs sandboxed programs inside the Linux kernel to capture traces, network flows, and profiles without changing application code. How it works, where it falls short, and how to query its output at scale.

    Last updated: 28 de jul. de 2026

  • What is distributed tracing? Traces, spans, and context propagation

    Distributed tracing follows one request across every service it touches, recording each step as a span under a shared trace ID so you can see where the time went.

    Last updated: 28 de jul. de 2026

  • What is AIOps, and what does it actually deliver?

    AIOps applies machine learning to IT operations data to detect anomalies, correlate events, and cut alert noise. What it does well, where it stops, and what it needs underneath.

    Last updated: 28 de jul. de 2026

  • What is AI agent observability?

    AI agent observability traces multi-step, non-deterministic agent workflows (LLM calls, tool calls, retrievals, sub-agent spawns) as spans in one trace, so teams can debug agent behavior.

    Last updated: 28 de jul. de 2026

  • The three pillars of observability - and where the model breaks

    Logs, metrics, and traces defined honestly: what each pillar captures, when to use which, how they correlate, and why siloed pillars break down at scale.

    Last updated: 28 de jul. de 2026

  • What is tail latency? Why p99 spikes when averages look fine

    Tail latency is the slow end of the response-time distribution (p95 and beyond). Why fan-out makes rare slowness common, what causes it, and how hedged requests, timeouts, and load shedding reduce it.

    Last updated: 28 de jul. de 2026

  • SLOs, SLIs, and SLAs: definitions, differences, and worked examples

    An SLI measures a service, an SLO sets the internal target for that measurement, and an SLA is the external contract with penalties. How the three layers fit together, with error-budget math and worked examples.

    Last updated: 28 de jul. de 2026

  • RUM vs synthetic monitoring: which do you need?

    RUM measures what real users experienced; synthetic monitoring measures what scripted probes experienced. How the two differ on alerting, coverage, and cost, and when to run both.

    Last updated: 28 de jul. de 2026

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