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I am Leonardo Di Donato ,

OBSERVABILITY insights deductions ongoing blackbox data fine-grained MONITORING on just any data garbage Data lake Another really cool buzzword is TRACING. Execution path along the code. Impacts runtime performances. Usually disabled or sampled.

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“ observability

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Towards OpenMetrics.

AFTER PROMETHEUS BEFORE PROMETHEUS Metrics?

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New metric types ● counter ● gauge ● histogram ● summary ● untyped → unknown ● state set ● info ● gauge histogram Format ● ● ● Exemplars A normal sample line but without the metric name. A space after the value (or timestamp if present), a hash sign, a space and then the exemplar. Histogram buckets can have them!

Prometheus OpenMetrics # TYPE foo histogram foo_bucket{le="0.01"} 0 foo_bucket{le="0.1"} 8 # {} 0.054 foo_bucket{le="1"} 10 # {id="9856e"} 0.67 foo_bucket{le="10"} 17 # {id="12fa8"} 9.8 1520879607.789 ...

→ →

Berkeley Packet Filters

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Why don’t we make BPF programs look more YAML ✌

Did y’all say

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Custom resources store retrieve structured data Controllers continuously trying Shared informers watches shared state workqueue

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Doing all the BPF things, with YAML

# HELP test_packets Data coming from packets BPF map # TYPE test_packets counter test_packets{key="00002",node="127.0.0.1"} 1 test_packets{key="00006",node="127.0.0.1"} 551 test_packets{key="00008",node="127.0.0.1"} 1 test_packets{key="00017",node="127.0.0.1"} 15930 test_packets{key="00089",node="127.0.0.1"} 9 test_packets{key="00233",node="127.0.0.1"} 1 bfptools/kube-bpf

Any questions?

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