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At QCon London 2026, Nicholas Herring, Technical Director for EVE Online at CCP Games, will present a case study in observing a real-time multiplayer universe without storing every event. The session describes a telemetry approach centered on head-based sampling, dynamic and deterministic sampling, and exponential moving averages (EMA) to identify traffic that matters—including interactions that may express a player’s personality or create “fun.” The conference abstract outlines the problem and topics, but it does not publish EVE Online’s production rules, metrics, sampling rates, or measured results.
What the QCon session covers
QCon London lists the 50-minute presentation for Tuesday, March 17, 2026, at 11:45 GMT in Whittle at the QEII Centre in London. It is scheduled under Distributed Tracing. The speaker is Nicholas Herring, identified by the conference as Technical Director, Eve Online at CCP Games.
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The abstract frames the challenge this way: “A unique pattern in video game software is real-time interactions to express the personality of users.” It says the talk will explain how the team instruments the universe of New Eden to identify the traffic that matters, “even the ‘fun’ parts!”
Its stated scope has four elements:
- A “100% Head base sampling ecosystem.”
- A blend of dynamic and deterministic sampling techniques.
- “The blessing and curse that is the Exponential Moving Average (EMA).”
- Observing “fun” without breaking the bank.
Those are the speaker’s declared discussion points, not independently verified descriptions of CCP’s implementation or outcomes. The abstract also describes a 20-year-old legacy system operating alongside modern technologies; that wording is the speaker’s characterization rather than a separately measured age claim.
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How does EVE Online use head-based sampling to observe “fun”?
The available session information supports a problem statement, not a complete design specification. EVE Online needs observability for a continuously running, highly interactive game, yet retaining every trace and event can create excessive collection, processing, and storage costs. Sampling is the mechanism for reducing that volume while trying to preserve the interactions most useful for understanding the game.
With head-based sampling, a retention decision is made near the beginning of a trace. The sampler chooses whether the trace should be collected or kept before the full sequence of operations is known. That makes the approach suitable for controlling telemetry volume early, but it also creates a fundamental limitation: the sampler cannot know at decision time whether a later span will fail, become slow, or reveal an especially interesting player interaction.
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The phrase “100% Head base sampling ecosystem” is not explained operationally in the published abstract. It could refer to the scope of the sampling architecture, a policy that all decisions are made at the trace head, or another internal definition. The session page does not state a percentage of traces retained, a probability function, or a rule for combining samplers.
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Head and tail sampling differ mainly in when the retention decision is made. A general tracing explanation describes tail-based sampling as deciding after a trace has completed, when its full outcome is available. That allows a policy to retain traces because they contain an error, unusual latency, or another attribute discovered late. Head sampling must decide before those later outcomes are visible.
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| Aspect | Head-based sampling | Tail-based sampling |
|---|---|---|
| Decision timing | Near the start of the trace | After the trace completes |
| Visibility when deciding | Initial context; later spans are not yet known | Full trace outcome, including later spans |
| Selection of late errors or latency | Cannot selectively retain a trace based on a later event at decision time | Can retain traces using completed-trace conditions |
| Operational trade-off | Controls volume early, but may miss traces that become important later | Requires holding and processing completed traces before deciding, which can increase resource demands |
This comparison explains why head sampling is technically interesting for a large game, but it does not establish that EVE Online uses tail sampling, or that it rejects it. The QCon abstract names head-based sampling; it does not describe a tail-sampling subsystem.
What dynamic sampling, deterministic sampling and EMA might address
Dynamic sampling
Dynamic sampling generally implies that retention behavior can change as traffic or operating conditions change. In a game, a dynamic policy could be relevant when event rates, system load, or the value of a signal varies. The abstract confirms that dynamic techniques are a topic, but it does not identify the inputs, thresholds, update interval, or control plane used by CCP.
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Deterministic sampling
Deterministic sampling uses repeatable rules so that the same qualifying input can receive the same sampling decision. Such rules can help teams reason about coverage and maintain consistency across components. The presentation title does not disclose whether determinism is based on user, session, trace, event type, or another key.
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Exponential moving average
An EMA is a smoothing calculation that gives more weight to recent observations while retaining a diminishing influence from older ones. It can make a noisy rate or workload signal easier to use for control decisions. Herring’s abstract calls EMA both a “blessing and curse,” indicating that the session will discuss its benefits and drawbacks. It does not state which signal is smoothed, what smoothing factor is used, or how the result affects sampling.
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Why “fun” is an observability problem
Errors and latency are comparatively straightforward telemetry targets: they can be represented by status, duration, and infrastructure context. “Fun” is different. In a real-time game, a memorable interaction may emerge from many normal operations, player choices, and social responses rather than from a single failed request. The abstract’s reference to personality points to this behavioral dimension: useful telemetry may need to preserve patterns of interaction, not merely system health.
That creates a selection problem. A sampler must keep enough context to study meaningful activity while avoiding a stream so large that storage and analysis become impractical. The talk’s stated goal is to identify traffic that matters, including these player-expressive interactions, without “breaking the bank.” The public description does not define fun as a metric, identify a classifier, or report a cost reduction.
What is established—and what remains unknown
Readers can treat the following as established by the conference listing:
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- The event is a QCon London 2026 session on March 17, 2026, in London.
- Nicholas Herring is listed as the speaker and as Technical Director, Eve Online at CCP Games.
- The stated subject is observability for New Eden, with attention to real-time interactions and player personality.
- Head-based sampling, dynamic and deterministic techniques, EMA, and telemetry cost are explicitly named topics.
The published material does not establish the actual sampling rules, how “100%” is defined, the metrics or signals used, the way fun is classified, the storage architecture, or any measured performance or cost result. It also does not confirm whether slides or a recording are publicly available. Those details require the talk’s primary materials or a later technical publication.
Practical lesson for observability teams
The case study’s useful design question is not simply whether to sample. It is how to decide what must remain visible when the most valuable behavior may be contextual, delayed, and difficult to label. Head-based decisions can keep collection manageable from the outset, while adaptive and repeatable policies may help allocate coverage. But every early decision trades away some ability to select traces using information that appears later. Teams applying the same reasoning should document the decision point, the signals available there, the behavior they are willing to miss, and the resource ceiling that the telemetry system must respect.
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