Attribute endpoint latency and throughput limits to architectural choices when query counts grow with result size, remote calls are chatty, connections are held across other work, or a cache, layer removal or service extraction is proposed as a performance fix. Compare fetching, call topology, resource occupancy and data movement across the whole request path. Does not replace investigation methodology (performance-methodology), profiling (jfr-and-async-profiler), individual SQL tuning (sql-q...
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---
name: architecture-and-performance
description: >
Attribute endpoint latency and throughput limits to architectural choices when query counts
grow with result size, remote calls are chatty, connections are held across other work,
or a cache, layer removal or service extraction is proposed as a performance fix.
Compare fetching, call topology, resource occupancy and data movement across the whole
request path. Does not replace investigation methodology (performance-methodology),
profiling (jfr-and-async-profiler), individual SQL tuning (sql-query-performance),
pool configuration (connection-pool-sizing) or load-test construction (load-testing).
---
# Architecture and Performance
The unit is the operation from arrival to its promised completion, including work deferred
to other services when that completion requires it. Attribute cost to concrete choices:
how much data is fetched, how often a boundary is crossed, which calls must wait for others,
and how long scarce resources remain occupied. Separate direct work savings from indirect
queue effects: faster mapping may reduce pool waits when it shortens connection holds, even
with unchanged SQL. Neither that effect nor an end-to-end gain follows from local timing alone.
## Workflow
Match the requested role: diagnosis or review produces findings and checks; implement changes
only when the request includes fixes. Inspect endpoint contracts, tests, configuration and prior
decisions before treating a current pattern as a requirement. Ask only for unresolved constraints
that change the choice; continue with reversible analysis using explicit assumptions.
1. **Define the operation and workload.** Obtain the latency/throughput objective, measurement
boundary, request mix and rate, page/payload sizes, data distribution, concurrency and cache
state. Identify the relevant code, SQL/call graph and deployment/framework versions.
Without measurements, produce a conditional cost model and ask for the smallest evidence
needed to distinguish options; do not announce a bottleneck or predict an empirical speedup.
2. **Map work and waits.** Record query/remote-call counts as functions of input size, rows
and bytes returned, serial versus parallel dependencies, retries, queue waits and resource
hold intervals. Compare expected work with observed work. Read
[request-path-budget.md](references/request-path-budget.md) when attributing a slow path,
estimating occupancy, translating ingress into dependency demand or checking a proposal.
3. **Locate the multiplier or limiting resource.** Correlate representative normal and slow
requests with SQL, pool, downstream and CPU evidence. A growing call count suggests a
repeated-access problem; low CPU or any nonzero pool wait alone does not identify its cause.
Keep observation, hypothesis and recommendation distinct. State what would refute the
proposed architectural explanation.
4. **Compare the smallest adequate change.** For fetching, persistence boundaries, mapping,
locking or remote-call alternatives, read
[persistence-cost-model.md](references/persistence-cost-model.md). Predict the mechanism:
calls removed, rows avoided, occupancy reduced or critical-path work overlapped. Compare
against keeping the design and fixing a local query/implementation issue.
5. **Validate the mechanism and outcome.** Preserve authorization, invariants, consistency,
pagination and failure behavior. Re-run comparable work and check both the predicted
mechanism and end-to-end latency, achieved throughput and errors. Delegate experimental
design to `performance-methodology`; code/query-budget tests do not establish a production
latency improvement.
## Decision constraints
- Count round trips, but also work per trip. One huge join can cost more than several bounded
queries. There is no universal query-count threshold proving an architectural defect.
- Separate time on the critical path from total resource consumption. Parallel calls can
shorten elapsed time while increasing downstream concurrency, queues and failure exposure.
- Before adding replicas or parallelism, account for total dependency attempts across callers,
including fan-out, cache misses and retries. More callers do not add capacity to a shared
database or quota. Use bounded parallelism only when independent work and downstream headroom
support it; when the shared dependency is saturated, compare reducing work and limiting
admission before increasing concurrent demand. Request rate alone does not measure capacity.
- Distinguish method duration, transaction lifetime, connection hold time and lock hold time.
Changing one does not guarantee that the others change.
- Before adding a cache, quantify source demand and representative hit/miss behavior, lookup
cost, freshness requirements and miss amplification. A cache can reduce saturated-source
load, but cannot repair incorrect fetching or make stale reads acceptable by itself.
- Before extracting a service, identify the resource or placement advantage that extraction
creates and the new network/serialization/coordination cost. Neither “distribution scales”
nor “distribution can never reduce latency” is a supported conclusion without this model.
- Do not remove a useful layer or weaken a consistency boundary based on a pattern's reputation.
State the observable cost and prove required behavior survives the adjustment.
## Minimum deliverable
For a small review, report evidence or gap, architectural hypothesis, consequence, proposed
adjustment and a confirming/refuting check. For a design, add the workload assumptions,
cost/budget comparison and correctness constraints. Separate measured results from estimates
and tests still to run; leave unsupported conclusions open.
For specialist handoffs, pass the operation/versions, required semantics, scoped evidence and
the unresolved decision. Request the corresponding mechanism, experiment or configuration
check, then bring its result back into the whole-path comparison. If that skill or tool is
unavailable, give the specific check and limit the conclusion; do not fabricate its result.
For worked decision boundaries or when reviewing this skill's behavior, use
[validation-cases.md](references/validation-cases.md). These teaching cases include expected
behavior; they are known examples, distinct from tests of application code.