EPIC Goal

Goal: Thoroughly investigate results from large-scale performance scenarios to identify system limits and create an actionable follow-up plan. We aren't just looking for "slow numbers"—we are hunting for the root causes (code, DB, or infra) and fixing them.

The Investigation Checklist:

• Infrastructure Sizing: Determine if current instance types (CPU/RAM) are actually sufficient for 30k users or if we’re over/under-provisioned.

• Database Health: Identify missing indexes, inefficient schemas, or architecture bottlenecks that stall at high concurrency.

• Code Quality: Catch anti-patterns (e.g., N+1 queries, synchronous blocking calls) that only surface under heavy load.

• Resource Management: Fine-tune connection pooling, cache hit ratios, and memory management to prevent leaks and contention.

• Plugin Impact: Isolate specific slow plugins that are dragging down the rest of the instance.

• Network & Latency: Pinpoint bottlenecks in the mesh, load balancers, or external service calls.

Background/Feature Origin

Why is this important?

User Scenarios

Dependencies (internal and external)

Acceptance Criteria

Release Enablement/Demo - Provide necessary release enablement details
and documents

DEV - Upstream code and tests merged: <link to meaningful PR or GitHub
Issue>

DEV - Upstream documentation merged: <link to meaningful PR or GitHub
Issue>

DEV - Downstream build attached to advisory: <link to errata>

QE - Test plans in Playwright: <link or reference to playwright>

QE - Automated tests merged: <link or reference to automated tests>

DOC - Downstream documentation merged: <link to meaningful PR>