Feature Flag Rollout Schedule Record

Template Overview

Shipping large feature branches in a single monolithic deploy introduces catastrophic risk. Feature flags decouple deployment from release, allowing engineering teams to progressively expose features to canary cohorts while retaining instant kill-switch capabilities. The Feature Flag Rollout Schedule organizes rollout percentages, telemetry gates, kill-switch criteria, and code cleanup dates in plain Markdown.

Markdown Template Structure

Copy the block below or click Download .md File to add this template directly to your personal vault:

---
title: "Flag Schedule: [Feature Flag Key / Name]"
date_initiated: [YYYY-MM-DD]
flag_owner: "[[Staff Software Engineer]]"
flag_key: "ff_local_whisper_large_v3"
default_state: "DISABLED (False)"
target_audience: "All macOS Desktop Users"
kill_switch_authorized_leads: ["[[Lead Engineer]]", "[[SRE Lead]]"]
technical_debt_cleanup_date: "2026-11-30"
tags: [feature-flags, rollout, devops, progressive-delivery, release]
---

# Feature Flag Rollout Schedule — [Feature Flag Key]

## 1. Feature Flag Purpose & Architecture
- **Flag Key:** `ff_local_whisper_large_v3`
- **Feature Scope:** Activates optional high-accuracy Whisper Large v3 model downloading and inference for users with >= 16GB unified RAM.
- **Rollout Mechanism:** Client-side evaluated configuration file loaded upon application launch.

## 2. Progressive Phasing Cadence & Telemetry Gates
| Phase | Percentage | Target Cohort | Start Date | Gate Criteria to Advance | Status |
|---|---|---|---|---|---|
| **Phase 0** | 0% (Internal) | Core Engineering Team | 2026-10-10 | Zero crashes across 100 test runs | **Passed** |
| **Phase 1** | 5% | Beta Opt-In Users | 2026-10-14 | Crash rate < 0.02%; zero OOM errors | **Active** |
| **Phase 2** | 25% | General Mac Users | 2026-10-18 | Memory consumption steady < 4.2GB | Queued |
| **Phase 3** | 50% | General Mac Users | 2026-10-22 | Support tickets < 5 per 1,000 users | Queued |
| **Phase 4** | 100% | Full General Availability | 2026-10-26 | All telemetry healthy for 7 days | Queued |

## 3. Kill-Switch Triggers & Emergency Revert Protocol
> [!CAUTION] Automatic Kill-Switch Triggers
> Instantly toggle `ff_local_whisper_large_v3` to **FALSE** if any of the following occur:
- Application crash rate exceeds **0.1%** in any 1-hour window.
- Out-of-memory (OOM) OS kill events exceed **3 instances** on 16GB hardware.
- Model execution causes fan throttling > 4,000 RPM on M-series laptops.

### Revert Execution Steps:
1. Update remote configuration payload to set `enabled: false`.
2. Push Git tag marking emergency flag disablement.
3. Post incident notification in engineering alert channel.

## 4. Telemetry Verification Checklist
- [ ] Memory consumption telemetry verified on Apple M1, M2, and M3 hardware.
- [ ] Fallback logic gracefully downgrades to Whisper Small if user lacks required free RAM.
- [ ] Telemetry events respect local-first privacy (zero audio or note content transmitted).

## 5. Post-Rollout Technical Debt Cleanup Plan
- **Permanent Flag Removal Target:** 2026-11-30.
- **Cleanup PR Scope:** Delete conditional `if (flag_enabled)` branches, remove flag key from config schemas, and set new engine as permanent default codebase behavior.

## 6. Action Items
- [ ] Monitor Phase 1 canary metrics for 48 hours.
- [ ] Convene go/no-go review before advancing to Phase 2 (25%).

Filled Real-World Example

Here is a realistic example demonstrating how this template captures actual deliberations:

---
title: "Flag: Markdown AST Parser v2"
date_initiated: 2026-10-07
flag_owner: "[[Elena Rostova]]"
flag_key: "ff_ast_parser_v2"
cleanup_date: "2026-10-31"
tags: [feature-flags, ast-parser]
---

# Feature Flag Rollout Schedule — Markdown AST Parser v2

## 1. Overview
Elena Rostova managed the progressive rollout of the updated CommonMark Abstract Syntax Tree parser.

## 2. Rollout Progression
Advanced from 5% to 50% over 4 days with zero rendering exceptions. Full 100% rollout approved for next Monday, followed by complete removal of legacy regex parser code.

When to Use and When to Avoid

When to Use

• Use whenever launching complex, risky backend logic, new parsers, or high-memory models.
• Use to establish clear percentage rollout schedules across multi-week launch windows.
• Use to schedule explicit cleanup deadlines to prevent technical debt accumulation.

When to Avoid

• Avoid using for small visual CSS style changes or static copy updates.
• Avoid keeping permanent feature flags that never get cleaned up.

On-Device AI Integration

Summarize your recording in Oyma with this local instruction:

Analyze the feature flag configuration and telemetry metrics:
1. Evaluate progressive canary rollout stages against established safety criteria.
2. Outline explicit emergency kill-switch thresholds and revert procedures.
3. Formulate a technical debt cleanup schedule in structured Markdown.

Your data remains securely on your Mac with zero cloud exposure.