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runtime-config-flagd

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UpdatedJune 2, 2026 at 08:13

Feature flag management via flagd (OpenFeature). Use to list, inspect, and toggle feature flags in the OTel Demo environment. Flags control incident injection scenarios (payment failures, CPU spikes, memory leaks, etc.) and can be toggled for remediation.

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name	runtime-config-flagd
description	Feature flag management via flagd (OpenFeature). Use to list, inspect, and toggle feature flags in the OTel Demo environment. Flags control incident injection scenarios (payment failures, CPU spikes, memory leaks, etc.) and can be toggled for remediation.
category	runtime-config
required_integrations	["kubernetes"]

Feature Flag Management (flagd)

How It Works

The OpenTelemetry Demo uses flagd as its feature flag provider. Flags are stored in a Kubernetes ConfigMap and loaded by the flagd service. Services check flags at runtime via the OpenFeature SDK to decide whether to inject failures.

Flag lifecycle:

Flag definitions live in a ConfigMap (flagd-config in otel-demo namespace)
flagd watches the ConfigMap and hot-reloads on changes
Services evaluate flags via gRPC and behave accordingly
To remediate an incident, set the flag's default variant to off

Available Scripts

All scripts are in .claude/skills/runtime-config-flagd/scripts/

list_scenarios.py - List Incident Scenarios (START HERE)

Shows all available incident scenarios with their current status.

python .claude/skills/runtime-config-flagd/scripts/list_scenarios.py

# Only show currently active scenarios
python .claude/skills/runtime-config-flagd/scripts/list_scenarios.py --active-only

# JSON output
python .claude/skills/runtime-config-flagd/scripts/list_scenarios.py --json

Output includes: flag name, current state (active/inactive), affected service, effect description, detection method, and remediation steps.

list_flags.py - List All Feature Flags

python .claude/skills/runtime-config-flagd/scripts/list_flags.py

# Show full variant details
python .claude/skills/runtime-config-flagd/scripts/list_flags.py --verbose

# Only incident-related flags
python .claude/skills/runtime-config-flagd/scripts/list_flags.py --incidents-only

get_flag.py - Inspect a Specific Flag

python .claude/skills/runtime-config-flagd/scripts/get_flag.py <flag_key>

# Examples:
python .claude/skills/runtime-config-flagd/scripts/get_flag.py paymentServiceFailure
python .claude/skills/runtime-config-flagd/scripts/get_flag.py adServiceHighCpu --json

set_flag.py - Toggle a Flag (Remediation)

# ALWAYS dry-run first
python .claude/skills/runtime-config-flagd/scripts/set_flag.py <flag_key> <variant> --dry-run

# Then apply
python .claude/skills/runtime-config-flagd/scripts/set_flag.py <flag_key> <variant>

# Examples:
python .claude/skills/runtime-config-flagd/scripts/set_flag.py paymentServiceFailure off --dry-run
python .claude/skills/runtime-config-flagd/scripts/set_flag.py paymentServiceFailure off
python .claude/skills/runtime-config-flagd/scripts/set_flag.py adServiceHighCpu off
python .claude/skills/runtime-config-flagd/scripts/set_flag.py emailMemoryLeak off

Incident Scenarios Reference

Scenario	Flag	Service	Effect	Remediation
Payment Failure	`paymentServiceFailure`	payment (Node.js)	Configurable % of requests fail	Set to `off`
Payment Unreachable	`paymentServiceUnreachable`	payment	Complete unavailability	Set to `off`
High CPU	`adServiceHighCpu`	ad (Java)	CPU spike 80-100%	Set to `off`
GC Pressure	`adServiceManualGc`	ad (Java)	Frequent full GC pauses	Set to `off`
Ad Failure	`adServiceFailure`	ad (Java)	Ad service errors	Set to `off`
Memory Leak	`emailMemoryLeak`	email (Ruby)	OOM after minutes	Set to `off` + restart pod
Latency Spike	`imageSlowLoad`	image-provider	5-10s delay	Set to `off`
Kafka Lag	`kafkaQueueProblems`	checkout/accounting	Consumer lag	Set to `off`
Cache Failure	`recommendationServiceCacheFailure`	recommendation	Cache miss storm	Set to `off`
Catalog Failure	`productCatalogFailure`	product-catalog	Product query errors	Set to `off`
Cart Failure	`cartServiceFailure`	cart (.NET)	Cart ops fail	Set to `off`
Traffic Spike	`loadgeneratorFloodHomepage`	all services	Request flood	Set to `off`
LLM Inaccuracy	`llmInaccurateResponse`	product-reviews	Wrong AI content	Set to `off`
LLM Rate Limit	`llmRateLimitError`	product-reviews	429 errors	Set to `off`

Flag Variant Reference

Flags have different variant types:

Boolean flags (on/off):

adServiceHighCpu, adServiceManualGc, adServiceFailure, paymentServiceUnreachable, cartServiceFailure
recommendationServiceCacheFailure, productCatalogFailure
llmInaccurateResponse, llmRateLimitError
Variants: on (true), off (false)

Percentage flags (graduated failure rate):

paymentServiceFailure: off (0), 10% (0.1), 25% (0.25), 50% (0.5), 75% (0.75), 90% (0.95), 100% (1)

Intensity flags (graduated effect):

emailMemoryLeak: off (0), 1x (1), 10x (10), 100x (100), 1000x (1000), 10000x (10000)
imageSlowLoad: off (0), 5sec (5000ms), 10sec (10000ms)

Numeric flags:

kafkaQueueProblems: off (0), on (100)
loadgeneratorFloodHomepage: off (0), on (100)

Version Compatibility

Flag	otel-demo Version	Notes
All flags except below	v1.11.1+	Standard deployment
`emailMemoryLeak`	> v1.11.1	Not in v1.11.1 ConfigMap
`llmInaccurateResponse`	> v1.11.1	Requires product-reviews LLM
`llmRateLimitError`	> v1.11.1	Requires product-reviews LLM

Note: loadgeneratorFloodHomepage uses a lowercase 'g' in loadgenerator.

Remediation Workflow

Identify the scenario - Use list_scenarios.py --active-only to see active incidents
Confirm the flag - Use get_flag.py <flag_key> to verify current state
Dry-run - Use set_flag.py <flag_key> off --dry-run to preview change
Apply - Use set_flag.py <flag_key> off to disable the incident
Verify - Check metrics/logs to confirm the issue is resolving
Post-remediation - Some scenarios (memory leak) may also require a pod restart

Safety

ALWAYS dry-run first before setting flags
Setting a flag to off is always safe — it restores normal behavior
Setting a flag to on or a non-zero variant injects failures — only do this intentionally
Flag changes take effect within seconds (flagd hot-reload)
For emailMemoryLeak, after setting to off you may also need to restart the email pod to reclaim leaked memory

Quick Commands

Goal	Command
See active incidents	`list_scenarios.py --active-only`
Check a specific flag	`get_flag.py paymentServiceFailure`
Disable payment failure	`set_flag.py paymentServiceFailure off`
Enable payment failure at 50%	`set_flag.py paymentServiceFailure 50%`
Disable all CPU spikes	`set_flag.py adServiceHighCpu off`
See all flags verbose	`list_flags.py --verbose`