Operations and → Management Incident Prevention

Incident prevention

1) Why do you need it

The best reaction to an incident is not having one. For iGaming/fintech, every minute of downtime is lost bets/deposits, fines from providers, reputational risks. Systemic prevention reduces Change Failure Rate, stabilizes SLOs, and frees up command time to develop rather than extinguish fires.

• Minimize the likelihood of incidents on critical paths (deposit, bet, game launch, withdrawal).
• Intercept degradation before hitting the SLO and wallet.
• Limit the radius of failure (blast radius) and speed up recovery.

2) Basic principles of prevention

1. SLO-first and error budget: Changes are not released if they risk knocking out SLOs and burning down the budget.
2. Defense in depth: layers of protection - from data schemas and configs to network policies and phicheflags.
3. Design for failure: breakers, timeouts, jitter retreats, idempotency, degradation.
4. Small & reversible changes: small increments + quick rollback (feature flags/canary).
5. Observability by design: metrics/logs/traces for each critical step and link.

3) Risk and critical path map

Make a "pain map" by domains: Payments, Bets, Games, KYC, Promotions, Jackpots, Content.

• Business metrics (conversion, GGR, average check).
• Technical SLOs (latency p95/p99, uptime, success rate).
• Dependencies (internal/external), limits/quotas.
• "Safe mode" behavior (which we disable/simplify).
• Runbook owner.

4) Guardrails (protective barriers)

Timeouts and breakers: the calling service has a timeout shorter than the sum of the internal ones; breaker opens when errors/latency increase.
Bulkhead isolation: separate pools of connections/workers for downstreams.
Rate limit & backpressure: protection against avalanches and retray storms.
Degradation ficheflags: "minimum mode" - easy answers, cache replays, disabling heavy features.
Multi-vendor and feilover: alternative PSP/KYC, route switching.
Validation of configs: schemes/liners/policies for safe change of features and limits.

5) Change Management

Pre-release gates: tests, safety, CDC (consumer-driven contracts), scheme compatibility.
Canary release + autogates: 1% → 10% → 100%; auto-stop at p99/error rate/combustion budget growth.
Feature flags: instantaneous roll back/switch behavior without deploy.
Release calendar: avoid peak sports/tournament windows and maintenance at providers.
Post-deploy checks: auto-sync, comparison of before/after metrics with thresholds.

6) Testing as a preventive measure

Unit/contract/integration: OpenAPI/AsyncAPI contracts, CDC vs. provider/moka.
Load & stress: traffic profiles for prime time; tests for connection/IOPS/quota limits.
Soak/long-haul: Resource leaks, rising delays on the hour/day horizon.

Chaos/game-days: Broker/PSP/KYC drop, region gap, "slow provider."

Disaster Recovery Drills: regular training for switching regions and restoring databases.

7) Early detection of degradation

Capacity-alerts: headroom, queue lags, database connections, eviction in caches.
SLO-burn-rate: signal at a dangerous rate of "burning" the budget.
Adaptive thresholds: seasonality/daily patterns to reduce false.
Composite alerts: "lag ↑ + HPA at max + open circuit" ⇒ high risk.
Vendor health: quotas/timeouts/errors for each provider + cost of calls.

8) Working with external providers

OLA/SLA ↔ SLO: linking agreements to our goals.
Playbooks of the feilover: PSP-X ⇆ PSP-Y routes, token cache, grace deposit modes.
Sandboxes and contracts: Test flow before each major change.
Provider windows: annotations on dashboards and automatic suppress rules.

9) Data, configs and secrets

Change policies: code-review of two pairs of eyes, validation of schemes/JSON/YAML.
Secrets: KMS/Secrets Manager, rotation, separation by environment/role.
Flags/limits: change via API with audit and instant rollback.
Migrations: "two-step" (expand → migrate → contract), total backward compatibility.

10) Training and team readiness

On-call training: incident simulations, shadow duty, centralized runbook 'and.
Unified communication formats: status/handover/incident-update templates.
Safe culture: postmortem without blame, mechanistic reasons and preventive action.

11) Prevention dashboards (minimum)

Risk & Readiness: SLO/budget, headroom by layer, "top vulnerable connections."

Change Safety: percentage of canaries, kickbacks, alerts "after release," CTR of autogates.
Vendor Panel: p95/error/quotas/cost for each provider, vendor support response time.
Chaos/DR Readiness: exercise frequency, region switching time, recovery success.
Config/SecOps: flag/limit/secret changes, anomalies.

12) Examples of preventive alerts

ALERT SLOBurnRateHigh
IF slo_error_budget_burnrate{name="payments_api"} > 4 FOR 10m
LABELS {severity="critical", team="payments"}

ALERT PostDeployRegression
IF (api_p99_ms{service="bets"} > baseline_1d 1. 3) AND (release_window="canary")
FOR 10m
LABELS {severity="warning", team="bets"}

ALERT ProviderQuotaNearLimit
IF usage_quota_ratio{provider="psp_x"} > 0. 9 FOR 5m
LABELS {severity="warning", team="integrations"}

ALERT QueueLagAtRisk
IF (kafka_consumer_lag{topic="ledger"} > 5e6 AND rate(kafka_consumer_lag[5m]) > 5e4)
AND (hpa_desired == hpa_max)
FOR 10m
LABELS {severity="critical", team="streaming"}

13) Prevention checklist (daily/before peaks)

• Up-to-date peak calendar (matches, tournaments, campaigns, provider windows).
• Headroom by API/DB/cache/queues, HPA/VPA readiness, cache warm-up.
• State of providers (quotas, limits, degradation in 24 hours), feiler configured.
• Canary gates are enabled, rollback feature flags are available to owners.
• SLO/Capacity alerts are active, suppression is prescribed for planned work.
• Runbook 'and updated, on-call confirmed, escalation channels working.

14) Anti-patterns (what to avoid)

"Big Night Releases" without canary or flags.
Common head-of-line blocking pools.
Retrays for non-idempotent operations and for bottleneck timeouts.
The absence of hysteresis in the alerts → sawing along the threshold.
Blind faith in vendor SDK without observability and timeout management.
"Let's Do the Prod" without the stage/sandbox and CDC.

15) Prevention KPIs

Change Failure Rate (target ≤ 10-15% or your target).
Pre-Incident Detect Rate: percentage of incidents averted at the degradation stage.
Mean Time Between Incidents (MTBI) и MTTR.
Coverage protection:% critical paths with flags/breakers/timeouts/canary.
Chaos/DR cadence: Frequency and success of exercises.
Vendor readiness: average switching time to the backup provider.

16) Fast start (30 days)

Week 1: critical path map, SLOs and owners; include SLO-burn alerts and capacity alerts.
Week 2: Canary Gates + Phicheflags; basic chaos scripts (provider/queue).
Week 3: dashboards "Change Safety" and "Vendor Panel," feilover playbooks.
Week 4: DR exercise (partial), retrospective and hardening plan for the quarter.

17) Templates (fragments)

canary_policy:
guardrails:
- metric: api_p99_ms threshold: 1. 3 baseline_1d window: 10m action: pause_and_rollback
- metric: error_rate threshold: 2 baseline_1d window: 5m action: pause max_step: 10%
step_interval: 15m required_annotations: [release_notes, feature_flags, runbook_link]

safe_mode:
payments:
- freeze_heavy_providers
- enable_cached_token_flow
- route_to_psp_y_if(psp_x_error_rate > 5%)
games:
- limit_broadcasts
- reduce_lobby_heavy_widgets bets:
- raise_risk_score_threshold
- cache_odds_snapshot

18) FAQ

Q: What to implement first if resources are scarce?
A: SLO-burn alerts on critical paths, canary gates and rollback phicheflags; then - a risk map and a provider fake.

Q: How do you know that prevention "works"?
A: Change Failure Rate is going down, the proportion of incidents prevented is going up, MTTR and alert noise is going down, the number of "night" pages is going down.

Q: Do we need regular chaos exercises?
A: Yes. Without training, a feuillower and DR are almost always longer and more painful than they seem on paper.