postmortemincident-responseSRE

Incident Postmortem Template for Datastore Failures During Multi-Service Outages

UUnknown

2026-02-22

11 min read

Reusable postmortem template for datastore teams hit by CDN/cloud failures—metrics, timeline, remediation tasks, and verification steps.

When an upstream CDN or cloud provider takes down your app, your datastore is the canary — and the postmortem must be surgical

Hook: If your datastore team has ever watched client errors spike while the CDN or a cloud edge provider reports an incident, you know the unique pressure: data integrity risks, unpredictable latency, and hard product decisions under fire. This template gives a reusable, technical postmortem for datastore outages caused by upstream CDN/cloud failures — with precise metrics to collect, triage steps, remediation tasks, and follow-ups SREs and DBAs can act on immediately.

Why this matters in 2026

Through late 2025 and early 2026 the industry saw repeated multi-service disruptions where a single CDN or edge-cloud incident cascaded into application and datastore instability. Public reporting (e.g., coverage of CDN/AWS/edge incidents in January 2026) shows that more teams are confronting upstream-induced datastore failures rather than purely internal bugs. Today, datastores sit behind distributed edges, serverless functions, and third-party caches — increasing attack surface and cross-service coupling.

Expect the trend to continue in 2026: more edge compute and multi-CDN deployments, stronger emphasis on provider transparency, and more mandatory RPKI/DNSSEC adoption. Your postmortem must therefore surface cross-provider dependencies and measurable remediation steps that reduce blast radius.

How to use this template

This is a fillable incident postmortem optimized for datastore teams impacted by upstream CDN/cloud failures. Use it as your canonical postmortem document after every incident. Populate the timeline, attach raw metrics, and assign remediation owners. Where possible, link to provider incident pages, traceroutes, and relevant logs.

Audience

SREs and on-call DBAs who run production datastores
Platform and network engineers responsible for CDN/cloud integrations
Engineering managers and compliance teams who need actionable remediation and SLIs

Incident Postmortem Template — Datastore Focus (Fillable)

1) Executive summary (Top-of-doc)

Incident ID: [INC-YYYYMMDD-XXX]
Start / End: [UTC timestamps — detection and mitigation times]
Severity: SEV1 / SEV2
Services impacted: API Gateway, CDN-X, Datastore (write path / read path), Background jobs
Short impact statement: e.g., "From 2026-01-16T10:28Z–2026-01-16T14:04Z, an upstream CDN routing failure caused origin authentication to fail for 62% of edge requests, increasing datastore p99 latency and producing 5xx errors for 22% of client requests. Writes were delayed up to 3 hours for some tenants."
Status page / provider link: [CDN provider incident URL, cloud provider status log, BGP reports]

2) Impact (Quantified)

Always quantify. Replace bracketed queries with real numbers and attach graphs.

Requests failed (total): [x requests / % of total traffic]
Error types: 502/503/504 origin-errors, TLS handshake failures, DNS NXDOMAIN, connection resets
Time-to-detection: [minutes]
Time-to-mitigation: [minutes/hours]
SLO/% error budget burned: e.g., "Web API SLI (5xx rate) rose from 0.12% baseline to 21% causing 92% of the monthly error budget burned in 3 hours."
Data risk: lost writes, potential duplication, delayed replication? e.g., "Write queue backlog reached 45M operations; eventual-consistency delay 2–4 hours for downstream read replicas."

3) Timeline (5–15 min resolution during incident)

Provide an ordered, timestamped sequence. Link to provider status updates and internal comms.

[T0] 10:28Z — CDN provider reported edge routing errors (public status page).
[T0+2m] 10:30Z — Pager triggered for high 5xx rate on API layer originating from CDN X.
[T0+6m] 10:34Z — On-call confirmed: origin TLS handshakes failing from multiple edge POPs.
[T0+15m] 10:43Z — Failover to alternate ingress (bypass CDN) initiated for critical write endpoints.
[T0+90m] 12:00Z — CDN mitigations reported; partial traffic restore; backlog drain initiated.
[T1] 14:04Z — Traffic normalized; follow-up verification completed.

4) Root cause analysis (RCA)

Describe root cause with evidence. Keep cause-and-effect crisp.

Root cause: e.g., "Edge routing misconfiguration at CDN provider led to TLS session resets for a subset of POPs. Our ingress relied on Cache-Accelerated TLS from CDNX and did not maintain a direct origin fallback route for authenticated writes."
Contributing factors:
- Single-CDN dependency for write path.
- Missing circuit breaker between edge and app origin; retries amplified load.
- Insufficient health-checks that validate TLS and application-layer auth rather than only TCP level.
- Runbook gaps: no documented procedure to immediately switch critical write endpoints to direct-origin routes.
Evidence collected: provider incident logs, mtr/traceroute captures, CDN edge logs, origin TLS debug logs, Prometheus/Datadog dashboards (attach screenshots/queries).

5) Detection & monitoring analysis

List which alerts fired, missed alerts, and false positives.

SLIs to include in every datastore CDN incident:
- Client-facing 5xx rate (per minute) — baseline vs incident
- Origin request rate from CDN → number of origin auth failures (per POP)
- Datastore write queue length and replication lag (seconds)
- p50/p95/p99 and p99.9 latency for reads and writes on origin
- Retry amplification metric (ratio of edge retries to originating client requests)
- Cache hit ratio and origin burn-rate (requests/sec to origin vs historical)
Missed detection: Our alert monitored TCP health to the origin but not TLS session failures. Add/update alerts below.

6) Immediate remediation actions (what we did)

Timeline of actions and effect. For each action include who performed it, time, and result.

Initiated direct-origin ingress (bypass CDN) for three critical write endpoints. Result: 78% reduction in 5xx for write traffic within 4 minutes.
Enabled rate-limiting at API gateway to prevent retry storms. Result: reduced origin CPU usage by 40% during peak.
Placed datastore write paths into degraded/append-only mode for non-critical tenants to protect integrity while backlog drained.
Opened support channel with CDN provider; correlated POPs experiencing TLS resets.

7) Short-term remediation (within 7 days)

Implement an automated switch to direct origin for write endpoints via feature-flagged routing change (owner: network/platform team; ETA: 72 hours).
Add TLS session and application-layer health checks in synthetic monitoring for every ingest endpoint (owner: SRE; ETA: 48 hours).
Patch retry/backoff logic to use exponential backoff with jitter and a global circuit breaker to prevent amplification (owner: backend team; ETA: 5 days).
Document runbook steps for CDN provider incidents and test via a game-day within 2 weeks (owner: SRE; ETA: 14 days).

8) Long-term remediation (architectural)

Adopt multi-CDN for critical write endpoints with a provider-agnostic ingress control plane (owner: platform; ETA: Q2 2026).
Introduce origin shielding + signed origin headers so the origin can quickly identify edge POPs and apply targeted mitigations (owner: security/network; ETA: Q3 2026).
Re-architect client SDKs to support degraded modes (read-only, eventual write queue) and clearer client-side error codes for upstream issues (owner: API/SDK teams; ETA: Q3 2026).
Introduce SLIs that measure cross-provider coupling: e.g., % of requests served by edge vs direct origin and % of origin-authenticated requests failing at edge layer (owner: SRE; ETA: Q2 2026).

9) Action items (table format — convert to your tracker)

Action: Automated direct-origin switch for writes — Owner: NetOps — Priority: P0 — ETA: 72h — Verification: Failover tested in staging, synthetic checks green.
Action: Add TLS and app-level health checks — Owner: SRE — Priority: P0 — ETA: 48h — Verification: Runbook and alert thresholds validated.
Action: Retry & circuit breaker changes — Owner: Backend — Priority: P1 — ETA: 5d — Verification: Load test with simulated edge failures.

10) Verification plan

Every remediation must have a verification step:

Run canary that simulates CDN-edge failures and assert writes succeed via direct-origin path in < 200ms for 95% of requests.
Assure that error budget burn rate for writes returns to baseline within one SLO period after deployment.
Document post-deploy monitoring queries and dashboards used to validate (attach queries below).

11) Metrics & example queries (attach to dashboards)

Include exact queries you can paste into Prometheus/Datadog/Cloud Monitoring. Replace metric names as necessary.

Client 5xx rate:

sum(rate(http_requests_total{status=~"5.."}[1m])) / sum(rate(http_requests_total[1m]))

Origin auth failures by POP:

sum by(pop) (increase(origin_auth_failures_total[5m]))

Origin request burn rate:

rate(origin_requests_total[1m]) / avg_over_time(rate(origin_requests_total[1m])[1h])

Datastore write queue length:
```
max(datastore_write_queue_length)
```

Replication lag:

histogram_quantile(0.99, sum(rate(replication_lag_seconds_bucket[5m])) by (le))

Retry amplification:

rate(edge_retries_total[1m]) / rate(client_requests_total[1m])

12) Communication & compliance

List exactly what was communicated and when. Keep templates ready for external customers.

Internal triage channel established at T0+1m. Weekly follow-up with impacted teams until all action items closed.
Customer status updates on public status page at 30-minute cadence while incident active.
Regulatory/compliance: evaluate whether SLA credits or breach notices needed based on SLOs. Log decisions in ticketing system.

13) Lessons learned (must be explicit and actionable)

"We treated the CDN as a transparent transport. In reality it is a stateful dependency that requires app-level health checks and explicit fallback behavior." — postmortem insight

Always instrument and alert on application-layer failures from edge to origin (TLS and auth failures), not just TCP.
Design write paths with a tested direct-origin fallback; build the switch to be automated and safe by default.
Simulate provider outages in game-days to exercise runbooks and verify SLO protection mechanisms (circuit breakers, rate-limits, degraded modes).

Practical runbook snippets & commands

Use these during incident triage — copy into your runbook.

Quick TLS check from an edge POP:

openssl s_client -connect origin.example.com:443 -servername origin.example.com -showcerts

Compare CDN vs direct-origin response:

curl -v -H "Host: api.example.com" https://edge.example-cdn.net/endpoint && curl -v https://origin.example.com/endpoint

DNS / traceroute checks:

dig +short api.example.com @8.8.8.8 && mtr -r -c 10 origin.example.com

Inspect retry amplification:

grep "retry" /var/log/app/access.log | wc -l

Case study (anonymized) — how a multi-hour outage was contained

Context: A SaaS analytics vendor experienced a January 2026 CDN edge routing failure. Key facts below are anonymized and illustrative.

Incident: CDN POPs returned truncated TLS sessions for authenticated clients. Client SDKs retried aggressively, tripling origin load.
Immediate effect: Client-facing 5xx rose from 0.08% to 18% in 10 minutes; p99 write latency from 140ms to 3.2s; write queue backlog grew to 32M records.
Response: Platform toggled direct-origin switch via feature flag for write endpoint in 6 minutes; rate-limiting applied to SDKs; backlog drained in 2.5 hours. No data loss, but replication delays occurred for non-critical regions.
Postmortem actions: Game-day scheduled, multi-CDN PoC started, SDK retry logic changed to use exponential backoff + client-side circuit breaker.

Advanced strategies and 2026 predictions

Plan your roadmap with these trends in mind.

Provider transparency & SLA granularity: Expect more granular provider SLAs and machine-readable incident feeds in 2026. Integrate these feeds into your incident detection pipeline.
Multi-CDN and provider-agnostic control planes: Multi-CDN strategies will move from edge caching to actively protecting write paths and critical APIs, not just static assets.
Edge-to-origin authentication patterns: Signed origin headers, mTLS, and per-POP certificates will become common; monitor and test these flows regularly.
Chaos + game-days: Post-2025 outages accelerated adoption of chaos engineering for third-party failures — schedule regular failure-injection exercises that mimic real provider incidents.
Observability: correlated cross-provider traces: Correlate CDN provider logs, BGP/DNS signals, and your application traces to reduce time-to-detection. Use eBPF or distributed tracing adapters to observe at the system level.

Checklist: What to commit to before the next outage

Automated direct-origin fallback for write-critical endpoints.
App-layer health checks (TLS + auth) in synthetic monitors across POPs.
Retry/circuit-breaker patterns in SDKs and server code.
Game-day schedule that simulates CDN/provider edge failures every quarter.
Actionable postmortem with owners and measurable verification steps.

Closing: How to make your postmortems faster and safer

Postmortems are not punishment — they are the map to preventing the next incident. For datastore teams, that means focusing on preserving data integrity first, then availability. Use this template as the canonical artifact after every CDN/cloud-induced outage. Prioritize measurable remediations with owners, and integrate provider incident signals into your SRE tooling so you detect upstream issues before they cascade into your datastore.

Actionable takeaways

Instrument app-layer failures (TLS, auth) from edge to origin — not just TCP checks.
Automate and test direct-origin fallbacks for write traffic.
Limit retry amplification via client/server-side circuit breakers and exponential backoff.
Run provider-failure game-days quarterly and add findings to your runbook.
Track and publish remediation verification metrics with clear owners and ETAs.

Call-to-action

If you run a production datastore, copy this postmortem into your incident template repository, run a CDN-edge game-day this quarter, and assign the top three remediation tasks now. Need help implementing automated direct-origin failover, observability queries, or a multi-CDN PoC? Contact our platform team for a tailored workshop and runbook review.

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