Postmortem Template: Investigating a Multi-Service Outage Involving CDN, Cloud, and Social Platforms

Hook: Why standard postmortems fail for multi-service outages

When a CDN, a cloud provider, and one or more social/SaaS platforms fail at the same time, investigations become a grind: logs live in different systems, timestamps drift, legal preservation requirements bite, and stakeholders demand answers fast. If you've struggled to reconstruct a coherent timeline or preserve evidence in a way that survives legal scrutiny, this template is built for you.

Executive summary — what this template delivers

This is a reproducible, investigation-grade postmortem template tailored to outages that cross CDN edges, cloud infrastructure, and external SaaS/social dependencies. It includes a prioritized timeline format, step-by-step evidence collection for major vendors (AWS, GCP, Azure, Cloudflare/Akamai, and common social platforms), root cause analysis (RCA) heuristics, mitigation playbooks, SLA review checklist, and a mitigation/prioritization matrix you can apply immediately.

Context (2026 trends that matter)

Incident investigators in 2026 face a different landscape than five years ago:

• Edge compute and multi-CDN adoption exploded in 2024–2025, increasing attack and failure surface across providers.
• AI-driven routing and load management are now common, which can obscure causal chains when models adapt during an outage — see notes on edge AI and observability.
• Regulatory pressure for cross-border evidence preservation (e.g., data localization and e‑discovery updates in 2025–2026) complicates preservation strategy.
• Observability standards moved towards structured, immutable telemetry, but many orgs still lack end-to-end log correlation — explore edge-first tooling and cache patterns in this edge-powered dev tools note.

Inverted pyramid: Most important actions first

1. Preserve evidence: snapshot configurations, export logs, enable retention holds. For large archives and OLAP-style log storage guidance, consider principles from storing structured experiment data in ClickHouse-like systems as a reference: ClickHouse-like OLAP.
2. Reconstruct timeline: collect canonical time sources, correlate via unique request IDs (CDN RayIDs, cloud trace IDs, social post IDs).
3. Identify root cause: separate primary failure from cascading failures and misconfigurations.
4. Mitigate & communicate: implement short-term fixes, then long-term corrective actions; author SLA and vendor remediation review.

Real-world case snapshot (brief)

In January 2026 several major services reported coupled outages affecting social platforms and web properties. Investigations highlighted three repeating patterns: (1) a CDN configuration rollout that invalidated origin authentication tokens, (2) a cloud provider control-plane flakiness that delayed autoscaling, and (3) social platform API throttling which amplified customer-visible failures. Use this template to avoid repeating those mistakes.

Postmortem template — structured sections

Copy this structure into your incident tracker or documentation system. Each section includes fields and guidance for investigators.

1) Summary

• Incident ID: [INC-YYYYMMDD-XXX]
• Start/End: [UTC timestamps — use ISO 8601]
• Services impacted: CDN, Cloud Provider (region/zone), Social/SaaS platform(s)
• Customer impact: [% requests failed, percent revenue affected, critical customers]
• Severity: P1/P2

2) Short timeline (first 6–12 hours)

Include only high-level milestones for executives. Use the detailed timeline later for technical audiences.

• HH:MM — First alert: synthetic checks failed for primary website
• HH:MM+5 — Multiple customer reports and DownDetector spikes
• HH:MM+15 — CDN status page reports edge errors in region X
• HH:MM+45 — Cloud provider reports partial control-plane degradation: autoscaling delayed
• HH:MM+2h — Social platform API returns 429; partner integrations missing webhooks
• HH:MM+6h — Workaround: switch to backup CDN and enable circuit breaker for social integrations

3) Detailed timeline reconstruction (reproducible format)

This section is the investigation core. Use UTC and specify the source for each timestamp.

1. Timestamp (UTC)
2. Event
3. Source/Artifact (e.g., CloudWatch log stream ID, Cloudflare RayID, social post ID)
4. Confidence (low/medium/high)

Example entry:

2026-01-16T15:11:05Z — 502s observed at CDN edge for host example.com — source: Cloudflare RayID 7623a — confidence: high (CDN edge logs and synthetic fail)

Recommended timeline reconstruction process

1. Collect canonical time sources: NTP/Chrony server offsets, cloud provider time (CloudTrail/CloudWatch timestamps), and CDN edge timestamps.
2. Normalize all timestamps to UTC and document clock skew corrections.
3. Correlate by unique IDs: request IDs, trace IDs, CDN RayIDs, social post/webhook IDs.
4. Create an event chain: map first-error → downstream error → customer-visible symptom. Instrumentation and propagating a single trace ID across the stack is crucial; consider edge and tracing guidance from edge-powered tooling notes: edge-powered strategies.

4) Evidence preservation checklist (immediate actions)

Start these within the first hour. Aim for reproducible, tamper-evident artifacts.

• Enable retention holds / legal holds on affected S3 buckets, object storage, and log sinks (S3 object lock, Azure immutable storage).
• Take snapshots of VM instances and container state (EBS snapshots, GCP disk snapshots).
• Export and archive logs: CloudTrail, CloudWatch Logs, GCP Cloud Logging exports, Azure Monitor, CDN edge logs. Tool rationalization helps here — cut noise and ensure the right sinks are configured: tool sprawl rationalization.
• Collect CDN artifacts: edge logs, config versions, WAF logs, and RayIDs (Cloudflare) or EdgeRequestID (Akamai).
• Preserve social/SaaS artifacts: API request/response logs, webhook payloads, and platform status announcements. If you rely on mobile/webhook capture patterns, review on-device capture strategies: on-device capture & live transport.
• Record network state: BGP route captures, routeview snapshots, and firewall ACLs.

5) Vendor-specific evidence collection quick commands

Include these commands in your runbook. Adapt IAM roles and permissions for least privilege.

AWS

• CloudTrail: export CloudTrail logs to S3 and enable object lock
• CloudWatch Logs: create an export task to S3
• EBS snapshot: aws ec2 create-snapshot --volume-id vol-XXXXX --description "incident-snapshot-INC-..."
• EC2 instance metadata & instance console logs capture

GCP

• Cloud Logging: export to Cloud Storage or BigQuery with retention lock
• Persistent Disk snapshot: gcloud compute disks snapshot DISK --snapshot-names=INC-...

Azure

• Export Azure Monitor logs to storage account with immutable policy
• Disk snapshot: az snapshot create --resource-group RG --source /subscriptions/.../disks/DISK

Cloudflare (CDN) / Akamai

• Export edge logs: Cloudflare Logpush to S3 / BigQuery; collect RayIDs and edge response codes — record RayIDs and edge artifacts alongside your trace IDs for correlation. See edge-first tooling guidance at edge-powered strategies.
• Capture config version and recent edge rules/worker deployments
• Collect WAF events and firewall rule changes

Social platforms / SaaS

• Request API logs and archive webhook request bodies
• Preserve platform status pages and support ticket IDs

6) Root Cause Analysis (RCA) framework

Use a layered approach to separate the primary root cause from contributing and latent conditions.

1. Immediate cause: the event that directly created the outage (e.g., CDN config invalidated token validation).
2. Contributing factors: what allowed the immediate cause to have a large impact (e.g., lack of multi-CDN failover, autoscaling limits).
3. Latent conditions: organizational or process gaps (e.g., rollout review skipped, insufficient incident runbook).

RCA techniques:

• Five Whys for quick causal chains.
• Fault-tree analysis to map combinations of failures across systems.
• Trace correlation using distributed tracing (OpenTelemetry) to link frontend errors to backend failures; propagate trace IDs across CDN → origin → third-party calls and instrument edge logs accordingly. For edge AI and observability patterns, see edge AI & observability.

7) Example RCA (concise)

1. Observed symptom: 50% of requests return 502 at the edge.
2. Immediate cause: CDN edge rejects origin responses due to invalidated origin authentication header after a token rotation rollout.
3. Contributing: Cloud autoscaling delayed due to control-plane throttling in region; origin capacity insufficient, increased error rate.
4. Amplifier: Social platform webhooks retried aggressively (429 backoff missing) flooding origin and increasing error rate.
5. Latent: No pre-rollout test for token expiry across CDN edge clusters; runbook lacked multi-CDN failover steps.

8) Mitigations and corrective actions (short- and long-term)

Prioritize actions by impact and implementation effort. Use the following categories: Immediate (0–4 hours), Short-term (1–7 days), Long-term (30–90 days).

• Immediate
  • Revert CDN config rollout; fallback to previous origin auth token.
  • Apply circuit breaker on social webhooks to cap retry storms.
  • Enable backup CDN via DNS failover or service mesh.
• Short-term
  • Increase origin capacity and tune autoscaling thresholds; validate control-plane health checks.
  • Implement synthetic tests that validate auth tokens across edge clusters before rollout.
  • Negotiate accelerated remediation with CDN vendor and request detailed edge logs.
• Long-term
  • Adopt multi-CDN architecture and automated traffic steering with chaos testing of failover — include vendor failover scenarios in chaos runs and edge tests guided by edge-powered strategies.
  • Implement strict SLOs for third-party dependencies and embed SLAs into vendor contracts with remediation clauses. For playbook-level vendor responses, review enterprise incident playbooks such as the enterprise playbook.
  • Harden runbooks: playbooks for cross-service outages, plus forensic evidence preservation checklists.

9) SLA review and vendor follow-up

After containment, evaluate SLA credits and vendor remediation plans. Include:

• Timeline of vendor status announcements vs. customer impact window.
• Evidence package for SLA/requested credit (logs, traffic graphs, customer complaint volume).
• Requested vendor actions: detailed RCA, patch timelines, and edge configuration rollbacks.
• Contractual review: update contracts to include evidence delivery requirements and runbook access for enterprise support.

10) Regulatory and legal considerations (2026 updates)

In 2025–2026 legislation and precedent emphasized timely cross-border preservation for e-discovery and regulator requests. Immediate legal steps:

• Engage legal to issue preservation notices to vendors and partners.
• Log chain-of-custody: document who exported which artifact, when, and where it was stored (immutable storage recommended).
• Consider forensic hashing of snapshots/log bundles (SHA256) and store hashes in a separate, tamper-evident ledger. For automation around evidence collection, consider building runbooks that trigger automated collectors described in the devops playbook: micro-apps & DevOps playbook.

11) Communication plan and post-incident reporting

Clear, timely communication reduces repeated load on incident responders. Use this cadence:

1. Initial incident advisory within 30 minutes with impact, scope, and ETA for next update.
2. Technical update every 1–2 hours during P1 with key troubleshooting actions and customer mitigation steps.
3. Postmortem published within 7 business days (technical) and an executive summary for customers within 48 hours.

12) Lessons learned / blameless review checklist

• Did rollout gating and pre-deploy tests catch token expiry across all edge clusters?
• Were alerting and SLOs tuned to detect degradation before full outage?
• Was vendor escalation effective? How can SLAs be improved?
• What automation will reduce manual rollback time?

13) Reproducible artifacts to attach to the postmortem

• Canonical timeline CSV (timestamp,event,source,artifact_id,confidence)
• Log bundle archive (with SHA256 hash and manifest)
• Snapshots and disk image references
• Configuration diffs (pre/post rollout)
• Vendor communications and support ticket IDs

14) Automation & tooling recommendations (2026 advanced strategies)

Reduce mean time to remediate with these practices:

• Immutable telemetry pipelines: forward all logs to a centralized, write-once store (S3 with object lock or equivalent).
• Automated evidence collectors: use Lambda/GCF Functions to snapshot logs/configs on incident trigger — automate collectors using patterns from a pragmatic devops playbook: micro-apps & DevOps.
• Distributed tracing across CDN → origin → SaaS: propagate trace IDs and ensure edge logs capture them; link traces back to edge observations and RayIDs using edge-focused tooling described in edge-powered strategies.
• Chaos tests that include vendor failover: run scheduled failovers of CDN and social API dependencies in pre-prod to validate runbooks.
• AI-assisted RCA triage: use anomaly detection to surface most-likely root-cause clusters — platforms exposing explainability APIs and model outputs can help; see live explainability APIs, but always validate model outputs manually.

15) Template: Ready-to-copy postmortem skeleton

Use the following skeleton in your internal documentation system or issue tracker.

1. Incident ID & Summary
2. Impact & Scope
3. Short Timeline (executive)
4. Detailed Timeline (investigator)
5. Evidence Collected (artifacts + storage locations + hashes)
6. Root Cause Analysis (Immediate / Contributing / Latent)
7. Mitigations (Immediate / Short / Long)
8. SLA Review & Vendor Actions
9. Regulatory & Legal Notes
10. Communications Log
11. Lessons Learned & Action Items (owners & due dates)

Actionable takeaways (what to do now)

1. Implement the evidence preservation checklist in your incident runbooks and test it weekly.
2. Add CDN token-validation checks in pre-deploy pipelines and synthetic tests that simulate social API webhook retries.
3. Instrument and propagate a single trace ID across CDN → origin → third-party calls to make timeline reconstruction trivial.
4. Negotiate vendor SLAs that include log export and forensic access windows — use vendor playbook patterns for escalation and evidence requests (see enterprise playbook references).

Closing notes — why this matters in 2026

Outages that span CDNs, clouds, and social platforms are increasingly common as services fragment across providers and edge compute proliferates. A repeatable, legally defensible postmortem process saves time, preserves trust with customers, and protects your organization during contractual and regulatory reviews. Use this template to move investigations from reactive triage to disciplined forensic practice.

"Fast restores are important. So is a defensible, repeatable investigation practice." — Incident Response Lead, 2025 multi-service outage review

Call to action

Use this template in your next incident review and run a tabletop exercise within 30 days. If you want a customized version tailored to your vendor mix and compliance needs, contact our incident engineering team for a 90‑minute workshop and an automated evidence-collector playbook designed for your environment.

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