Personal blog — thoughts and experiences, not employer-related. Disclaimer

DR. ATABAK KH

Cloud Platform Modernization Architect specializing in transforming legacy systems into reliable, observable, and cost-efficient Cloud platforms.

Certified: Google Professional Cloud Architect, AWS Solutions Architect, MapR Cluster Administrator

Personal content — not employer-related. This article is published in a personal capacity and shares thoughts and experiences based on public industry patterns — not a description of employer or client systems, and not professional instructions. It does not reflect the views, systems, projects, or policies of any current or past employer, client, or financial institution. See the full site disclaimer.

Takeaway: You can cut cost and improve reliability/observability without any access to PII or raw logs. Here’s the artifact-only method I use.

Why this works

Most performance/cost failures live in patterns & policies (autoscaling, retries, retention) not in user data. So inspection needed for signals and structure, not payloads.

What to check as inputs (no PII)

  • Billing exports (GCP BigQuery export / AWS CUR)
  • IaC (Terraform modules), autoscaling & alert rules
  • Logging/metrics schemas (+ retention), aggregated charts: p95/p99, 5xx, queue lag
  • Architecture diagrams, runbooks, incident summaries (redacted)

What can be analyzed (examples)

  • Reliability: retry storms, queue lag vs consumers, DLQ policy, alert fatigue
  • Latency: p95/p99 tails, cold starts/GC signatures, saturation, query latency logs
  • Observability: missing SLIs/SLOs, noisy alerts, unbounded logs
  • Cost: wrong SKUs, mis-sizing, egress hotspots, over-retention

Example: aggregated latency schema

service, endpoint, date, count, p50_ms, p95_ms, p99_ms, error_rate

Optional: one possible way to get rough p95 from a sample table in BigQuery (no payloads)


SELECT
  service, endpoint, DATE(ts) AS d,
  COUNT(*) AS n,
  APPROX_QUANTILES(latency_ms, 100)[OFFSET(95)] AS p95_ms,
  SUM(CASE WHEN status>=500 THEN 1 ELSE 0 END)/COUNT(*) AS error_rate
FROM telemetry_samples
WHERE ts >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)
GROUP BY service, endpoint, d;

How we can help you for that

Security & GDPR stance

  • Default: no PII, no tenant access, no extraction
  • EU-only processing, NDA; DPA only if you later add tenant-only read-only
  • Notes auto-deleted <= 30 days

Deliverables you get in 2 weeks

  • Top 10 findings with screenshots/tables (aggregates only)
  • 3 Day-7 Quick Wins your team can do immediately
  • 90-day roadmap (owner, effort, impact, risk)
  • Optional SLO baseline + alert/runbook templates

Want a 1-page checklist to run this audit internally? Email me and I’ll send it.


This is a personal blog. The views, thoughts, and opinions expressed here are my own and do not represent, reflect, or constitute the views, policies, or positions of any employer, university, client, or organization I am associated with or have been associated with.

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