Regulated fintech operations reliability, audits, and cloud efficiency.

THE ENGAGEMENT

A clear scope of responsibility.

Engagement

6 weeks, embedded delivery

Team

Platform lead, SRE, Cloud architect

Focus areas

Reliability, compliance, cost optimization

01 / THE STARTING POINT

Situation

Flexiwage is a regulated fintech platform that processes payroll advances and earned-wage access payments, with production deployed on Microsoft Azure. Growing transaction volumes and tightening compliance requirements were straining the team’s ability to maintain uptime, pass audits, and control cloud costs.

• Reliability

  No formal SLOs for payroll-critical workflows, alerting based on infrastructure thresholds rather than business impact.

• Compliance

  Manual audit evidence collection, no policy-as-code, deployment approvals tracked in spreadsheets.

• Incidents

  Reactive firefighting with no severity model, unclear ownership, and no post-incident review process.

• Cost

  Over-provisioned compute for batch payroll jobs, no per-team spend visibility, costs growing ahead of revenue.

02 / THE WORK

What we did.

• 01

  Reliability baseline & SLO architecture

  Defined service-level objectives for the payroll pipeline, payment processing, and employer-facing API — covering availability, latency, and data freshness. Rebuilt alerting around error budgets tied to business impact so the team gets a clear signal when real users are affected, not when infrastructure metrics fluctuate.

• 02

  Compliance-safe platform controls

  Introduced policy-as-code checks into the CI/CD pipeline, automated deployment evidence collection for audit trails, and added release guardrails that enforce approval gates without blocking the team’s shipping cadence.

• 03

  Incident response & recovery

  Stood up a severity model aligned to payroll-cycle impact, on-call escalation paths, and a post-incident review framework with corrective-action tracking. Delivered runbooks for the highest-risk failure modes so responders could act within minutes instead of improvising.

• 04

  Cost & capacity optimisation

  Right-sized Azure compute for batch payroll processing, eliminated idle resources across non-production environments, and introduced per-team spend dashboards with monthly review cadences — cutting cloud costs while preserving headroom for payroll-cycle peaks.

Technologies & approach (at a glance)

Microsoft Azure production estate; service-level objectives and error budgets for payroll, payments, and APIs; user-impact–based alerting; policy-as-code and deployment evidence in CI/CD; Terraform modules with policy validation; incident severity tiers, on-call escalation, and post-incident reviews; batch and environment right-sizing with per-team cost reviews.

What the team received

• SLO framework — service-level objectives for payroll pipeline, payment processing, and employer API with error-budget tracking.
• Incident operations playbook — severity model, escalation paths, runbooks for critical failure modes, and post-incident review framework.
• Compliance automation — policy-as-code in CI/CD, automated deployment evidence, and release approval gates for audit readiness.
• Infrastructure standards — Terraform modules for Azure with policy validation, environment parity controls, and release guardrails.
• Cost & capacity dashboards — per-team spend visibility, batch-job right-sizing recommendations, and monthly review cadence.
• Internal enablement workshops — hands-on sessions covering SLOs, incident response, compliance controls, and cost management.

03 / THE DELIVERY

Timeline

Six weeks from discovery to full operating-model handoff, with SLO alerting and compliance controls live by week three.

• Week 1

  Discovery & risk baseline

  Service dependency mapping, failure-mode inventory, SLO target definition, and compliance gap analysis.

• Weeks 2–3

  SLOs, alerting & compliance controls

  Error-budget alerting live, policy-as-code in CI/CD, deployment evidence automation, and incident severity model rolled out.

• Weeks 4–5

  Cost optimisation & hardening

  Batch-job right-sizing, idle-resource removal, per-team cost dashboards deployed, and incident playbooks tested in production.

• Week 6

  Embed & transfer

  Operating cadence embedded, enablement workshops delivered, and full knowledge transfer to the Flexiwage team.

04 / THE OUTCOME

Impact & ROI

Flexiwage doubled its deploy frequency while hitting 99.9% payroll-pipeline availability — the metric that directly protects revenue and regulatory standing. The 28% cloud cost reduction began paying back the engagement immediately, and automated compliance evidence cut hours of manual audit prep every cycle. Building this internally — hiring SRE and compliance engineering capacity, reworking CI/CD for audit trails, and defining SLOs for regulated workloads — would have left the platform exposed through multiple payroll cycles.

Figures shown are typical ranges for comparable work and will vary by baseline maturity, constraints, and team size.

• Payroll pipeline hardened — 99.9% availability target met and sustained through peak payroll cycles with SLO-driven reliability and proactive capacity planning.
• Faster incident recovery — 35% reduction in mean time to recovery through structured runbooks, severity-based triage, and clear escalation ownership.
• Cloud spend reduced — 28% cost saving from batch-job right-sizing, idle-resource removal, and per-team spend dashboards preventing drift.
• Shipping velocity doubled — 2× safe deploy frequency enabled by compliance-safe release guardrails and automated deployment evidence.

Measured outcomes.

• 99.9% payroll pipeline availability
• 35% MTTR reduction
• 28% cloud cost reduction
• 2× safe deploy frequency

“StationOps gave us a model our team could actually sustain. We hardened reliability and compliance without slowing product delivery.”

VP of Engineering, Flexiwage