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Cloud Consulting

Cloud that's secure, observable, and cost-aware from the first commit — not the first audit.

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Overview

Cloud is easy to start. Hard to run well.

Most cloud estates we walk into share the same three problems: a sprawl of accounts and projects with no consistent guardrails, infrastructure built by click-ops instead of code, and a bill that keeps going up faster than the business it supports. The fix isn't a re-platform. It's an operating model.

We engage against the AWS Well-Architected Framework and its Azure / GCP equivalents — building landing zones, modernizing workloads, and setting up the FinOps and SRE practices that make cloud a durable advantage rather than a recurring surprise. Every recommendation maps back to one of the six pillars: operational excellence, security, reliability, performance, cost, and sustainability.

We've built multi-account AWS landing zones for healthcare workloads (HIPAA, HITRUST) and high-throughput data platforms for retail intelligence — so we treat your auditor and your CFO as first-class users from day one.

Engagement at a glance

  • 6-week landing zone build
  • 100% IaC — no console drift
  • FinOps from day one, not year two
  • AWS, Azure, GCP — pragmatic, not religious

30–50%

Infra cost reduction at maturity

6 weeks

Production-ready landing zone

99.95%

Target availability for tier-1 workloads

6 pillars

Well-Architected, every review

What we deliver

From strategy to a cloud your engineers and finance team both trust

Cloud Strategy & Migration

TCO modeling, the 6 Rs (rehost, replatform, refactor, repurchase, retain, retire), and a wave-plan with clear exit criteria. No "lift and pray".

Landing Zones

Multi-account / multi-subscription structure, IAM, networking, logging, guardrails, baseline controls — built in Terraform, version-controlled, drift-free.

Workload Modernization

Containers (Kubernetes / ECS / Cloud Run), serverless (Lambda / Functions / Cloud Run), and event-driven re-architecture for workloads where it earns its keep.

FinOps

Tagging strategy, showback / chargeback, reserved & savings plans, anomaly detection, and the engineering culture that makes unit cost a first-class metric.

SRE & Observability

SLOs and error budgets that actually drive decisions; OpenTelemetry across logs, metrics, traces; runbooks & on-call rotations that don't burn the team out.

Disaster Recovery

RPO/RTO modeling, multi-region designs, regular game-days. Backups that have actually been restored, not just scheduled.

How we work

A phased, outcome-driven approach

01
Assess

Workload & cost baseline

02
Design

Landing zone & target arch

03
Migrate

6 R's, wave by wave

04
Optimize

Right-size, reserve, refactor

05
Operate

SLOs, FinOps, on-call

Frameworks & tools

Hyperscalers, the IaC and platform layer above them

AWS

Well-Architected Partner

Azure

CAF-aligned

GCP

Cloud Adoption Framework

Terraform / Pulumi

IaC, end-to-end

Kubernetes

EKS, AKS, GKE

Argo / Flux

GitOps

OpenTelemetry

Vendor-neutral observability

FinOps Foundation

FOCUS-aligned reporting

Outcomes

What good looks like

Unit cost

Cost per request / per tenant

MTTR

Sub-hour for tier-1 services

Deploys

From weekly to many-per-day

Audit posture

Continuous evidence, not crunch

FAQ

Common questions

Multi-cloud has a real cost — duplicated tooling, harder hiring, looser security baseline. Most companies are better off picking one as primary and using a second for specific workloads (e.g., a BI stack on BigQuery, an EHR on AWS). Multi-region on one cloud usually beats one region across two.

The account / subscription structure, identity federation (SSO + IAM roles), networking (VPCs/VNets, transit, DNS, egress), logging and audit (CloudTrail / Activity Log + central S3/Storage), guardrails (SCPs / Azure Policy / Org Policies), baseline security tooling, and a CI/CD path that uses all of them. Workloads land on top of this, not around it.

Both, in waves. Lift-and-shift compounds your data-center exit; refactor where the workload's economics or velocity warrant it. We classify workloads by business value and architectural fit, then sequence so each wave's savings funds the next.

First wave (tagging, right-sizing, reserved/savings-plan coverage, idle-resource cleanup) usually returns 15–25% in the first quarter and pays for the engagement many times over. The second wave (architectural moves like autoscaling, storage tiering, serverless conversion) takes longer and compounds.

Industries we apply this in

Other services that often pair with this

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Cloud bill not behaving? Audit looming?

A focused conversation about your estate and where the next 25% of cost — or risk — is hiding.