IrenicTech

Cloud infrastructure services.
Engineered, not rip-and-replaced.

Cloud infrastructure services by IrenicTech: AWS, GCP, and Azure architecture, infrastructure-as-code, multi-region deployments, and cost-aware engineering built to scale and stay within budget
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IrenicTech cloud infrastructure at a glance

Cloud as engineering, not procurement. Built to scale and stay within budget.

Most cloud work today is one of two patterns. A rip-and-replace migration that takes a year and ends with a worse system than what was replaced. Or an AWS reseller pushing credits and re-Architected programs as if checking boxes counted as architecture. Both ship slowly and bill heavily.

We build cloud infrastructure services as a real engineering discipline. Architecture designed for your actual workload, not a generic Well-Architected slide deck. IaC from sprint one. Cost guardrails before the first deploy. Public cloud, hybrid, or bare metal picked per the workload, not per the partner discount. Linux and the OS layer treated as engineering surface, not as something the managed service hides. Migrations phased, parity tested, reversible.

The teams we work with do not want a cloud sales presentation. They want a platform that scales when the customers arrive, costs what it should, and runs on infrastructure their engineers actually understand.

Productized engagements

Fixed-scope cloud sprints. Buyable, not negotiable.

Time-boxed, fixed-price, with a deliverable that lands as a working landing zone, a target architecture brief, or a closed cost-optimization backlog at the end of the sprint. Every sprint hands you the IaC, the runbooks, and the cost dashboards on day one.

  • For founders

    Cloud Foundation Sprint

    From zero to a production-grade AWS, GCP, or Azure account in four weeks.

    • Multi-account landing zone (Organizations, billing, audit account)
    • IaC baseline with Terraform or Pulumi, state backend in your account
    • Networking, IAM, and cost-monitoring guardrails turned on from day one
    Book a discovery call
  • For scaling teams

    Cloud Architecture Sprint

    Re-architect to scale or to cut cost. Pick the bottleneck.

    • Current-state architecture audit and cost-shape analysis
    • Target architecture (containerization, serverless, data tier, networking) for your real workload
    • Phased migration plan with parity tested before cutover and a rollback budget at each step
    Book a discovery call
  • For mature platforms

    FinOps & Cost Sprint

    Cut cloud bills without cutting capability, in six weeks.

    • Cost-attribution baseline with tagging strategy baked into IaC
    • Right-sizing, Reserved Instances and Savings Plans review, idle-resource cleanup
    • Cost dashboards by team, environment, and service, with budget alerts before the bill arrives
    Book a discovery call

Our cloud infrastructure deliverables

  • Multi-cloud architecture

    AWS, GCP, or Azure designed per workload, not per partner discount. Multi-cloud only when the use case earns the operational cost (regulated region, vendor concentration risk, true price arbitrage).

  • AWS landing zones

    Multi-account landing zone via Organizations, audit-logging to a separate audit account, security baseline, billing centralized. All IaC-managed; the console is for reading, not for clicking changes.

  • Infrastructure as code

    Terraform or OpenTofu by default, Pulumi when the team is in TypeScript or Python. State backend in your account, PR review on every change, drift detection in CI.

  • Container orchestration

    Kubernetes on EKS, GKE, or AKS when the workload justifies the operational cost. ECS Fargate or Cloud Run when it does not. The choice is made on the workload, not on resume optimization.

  • Networking & VPC architecture

    Multi-AZ for resilience, multi-region when latency or compliance demands it. Transit Gateway, VPC peering, PrivateLink, and the IAM boundaries that keep the blast radius small.

  • Cloud security architecture

    IAM least-privilege via SCPs and permission boundaries, KMS-managed encryption at rest and in transit, audit logging to a separate account, the CIS Benchmarks applied via IaC.

  • FinOps & cost monitoring

    Cost-attribution baseline with tagging in IaC, right-sizing and Reserved Instance strategy, idle-resource cleanup. Dashboards via Vantage, CloudHealth, or Cloudability; Kubecost where the workload is K8s-heavy. Budget alerts wired into Slack, PagerDuty, or Opsgenie before the bill arrives.

  • Migration & cutover

    Phased migration with the new environment built alongside the old, parity tested before any traffic shift, rollback budget documented per step. The cutover is a planned event, not a panic.

Beyond public cloud

Hybrid, bare metal, and the OS layer.

Most cloud agencies stop at the AWS console. We do the broader infrastructure work too: hybrid bridges between on-prem and cloud, bare metal where the economics or latency demand it, OS-layer tuning where managed services cannot reach. The choice of layer is made on the workload, not on what is easiest to bill for.

  • Hybrid cloud

    On-prem and public cloud, bridged with intent

    Direct Connect, ExpressRoute, or site-to-site VPN. Hybrid identity via AD and Okta. VMware Cloud Foundation bridges where the on-prem investment still pays. Data-residency-aware routing where regulation demands it. Hybrid is not a religion; we do it when latency, sunk cost, or regulation actually demand it.

  • Bare metal

    Dedicated hardware where economics or latency rule out public cloud

    Hetzner, OVH, Equinix Metal, or on-prem hardware for workloads where the public-cloud premium stops making sense: high-throughput databases, GPU clusters, HPC, latency-sensitive trading, certain regulated workloads. Provisioned with Terraform, configured with Ansible, monitored with the same stack as the cloud side.

  • Linux & OS-layer depth

    The operating system is not a black box we ignore

    Kernel-parameter tuning where the workload demands it. Custom AMIs and base images for the running environment you actually want. systemd units written by engineers who know what they do. eBPF for observability at the OS layer. Most cloud agencies stop at the container; we keep going where the workload needs us to.

Reseller architecture vs engineered cloud

Why most cloud projects ship slowly and bill heavily.

Two ways to ship cloud infrastructure. One scales with the customers and costs what it should. The other is a rip-and-replace project sold by someone with a partner-tier quota to hit.

The default pattern

Reseller architecture

Credits, partner programs, and Well-Architected slides as the deliverable. Ships slowly, bills heavily, and the architecture serves the seller’s quota.

  • AWS-reseller architecture: someone sold you credits and called it a re-Architected program.
  • Rip-and-replace migration that takes twelve months and ships a worse system than what was replaced.
  • Console-clicked infrastructure: nobody owns it, nobody can reproduce it, the audit trail is a screenshot.
  • Multi-cloud because the partner program said to; operational cost is double, the benefit is theoretical.
  • Cost optimization is 'we will fix it after we launch'; the bill arrives, the panic starts.
  • Kubernetes adopted because the deck said to. Two engineers know how it works; both are looking for new jobs.

How we ship

IrenicTech engineered cloud

Architecture designed for the workload, IaC from sprint one, cost guardrails before deploy, phased migrations with rollback budgets, no partner kickbacks.

  • Architecture designed for your actual workload, with slides as a side effect of the work, not the deliverable.
  • Phased migrations with the new environment built alongside the old, parity tested before any traffic shift.
  • Infrastructure as code from sprint one; every change goes through PR with drift detection in CI.
  • Multi-cloud only when the workload genuinely earns the operational cost (regulated region, vendor concentration).
  • Cost guardrails before the first deploy: tagging in IaC, budget alerts, right-sized defaults, reservation strategy.
  • Kubernetes only when the workload justifies the ops cost; PaaS, Fargate, or Cloud Run when it does not.

Where engineered cloud earns its place.

  1. 01 · SaaS startup

    First production cloud architecture

    Move from 'Heroku and a spreadsheet' to a real AWS or GCP account with multi-account landing zone, IaC baseline, IAM least-privilege, and cost monitoring. The architecture your second engineering hire can actually inherit.

    See our SaaS Platforms practice

  2. 02 · Scale-up

    Re-architecture before the bill or the latency curve breaks

    The MVP architecture worked at 100 tenants. At 10,000 it does not. Target architecture designed before the next quarter's bill or the next product launch, with a phased migration plan that does not stall the roadmap.

  3. 03 · Compliance

    Compliance-aware cloud landing zone

    Multi-account AWS with audit-logging to a separate account, security baseline applied via IaC, PHI and PCI scope boundaries baked into the deploy gate. Compliance is enforced by the architecture, not by the policy doc.

    See our Security & Compliance practice

  4. 04 · Resilience

    Multi-region active-active for a B2B SaaS

    Active-active across two AWS regions with expand-and-contract database migrations and a blue-green cutover pattern. Region failover from primary to secondary measured in minutes, not in panic.

  5. 05 · AI platform

    GPU and model-serving infrastructure

    Burstable GPU pools, model artifact storage with versioning and lifecycle, eval pipeline infrastructure, per-model cost attribution. The cloud architecture AI workloads actually need.

    See our AI Native practice

  6. 06 · FinOps

    Cloud cost cutting without capability loss

    Cost audit, right-sizing, Reserved Instance and Savings Plans strategy, idle-resource cleanup, cost dashboards by team and service. Typical savings on bloated bills: thirty to fifty percent, without losing capability.

Architectures we have shipped

What we have shipped into production.

A short, honest cut of cloud architecture work that landed in production for real customers. The landing zones, the migration patterns, the cost models we know work because we built and operated them.

  • Multi-account landing zone

    Regulated SaaS on AWS with audit boundaries baked into the deploy gate

    Tenant-isolated accounts via Organizations, audit-logging to a separate audit account, security baseline applied via IaC, automated SOC 2 evidence collection. The compliance posture is the architecture, not an afterthought.

  • Multi-region active-active

    Two-region B2B platform with expand-and-contract migrations

    Active-active deployment across us-east-1 and eu-west-1, expand-and-contract schema migrations, blue-green cutover pattern. Region failover from primary to secondary measured in minutes; ten-minute incident, not an hour-long outage.

  • Heroku to AWS migration

    Phased cutover from Heroku to AWS ECS Fargate over six weeks

    New environment built alongside the old, parity tested before any traffic shift, traffic moved in phases with a rollback budget per step. Cloud cost dropped sixty percent in the first quarter; the new engineering hires inherited infrastructure they could read in a sitting.

  • GPU and model serving

    Burstable GPU pools for an AI platform with per-model cost attribution

    Auto-scaling GPU pools on AWS, model artifact storage in S3 with versioning and lifecycle policies, eval pipelines that run on every prompt change, per-model cost attribution baked into the tagging strategy. Cost is measured per model, not per month.

  • On-prem to cloud (phased)

    Six-month phased migration from on-prem VMware to AWS for a regulated team

    Direct Connect link established first, hybrid identity bridged via AD, workloads moved one service at a time with parity tested before each cutover. Bare-metal databases kept on-prem where the I/O profile demanded it; everything else moved. Zero unplanned downtime across the migration window.

  • Cross-cloud federation

    AWS to GCP federation for an AI workload needing Vertex AI and TPUs

    Workload split across AWS (existing application tier, customer data, S3) and GCP (Vertex AI training, TPU access, BigQuery analytics). Cross-cloud networking via Interconnect, IAM federation via workload identity, cost attribution tracked across both clouds in a single dashboard.

Voice of the customer

From platform leads running the cloud after we leave.

  • “The architecture brief alone changed how our engineering team thinks about cost. Six months later our AWS bill is forty percent lower, the platform is faster, and we did not lose a single capability in the process.”

    Lukas Brennan

    Head of Platform, Stoneheath Networks

  • “The Heroku-to-AWS migration finished on time, under budget, with zero customer-facing downtime. The infrastructure our new hires inherited reads like documentation, not archaeology.”

    Calla Whitmore

    CTO, Greythorn Logistics

  • “The FinOps sprint paid for itself in the first month. Reservation strategy alone saved us seventy thousand a year, and the cost dashboards mean we catch overspending before the bill arrives.”

    Otis Pemberton

    VP Engineering, Mossbridge Analytics

How we ship cloud infrastructure engagements.

Six steps from first call to a production architecture your team operates without us. The target-architecture review gates any production work; the handover comes with documentation, not promises.

  1. 01

    Discovery & architecture audit

    Current state, workload shape, cost shape, regulatory constraints, customer commitments. One-page brief and a prioritised remediation or migration backlog. No production changes yet.

  2. 02

    Target architecture

    Architecture diagram, cost model, networking and IAM strategy, data tier, IaC layout. Reviewed with your team before any production changes land.

  3. 03

    IaC baseline

    Terraform or Pulumi modules for the target environment. Tested with plan against a real account, pull-request flow, drift detection in CI, state backend that lives in your cloud account.

  4. 04

    Phased build & migration

    New environment built alongside the old, parity tested, traffic shifted in phases with a documented rollback budget per step. Migrations are planned events, not panics.

  5. 05

    Cost & observability

    Cost tagging baked into IaC, budget alerts, cost dashboards by team and service. Logs, metrics, traces wired in. The cost trajectory and the failure modes are both visible from day one.

  6. 06

    Handover & retainer

    Your team owns the architecture after handover. We document the IaC and runbooks. Optional retainer for ongoing architecture evolution, FinOps maintenance, and incident response backstop.

The frameworks we architect to.

The standards we measure ourselves against, and the ones we engineer into the architectures we hand off. Designed in from sprint one, not retrofitted before the first audit.

Architecture audits and FinOps reviews available as standalone engagements. Bring your current state, leave with a prioritised remediation backlog and a cost model that holds up.

Common questions, answered.

  • How long does a cloud engagement take?

    Cloud Foundation Sprint: four weeks to a production-grade landing zone. Cloud Architecture Sprint: six to twelve weeks depending on scope. FinOps & Cost Sprint: six weeks with ongoing cost guardrails handed to your team. Full multi-phase migration: twelve to twenty-four weeks. Ongoing: monthly retainer for architecture evolution and incident response.

  • What does a cloud engagement cost?

    Price varies with the scope of the work. The productized sprints are fixed-price for the scope they cover. A full architecture and migration engagement is quoted after the discovery call, with the number driven by current state, target architecture, regulatory constraints, migration complexity, and ongoing operational commitments. The discovery call itself is free; you accept the estimate or you do not.

  • AWS, GCP, or Azure: which?

    AWS by default for B2B SaaS (deepest service catalog, mature compliance posture, biggest hiring pool). GCP for AI workloads where Vertex AI or TPU access materially changes the cost model, or when BigQuery is the natural data tier. Azure when procurement insists, the customer base is Microsoft-heavy, or AD integration is the operating reality. Multi-cloud only when the workload genuinely earns the operational tax.

  • Should we adopt Kubernetes?

    Only when the workload justifies the operational complexity. PaaS (Heroku, Render, Fly.io), AWS ECS Fargate, or Google Cloud Run handle the majority of B2B SaaS workloads with a fraction of the ops overhead. Kubernetes is the right call when per-tenant isolation, regulated regions, GPU scheduling, or per-second cost optimization actually matter, not because a conference talk said it should.

  • Do you do rip-and-replace migrations?

    No. Rip-and-replace migrations take twice as long, cost three times as much, and end with a worse system than what was replaced. We do phased migrations: build the new environment alongside the old, parity test before any traffic shift, move traffic in phases with a documented rollback budget per step.

  • Will you sell us AWS credits or partner discounts?

    No. We are not an AWS reseller and we do not take partner kickbacks. The architecture we ship is the one your workload actually needs, with the cost model that fits your bill. The credit conversation happens directly with AWS or with the reseller of your choice; that is not the work we are doing for you.

  • Can you help us cut our cloud bill?

    Yes, the FinOps & Cost Sprint is built for this. Typical savings on bloated cloud bills: thirty to fifty percent without losing capability. The win is in right-sizing, Reserved Instances and Savings Plans, idle-resource cleanup, and the cost dashboards that prevent the next round of bloat. Cost is treated as an engineering metric, not a finance team's complaint.

  • Do you do hybrid cloud, bare metal, or on-prem work?

    Yes, all three. Hybrid bridges (Direct Connect, ExpressRoute, VPN, hybrid identity via AD or Okta, VMware Cloud Foundation) where the on-prem investment still pays. Bare metal on Hetzner, OVH, Equinix Metal, or on-prem hardware for workloads where the public-cloud premium stops making sense (high-throughput databases, GPU clusters, HPC, latency-sensitive trading). Linux and OS-layer work (kernel tuning, custom AMIs, eBPF, systemd) where the managed-service abstraction does not reach. We pick the layer per the workload, not per what is easiest to bill for.

  • What is your stance on multi-cloud?

    Skeptical unless you have a real reason. Multi-cloud is operationally expensive and most 'multi-cloud benefits' (vendor leverage, disaster recovery) can be achieved with single-cloud strategies plus a documented exit plan. We default to one cloud done well over two clouds done badly.

  • Do you handle the ongoing operations after the build?

    Your team owns operations after handover. We document the IaC, the architecture, and the runbooks. Optional retainer for ongoing architecture evolution, FinOps maintenance, incident response backstop, and the per-cloud-service updates that come with the platform. Operations belongs with your team; we are the backstop, not the SLA.

  • Who owns the IaC, the deploy keys, and the cloud accounts?

    You. From day one. Cloud accounts in your organisation, IaC in your GitHub organisation, Terraform state in your account, deploy keys in your secret manager. We push to your repos and deploy to your accounts; everything is documented in your wiki. No proprietary tooling you cannot leave; no ongoing dependency on us unless you want one.

Start a conversation

Tell us what you’re building.

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What happens next

  1. We reply within 4 hours, from a real person, not an auto-responder.
  2. A short scoping call to understand the goal, constraints, and timeline.
  3. A fixed-scope discovery sprint: a working prototype and a written estimate.
Email
[email protected]
Phone
+1 504 732 9446
Office
Austin, TX, United States
Hours
Mon–Fri · Async + scheduled calls

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