Cloud-native, with the run discipline to make it pay.
Cloud is an operating model, not a hosting decision. We do the strategy, the migration, and the platform engineering that makes the cloud bill, the release cadence, and the reliability targets all move in the right direction.
Outcomes we are accountable to
- Predictable cloud spend with workload-level attribution
- Faster release cycles via platform self-service
- Resilience targets met through SRE practices
Problems we solve
When teams call us in.
- 01A cloud migration that moved the bills up but left the architecture coupled the same way as before.
- 02Multiple AWS / Azure / GCP accounts with no landing-zone discipline, no cost attribution, and no platform team.
- 03Lifted-and-shifted workloads sitting on EC2 and never refactored toward managed services or containers.
- 04A cloud cost that gets attention only at quarter-end, by people who have no levers to change it.
Methodology
The Dezynum Cloud Realization Model
- Phase 1
Assess
Discovery of workloads, dependencies, and current cloud posture. Output is a target landing zone and a sequenced migration plan.
- Phase 2
Design
Reference architectures for the target state — landing zones, networking, IAM, observability, and the platform layer that everything else sits on.
- Phase 3
Migrate
Wave-based migrations with workload-level reconciliation, application owners, and rollback paths. Cutover is a decision, not a guess.
- Phase 4
Operate
A run model with FinOps, reliability engineering, platform self-service, and continuous modernization built in. The cloud bill stays a daily conversation, not a quarterly fight.
Capabilities
What we deliver inside this practice.
Cloud strategy and landing zones
Decide what runs where, why, and what the operating model around it looks like. Landing zones are designed once, used for years.
Migration to containers and serverless
Re-platform and re-architect workloads where the math justifies it. Lift-and-shift only when the destination is a stepping stone.
Hybrid and multi-cloud operating models
Most enterprises are hybrid by accident. We make hybrid an explicit design choice with the operational practices to back it.
FinOps and cost engineering
Workload-level cost attribution, automated rightsizing, anomaly detection, and a culture where cost is everyone's problem — not finance's.
Site reliability and platform engineering
SLOs, error budgets, runbooks, and the internal developer platform that makes "doing the safe thing" the easy thing.
Typical pod
Who actually shows up to do the work.
- Cloud architect
- Platform / SRE engineer
- Application engineer
- Security engineer
- FinOps practitioner
Time to value
Realistic timelines, not sales-deck timelines.
Landing-zone v1 in 4–8 weeks. First migrated workload in production within 12 weeks.
Ecosystem we work with
Technologies and platforms we have engineering depth in.
We do not list logos for partnerships we do not formally hold. The list below reflects platforms we have built and run on, not vendor relationships.
- AWS — landing zones, ECS, EKS, Lambda, RDS, Aurora
- Azure — Landing Zones, AKS, App Service, Functions
- Google Cloud — Cloud Run, GKE, BigQuery
- Kubernetes, Helm, Argo CD
- Terraform, Pulumi, AWS CDK
- Datadog, Grafana, OpenTelemetry
Industry context
How this service shifts by industry.
Banking & Financial Services
Cloud in BFSI prioritizes compliance, data residency, and resilience. Landing zones are designed around regulator-readiness.
Retail & Consumer Goods
Peak-handling and elasticity drive the architecture. The cloud bill scales smoothly across the year.
Healthcare & Life Sciences
Clinical workloads need uptime and audit trails. We design for both, including the parts auditors actually look at.
Engagement models
How clients buy this work.
Cloud readiness assessment
Two to four weeks of senior cloud and platform time. Output: target landing zone, migration plan, FinOps baseline.
Sequenced migration program
Wave-based migrations across multiple quarters. Outcomes-based commercials tied to migrated-workload milestones.
Cloud platform managed service
Long-horizon run engagement covering platform engineering, SRE, and FinOps. The same engineers stay close to the system.
Frequently asked
Questions we tend to get.
Engineering perspectives
Reading from the work.
Lineage Without Decision State Fails Audits
Your registry can prove a model existed. It cannot prove what an approver reviewed before clicking approve. That gap surfaces during the first serious audit, six months after the promotion, when nobody in the room can reconstruct the screen the approver saw. Here is the record-design fix.
Your Registry Cannot Reconstruct the Approver's Screen
Six weeks after a credit model goes live, an auditor asks what the approver actually saw before clicking approve. The registry has the artefact, the metrics, the dataset hash. None of that reconstructs the screen. This is a recording discipline problem, not a tooling one, and the fix is a separate immutable record of decision state.
The Approval Click Needs Its Own Event
Your model registry knows the version, the metrics, and the dataset hash. It does not know what the approver was looking at when they clicked approve. Six months later, that is the gap an auditor will sit in. Here is the event you should have been writing all along, and what belongs inside it.
Where this matters most
Related industries
Bring us the system, the constraints, and the timeline.
Most engagements start with a working session — not a sales pitch. We will be back to you within two business days, with a senior engineer or partner on the call.
- For RFPs and assessmentsrfp@dezynum.com
- Direct linehello@dezynum.com