What is it?
Optimising as you migrate is an approach that treats each migration wave as an opportunity to right-size resources, modernise architecture, enforce cost visibility, and embed resilience, rather than relocating workloads unchanged.
Fintechs often treat cloud migration like moving day: pack everything, relocate, sort it out later. Later rarely comes. Sandboxes stay running, logs are retained too long, experiments get promoted without budgets, and engineers inherit firefighting instead of product work.
Use this approach when planning AWS migration waves, when cloud bills are growing faster than customer revenue, or when engineering time is consumed by infrastructure maintenance instead of product delivery.
Why it matters
Risks
- Workloads migrated without right-sizing inherit legacy inefficiencies at consumption pricing, making cost growth outpace revenue.
- Manual infrastructure processes introduce drift and slow recovery when incidents occur in the new environment.
- Without tagged cost attribution, finance and engineering cannot distinguish healthy growth from waste.
Costs
- Idle resources, oversized databases, and environments without owners quietly accumulate charges that fund nothing.
- Savings Plans or Reserved Instances purchased before understanding workload behaviour lock spend against volatile demand.
Operational impact
- Teams without automation rebuild environments manually, creating inconsistencies between development, staging, and production.
- Untagged resources make anomaly investigation slow because nobody can identify which product or team caused the spike.
Strategic impact
- Executives stay patient when they see tagged unit economics, rehearsal-backed resilience, and a quarterly cadence after go-live.
- POPIA, FSCA, and FIC alignment is easier to embed while architecture is still flexible than after design decisions lock.
Five phases to optimise during migration
Audit and right-size before the first wave
- Inventory idle resources, undersized databases pretending to be oversized, and environments nobody owns.
- Pair AWS Cost Explorer, Budgets, and Auto Scaling with honest demand curves so finance and engineering read the same chart.
- Automation keeps spend predictable and performance consistent while you still have runway to fix mistakes cheaply.
Modernise architecture, not only the address
- Containerise services with AWS ECS or EKS to isolate blast radius and speed deployments.
- Use serverless patterns such as Lambda and EventBridge for bursty work so you pay for execution, not idle capacity.
- Adopt infrastructure as code with CloudFormation or Terraform so every rebuild is repeatable evidence.
Tag everything and model spend
- Tag workloads by team, environment, and purpose so every rand traces to a business owner, not a shared mystery bucket.
- Model steady versus intermittent load before purchasing Reserved Instances or Savings Plans.
- Predictable spending unlocks predictable growth conversations with finance and the board.
Embed resilience and compliance while architecture is flexible
- Design multi-region backups, clear RTO and RPO, quarterly failover drills, and regulatory alignment during migration when change is expected.
- POPIA, FSCA, and FIC controls embedded early avoid the expensive retrofit that blocks audit cycles later.
- Treat failovers like fire drills: if they feel boring, you are doing them right.
Measure after cutover and keep iterating
- Track deployment frequency, cost per transaction, incident recovery time, and audit cycle length after go-live.
- Continuous monitoring through CloudWatch and observability partners keeps the stack honest once the programme spotlight moves on.
- Quarterly cost and capacity reviews turn migration lessons into a living roadmap instead of a one-off project memory.
Common mistakes
Carrying broken furniture into the new house
Consequence: Legacy patterns, idle capacity, and unowned environments inherit AWS pricing without any improvement in capability or observability.
Avoidance: Treat each migration wave as a right-sizing opportunity and retire waste before workloads depart the legacy environment.
Buying commitments before understanding demand
Consequence: Reserved Instances or Savings Plans lock spend against volatile demand, and unused capacity becomes sunk cost.
Avoidance: Baseline utilisation with real demand curves, separate steady from burst workloads, and purchase commitments only after one billing cycle of data.
Deferring tagging to a post-migration cleanup project
Consequence: Cost anomalies arrive in the invoice instead of sprint reviews, and no one can attribute the spike to a product, team, or experiment.
Avoidance: Enforce mandatory tags at provisioning time as a gate, not a follow-up task.
Optimising only during the migration programme window
Consequence: Savings decay as new workloads, experiments, and team changes introduce the same patterns the programme addressed.
Avoidance: Establish a quarterly review cadence with engineering, finance, and product that outlives the programme.
Best practices
- Every migration wave exits cleaner than it enters, with measured waste reduction.
- Right-sizing decisions are backed by at least one billing cycle of utilisation data.
- Containers or serverless are evaluated for each workload based on traffic pattern, not only familiarity.
- Infrastructure is defined in code with version control and automated promotion.
- Tags are enforced at provisioning time for workload, owner, environment, and cost centre.
- Resilience is tested with scheduled failover drills, not only documented in plans.
- Post-cutover metrics (deploy frequency, unit cost, recovery time, audit duration) are tracked beyond launch.
- Quarterly reviews include engineering, finance, and product in the same forum.
How to get started
- Audit current workloads for idle capacity, oversized resources, and unowned environments.
- Right-size resources using utilisation data and configure Auto Scaling for variable demand.
- Define a tagging taxonomy and enforce it as a provisioning gate.
- Evaluate container (ECS/EKS) and serverless (Lambda) patterns for each workload type.
- Establish infrastructure as code for all environment tiers with automated promotion.
- Schedule quarterly cost and capacity reviews with engineering, finance, and product representation.
If migration is already underway, start with the next scheduled wave and apply right-sizing and tagging as entry criteria. If planning has not started, run an AWS Cost Optimisation Assessment to quantify the opportunity before sequencing waves.
How KineticSkunk helps
KineticSkunk helps South African fintechs treat migration as a modernisation opportunity, wiring cost visibility, automation, and resilience into each wave so savings fund the next phase of growth.
Teams gain lower running costs, faster releases through containers and IaC, rehearsal-backed resilience, and a quarterly rhythm that keeps improvements compounding.
Do not carry old inefficiencies into a new cloud bill. Treat your move to AWS as a chance to reimagine how your fintech runs. Start a conversation with KineticSkunk when you want hands-on help optimising as you migrate. Explore more of the Cloud Without Chaos series or the Cloud Without Chaos campaign for further guidance.
Frequently asked questions
Architecture is already in motion during migration. Right-sizing, tagging, and modernisation are cheaper to implement while workloads are being rebuilt than as a separate retrofit programme on live infrastructure.
Right-sizing means matching resource allocation (compute, memory, storage) to actual utilisation patterns rather than peak assumptions. It uses demand data to select instance types, configure auto-scaling, and retire idle capacity.
Not necessarily. Containers suit services that benefit from isolation, consistent deployment, and horizontal scaling. Bursty event-driven workloads may suit serverless patterns. Evaluate each workload against its traffic pattern and team capability.
Establish a quarterly review cadence with engineering, finance, and product. Track unit cost metrics, investigate anomalies, and treat cost optimisation as a continuous practice rather than a one-off project.
IaC makes environments repeatable, diffable, and auditable. Teams can destroy and rebuild non-production environments on schedule, eliminate configuration drift, and promote changes through governed pipelines that prevent accidental oversizing.
