Capabilities/Build/Cloud & Platform Engineering
BuildMicroservices · Containers · Serverless · Edge

Platforms that scale with the business, not the bill.

We design and build cloud-native platforms on AWS for organisations whose applications can no longer scale to match growth, where deployments take days, or where a monolithic architecture has become a real bottleneck. As an AWS Premier Partner, our recommendations stay objective: not every system needs Kubernetes, and not every workload belongs in cloud.

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When this is needed

Three signals that this is the right next step.

01 / Hitting the ceiling Applications can no longer scale to match user or transaction growth.
02 / Deploys are risky Deploying a change takes days and carries significant operational risk.
03 / Monolith is the bottleneck A monolithic architecture has become a real bottleneck preventing engineering from matching business speed.
Reference architecture

Edge to applications. Sitting on a real foundation.

Illustrative reference architecture. The exact services, account structure, and modernisation path are tailored to your existing estate, regulatory context, and team capability. The shape stays consistent.

01 / EDGE

Edge delivery

Akamai Secure Edge

DDoS protection

Performance & caching

02 / APPLICATIONS

Microservices & serverless

Containers on EKS

Event-driven serverless

03 / PLATFORM

Kubernetes (EKS)

Autoscaling, rightsizing

CI/CD integration

04 / FOUNDATION

AWS multi-account landing zone

Standardised baselines:

· Security baseline

· Network configuration

· Governance guardrails

· Cost & account separation

· Identity & access

05 / MODERNISATION

Strangler fig

Incremental decomposition of monolithic systems

No big-bang rewrites

EdgeEdge delivery and DDoS protection through Akamai Secure Edge. Performance and resilience close to the user, before traffic reaches your applications.
Applications & platformMicroservices on Docker and Kubernetes (EKS), with serverless for event-driven and variable traffic. Service granularity decided by team capability, not by trend.
FoundationAWS multi-account landing zone with standardised security baseline, network configuration, governance guardrails, identity, and cost separation. The platform every workload sits on.
ModernisationApplication modernisation using the strangler fig pattern , incremental decomposition of monolithic systems, never a big-bang rewrite.
Engineering principles

The platform filter. Built for scale, not sprawl.

We merge service scope and anti-patterns into one operating model so the platform is useful, governable, and realistic for the team that has to run it.

01 / SizeServices fit the team

Microservices and containers are decomposed only as far as the operating team can sustain, avoiding service proliferation that makes the platform harder to run than the monolith.

02 / ChooseWorkload-fit compute

EKS, ECS, and serverless each earn their place through workload shape, traffic pattern, and ownership needs, not because Kubernetes became the default answer.

03 / GovernLanding zone before workloads

AWS accounts start with security, network, identity, governance, and cost baselines in place, preventing greenfield account sprawl from becoming quiet technical debt.

04 / ReleaseDeploy without drama

Blue-green releases, feature flags, and canary patterns make change reversible in minutes, removing the need for weekend windows and high-risk deployment events.

05 / ModerniseIncremental over big-bang

Monoliths are decomposed through strangler fig migration, with edge delivery and protection added where it improves resilience, performance, and customer-facing continuity.

Merged platform model

Every architecture choice has to justify its operating cost.

Container platforms, serverless workloads, landing zones, edge delivery, and modernisation waves are selected around the workload and the team. Cost optimisation starts at design time, and recommendations stay objective even where AWS is the target platform.

Case studies & outcomes

Two platform engagements. Both verifiable.

01
E-commerce · promotional traffic spikes

From fixed servers to auto-scaling EKS, with cost down on normal days.

Context
An e-commerce platform faced traffic spikes during major promotional events that the existing fixed-capacity infrastructure could not absorb without overprovisioning year-round.
Before
Fixed-capacity servers sized for peak traffic. Performance was acceptable during peaks but the always-on capacity was paying a steep cost on normal days.
What we delivered
Transition to an auto-scaling EKS architecture that absorbs peak traffic during promotional events and rightsizes back down during normal operation.
Outcome
−40%Infrastructure cost on normal days
Zero downtime during peak periods. Infrastructure costs reduced by 40% on normal days.
02
Financial technology · 7-year-old monolith

Deployment frequency from 2 per month to 15 per week, no service disruption.

Context
A financial technology company operated a monolithic system more than seven years old. Deployment velocity was the binding constraint on the engineering team’s output.
Before
Manual deployment cycles produced 2 releases per month, each one a multi-hour event with end-customer service implications.
What we delivered
Incremental decomposition over 8 months using the strangler fig pattern, with blue-green deployment and feature flags enabling gradual traffic shifting.
Outcome
2/month → 15/weekDeployment frequency
Deployment frequency increased from 2 times per month to 15 times per week without service disruption to end customers.
What we do

What we do.

The services below define the scope of a Cloud & Platform Engineering engagement with ICS. Service selection is tailored per workload.

Microservices & containers
Docker, Kubernetes (EKS) on AWSService granularity sized to team capacity
What this includesContainerised microservices designed to run sustainably with the team that will operate them , not a textbook architecture.
Serverless
Event-driven serverless on AWSFor variable traffic and event workloads
What this includesServerless where the workload pattern fits , not as a default. The trade-offs are deliberate.
Landing zone
AWS multi-account landing zoneSecurity · network · governance baselines
What this includesA standardised foundation that every workload sits on, with guardrails in place before applications land.
Edge delivery
Akamai Secure EdgePerformance · DDoS resilience
What this includesEdge protection and delivery close to your users, sized to your traffic profile.
Modernisation
Strangler fig patternIncremental, never big-bang
What this includesMonolith decomposition done in waves so customer-facing service stays uninterrupted through the migration.
After we hand off
After the platform is live, you can keep ICS engaged through Managed Cloud & AI Operations for 24/7 monitoring, incident response, and continuous FinOps , or your team can take over directly. The handover decision is based on your internal capacity, not on a vendor lock-in model.
Related capabilities

Where teams go from here.

Transform

Cloud Strategy & Cost Optimization

Where the cloud target architecture and migration roadmap come from before the build starts.

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Operate

DevOps & Site Reliability

CI/CD, infrastructure as code, observability, and SRE practices that make the platform reliable in production.

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Operate

Managed Cloud & AI Operations

Ongoing monitoring, incident response, and FinOps after handover.

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Talk to us

Start with a platform assessment. Then build what matters.

If applications cannot scale, deployments take days, or a monolith is the binding constraint on engineering velocity, the next step is a structured assessment of your existing platform.

The output is a platform recommendation and a migration plan your team can execute, or that ICS can deliver. Architecture stays objective even as an AWS Premier Partner.

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Platform assessment

What the assessment covers

  • Application and workload inventory
  • Current platform architecture review with bottleneck analysis
  • AWS landing zone gap assessment against governance and security baselines
  • Modernisation plan: what to decompose, what to leave, and what to retire
  • A reference platform recommendation sized to your scale and team