AWS Cloud
Moving a workload to the AWS cloud does not automatically make it cheaper, faster, or more reliable. It only does those things when the architecture matches the workload and the operational model matches the team.
AWS cloud architecture, delivery, and operations for agencies and their clients in Australia, the UK, and Singapore.
What AWS Cloud Adoption Actually Involves Beyond Provisioning a Server
A company moves to AWS. A developer provisions an EC2 instance, copies the application across, points DNS at the new IP address, and declares the migration complete. Six months later the monthly bill is three times the old hosting provider. The instance runs at eight percent CPU, there are no backups, and the security group allows inbound access on every port. The application is on the cloud. It is not benefiting from it.
Adoption that delivers the outcomes the decision was supposed to achieve involves more than moving a workload to a different location. It means selecting compute that matches the request pattern, designing the network so only intended traffic reaches the application, and building operational capability so incidents are detected and resolved rather than discovered by customers. The full scope of AWS development services that produces reliable outcomes is wider than most initial engagements scope for, especially on security, operations, and cost management.
AWS Cloud Services We Design, Build, and Operate
Six AWS cloud capability areas that cover the full adoption lifecycle from architecture design through ongoing operations.
AWS Cloud Architecture and Infrastructure Design
Architecture design covers the full structural layer of an AWS cloud environment: VPC topology with subnet segmentation for public, private, and isolated workloads; compute selection across EC2, ECS Fargate, EKS, Lambda, and App Runner matched to request pattern and team capability; database tier selection across RDS Aurora, DynamoDB, and ElastiCache; and networking with ALB, CloudFront, and API Gateway. Infrastructure is delivered in CloudFormation or CDK so every resource is version-controlled and reproducible, not hand-provisioned in the console and impossible to recreate reliably.
AWS Cloud Migration from On-Premises and Hosted Environments
Migration engagements cover the full lifecycle from discovery through cutover and post-migration validation. AWS Application Discovery Service maps current workload dependencies before any infrastructure is provisioned in the target account. The 6Rs framework classifies each application: rehost, replatform, repurchase, refactor, retain, or retire. Rehost migrations use Application Migration Service for minimal-disruption lift-and-shift. Replatform migrations move self-managed databases to RDS and applications to ECS. Every workload has a documented cutover plan and a tested rollback path before the cutover window opens.
AWS Cloud Security and Network Hardening
Security covers the account-level controls that prevent misconfiguration from becoming an incident: IAM least-privilege role design, security groups allowing only necessary traffic, S3 public access blocks via Config rules, CloudTrail in all regions with tamper-resistant log storage, GuardDuty for threat detection, Security Hub for centralised findings, VPC flow logs, and KMS customer-managed keys. All security configuration is delivered as IaC so it cannot drift from the approved baseline.
AWS Cloud Cost Management and FinOps
Cost management covers the controls that prevent spend growing faster than the workload: Reserved Instance and Savings Plan analysis with modelled payback periods, rightsizing recommendations from CloudWatch utilisation data, S3 Intelligent-Tiering and lifecycle policies, cost allocation tagging via Config rules, and Cost Anomaly Detection with per-service monitors. Monthly cost reports show variance against baseline and identify the specific resources driving unexpected spend.
AWS Cloud Operations and Ongoing Monitoring
Operations cover the ongoing management layer: CloudWatch alarm coverage with thresholds tuned to observed baseline, EC2 and RDS patching via Systems Manager on a defined schedule, incident response with runbooks for the most likely failure patterns, and monthly reporting covering alarm activity, patch compliance, and cost variance. Retainers run on a fixed monthly price with defined response time commitments and a named engineer.
AWS Cloud DevOps and Continuous Delivery Pipelines
DevOps pipelines cover the delivery infrastructure: CodePipeline orchestration with CodeBuild for build and test, blue/green ECS deployment via CodeDeploy, IaC change sets reviewed before infrastructure changes are applied, ECR image scanning as a pipeline gate blocking promotion on critical CVEs, and Secrets Manager integration so credentials never appear in buildspec files. Pipelines are themselves delivered as IaC, making them as reproducible as the application infrastructure.
How We Approach AWS Cloud Engagements Differently From General Infrastructure Providers
Most cloud providers start with tooling and work backwards to the workload. They have a preferred stack and apply it regardless of whether it fits the client team. The result is environments that work according to the provider’s mental model but are difficult to extend and operate after the engagement ends. We start from the workload and the team, then select tooling that fits both.
We treat handover as part of the scope. Every AWS cloud engagement closes with client-owned infrastructure code, documented architecture decisions, and operational runbooks. The AWS Cloud Adoption Framework defines six perspectives: business, people, governance, platform, security, and operations. We raise all six during scoping. The Well-Architected Framework underpins our review process. Clients on our white-label model receive this approach under their agency brand.
Four Principles That Separate Effective AWS Cloud Adoption From a Hosting Migration
Architecture That Matches the Workload, Not the Tutorial
Security Configured Before Traffic Arrives, Not After an Incident
The most common architecture mistake is selecting a service prominent in getting-started documentation rather than one that fits the workload. A batch job does not need always-on EC2. A variable-traffic API needs different architecture to a steady-rate data pipeline. Workload characterisation identifies the request pattern, execution duration, data access model, and team capability that determine which AWS cloud services fit, before any infrastructure is provisioned.
Cost Visibility From the First Invoice, Not the Third
Security configuration added after a production environment is live costs more in every dimension than configuration built in from the start. Remediating an overly permissive security group on a live environment requires testing the change does not break application traffic. Adding RDS encryption requires a snapshot-and-restore during a maintenance window. Enabling CloudTrail after a potential incident means the evidence may not exist. Security controls configured during the build are present from the first deployment.
Handover That Leaves the Client Capable, Not Dependent
AWS cloud costs not visible from the first billing cycle produce surprises that damage client relationships. Cost allocation tagging applied from day one means every resource is attributed to the correct product or environment from the first invoice. Cost Anomaly Detection configured during build catches spend deviations before they compound. A client receiving a structured monthly cost report from month one is in a fundamentally different position from one who discovers spend has tripled three months after go-live.
An engagement that closes with a working environment but no architecture documentation, no operational runbooks, and no knowledge transfer leaves the client dependent on the provider for every subsequent change. We structure every engagement so the client team understands what was built and why, can operate it independently, and can make informed decisions about when to bring in external expertise. This approach is detailed in our agency partner program.
White-Label AWS Cloud Delivery for Digital and Marketing Agencies
Digital and marketing agencies win cloud project work that requires capabilities their teams do not carry. Bringing in a freelancer creates a delivery dependency that does not scale. Building an internal team carries salary commitment the pipeline may not justify. White-label delivery removes both constraints by giving the agency access to a full AWS engineering team operating under their brand. Agencies across Australia, the UK, and Singapore use this model to grow cloud work as a recurring revenue line without adding headcount. The agency partner program documents how the arrangement works.
Getting started requires a single conversation about the opportunities in your current client portfolio. We scope the technical requirement, estimate delivery effort, and flag risks your proposal pricing should reflect. No retainer or commitment is required to access pre-sales support. Contact us to start.
Two AWS Cloud Patterns That Look Like Progress but Create Technical Debt at Scale
The first pattern is treating cloud adoption as a hosting upgrade. A company lifts a virtual machine from a managed provider to EC2 and keeps everything else the same. The bill arrives higher because EC2 on-demand pricing for a persistent instance is not competitive with managed hosting at the same compute level. The application cannot use autoscaling or Spot capacity because it was designed to run on a server that is always on. Lift-and-shift is valid for exiting a data centre on a deadline; it is not a cost optimisation strategy.
The second pattern is multi-account sprawl with no governance. A team creates accounts as needed: development, staging, one per client, one from a proof of concept never deleted. Two years later: seventeen accounts, inconsistent IAM, no centralised billing visibility. AWS Organizations with a Landing Zone prevents this through account vending with baseline controls, service control policies, and centralised CloudTrail and Config aggregation. Both patterns are addressed in our AWS engineering work. The case studies show the outcomes.
AWS Cloud Engagement Models by Starting Point and Delivery Goal
Greenfield AWS Cloud Build
AWS Cloud Migration from Existing Infrastructure
A greenfield engagement starts from zero: account structure, network design, compute and database tier selection, security baseline, and delivery pipeline. Deliverables are agreed before work begins and priced on a fixed scope basis. The engagement closes with client-owned infrastructure code, architecture documentation, and operational runbooks. Typical timeline is four to ten weeks depending on environment complexity. The client team is involved throughout so the handover is a knowledge transfer, not a handover of something unfamiliar.
AWS Cloud Audit and Remediation
Migration engagements cover the movement of workloads from managed hosting, on-premises infrastructure, or alternative cloud platforms to AWS. The engagement begins with workload discovery and dependency mapping before any target infrastructure is provisioned. Migration approach is selected per application using the 6Rs framework. Cutover is executed with a documented plan and a validated rollback path. Post-migration validation confirms the environment is performing to the baseline from the source.
Ongoing AWS Cloud Operations Retainer
Audit and remediation engagements review an existing AWS environment against a defined set of security, operational, and cost criteria. The audit produces a findings report with each item categorised by severity and effort to remediate. Remediation is scoped as a follow-on engagement or delivered within the audit engagement for high-severity findings. Audit engagements have a fixed timeline and a defined output. They do not expand into open-ended consultancy.
Operations retainers provide ongoing management of an AWS cloud environment after project delivery: CloudWatch monitoring with tuned alarm thresholds, EC2 and RDS patching on a defined schedule, incident response with named engineers and defined response time commitments, monthly cost reporting with variance analysis, and security posture monitoring through Config and GuardDuty. Retainer scope is fixed monthly with no variable billing against ticket volume. Named engineer rather than a support queue. Available to agencies as a white-label service delivered under their brand.
How We Deliver AWS Cloud Engagements From Discovery to Operations
Phase 1: Workload Assessment and AWS Cloud Readiness Review
Phase 2: Architecture Design and Infrastructure Decision Records
The assessment phase maps the current workload: what runs where, what depends on what, what the traffic and data volume profile looks like, what the team can operate after delivery, and what compliance requirements constrain the architecture choices. Gaps between the current state and readiness become the scope of the build engagement. Workloads that are not good candidates for migration are identified now, not after infrastructure has been provisioned for them.
Phase 3: Security Baseline and Network Configuration
Architecture design produces the VPC topology, compute and database tier selection, network routing, and security group design before a single resource is provisioned in the target AWS account. Each significant architecture decision is recorded in an Architecture Decision Record with the alternatives considered and the specific constraints that drove the choice. ADRs are stored alongside the infrastructure code so future engineers understand the reasoning, not just the outcome.
Phase 4: Infrastructure Build, Pipeline, and Environment Validation
Security baseline configuration covers IAM role design, security group rules, S3 public access blocks, CloudTrail enablement, Config rule deployment, GuardDuty activation, and KMS key creation for data at rest encryption. All security configuration is delivered as IaC so it cannot drift from the approved baseline after go-live. Security Hub is configured to aggregate findings from GuardDuty, Config, and Inspector so the security posture of the AWS cloud environment is visible in one place rather than requiring separate console access per service.
Phase 5: Migration Execution or Application Deployment
Infrastructure build implements the designed architecture in CloudFormation or CDK with staging and production environments sharing the same template parameters. The delivery pipeline is built alongside the application infrastructure so the first deployment to the staging environment uses the same pipeline that will deploy to production. Cost allocation tags are applied to all resources from the first deployment so the first billing cycle produces attributable data.
Phase 6: Operations Handover, Runbooks, and Knowledge Transfer
Migration execution follows the cutover plan documented during the assessment phase, with rollback procedures validated in a dry run before the live cutover window. For greenfield deployments, this phase covers application deployment and end-to-end testing against the staging environment before production traffic is switched. Post-cutover validation confirms the AWS cloud environment is serving traffic correctly and that monitoring is capturing the expected baseline metrics.
From Discovery to a Production AWS Cloud Environment You Can Operate
Operations handover produces runbooks for each procedure the client team will own: responding to alarms, applying patches outside the scheduled window, rotating secrets, scaling the environment for planned traffic events, and escalating incidents that exceed the runbook scope. A knowledge transfer session walks the client team through the architecture, the infrastructure code, and the runbooks. All deliverables are client-owned from the first commit. Ongoing support is available through an operations retainer. Contact us to discuss how the handover structure fits your team.
AWS Cloud FAQs: Architecture, Migration, and Operations Questions Answered
Common questions about AWS cloud adoption covering architecture decisions, migration approach, security, cost management, and ongoing operations.
How is moving to the AWS cloud different from moving to a different hosting provider?
Moving to a different hosting provider swaps one server for another. Moving to AWS replaces a fixed infrastructure model with managed services, each with its own pricing model and scaling behaviour. An EC2 instance at low utilisation on on-demand pricing costs more than an equivalent VPS. A correctly architected environment with autoscaling, managed databases, and serverless compute costs less than the hosting bill it replaces and handles traffic spikes the old infrastructure could not. The outcome depends on whether the architecture was designed to fit the cloud cost model or transplanted without change.
Which AWS cloud compute option is right for our workload?
Compute selection starts with three questions: how long does a typical request take, how variable is the request volume, and what does the application need that is incompatible with a managed compute layer. Lambda suits short-duration requests with variable traffic. ECS Fargate suits containerised applications with longer request durations or WebSocket connections. EC2 suits workloads with specific instance requirements. EKS adds Kubernetes orchestration when workload density justifies the operational complexity. The correct answer depends on characterising the specific workload, not following a general recommendation.
How should AWS cloud security be configured from the start?
The minimum AWS cloud security baseline covers eight areas: root account with MFA and access keys deleted, CloudTrail in all regions with log storage in a separate account, Config rules enforcing encryption and public access, IAM roles following least-privilege with no wildcard permissions in production, security groups allowing only specific ports and sources, S3 public access blocked at the account level, GuardDuty enabled, and KMS customer-managed keys for data at rest. All of this should be in place before application traffic arrives, not added after the first compliance audit finding.
What causes AWS cloud costs to grow unexpectedly and how is it prevented?
Unexpected cost growth has four common causes: resources provisioned for testing that were never terminated, data transfer costs not modelled during architecture design, on-demand compute running continuously for workloads better suited to Reserved Instances or Savings Plans, and marketplace services enabled and forgotten. Prevention requires cost allocation tagging from day one, Cost Anomaly Detection configured to catch deviations before they compound, and a regular rightsizing review. Cost management built in from the start produces predictable bills; added after the first surprise produces catch-up work.
How long does an AWS cloud migration typically take?
Migration duration depends on three variables: the number of applications being migrated, the complexity of dependencies between them, and the migration approach applied to each. A single rehost migration for a three-tier application typically takes two to four weeks from discovery to post-migration validation. A multi-application programme covering rehost, replatform, and refactor workloads across multiple waves runs three to six months. The most common cause of delays is undiscovered application dependencies that prevent the planned cutover sequence, which is why discovery and dependency mapping happen before any target infrastructure is provisioned.
What ongoing management does an AWS cloud environment require after go-live?
A production environment requires four categories of ongoing management. Monitoring: CloudWatch alarm coverage must be maintained as the environment evolves, with thresholds adjusted as workload patterns change. Patching: EC2 operating systems and RDS minor versions require regular updates on a schedule that avoids peak traffic windows. Cost: Reserved Instance coverage needs reviewing as instance types change. Security: Config rule compliance must be reviewed and GuardDuty findings triaged. Teams covering all four categories alongside feature development consistently find that one or more areas degrades. A retainer provides a dedicated function for each without adding headcount.