AWS Solutions
The right AWS solution for your workload is not the most popular one , it is the one that fits your traffic pattern, team capability, and cost tolerance. We design and build it properly from the start.
AWS solution architecture and delivery for agencies across Australia, the UK, and Singapore.
What AWS Solutions Engineering Covers and Why Architecture Decisions Made Early Are Hard to Reverse
A SaaS startup migrates its monolith to AWS, choosing ECS Fargate because a benchmark post favoured it. Six months later the team pays for persistent task capacity to serve workloads that are almost entirely request-driven and would cost a fraction on Lambda. The containers run around the clock to avoid cold starts a properly designed application could have tolerated. The cost is the symptom, not the problem. The problem is that the AWS solution was chosen on familiarity rather than a structured analysis of the actual workload.
AWS solutions engineering starts from the workload: characterising request patterns before choosing compute, and mapping team capability before committing to an architecture that requires months of learning. The AWS development work that follows a well-designed solution is faster to build, cheaper to operate, and easier to hand over than work built to a familiar pattern without questioning whether it fits.
AWS Solutions by Workload Type and Architecture Pattern
Six AWS solution categories covering the application patterns that agency clients most commonly need to design, build, or migrate onto AWS.
Serverless AWS Solutions on Lambda and API Gateway
Serverless AWS solutions suit workloads where request volume is variable, cold start latency is tolerable, and the per-invocation cost model beats persistent compute. Lambda sits behind API Gateway with request validation, Cognito authorisation, and downstream DynamoDB or Aurora Serverless v2 depending on data access patterns. Step Functions handle multi-step orchestration where direct Lambda chaining creates brittle invocation chains and retry complexity.
Container-Based AWS Solutions on ECS and EKS
Container-based AWS solutions suit workloads with long-running processes, WebSocket connections, or startup sequences incompatible with Lambda. ECS Fargate is the default starting point for teams without Kubernetes investment: task definition management and blue/green deployment via CodeDeploy are simpler to operate than a full EKS cluster. EKS suits workloads where density justifies the control plane cost and the team has the Kubernetes operational capability to run it without accumulating cluster debt.
Multi-Tier Web Application AWS Solutions
Multi-tier web application AWS solutions cover SaaS platforms and B2B applications where frontend, API, and database tiers need to scale independently. CloudFront serves static assets from S3 with cache behaviours tuned per asset type. ALB routes to ECS or Lambda based on compute selection. RDS Aurora handles relational workloads with read replicas for reporting traffic. ElastiCache reduces database round-trips for session state. Each tier is sized to actual workload, not eighteen months of anticipated headroom.
Event-Driven and Async Processing AWS Solutions
Event-driven AWS solutions decouple producers and consumers using SQS, SNS, or EventBridge depending on the messaging pattern. SQS handles point-to-point queuing with visibility timeout and dead-letter queue configuration preventing message loss on consumer failures. EventBridge routes events by content to multiple targets without the producer knowing about consumer topology. Step Functions Express Workflows handle high-volume async orchestration. Dead-letter queue monitoring and poison message handling are designed in from the start, not retrofitted after the first production message loss.
Data Pipeline and Analytics AWS Solutions
Data pipeline and analytics AWS solutions cover batch ingestion into S3 data lakes, transformation via Glue or EMR, and query access via Athena or Redshift. Kinesis Data Streams handles real-time ingestion when latency requirements fall below the fifteen-minute Glue micro-batch window. Data Firehose delivers to S3 with timestamp partitioning to reduce Athena scan costs on time-bounded queries. Each component is sized to actual ingestion volume and query pattern, not roadmap capacity that does not yet exist.
AWS Migration Solutions for On-Premises Workloads
AWS migration solutions cover assessment, planning, and execution of workloads moving from on-premises or competing cloud providers. The 6Rs framework classifies each workload: retire, retain, rehost, replatform, repurchase, or refactor. Rehost migrations use Application Migration Service for lift-and-shift. Replatform migrations target managed services like RDS or ECS. Refactor scopes are set conservatively to avoid converting a migration into a concurrent rewrite. Each workload needs a validated rollback path before the cutover window opens.
How We Evaluate AWS Solution Architecture Options Before Recommending One
AWS solution selection follows a structured evaluation before any architecture diagram is drawn. Four questions drive it: what is the request and data volume at current and projected scale; what latency and availability requirements will users actually notice; what is the team’s operational capability after delivery; and what compliance constraints apply. These questions eliminate most plausible options before detailed design begins. Cost modelling covers compute, storage, data transfer, and service-specific charges using real workload parameters, not calculator defaults.
An AWS Well-Architected review is conducted after the architecture is defined, using the Well-Architected Framework to validate the design before build begins. Clients on our white-label model receive the Architecture Decision Record under their agency brand.
Four AWS Solutions Principles That Prevent Expensive Architecture Rework
Workload Characterisation Before Service Selection
Cost Modelling at Projected Scale, Not Current Traffic
Selecting an AWS service before characterising the workload produces solutions that fit the service’s strengths rather than the application’s requirements. Workload characterisation maps request concurrency, execution duration, data access patterns, and downstream dependency latency before any service is selected. A workload with highly variable traffic spikes needs different compute than one with a flat, predictable rate, even if both could technically run on Lambda or ECS. Services are chosen to fit the characterised workload.
Operational Fit Matched to Team Capability
An AWS solution that costs within budget at current traffic may become unviable at projected scale. DynamoDB on-demand pricing is cost-effective at low volume but becomes significantly more expensive than provisioned capacity at predictable high-volume access patterns. API Gateway request pricing compounds quickly compared to ALB fixed pricing at the same traffic volume. Cost modelling covers each tier at current and projected scale so architecture decisions account for the cost trajectory rather than just the launch-day bill.
Architecture Decisions Documented Before Build Begins
An AWS solution requiring Kubernetes operational knowledge is not a good fit for a team that has never managed a cluster. Operational fit assessment maps the architecture’s management requirements against the capability of the team that will own it after delivery. Where there is a gap, the options are to simplify the architecture, add a managed services arrangement, or plan a capability uplift. Choosing the most sophisticated option without addressing the gap creates a support burden within three months of go-live.
Architecture decisions made verbally during a discovery call are starting positions, not decisions. Writing an Architecture Decision Record before build begins forces the decision to be explicit: what was chosen, what was rejected, and why. When a stakeholder asks six months later why the solution uses Aurora instead of DynamoDB, the ADR provides the answer. Clients through the agency partner program receive ADRs as a standard deliverable on every AWS solutions engagement.
White-Label AWS Solutions for Digital and Marketing Agencies
Agencies that win AWS project work often face a constraint at the architecture stage: the client needs a credible solution design, but the agency does not have an AWS solutions architect on the team. We deliver the full engagement under your agency brand covering architecture evaluation, ADR production, infrastructure design, and build delivery, without any visible reference to NextEnvision. When the same team that designs the AWS solution also builds it, architecture decisions are not lost in the handoff between a solutions architect and a separate development team. Read more about the agency partner program.
White-label AWS solutions engagements are scoped per project with fixed deliverables for the architecture phase and a separate scope for the build phase. Agencies retain full margin control. Clients working through agency partners see no indication that the architecture or delivery is provided by anyone other than the agency. Contact us to discuss how a white-label AWS solutions arrangement fits your next client proposal.
Two Architecture Patterns That Look Right in Diagrams but Fail in Production AWS Solutions
The first failure pattern is synchronous Lambda chains replacing a purpose-built orchestration layer. Lambda function A invokes B synchronously, which invokes C, which writes to DynamoDB. In production, A’s execution time includes B and C’s full duration, hitting the 15-minute limit for what should be a fast API response. When C fails, a generic 500 propagates to the caller. Retry logic in A retries the whole chain including a DynamoDB write that may have already succeeded, creating duplicate records. The correct AWS solution uses Step Functions with per-step error handling and idempotent DynamoDB writes via condition expressions.
The second failure pattern is Aurora Serverless v1 on a workload with sub-second connection patterns. Serverless v1’s warm-up from zero appears as a connection timeout to the caller. A product with users across time zones rarely scales fully to zero, so cold-start behaviour surfaces precisely during maintenance windows and deployment restarts. For workloads with any sustained traffic, provisioned Aurora with a read replica is more predictable. The AWS development team needs firsthand experience of both patterns. The project outcomes from getting database selection right from the start are measurably better.
AWS Solutions Engagement Models by Project Stage and Starting Position
Architecture-First AWS Solutions Design
AWS Solutions Audit of Existing Architecture
An architecture-first engagement produces the solution design before any infrastructure is provisioned. Deliverables include the workload characterisation document, candidate architecture evaluation, ADR for the chosen solution, infrastructure diagram, cost model at current and projected scale, and an implementation backlog for the build phase. Architecture phases typically take one to two weeks depending on solution complexity. Build phases begin with an agreed architecture, not mid-build discovery.
Migration Architecture and Execution
AWS solutions audit engagements review an existing architecture against the workload it serves and the constraints it operates under. The audit produces a findings report covering cost inefficiencies, architectural risks, and Well-Architected pillar gaps, each with a remediation recommendation and effort estimate. Findings are prioritised by impact so the client can address highest-value items first. Audit engagements have a fixed scope and a defined deliverable.
Ongoing AWS Solutions Evolution Retainer
Migration architecture engagements cover assessment of current workloads, 6Rs classification per application, sequencing of migration waves to minimise dependency risk, and target architecture definition for each migration approach. Rehost migrations preserve the current architecture while eliminating on-premises dependencies. Replatform migrations are scoped to one architectural improvement per migration, not a concurrent refactor. Each workload has a defined cutover plan and a validated rollback path.
AWS solutions evolution retainers suit product teams with active environments whose architecture needs to keep pace with growth. Monthly scope covers architectural review of new features before they are built, cost optimisation recommendations as the workload grows, and Well-Architected review on a quarterly cadence. The retainer provides access to a named AWS solutions architect without the overhead of scoping a new project engagement every time an architectural question arises.
How We Deliver AWS Solutions From Architecture Decision to Production Build
Phase 1: Workload Characterisation and Constraint Mapping
Phase 2: Architecture Option Evaluation and ADR Production
Workload characterisation collects the data that drives every subsequent architecture decision: request concurrency and duration distributions, data volume and growth rate, read/write ratio for each data store, downstream dependency latency and failure rate, compliance requirements, and the team’s existing AWS operational capability. Where workload data does not exist because the application is new, we construct a characterisation from comparable workloads and validate the assumptions explicitly so they can be updated as the application accumulates real traffic.
Phase 3: Cost Modelling and Capacity Planning
Architecture option evaluation compares two to three candidate approaches against the characterised workload and documented constraints, assessed on operational complexity, cost at current and projected scale, risk surface, and team capability fit. The evaluation produces a recommendation with explicit reasoning and an ADR recording both the chosen option and the rejected alternatives with the specific reasons they were ruled out. The ADR is reviewed with the client before build begins.
Phase 4: Infrastructure Design and IaC Scaffolding
Cost modelling builds a twelve-month projection for the chosen architecture using real workload parameters from the characterisation phase. The model covers compute, storage, data transfer, managed service charges, and support tier cost. Reserved Instance or Savings Plan coverage recommendations are included where the workload profile justifies the commitment. The model is presented as a range , low, expected, high , based on traffic growth scenarios so the client understands the cost trajectory under different demand assumptions.
Phase 5: Build, Test, and Well-Architected Validation
Infrastructure design translates the chosen architecture into a CloudFormation or CDK implementation plan covering resource types, configuration parameters, networking topology, IAM permission model, and environment structure. IaC scaffolding creates the initial stack so the build phase begins with a working environment rather than provisioning infrastructure manually. Security group rules, encryption settings, and public access configurations are defined in IaC before the first resource is created.
Phase 6: Handover, Documentation, and Knowledge Transfer
The build phase implements the infrastructure design, with a Well-Architected review conducted after the core infrastructure is in place and before application integration begins. The review covers all five pillars: operational excellence, security, reliability, performance efficiency, and cost optimisation. Findings from the review are addressed during the build phase rather than deferred to a post-launch improvement backlog. Load testing validates the solution behaviour at projected peak traffic before the production environment accepts real user traffic.
From Architecture Decision to Production-Ready AWS Solution
Handover documentation covers the architecture overview, ADR library, infrastructure runbook, deployment procedure, and cost optimisation notes. Knowledge transfer sessions walk the client team through the architecture decisions so they understand the solution they are inheriting. All IaC is client-owned from the first commit. Post-handover support for architectural questions is available on retainer or time-and-materials. Contact us to discuss how handover fits your project timeline.