Project Name
Shared AWS Infrastructure Replaced With Per-Client Isolated Stacks - Noisy-Neighbour Risk Eliminated
A cloud-native operations technology platform serving multiple retail clients processes high-frequency transactional events, counts, scans, and soft-close jobs – with workloads varying significantly by time of day and season. As the client base grew, the shared-infrastructure model exposed scalability and cost risks. A spike from one client could silently degrade service for every other. Applying its AI-First approach, Ksolves redesigned the backend so every client runs on entirely their own AWS stack, and the platform only pays for what is actually used.
- Noisy-Neighbour Risk: All clients shared the same database and message queues. A peak workload from one client could slow query response times and queue throughput for every other client with no isolation boundary to contain the impact.
- Flat Cost Model Disconnected From Use: Infrastructure provisioned at peak capacity and billed at a flat rate regardless of actual load. Light or seasonal clients generated the same cost as continuously active ones, eroding margin on smaller accounts.
- Wide Blast Radius for Failures: A misconfigured queue or application bug on one client's workload could propagate errors into shared components, affecting unrelated clients and making root-cause isolation slow.
- No Client-Level Start and Stop Control: When a client was paused or offboarded, infrastructure remained running and accruing cost with no mechanism to cleanly stop a database or drain queues tied to that client.
- Manual and Inconsistent Onboarding: Provisioning new clients required manual steps across multiple AWS consoles, introducing configuration drift and slowing time from contract to live operation.
- No Dead-Letter Visibility: Failed messages were lost or mixed with active traffic with no systematic strategy to catch, preserve, and surface processing failures for investigation.
Ksolves eliminated sharing entirely. Each client receives their own AWS stack, data store, and event queues. CloudFormation automates the full lifecycle from onboarding to teardown. The governing design rule: if a problem occurs on one client's stack, no other client should know or care.
- Per-Client AWS Stack: Each client is provisioned with their own SNS topic and three dedicated SQS queues (count, scanner, soft-close) with associated dead-letter queues. Queue traffic for one client never touches another's.
- Dedicated Amazon RDS Instances: Every client gets an isolated database instance. Load, contention, and storage growth on one account have zero impact on others. Instances are stopped when the client is inactive to eliminate idle costs.
- AWS CloudFormation Automation: Single template creates SNS, SQS, RDS, and DNS resources in one automated run at onboarding. Stack deleted cleanly at offboarding after queues drain - zero orphaned resources, zero manual steps.
- Dead-Letter Queue Strategy: Every SQS queue paired with a dead-letter queue capturing failures after the retry threshold. Per-client investigation and replay without affecting live traffic.
- Pay-for-Use Billing: RDS on compute-hours, SQS on message volume, SNS on publish events. Quiet clients cost nearly nothing. Active clients billed in proportion to actual use.
- Route 53 DNS-Bound Client Identity: DNS record created per client as part of the CloudFormation stack - unique identifiable endpoint, routing always tied to the correct isolated infrastructure set.
Technology Stack
| Category | Technology |
|---|---|
| Infrastructure | Amazon Web Services (AWS) |
| Messaging | Amazon SNS + SQS with Dead-Letter Queues |
| Database | Amazon RDS |
| DevOps | AWS CloudFormation |
| Infrastructure | Amazon Route 53 (DNS) |
| Architecture | Per-Client Infrastructure Pattern |
- 100% Client Infrastructure Isolation: Every client runs on its own SNS, SQS, and RDS stack. One busy client cannot degrade service, increase latency, or cause errors for any other client.
- Cost Proportional to Real Use: Paused client costs near zero. Active clients billed in proportion to messages processed and compute consumed. Flat-rate overprovisioning eliminated.
- Onboarding Automated to One Run: CloudFormation creates all resources in one automated operation with no manual steps between contract and go-live. Configuration drift eliminated.
- Zero Message Loss: Dead-letter queues capture all failures after the retry threshold. Per-client investigation and replay without touching live traffic.
- Clean Offboarding - Zero Orphaned Costs: Teardown automation stops the database and deletes the stack after queues drain. No resources left running and billing after client offboarding.
“The move to per-client infrastructure removed the one thing we were most worried about at scale – one client making another client’s experience worse. We can now onboard confidently knowing each customer’s stack is entirely their own.”
– Head of Engineering / Platform Lead.
A growth-stage SaaS platform running all clients on shared queues and a shared database, carrying noisy-neighbour risk, flat-rate infrastructure costs, and no clean offboarding mechanism, was transformed through Ksolves DevOps consulting services. Every client now operates on a fully isolated AWS stack, their own SNS, SQS with dead-letter queues, RDS instance, and Route 53 DNS record – provisioned automatically at onboarding and removed cleanly at offboarding. 100% isolation achieved. Cost aligned to real usage. Onboarding automated. Zero message loss. The per-client isolation model makes the platform enterprise-ready and removes shared-infrastructure risk as a barrier to client growth.
Is your multi-tenant platform one busy client away from a service degradation?
