Server Hosting Costs: AWS/Azure Fees for Self‑Hosted WMS
- Cost Breakdown : AWS EC2 + S3 + RDS vs Azure VMs + Blob + SQL Server.
- EdgeOS Advantage : Decreases outbound traffic, cutting data‑transfer bills by up to 30 %.
- Dark Store Mesh : Optimises compute utilisation for Tier‑2/3 fulfil‑centres, lowering idle capacity costs.
Introduction
India’s e‑commerce logistics ecosystem is a mix of mega‑cities and bustling Tier‑2/3 hubs. A warehouse management system (WMS) that can scale from a Bangalore dark‑store to a Guwahati fulfilment centre must balance performance and cost. Self‑hosted WMS solutions on cloud platforms like AWS or Azure promise agility, but the hidden fees—compute, storage, bandwidth, and licence—can quickly erode margin, especially when COD transactions and RTO (Return‑to‑Origin) spikes during festive seasons hit hard. This post dissects the true cost of hosting a self‑hosted WMS on AWS and Azure, then shows how Edgistify’s EdgeOS, Dark Store Mesh, and NDR Management layer can trim the bill without compromising service quality.
1. Understanding the Cost Components
| Component | AWS | Azure | Typical Use‑Case | Key Influencers |
|---|---|---|---|---|
| Compute (VM/Instance) | EC2 `m5.large` (2 vCPU, 8 GiB) | VM `Standard_D2s_v3` | Core WMS engine | Instance hours, Reserved vs Spot |
| Storage (Block) | EBS `gp3` 100 GiB | Managed Disks Premium SSD 100 GiB | Data lake, logs | IOPS, throughput |
| Object Storage | S3 Standard 500 GiB | Blob Storage Hot 500 GiB | Media, backups | Request count, data egress |
| Database | RDS PostgreSQL 2 XLB | SQL Server 2 DTU | Inventory, orders | Multi‑AZ, backup retention |
| Data Transfer | Inbound free, outbound 0.09 $/GB | Inbound free, outbound 0.087 $/GB | API calls, bulk sync | Bandwidth usage, Edge caching |
| Managed Services | SQS, SNS, CloudWatch | Service Bus, Event Grid, Monitor | Queueing, alerts | Message volume |
| Support | Developer tier 0 $ | Basic 0 $ | Incident response | 24/7 access |
> Note: Prices are region‑specific; Mumbai (ap-south-1) and Bengaluru (ap-south-2) differ by ~5 %. Spot pricing can reduce compute costs by 70–80 % but requires workload elasticity.
2. Problem‑Solution Matrix
| Problem | Consequence | Solution (Edgistify Lens) | Impact on Cost |
|---|---|---|---|
| High outbound data transfer | 30–40 % of bill | EdgeOS local caching, CDN edge nodes | Cuts egress by ~30 % |
| Under‑utilised compute during off‑peak | Idle VM costs | Dark Store Mesh auto‑scaling | Utilises spot instances, reduces idle time |
| Complex multi‑zone failover | Operational overhead | NDR Management for rapid rollback | Reduces downtime, saves support hours |
| Frequent database snapshots | Storage + I/O spikes | Incremental snapshot strategy | Lowers storage and I/O costs |
3. Cost Scenario: 1‑Year Projection
3.1 Baseline AWS (Mumbai)
| Item | Annual Cost |
|---|---|
| EC2 (m5.large, 730 hrs) | ₹ 1,20,000 |
| EBS gp3 (100 GiB) | ₹ 12,000 |
| RDS PostgreSQL (db.t3.medium) | ₹ 1,05,000 |
| S3 (500 GiB, 2 M requests) | ₹ 12,000 |
| Data Transfer (200 GB egress) | ₹ 18,000 |
| Support | ₹ 0 |
| Total | ₹ 2,47,000 |
3.2 Baseline Azure (Bengaluru)
| Item | Annual Cost |
|---|---|
| VM Standard_D2s_v3 | ₹ 1,10,000 |
| Managed Disk | ₹ 10,000 |
| SQL Server 2 DTU | ₹ 1,00,000 |
| Blob Storage | ₹ 10,000 |
| Data Transfer | ₹ 17,000 |
| Support | ₹ 0 |
| Total | ₹ 2,27,000 |
3.3 Optimised with Edgistify Layer
| Item | AWS Optimised | Azure Optimised | Savings |
|---|---|---|---|
| Spot Instances (70 % of compute) | ₹ 36,000 | ₹ 33,000 | ₹ 30,000 |
| EdgeOS caching (30 % egress reduction) | ₹ 12,600 | ₹ 12,000 | ₹ 12,000 |
| Dark Store Mesh auto‑scale | ₹ 8,400 | ₹ 9,000 | ₹ 1,200 |
| NDR Management (reduced incidents) | ₹ 3,000 | ₹ 3,000 | ₹ 0 |
| Total | ₹ 59,400 | ₹ 57,000 | ₹ 1,20,000 |
> Result: 75 % cost reduction for a self‑hosted WMS running across tier‑2/3 warehouses while keeping SLA at 99.99 %.
4. Why EdgeOS, Dark Store Mesh, and NDR Management Matter
- 1. EdgeOS – A lightweight edge compute layer that pre‑processes inventory updates and API calls locally. By serving 30 % of traffic from regional edge nodes, it slashes egress charges, which is a major driver in cloud bills, especially for COD‑heavy markets where order volumes spike post‑payment.
- 2. Dark Store Mesh – A mesh network of micro‑services deployed in a dark‑store topology (like those in Guwahati or Lucknow). It optimises compute utilisation by dynamically allocating resources based on local demand patterns, leveraging spot instances for low‑priority tasks. This means you’re never paying for idle racks.
- 3. NDR Management – Network‑Level Disaster Recovery tools that automatically replicate state across zones with minimal bandwidth usage. By reducing failover time from hours to minutes, you cut support incidents and avoid premium “out‑of‑hours” charges in AWS/Azure.
These layers work synergistically: EdgeOS reduces data transfer, Dark Store Mesh cuts compute waste, and NDR Management keeps the system resilient—collectively trimming the bill without a drop in performance.
5. Conclusion
Hosting a self‑hosted WMS on AWS or Azure can be economical if you understand where the money goes and apply the right optimisation techniques. For Indian e‑commerce, where COD, RTO, and festive spikes create unpredictable load patterns, layering EdgeOS, Dark Store Mesh, and NDR Management turns a cost‑driven operation into a margin‑preserving one. By targeting key cost drivers—egress, idle compute, and recovery—you can achieve up to 75 % savings while maintaining, or even improving, service reliability across tier‑2/3 cities.