Cloud Infrastructure & Platform Engineering for E-Commerce
E-commerce platforms fail when traffic spikes, when payment infrastructure is misconfigured, or when databases become bottlenecks at scale. Wolk Inc builds the cloud infrastructure, Kubernetes platforms, and data pipelines that keep e-commerce running under pressure.
50×
Peak Traffic Headroom Designed For
PCI DSS
Compliant Architectures
99.9%
Uptime SLA
30–60%
Cloud Cost Reduction
What E-Commerce Engineering Teams Face
Unpredictable Peak Traffic
E-commerce infrastructure must handle normal daily traffic alongside Black Friday spikes that can be 10–50× baseline volume. Static over-provisioning is expensive. Auto-scaling that triggers too slowly causes dropped sales. The solution is pre-warmed scaling, predictive HPA configurations, and load-tested infrastructure that has been validated before the traffic arrives.
PCI DSS Cardholder Data Security
Merchants processing payment cards must comply with PCI DSS. PCI scope creep — where cardholder data flows through systems that should never touch it — is the most common and costly compliance failure. Wolk Inc designs e-commerce infrastructure to minimize PCI scope, implement CDE segmentation, and produce the network diagrams assessors require.
Personalisation Infrastructure Complexity
Modern e-commerce personalisation — real-time product recommendations, dynamic pricing, cart abandonment prediction, and search relevance tuning — requires streaming data pipelines, feature stores, and low-latency inference infrastructure that most e-commerce engineering teams are not yet equipped to build and operate.
Database Bottlenecks at Scale
E-commerce databases are hit by read-heavy product catalogue queries, write-heavy order and inventory updates, and reporting queries that lock tables during peak hours. Without proper read replica routing, connection pooling, and caching layers, the database becomes the constraint on the entire order funnel.
E-Commerce Engineering Services
Peak Traffic Scaling Infrastructure
Kubernetes-based infrastructure designed for e-commerce traffic patterns: KEDA event-driven autoscaling, pre-warmed node pools for flash sales, load testing automation, and CDN configuration for static asset delivery. Includes peak traffic runbooks and real-time capacity dashboards.
PCI DSS-Compliant Cloud Architecture
Cloud infrastructure designed to minimize PCI scope: cardholder data environment (CDE) segmentation, tokenisation integration, encryption at rest and in transit, WAF configuration for OWASP Top 10, and network topology documentation compatible with PCI DSS assessment requirements.
E-Commerce Data & Personalisation Pipelines
Real-time event streaming pipelines for clickstream, cart, and purchase data using Apache Kafka. Feature store architecture for personalisation models, product recommendation inference infrastructure, and A/B testing data collection. dbt transformations for analytics and reporting warehouses.
Search & Catalogue Infrastructure
Elasticsearch and OpenSearch cluster architecture for product search: index design, relevance tuning, query performance optimisation, and zero-downtime re-indexing automation. Includes vector search configuration for AI-powered semantic product discovery.
Order & Inventory Platform Engineering
Distributed system design for order management and inventory: PostgreSQL read replica configuration, connection pooling, caching layer implementation with Redis, and event-driven microservice patterns that prevent overselling and inventory sync failures at high order volumes.
E-Commerce Observability & Uptime
Funnel-aware observability for e-commerce: checkout conversion SLOs, payment gateway latency alerts, inventory sync health checks, and real-time order error rate dashboards. On-call runbooks and escalation paths designed around revenue impact rather than generic system metrics.
Senior Engineers Who Understand Revenue-Critical Infrastructure
E-Commerce Engineering Questions
How does Wolk Inc ensure e-commerce infrastructure handles Black Friday traffic?▾
Wolk Inc combines pre-warmed Kubernetes node pools with KEDA event-driven autoscaling and predictive horizontal pod autoscaler configurations. Before peak events, we conduct load tests at 2–3× expected peak volume to identify and resolve bottlenecks. Peak traffic runbooks, real-time capacity dashboards, and pre-event infrastructure review calls are standard deliverables for e-commerce platform engagements.
Can Wolk Inc help an e-commerce company achieve PCI DSS compliance?▾
Yes. Wolk Inc designs cloud architecture that minimises PCI scope through tokenisation and CDE segmentation, implements the required encryption, access control, and logging controls, and produces the network topology diagrams required for PCI DSS assessments. We work alongside your QSA to ensure all technical evidence requirements are met.
Does Wolk Inc work with Shopify, Magento, or custom e-commerce platforms?▾
Wolk Inc works with the infrastructure layer beneath and around your commerce platform — the cloud infrastructure, CI/CD pipelines, data engineering, and integrations — regardless of whether you are on Shopify Plus, Magento/Adobe Commerce, WooCommerce, a custom-built platform, or a headless commerce architecture. We are platform-agnostic at the infrastructure level.
How does Wolk Inc approach e-commerce database scaling?▾
Wolk Inc analyses your current query patterns, identifies the read/write ratio, and designs a scaling strategy appropriate for your traffic profile. This typically includes PostgreSQL or MySQL read replica configuration, PgBouncer or ProxySQL connection pooling, Redis caching layers for product catalogues, and query optimisation for the most expensive EXPLAIN plans. We also handle schema migrations with zero downtime using tools like pgroll or gh-ost.
Can Wolk Inc build a real-time personalisation engine for e-commerce?▾
Yes. Wolk Inc designs and implements the infrastructure layer for e-commerce personalisation: Apache Kafka pipelines for real-time event ingestion, feature stores for model serving, and low-latency inference infrastructure for recommendation models. We work alongside your data science team to ensure the infrastructure supports your specific modelling approach and latency requirements.