Hybrid cloud is now the default enterprise architecture. Across industries, 73% of organizations operate hybrid estates, per Flexera’s, up 3% year over year. But that scale brings friction: integration sprawl, fragmented security, unpredictable costs, and teams stretched across two operating models.
That complexity can be worth it when enterprises need greater control over specific workloads, but not every workload justifies the added operational burden.
For enterprise commerce teams, there’s more to think about: Black Friday and Cyber Monday (BFCM) traffic spikes, omnichannel inventory sync, checkout latency across regions, and customer data residency. These are also the workloads where hybrid architecture gets tested hardest.
This guide breaks down the main challenges of hybrid cloud through a commerce lens. Each section covers what the challenge is, why it hits commerce workloads harder, and how enterprises mitigate it. You'll also get a framework for deciding when hybrid is the wrong choice for commerce workloads.
What is hybrid cloud (and why do enterprises adopt it)?
Hybrid cloud is an architecture that combines public cloud services with private cloud or on-premises infrastructure, managed as one environment. Workloads and data move between the environments based on cost, performance, security, or regulatory requirements.
Enterprises adopt hybrid cloud for practical reasons. Regulated data can stay in a private environment while elastic workloads run in public cloud. Legacy systems, such as an enterprise resource planning (ERP) platform, can remain on-premises while newer applications run elsewhere. Mergers and acquisitions can also leave many enterprises with a hybrid estate by inheritance rather than by design.
The model dominates at scale. Flexera's cross-industry survey found hybrid adoption rises to 78% among organizations with more than 5,000 employees. An enterprise retail setup might pair cloud commerce and analytics with on-premises ERP, warehouse systems, and store infrastructure.
The case for hybrid is real, but so are the costs of running it. The same flexibility that lets enterprises place workloads where they fit best also adds connections, controls, and operational overhead across environments.
The main challenges of hybrid cloud for enterprise commerce
Below, we cover what each challenge is, why commerce workloads make it harder, and how enterprises reduce the risk. The common thread is complexity: every environment you add multiplies the connections, controls, and skills required to operate the whole. That added complexity is the trade-off enterprises make for greater control over where workloads and data live.
Integration complexity across systems and environments
Every system in a hybrid estate needs to exchange data with systems it wasn't designed to integrate with. The scale of the problem is measurable. The average organization now manages 957 applications, and only 27% of them are connected, according to the "2026 MuleSoft Connectivity Benchmark Report".
Commerce raises the stakes because the systems that must talk to each other span every environment. The ERP, product information management (PIM) system, order management system (OMS), point of sale (POS), and storefront all need consistent, near-real-time data. A nightly batch sync may be enough for internal reporting. But it fails when a shopper buys the last unit in-store and the online store keeps selling it.
Navid Jilow, director of technology at Belstaff, described the problem his brand solved after they brought their POS and ecommerce systems onto one platform: “If you have a different POS system to your ecommerce system then you have to deal with the additional complexity of managing two different systems, using separate data models, therefore increasing the technical and integration complexity within your IT real estate.”
The fix is to shrink the integration surface rather than manage a bigger one. Commerce Components lets enterprises keep existing on-premises or private cloud systems like ERP, PIM, and customer relationship management (CRM), while adopting Shopify components for the commerce layer. That can reduce the amount of custom integration work needed between the commerce layer and existing systems.
For back-end connectivity, B2B external integrations provide prebuilt connectors for NetSuite, Microsoft Dynamics, and Acumatica. An integration-platform-as-a-service (iPaaS) and custom APIs can support connections that require additional customization.
Security and compliance across environments
Every additional environment expands the attack surface and splits security controls across toolsets. IBM’s "Cost of a Data Breach Report 2026" found that 30% of breaches involved data distributed across multiple environments. Those breaches cost an average of $5.05 million, the highest of any storage configuration. They also took 276 days to identify and contain, longer than any other storage location (on-prem, public cloud, or private cloud).
Commerce adds two compliance layers on top. The Payment Card Industry Data Security Standard (PCI DSS) obligations follow cardholder data wherever it flows. Systems that store, process, or transmit cardholder data can fall within PCI DSS scope. Global retailers also face data residency requirements for shopper personally identifiable information (PII), which dictate where customer data can physically live.
Enterprises mitigate this risk by reducing the environment they have to secure. Shopify provides a PCI DSS–compliant commerce layer for the storefront, checkout, and payments, helping keep cardholder data out of the enterprise’s hybrid infrastructure.
It's a workload enterprises can offload rather than manage. Security teams can then concentrate controls on the systems they manage directly.
Network latency and performance consistency
Data traveling between environments adds hops, and hops add milliseconds. In a hybrid estate, a single page load can depend on a cloud storefront, an on-premises inventory check, and a third-party payment call. The slowest link sets the pace.
Commerce feels this at checkout, at the worst possible time. During BFCM 2025, Shopify businesses generated $14.6 billion in sales, with sales peaking at $5.1 million per minute on Black Friday. Checkout slowdowns during these periods put transactions at risk, yet provisioning infrastructure for a few annual peaks is expensive and difficult to forecast.
This is a workload that enterprises can reduce exposure to within the hybrid latency problem. Shopify runs the commerce layer on managed infrastructure with 300 points of presence (PoPs) worldwide. A 99.9% uptime service-level agreement (SLA) backs it, with capacity for 40,000 checkout starts per minute.
You can see how its peak capacity performs at scale. During BFCM 2024, the platform peaked at 284 million edge requests per minute, rising to 489 million during BFCM 2025. Traffic scaling happens on Shopify’s infrastructure, without the enterprise provisioning capacity.
Cost unpredictability and egress fees
Hybrid cost models combine two very different accounting models. On-premises infrastructure carries fixed capital costs. Public cloud carries variable operational costs. And data moving between the two incurs egress fees that are easy to underestimate at planning time.
That can make costs difficult to predict. According to the 2025 Wasabi Global Cloud Storage Index (a survey of 1,600 IT decision-makers), fees for data movement and operations account for 49% of the average cloud-storage bill.
In the same study, 56% of organizations said egress and access fees have delayed IT or business initiatives. Flexera's 2026 data adds that 85% of organizations rank managing cloud spend as a top challenge, with estimated wasted cloud spend at 29%.
Commerce can involve significant data movement between environments. Orders, inventory updates, returns, and analytics events cross environment boundaries constantly, and every peak event multiplies the volume.
AI workloads can add another layer of cost and latency. Running artificial intelligence and machine learning (AI/ML) inference across a hybrid estate means moving training data and model outputs between environments. Those transfers can add costs.
In a February 2026 Cloudian-commissioned survey of 212 senior IT decision-makers, 55% said cloud cannot consistently meet AI inference latency requirements. Respondents ranked data egress fees as the leading cause of storage budget overruns. Flexera's respondents cite cost unpredictability among the top challenges of managing AI workloads.
Mitigation starts with visibility: this means FinOps practices, egress monitoring, and workload placement that keeps chatty systems in the same environment. Moving the commerce layer to software-as-a-service (SaaS) with subscription pricing can make one part of the cost model more predictable. That can also make total cost of ownership (TCO) easier to evaluate across the commerce stack.
Operational visibility and unified monitoring
Hybrid environments can fragment observability. On-premises systems, private cloud, and public cloud each produce their own logs, metrics, traces, and alerts in their own tools. Getting a single view of system health and performance means adopting a unified observability platform or stitching dashboards together manually. The long containment window for multi-environment breaches shows what happens when neither works well.
For commerce, the visibility problem can extend beyond infrastructure monitoring to the systems that support inventory, orders, and store operations. When monitoring can't see across environments, the first alert might be a shopper complaint.
Before Frankie4 moved to a unified commerce platform, the footwear brand's previous setup lacked real-time integration between the online store and back-end systems. Those systems included their ERP, warehouse infrastructure, and in-store POS. The result was inventory issues, poor customer experiences, and slow, manual processes.
On Shopify and Shopify POS, Frankie4 gained clear inventory and sales oversight across channels. The brand has since doubled their store footprint from four to 10.
Enterprises mitigate the issues above in two ways. They bring metrics together into a single observability layer with agreed service level objectives across environments. And they reduce the number of systems that need watching in the first place. A managed commerce layer reports its own health instead of adding another stack to monitor.
Skills gaps and organizational complexity
Hybrid cloud needs people who understand both operating models, and those people are scarce. In cloud computing, 59% of organizations report being understaffed, per the Linux Foundation's 2025 “State of Tech Talent” report. Cybersecurity and compliance run higher still, at 65%. Faced with the shortage, 70% of organizations prefer to upskill existing staff for cloud roles. Only 16% opt to hire new talent.
The organizational cost can be less visible than the technical one. Systems that span environments also span teams.
Incident response, change management, and capacity planning all require coordination across groups with different tools and priorities. Commerce sits at the center of this: a checkout issue can implicate the infrastructure team, the ecommerce team, and an ERP vendor all at once. The more systems and teams involved, the more coordination hybrid commerce requires.
Offloading the commerce layer to a managed platform through Commerce Components changes the staffing equation. Internal teams can reduce the commerce infrastructure they manage directly. They concentrate instead on the proprietary systems where their expertise creates competitive advantage: the ERP, the data warehouse, and custom applications.
Hybrid cloud challenges and their fixes
The table below maps each challenge to the teams it hits hardest, the commerce-specific risk, and the primary mitigation. Together, these show the main operational costs of hybrid complexity for enterprise commerce.
| Challenge | Teams most affected | Commerce-specific risk | Primary mitigation |
|---|---|---|---|
| Integration complexity | IT architecture, ecommerce engineering | Inventory and order data drifting out of sync across ERP, POS, and storefront | Shrink the integration surface; use prebuilt connectors |
| Security and compliance | Security, legal, compliance | PCI DSS scope and shopper PII spread across environments | Offload checkout and payments to a PCI-compliant commerce layer |
| Network latency | Infrastructure, site reliability engineering | Checkout slowdowns across regions during peak events | Serve the commerce layer from managed edge infrastructure |
| Cost unpredictability | Finance, FinOps, IT leadership | Egress fees on constant order, inventory, and analytics flows | Monitor egress; make commerce costs more predictable through subscription pricing |
| Operational visibility | IT operations, customer support | No single view of inventory, orders, and system health | Consolidate telemetry; reduce the systems that need watching |
| Skills gaps | IT leadership, HR | Commerce infrastructure competing with core systems for scarce talent | Upskill internally; reduce directly managed commerce infrastructure with a managed platform |
When hybrid cloud is the wrong choice for commerce workloads
Hybrid cloud becomes a problem when workloads sit in it by default. The challenges above are the cost of running systems across environments. For some workloads, that cost buys real control. For others, it buys nothing. The decision comes down to whether that added complexity serves a clear business or operational need.
The way out is a workload-by-workload decision. Ask four questions of each system. Where your answers cluster tells you where the workload belongs.
| Question | Keep it in your estate if... | Move it to a managed platform if... |
|---|---|---|
| Does running it in-house create advantage? | It gives you capability rivals can't copy | Shoppers wouldn't notice who runs it |
| What does regulation require? | Law dictates where the data lives | Compliance is standard, and a vendor can carry it (PCI DSS) |
| How customized is it? | It's built around your proprietary processes | Its needs are industry-standard, met out of the box |
| How does demand behave? | Demand is steady and predictable | Demand spikes past what you can provision, like BFCM |
For many retailers, the commerce layer lands in the right-hand column. A managed platform runs the same systems for thousands of brands and can invest in capacity and reliability that one retailer's budget can't.
These are some warning signs your commerce layer is may be ready to move:
- Peak events require capacity planning cycles that start months in advance
- PCI DSS audit scope covers systems your team maintains directly
- Checkout latency varies by region because commerce runs from one location
- Engineers spend more time maintaining commerce infrastructure than improving it
Moving a workload out of an environment is now routine, not an admission of failure. In Cloudian's 2026 survey, 75% of enterprises had repatriated at least some workloads from public cloud within 24 months. The same workload-placement logic can run in either direction: place each workload where it performs best.
One worry with any move is breaking systems already in place. Edwin Portillo, VP of technology at Good American, put it plainly when the brand added retail stores to their existing Shopify operation: “We needed to ensure that bringing on this new sales channel wouldn't interrupt what we already had in place and that we had all the hardware to support the purchases, inventory transfers, and returns.”
Brands migrating to Shopify complete implementations 20% faster on average, according to an independent consulting firm.
When hybrid cloud is the right choice
None of this argues against hybrid itself. The model still fits where direct control creates real value. Data residency law, deep ERP customization, proprietary data pipelines, and specialized hardware all qualify.
Moving commerce to managed infrastructure can narrow a hybrid strategy to the workloads where direct control matters most. Shopify for enterprise and Commerce Components run the commerce layer on Shopify’s infrastructure. Your proprietary systems stay in the environments built for them.
Teams that want full front-end control can pair that model with headless commerce and custom storefronts. That means integrating a private cloud front end, content management system (CMS), ERP, or PIM with Shopify's back end.
Challenges of hybrid cloud FAQ
What are the major challenges faced in the cloud?
The major cloud challenges are cost management, security, and skills availability. Flexera's 2026 survey ranks managing cloud spend first, cited by 85% of organizations, with security close behind at 82%. Hybrid architectures intensify these challenges because every added environment brings its own pricing model, security controls, and required expertise. For commerce teams, peak-event capacity and cross-environment data sync sit on top of that baseline.
What is a big security challenge when it comes to cloud and hybrid environments?
A major security challenge in hybrid environments is fragmented visibility across an expanded attack surface. Data spread across multiple environments takes the longest of any configuration to identify and contain after a breach, at 276 days per IBM's 2025 research. Retailers carry extra exposure because systems that store, process, or transmit payment data can fall within PCI DSS scope. Shopper PII adds residency rules that differ by market.
What are the top two challenges for hybrid cloud adoption?
Two major hybrid cloud adoption challenges are integration complexity and cost unpredictability. Connecting on-premises systems with cloud services requires custom work that grows with every application added. The average organization already runs 957 of them.
On the cost side, egress fees and mixed pricing models make hybrid costs hard to forecast. In Wasabi's 2025 index, 62% of organizations exceeded their cloud storage budgets.
What are the challenges of hybrid computing?
Hybrid computing challenges fall into six areas: cross-environment integration, a larger attack surface, latency consistency, cost forecasting, dual-expertise staffing, and operational visibility. AI inference workloads can add another layer of complexity, since moving models and training data between environments adds both latency and egress cost. The reference table above maps each challenge to the teams it affects and its primary mitigation.
Is hybrid cloud more secure than public cloud?
No, hybrid cloud is not inherently more secure than public cloud. Security depends on configuration and operations, not the model. IBM's 2025 data shows breaches involving multiple environments cost more on average ($5.05 million) than breaches of public cloud data alone ($4.18 million).
Hybrid can improve security for specific regulated workloads by keeping them under direct control. That only holds if teams manage controls consistently across every environment.
