An e-commerce application does not need to be completely down to be losing orders.
The storefront can load normally while a promotion calculates the wrong discount. A payment can be authorized while the corresponding order fails to appear in the order-management system. Inventory can show an item as available even though the warehouse has none left. Checkout can work on desktop while a new mobile release creates enough layout instability to make the payment button difficult to use.
That is why maintaining an e-commerce application requires more than watching uptime and fixing visible bugs.
The application is a chain of connected commercial processes:
Product discovery → product information → cart → pricing → checkout → payment → order creation → inventory → fulfilment → customer communication
A failure anywhere along that chain can affect a sale even when the rest of the application appears healthy.
The most useful e-commerce maintenance checklist therefore follows the transaction rather than the architecture. It asks whether customers can find the right product, see the right price and stock status, pay correctly, create exactly one valid order, and receive what they bought—while the systems behind those steps remain secure, performant and observable.
For Levelworks, that connects particularly strongly to Error Free, Performant, Secure, Observable, Integrable, Current & Updated and Tested App Health.
Do not use the homepage as the primary health check for an e-commerce application.
A much better test follows a real buying journey from product discovery through successful order confirmation.
That should exercise the parts of the system where commercial failures actually appear: product pages, cart state, pricing, checkout, payment and order creation.
Use representative scenarios rather than one ideal purchase. For example, periodically exercise guest and authenticated checkout, discounted orders, different shipping options and the major payment methods the business actually supports.
The objective is not exhaustive manual regression every morning. Critical purchase paths should be automated where practical and supplemented by targeted human testing after meaningful commerce changes.
Most importantly, confirm the final business outcome.
A checkout request returning 200 OK is not enough if payment succeeded but no valid order was created.
Pricing errors are unusually dangerous because the application may be functioning exactly as coded while producing the wrong commercial result.
Maintenance should pay particular attention when teams change:
Test the final order total, not merely whether the discount code was accepted.
Imagine a “20% off selected products” campaign. The promotion appears correctly on the product page and cart, but a change in promotion precedence causes the discount to apply after another offer that should have been mutually exclusive.
Nothing crashes. The store simply charges the wrong amount.
Tests should therefore include representative combinations of pricing rules, especially where promotions can overlap.
Also verify consistency between what the customer saw and what downstream systems received. The amount captured by the payment provider, recorded on the order and transmitted to fulfilment or accounting should agree with the final checkout amount.
Payment infrastructure deserves more scrutiny than simply checking whether the payment provider's API is reachable.
Track the lifecycle from payment attempt through confirmed order state.
Useful signals include payment initiation, authorization or confirmation, failure reasons, abandoned payment states, webhook-processing failures, refunds and cases where payment and order state disagree.
Payment APIs also need protection against duplicate operations. Stripe, for example, supports idempotent requests specifically so an interrupted request can be retried without unintentionally performing the same operation twice.
That principle is important beyond any specific provider.
Network failures create ambiguous states. The application may time out without knowing whether the provider completed the payment. A naive retry can potentially create duplicate work.
Maintenance testing should include these uncomfortable paths, not just successful card transactions.
OWASP's Web Security Testing Guide for payment functionality similarly emphasizes testing the business logic surrounding e-commerce payments rather than assuming gateway integration alone makes the flow secure.
One of the most important e-commerce checks happens between systems.
Compare:
successful payments
with:
successfully created orders
Those numbers should reconcile according to the application's payment model.
Any mismatch deserves investigation.
Examples include:
This is particularly important where payment status arrives asynchronously through webhooks.
Webhook infrastructure should be monitored for delivery failures, processing failures and unexpected delays. PayPal's current documentation, for example, notes that failed webhook deliveries can be retried repeatedly over several days, illustrating why webhook handlers must tolerate retries and maintain correct processing state. PayPal: Webhooks
Do not assume the user returning to a “Thank you for your order” page is the authoritative signal that payment completed.
Inventory failures can produce two commercially painful outcomes.
The store sells products that are not available.
Or products are available but incorrectly shown as out of stock.
Both deserve monitoring.
Where inventory synchronizes with an ERP, warehouse platform, POS or marketplace, track synchronization success rather than merely API availability.
Useful comparisons include:
Inventory updates expected
vs
Inventory updates successfully applied
and:
Store stock
vs
system-of-record stock
Pay particular attention to high-volume periods because concurrency can expose inventory assumptions that ordinary traffic does not.
Maintenance teams should also understand where stock becomes reserved. Is it when a product enters the cart, when checkout begins, when payment is authorized or when the order is confirmed?
You do not need one universal answer, but the implemented rule needs to remain consistent across failure and retry paths.
A successful checkout does not mean the transaction is finished from an operational perspective.
The order may still need to reach:
Track whether orders successfully progress through the expected lifecycle.
An important maintenance signal is orders stuck in intermediate states.
For example, if the normal progression is:
Paid → Confirmed → Sent to warehouse → Fulfilled
an increasing number of orders remaining in Confirmed may indicate a broken fulfilment integration even while the storefront and payment system remain perfectly healthy.
Alert on abnormal age as well as counts. Ten orders waiting two minutes may be normal; two orders waiting twelve hours may not be.
Purchase testing often concentrates heavily on checkout.
Post-purchase financial flows deserve equal precision.
When refund or cancellation logic changes, verify that the relevant systems agree:
Event
What should remain consistent
Cancellation
Order state, payment state, reserved inventory
Refund
Payment provider, internal order record, customer communication
Return
Returned quantity, inventory disposition, refund status
Partial refund
Refunded amount, remaining order value, accounting state
Partial transactions deserve particular attention because they tend to create more state combinations than simple full-order cancellation.
A refund that succeeds financially but fails to update the order-management system can create support and reconciliation problems later.
A store can be technically healthy while customers cannot find what they want.
Maintenance should verify that product creation and updates propagate correctly through the systems involved.
Check important product attributes such as availability, variant options, images, descriptions and prices wherever these are generated or synchronized.
Search and filtering deserve targeted regression testing after:
For web stores that publish product information to search engines, also monitor structured product data after template changes.
Google's current merchant-listing documentation supports information such as price, availability, shipping and returns in product markup and recommends checking Search Console after updating templates or structured-data implementations. Google Search Central: Merchant Listing Structured Data
This is a useful maintenance check because a storefront redesign can accidentally damage product markup without visibly breaking the page for customers.
E-commerce pages tend to accumulate weight.
Product imagery grows. Recommendation components are added. Analytics expand. Review widgets, chat tools, experimentation libraries and advertising scripts arrive over time.
A site that launched quickly can gradually become noticeably slower.
Monitor real-user performance across the pages that matter commercially, particularly:
Google's current Core Web Vitals remain Largest Contentful Paint (LCP) for loading, Interaction to Next Paint (INP) for responsiveness and Cumulative Layout Shift (CLS) for visual stability. Google recommends evaluating them at the 75th percentile rather than relying on averages. web.dev: Web Vitals
Segmentation matters.
A global performance average may hide a serious mobile problem or a slower experience in a particular geography.
Also inspect performance after adding third-party storefront scripts. A marketing tool that appears inexpensive organizationally can still impose a technical cost on every shopper's page.
[Internal Link: “How to Improve Web App Performance Without Rebuilding Your Application”]
Payment security is not something to verify once when the store launches.
The payment page itself evolves.
Analytics, tag-management tools, chat widgets and experimentation scripts may be added later, sometimes without being treated as payment-security changes.
That deserves special attention.
PCI DSS v4.0.1 is the current version highlighted by the PCI Security Standards Council. Its e-commerce guidance addresses risks such as malicious payment-page scripts and e-skimming. PCI SSC specifically points to controls around authorizing payment-page scripts, checking their integrity and detecting unauthorized changes. PCI SSC: Payment Page Security and Preventing E-Skimming
For some SAQ A e-commerce environments, PCI SSC's current guidance also addresses security expectations for merchant pages even where payment functionality is substantially outsourced. PCI SSC FAQ 1588
The precise PCI obligations depend on the payment implementation and compliance environment, so the maintenance team should work from the organization's applicable PCI scope rather than assuming one checklist applies to every merchant.
Operationally, the important principle is simpler: know which scripts can affect checkout and review changes to them intentionally.
[Internal Link: “Application Security Maintenance: What Needs to Happen After Launch?”]
E-commerce applications often depend on more external systems than users realize.
Payment, tax, fraud detection, shipping, address validation, email, inventory and marketplace services can all participate in a single order.
Monitor each integration at the boundary.
Look for:
Then monitor the business result.
A shipping API may return successfully while a later process fails to attach the shipping option to checkout.
A warehouse API may be online while product inventory has stopped synchronizing.
The distinction is important: integration availability and integration correctness are not the same thing.
[Internal Link: “How to Monitor the Health of Your App’s APIs and Integrations”]
Order confirmation, payment failure, dispatch and refund messages are part of the buying experience.
Changes to queues, email providers, templates or event handling can break them without affecting checkout itself.
Track whether important messages are:
You do not need to treat every bounced email as an application incident.
You do need to notice when no customer has received an order confirmation for the last two hours because a credential expired.
Transactional messages are especially useful as cross-system signals because their absence can expose failures elsewhere in the order lifecycle.
Many e-commerce systems have important work that happens away from the storefront.
Examples include catalog imports, inventory synchronization, marketplace feeds, settlement reconciliation and abandoned-cart processing.
These jobs can fail silently if monitoring focuses entirely on HTTP requests.
For important scheduled work, monitor:
A job reporting “success” after processing zero records may deserve just as much attention as a job returning an error.
Monitoring should reflect expected business output, not simply process completion.
Revenue analytics depend on technical instrumentation.
A checkout redesign can continue accepting purchases while silently breaking the event that records completed transactions in an analytics platform.
After changes to checkout, consent management, tag management or frontend tracking, verify critical commerce events.
This does not mean the maintenance team owns marketing analytics strategy.
It means a technical release should not accidentally make conversion reporting unreliable.
For commercial applications, observability includes knowing whether the business can still trust the signals used to understand transactions.
After an e-commerce deployment, validate more than the homepage.
A lightweight post-release suite should exercise representative high-value functionality, particularly when checkout or order processing has changed.
For example, validate product loading, cart updates, promotion calculation, checkout initialization, payment in an appropriate test path, order creation and key integrations.
Then compare production signals before and after the release.
If payment failures, JavaScript errors or checkout latency increase immediately after deployment, the connection should be visible quickly.
This is where Tested, Observable and Seamlessly Updatable App Health reinforce one another.
Testing reduces avoidable regressions; observability reveals the ones testing misses; safe release practices make correction easier.
The exact frequency depends on transaction volume and architecture, but a practical operating view looks like this:
Area
Maintenance check
Purchase journey
Complete representative purchases end to end
Pricing
Verify prices, promotions, tax, shipping and final totals
Payments
Monitor success/failure state and safe retries
Reconciliation
Compare payment state with order state
Inventory
Verify stock accuracy and synchronization
Orders
Detect orders stuck between lifecycle stages
Refunds/returns
Reconcile financial and order-system state
Catalog/search
Verify product updates, indexing and filtering
Product data
Check storefront/feed/structured-data consistency
Performance
Monitor real-user product, cart and checkout performance
Payment security
Review payment-page scripts and applicable PCI controls
Integrations
Monitor technical health and business outcomes
Communications
Verify important transactional messages
Scheduled jobs
Check completion, delay and processed output
Analytics
Validate critical commerce events after releases
Deployments
Run post-release commerce smoke tests
E-commerce applications make maintenance unusually measurable.
A failing background process is not merely a queue problem if paid orders never reach fulfilment. A slow database query is not merely a performance problem if customers abandon product search. A broken webhook is not merely an integration issue if payments and orders drift out of sync.
That is why Levelworks' App Health aspects are most useful here when viewed through the commerce journey.
Error Free means more than pages without exceptions; transactions need to remain correct. Integrable means data must continue moving reliably between payment, inventory and fulfilment systems. Performant has to hold where shoppers actually browse and buy. Secure includes the payment surface as it evolves. Observable means the team can detect when those commercial outcomes begin failing.
For an e-commerce maintenance team, the most important question after any change is therefore not simply whether the store is online.
It is whether a customer can still move from wanting a product to receiving a valid order without any part of the system quietly losing the transaction along the way.
