Prepare for holiday peaks by modeling your own demand, reducing avoidable work at the origin, testing the full purchase path and its dependencies, and rehearsing how your team will respond when something degrades. Treat shopping agents as a traffic and access-management consideration—not as a known holiday traffic multiplier: the available vendor guidance does not quantify how much AI agents will add to a store’s load.
1. Build a traffic model and map the request path
Start with your own promotions, architecture and demand history. Salesforce recommends modeling expected sale traffic from previous peak periods with reasonable growth assumptions, and using equivalent code, resources and data in load tests. Plan for the shape of the event as well as its total volume: a short burst during a product drop can stress a system differently from sustained high traffic.
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Use scenarios when the past is a poor guide
If the store has no relevant history, or has changed platforms or architecture substantially, do not disguise uncertainty with a single confident forecast. Test several plausible scenarios, including a sharp burst, sustained demand and a degraded dependency. Shopify Engineering describes controlled tests for increased traffic, database latency, cache failures, regional failover and cascading failures as part of its preparation for BFCM 2025; that is Shopify’s infrastructure practice, not a capacity prescription for merchants.
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Trace a shopper’s journey through the CDN or edge, storefront application, database, search, inventory, fraud checks, payment provider, analytics and other external services. Mark which calls are required to complete a purchase, which are optional, where work is queued, and who owns each service. A page can remain available while a payment, inventory or fraud dependency is failing, so capacity planning needs this end-to-end view.
2. Keep cacheable work away from the origin
Review product, catalog and campaign landing pages for safe caching opportunities. Personalization, inventory accuracy and other business rules may limit what can be cached, so validate behavior rather than making every page static. Normalize promotional tracking parameters where possible: arbitrary query strings can create distinct cache keys and reduce reuse. Salesforce also advises avoiding unique customer IDs or email addresses in campaign URLs when possible.
Apply platform-specific cache guidance carefully
Adobe’s September 30, 2026 holiday playbook recommends checking whether landing pages are cacheable, using GraphQL GET for PWA or headless Adobe Commerce storefronts to improve Fastly cache hit ratio, and using edge image optimization for image-heavy storefronts. These are Adobe Commerce-specific recommendations; confirm they fit your implementation before adopting them.
Salesforce’s 2026 B2C Commerce guidance describes a cache hit ratio above 70% as a performance objective for its context, not a universal threshold for every architecture. Salesforce also reports one mid-size apparel retailer’s Black Friday flash sale: traffic reached 12 times its reference level, cache hit ratio was around 55% before readiness changes and rose above 80% afterward, alongside caching, scheduling and quota work; the company says response times remained stable in that event. Those figures describe one vendor-reported example, not a forecast or guaranteed result for another store.
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Exercise browsing, search, product detail, cart, checkout, payment, inventory and essential external calls with realistic concurrency and data. Include background jobs if they compete with production requests or affect stock, pricing or fulfillment. A storefront-only test can miss a bottleneck in a payment gateway or another dependency.
Test safely and within platform rules
- Use a sandbox processor or an approved test environment where appropriate; confirm the commerce platform’s notification requirements and any seasonal testing restrictions first.
- Prevent test email from reaching real customers. Salesforce’s checklist warns that live test orders can incur GMV and recommends disabling test email sending to avoid floods.
- Use equivalent code, resources and data to production where the platform permits, and include third-party service calls wherever possible.
- Record where latency and errors appear in the journey, not only the overall request rate, so the team can distinguish storefront limits from dependency failures.
Shopify Engineering reports that its 2025 scale-testing program included five major tests. One reached 146 million requests per minute and more than 80,000 checkouts per minute; its final p99 test reached 200 million requests per minute. Shopify says its tests covered storefront browsing and checkout, admin/API traffic, analytics and reporting, webhooks, regional failover and cascading failures. These are Shopify platform engineering test results, not a target for an individual retailer.
4. Verify scaling and dependency failure behavior
For infrastructure you operate, check scaling policies, warm-up time, load balancing and health checks against the actual architecture. Scaling a component that takes several minutes to become useful will not solve a sudden burst unless it is prepared in advance. Managed commerce platforms expose capacity controls differently and may restrict load testing, so confirm the applicable controls and rules with the platform provider.
AWS Well-Architected guidance recommends AWS Auto Scaling for applicable resources and load balancing. It also notes that a CDN can serve cached content and reduce how much the underlying workload needs to scale. Treat these as AWS architecture recommendations, not platform-neutral requirements.
Set behavior for slow or unavailable services
List external services by business criticality. For each one, decide whether the shopper can still browse or buy if it slows down, what should be disabled or queued, and how the team will escalate with the provider. Salesforce’s 2026 B2C Commerce sale-event checklist suggests 1–3 second timeouts for storefront service requests and a maximum of 5–10 seconds for payment-provider timeouts in its context. It also recommends circuit breakers and rate limiting. These are Salesforce product guidance, not universal timeout standards.
Notify critical providers about event timing and expected demand, and confirm escalation contacts before the event. Identify a safe way to disable noncritical integrations if they become a source of latency or errors.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.5. Manage bots, crawlers and AI shopping agents deliberately
Holiday traffic can include scrapers, scalpers, credential stuffing and other automation as well as genuine shoppers. Salesforce recommends reviewing bot patterns and considering controls such as bot practices, CAPTCHA and rate limiting. Choose controls that protect checkout and origin capacity without needlessly blocking legitimate customers.
Inventory agent access instead of guessing at its impact
Shopping assistants may fetch product information and could generate additional requests, but the reviewed sources do not establish their share of holiday traffic or a reliable load multiplier. Inventory crawler and agent access, define which agents are authorized under your policy, and monitor their request rates and origin cost. Avoid blanket blocking or allowing without understanding the effects on security, discovery and service capacity.
Cloudflare’s 2026 holiday guidance presents a vendor approach combining edge DDoS protection, a branded waiting room, bot scoring, Web Bot Auth, WAF rules and machine-readable catalog content. Cloudflare also frames machine-readable product data as a way to help agents discover and recommend a store. These are Cloudflare’s product and vendor recommendations, not independent validation or evidence that every store needs those controls. If agent discovery matters to the business, make product information legible to machine consumers while applying the store’s own access policy.
6. Reduce change risk before the event
Review the calendar for deployments, replication, index builds, backups and heavy jobs that could compete with the live store. Salesforce recommends a code freeze several days before an event and, in its platform guidance, scheduling required replication at least four hours before a hype event. It also advises against heavy jobs and cache clears during peak. Keep campaign landing pages lightweight and cacheable where business rules allow.
Adobe’s September 30, 2026 playbook recommends monitoring storage use, slow queries, cron health, backups and cache warmup, and completing relevant security and performance updates before code freeze. For Adobe Commerce deployments, it cites keeping shared-files and database volumes below 70% usage; that threshold is platform-specific rather than a universal storage rule.
7. Run the event with named owners and decision triggers
Before traffic arrives, document alert thresholds, escalation steps, 24/7 contacts and rollback plans. Assign an owner to each critical alarm and rehearse the path to platform, payment and CDN providers. During the event, monitor latency and errors across the purchase journey, dependency health, quotas, capacity, cache behavior, bot traffic and job activity.
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Agree in advance when to throttle traffic, disable an optional feature, use a queue or waiting room, or roll back a change. A threshold without an owner and a corresponding action is only a notification; make sure the people on call can act on the signals your systems produce.
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