Prepare for holiday traffic by modeling your store’s own demand, reducing avoidable work at the origin, and testing the complete shopping path—including checkout and external services—before the sale. Add a separate plan for bots and AI shopping agents: identify which are welcome, monitor the load they create, and enforce a deliberate access policy. There is no established universal holiday traffic multiplier or quantified forecast for how much AI agents will add to a particular store’s traffic.
What should a holiday traffic plan account for?
A storefront is only one part of an order. A shopper may trigger requests to a CDN, application, database, inventory system, search service, fraud checker, payment provider, analytics tool, and other integrations. A page may load quickly while a dependency makes the cart or payment step slow or unavailable. Plan and test the whole request path, not just the pages a visitor sees.
Build the plan around the store’s platform, architecture, campaign schedule, and observed traffic. Salesforce recommends using previous peak periods and a reasonable growth assumption when modeling sale traffic, with equivalent code, resources, and data in load tests. Model both the shape of demand—a short burst, sustained traffic, or repeated surges—and the services each shopper journey calls.
When there is little history to use
If the store is new, a service has no representative traffic history, or the architecture has changed substantially, do not present an arbitrary multiplier as a forecast. Document the uncertainty and test multiple scenarios: for example, a short burst against a longer sustained load, with the relevant dependency available, slow, or failing. Shopify Engineering describes controlled tests of increased traffic, database latency, cache failures, regional failover, and cascading failures in preparation for its 2025 Black Friday/Cyber Monday period. Those tests describe Shopify’s infrastructure work; they are not a capacity prescription for an individual merchant.
Map the customer path and its owners
For each critical journey—browse, search, product detail, add to cart, checkout, and payment—record the systems involved, the team or provider responsible, and how to detect a failure. Include inventory, fraud, tax, shipping, and other services if the store calls them during a purchase. Mark optional features separately so the team knows what can be degraded or disabled without blocking orders.
How can you reduce unnecessary work at the origin?
Review which landing pages, product pages, and catalog responses can be cached without serving the wrong price, availability, customer-specific content, or other personalized data. Make campaign URLs consistent: arbitrary tracking parameters can create many distinct cache keys for otherwise identical pages. Adobe’s September 30, 2026 Adobe Commerce holiday playbook advises normalizing promotional tracking parameters and checking that campaign landing pages are cacheable. Salesforce likewise advises avoiding unique customer IDs or email addresses in campaign URLs where possible.
For Adobe Commerce PWA or headless storefronts, Adobe specifically recommends GraphQL GET to improve Fastly cache hit ratio and edge image optimization for image-heavy storefronts. These are Adobe Commerce-oriented recommendations; confirm that they fit the platform, caching layer, and business rules in use rather than applying them as generic ecommerce settings.
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Cache statistics can help show whether changes reduced requests reaching the application tier, but a target for one commerce platform is not a universal benchmark. Salesforce’s 2026 B2C Commerce guidance states that a cache hit ratio above 70% substantially reduces load reaching its application tier. Its article also describes one apparel retailer’s Black Friday flash sale: traffic reached 12 times its usual level, and the reported cache hit ratio rose from about 55% before readiness changes to above 80% afterward, alongside stable response times. That is a vendor-reported example, not a typical outcome or a forecast for other stores.
How should you test the complete sale path?
Run a test that represents realistic shopper activity and data across browsing, search, product detail, cart, checkout, payment, inventory, and essential external calls. Include background work when it competes with live requests or affects availability. A storefront-only test can miss a payment gateway or another dependency that becomes the limiting factor under load.
- Agree on a safe test environment. Check your commerce platform’s load-testing rules, seasonal restrictions, and notification requirements. Use a sandbox processor or other permitted test environment where appropriate.
- Reproduce the production shape. Use equivalent code, resources, and representative data where your platform allows it. Include realistic journeys and the third-party calls that matter to checkout.
- Test failure as well as capacity. Observe behavior when a dependency slows, times out, or becomes unavailable. Verify that failures do not cascade into the rest of the storefront.
- Protect customers and operations. Salesforce warns that live test orders can incur gross merchandise value (GMV); it also advises disabling test email sending to avoid sending floods of messages. Check any additional platform-specific safeguards before a test.
- Record the result in terms of your own service. Capture latency and errors through the full path, note the bottleneck and recovery behavior, and assign an owner to each follow-up.
Scale figures published by platform vendors should not be mistaken for retailer targets:
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| Published example | What it describes | How to use it |
|---|---|---|
| 146 million requests per minute and more than 80,000 checkouts per minute in one test; 200 million requests per minute in a final p99 test (Shopify Engineering, 2025) | Shopify’s own scale-testing program, which also covered storefront browsing and checkout, admin/API traffic, analytics and reporting, webhooks, regional failover, and cascading failures. | Use as evidence of the breadth of platform-level testing Shopify reported, not as a capacity benchmark for a merchant’s store. |
What should you check in scaling and external services?
If your team controls the infrastructure, verify that scaling policies, warm-up time, load balancing, and health checks match the application’s actual behavior. A scaling rule that reacts too slowly may not help with a sudden burst. A CDN can serve cached content and reduce the workload that needs to scale. AWS Well-Architected discusses AWS Auto Scaling and load balancing for applicable AWS resources; this is AWS architecture guidance, not a universal instruction for managed commerce platforms.
For every external service on the purchase path, confirm its role, timeout behavior, escalation contact, and failure mode. Decide in advance what happens if an optional function degrades: can it be disabled, queued, or temporarily bypassed without jeopardizing the order? Let critical providers know the sale timing and expected traffic, and verify how to reach them during the event.
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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →Salesforce’s 2026 B2C Commerce checklist gives the following timeout guidance in its platform context. These are not general timeout standards; choose values appropriate to your platform and customer journey.
| Salesforce B2C Commerce guidance | Scope |
|---|---|
| 1–3 seconds | Storefront service requests |
| Maximum of 5–10 seconds | Payment-provider timeouts |
Salesforce also recommends circuit breakers and rate limiting. Confirm that your implementation’s response to a timeout is safe—for example, that a customer is not encouraged to retry a payment in a way that can create duplicate attempts or unclear order status.
How should you handle bots and AI shopping agents?
Scrapers, scalpers, credential-stuffing attempts, and other automation can compete with shoppers for capacity. Treat their traffic separately from legitimate customer demand: monitor request rates and origin cost, review bot patterns, and choose controls based on the store’s policy and the behavior observed. Salesforce suggests considering bot practices, CAPTCHA, and rate limiting.
Shopping assistants may fetch product information and could add requests, but the official sources reviewed do not quantify AI agents’ share of holiday traffic or establish how much they will increase load at a given store. Treat agents as an access-management and observability question, not as a reason to assume a particular traffic increase.
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- Inventory the crawlers and agents accessing the store, and decide which are authorized under the business’s policy.
- Monitor their request rates, paths, and effect on origin capacity alongside other automated traffic.
- Distinguish legitimate agents from abusive automation before allowing or blocking traffic; avoid blanket rules without understanding their impact.
- If agent discovery is a business goal, check whether catalog information is machine-readable and accessible under the policy you intend to enforce.
Cloudflare’s 2026 holiday guidance frames AI shopping agents as part of bot management and recommends a vendor-specific combination of edge DDoS protection, a branded waiting room, bot scoring, Web Bot Auth, WAF rules, and machine-readable catalog content. Those are Cloudflare’s product and approach descriptions, not independent validation or a requirement that every store use Cloudflare.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should you freeze or prepare before the event?
Reduce avoidable change and workload close to the sale. Review scheduled deployments, replication, index builds, backups, cache warming, and heavy jobs that may compete with live requests. Salesforce’s B2C Commerce guidance recommends a code freeze several days before an event, scheduling required replication at least four hours before a “hype event,” and avoiding heavy jobs and cache clears during peak. It also advises keeping campaign landing pages lightweight and avoiding unique customer identifiers in email URLs where possible.
For Adobe Commerce deployments, Adobe’s September 30, 2026 playbook calls for monitoring storage use, slow queries, cron health, backups, and cache warmup, and for documenting alert thresholds, escalation steps, 24/7 contacts, and rollback plans. It recommends keeping shared-files and database volumes below 70% usage for Adobe Commerce deployments. That storage threshold is platform-specific, not a universal limit.
Make the event plan operational
Assign people to watch the customer journey and its dependencies during the sale. Before the event, confirm that alarms have owners and that responders can reach the platform, payment, CDN, and other critical providers. Rehearse what to do when latency or errors rise, a quota is reached, a dependency fails, or automation traffic spikes. Define the conditions for throttling, disabling an optional feature, using a queue or waiting room, and rolling back a change.
How do you choose controls that fit your store?
Do not choose a design or provider based on a single published traffic figure. Compare the options against the systems and failure modes the store actually has:
- Platform fit: Does the control work with the commerce platform and current CDN, application, and data architecture?
- Cache and personalization: Which content can safely be cached, and how are customer-specific responses and campaign parameters handled?
- Capacity and lead time: How quickly can capacity scale, and what warm-up or provider coordination does it require?
- Abuse and agent policy: Can the approach mitigate DDoS and harmful automation while handling authorized crawlers or AI agents according to policy?
- Checkout dependencies: What happens when payment, inventory, fraud, search, or another required service is slow or unavailable?
- Recovery and visibility: Can the team observe regional failover, errors, quotas, cache behavior, and escalation status, and can it roll back safely?
- Testing and operating cost: Are load tests permitted at the planned time, and what does sustained plus burst usage cost?
The cited vendor guidance covers different products and environments; it does not establish a universal provider winner or a comparative price/performance ranking. Use it as input to a plan validated against your own store’s architecture and policies.
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