# How to Get Your Side Project Ready for a Traffic Spike
> Get your side project ready for a traffic spike: find weak pages, cache the landing page, cap paid calls, load test safely and plan a spike mode for work.

```yaml
url: "https://sidehunt.io/studio/how-to-get-your-side-project-ready-for-a-traffic-spike"
markdown: "https://sidehunt.io/studio/how-to-get-your-side-project-ready-for-a-traffic-spike.md"
title: How to Get Your Side Project Ready for a Traffic Spike
slug: how-to-get-your-side-project-ready-for-a-traffic-spike
category: Growth
tags:
  - side projects
  - traffic spike
  - hug of death
  - load testing
  - caching
  - CDN
  - launch prep
  - serverless
  - indie makers
  - Growth
published_at: "2026-10-30T10:59:08.640Z"
updated_at: "2026-10-30T10:59:09.000Z"
featured_image: "https://txmhk1zrnc.ufs.sh/f/xSkWTCqmKWx90UaltR7uUMGtDgAeTkzHpnxayuvbZw12cLKE"
```

## Article

To get your side project ready for a traffic spike, find the one or two pages a spike will hit, make those pages cheap to serve (static or cached HTML behind a CDN, small images, no database call per view), put limits on anything that costs money per visit (AI calls, signup emails, database connections), set a spend alert before the day, and write a five-minute "spike mode" plan you can run from your phone at work: a light fallback page that still collects emails, signups switched to a waitlist, and heavy features turned off. Then spend the spike turning visitors into emails, not refreshing a dashboard.

This is for people with a day job running a side project on cheap or free hosting who might land on the Hacker News front page, a big subreddit, a newsletter or a viral post with no warning. Provider docs linked here were checked on 30 October 2026 and change often, so check your own plan. The worked example is made up.

## What does a traffic spike actually look like?

A spike is not your normal traffic times ten. It has a shape, and the shape tells you what to prepare:

- It lands on one or two URLs. The exact link someone shared, plus your homepage.
- Almost everyone is new and logged out. No account, no patience. They decide in seconds.
- Many are on phones. Links shared in social apps get opened on mobile, often on slow connections. Check your own analytics rather than trusting anyone's ratio.
- It is short. Most of it arrives while the link sits near the top of wherever it was posted, then it fades.

The old name for the crash version is the Slashdot effect, also called the [hug of death](https://en.wikipedia.org/wiki/Slashdot_effect): a big site links to a small one and the small one falls over. Wikipedia's entry lists the usual victims as sites on home servers or shared hosting, sites with large images or video, and pages that hit the database many times for every visit even when everyone requests the same page. That last one is the side project trap.

## Why do small sites crash from traffic?

When a website crashed from traffic, the reason is rarely "the server was too small." Usually each visit did more work than it needed to, and the work piled up somewhere with a hard ceiling. Common ceilings on a side project:

- A server-rendered page that queries the database on every view, even though the answer is the same for every visitor.
- A database that allows only a small number of open connections, with each serverless function opening its own.
- A third-party API, often an AI model, called once per visit or once per page load.
- An email provider with a daily cap, hit by signup confirmations.
- A free hosting plan that pauses your site when you use up the month's allowance.

Modern hosts scale well, so the failure is often a paused account, a database refusing connections, or a surprise bill rather than a dead server.

## How do you find your weak points in one evening?

- List the pages a spike would hit. The homepage, the page you would share, and the signup flow.
- Trace one request for each. Open the route's code and write down what it does: server render or file, database queries, external API calls, writes, emails.
- Weigh the page. Load it on your phone and note the image sizes and any third-party widgets (chat bubbles, embeds, video players).
- Read your plan's limits. For each service on the trace, note what happens at the limit: slower, error, pause or bill.

Put it in a table like this. The cheap fixes are all most side projects need.

Component

What breaks under a spike

Cheap fix

Landing page HTML

Server render plus database query on every view

Serve it static or cache it at the CDN for a few minutes

Images

Huge files eat bandwidth and slow mobile visitors

Resize to display size and compress before upload

Database connections

"Too many connections" errors when functions scale out

Use your provider's pooled connection string

View counters and "last seen" writes

One write per visit turns reads into a write storm

Drop them on public pages or count in analytics instead

AI or other paid API calls

Cost and rate limits scale with visitors, not customers

Only call after signup, cache demo results, cap per user

Signup emails

Daily send cap reached, new users never get the link

Know the cap; switch to a waitlist if you get close

Free hosting allowance

Site paused for the rest of the month

Know the pause rule before the day and decide in advance

![Rows of black server rack cabinets with red and blue cables behind mesh doors in a bright data center](https://images.pexels.com/photos/5480781/pexels-photo-5480781.jpeg?auto=compress&cs=tinysrgb&w=1200&h=800&fit=crop)

## How do you make the landing page cheap to serve?

The most useful change is making the page a spike hits cost almost nothing per view. If it is a plain file on a CDN, most traffic never reaches your code.

If your framework can pre-render the page at build time, do that for the homepage and anything you plan to share. If the page must be dynamic, let a shared cache hold it for a short time. The [Cache-Control reference on MDN](https://developer.mozilla.org/en-US/docs/Web/HTTP/Reference/Headers/Cache-Control) explains the two directives that matter here: `s-maxage` sets how long a shared cache such as a CDN treats the response as fresh, and `stale-while-revalidate` lets the cache keep serving the stale copy while it fetches a new one in the background. A header like `Cache-Control: public, s-maxage=300, stale-while-revalidate=600` (example values, pick your own) means your origin sees roughly one request per cache location every few minutes instead of one per visitor.

Two warnings. First, never cache personalised responses in a shared cache; MDN says to mark those `private`. Keep the cached page logged-out and identical for everyone. Second, check that your CDN actually caches HTML. Cloudflare's docs on [default cache behavior](https://developers.cloudflare.com/cache/concepts/default-cache-behavior/) say it does not cache HTML or JSON by default, so you need a cache rule for it.

Then trim the page: resize images to their display size, move chat widgets and embedded video off the shared page, and load anything heavy only after a click. For deeper speed work, see the IndieHunt guide to [passing Core Web Vitals on an indie SaaS site](https://indiehunt.io/studio/how-to-pass-core-web-vitals-on-your-indie-saas-site).

## How do you protect the expensive paths?

Once the page is cheap, the remaining risk is anything that costs money or has a hard cap.

- AI calls. Never run a model on page load for anonymous visitors. Show a saved example result and call the model only after signup, with a per-user cap and a simple rate limit on that endpoint.
- Emails. Know your provider's limit before the day. For example, [Resend's free plan quotas](https://resend.com/docs/knowledge-base/account-quotas-and-limits) list 100 transactional emails a day, resetting at midnight UTC. New users who never get their magic link just leave.
- Database connections. Serverless functions can each open their own connection. Neon's [connection pooling docs](https://neon.com/docs/connect/connection-pooling) show a 0.25 CU compute with a max_connections of 104 (7 reserved), while its PgBouncer pooler accepts up to 10,000 client connections. Supabase's [connection guide](https://supabase.com/docs/guides/database/connecting-to-postgres) recommends its shared pooler in transaction mode for serverless and edge functions. Use the pooled string in production.
- Writes on public pages. View counters, "trending" scores and last-seen timestamps turn every visit into a database write. Remove them from shared pages or batch them.
- Nonessential features. Put an off switch on anything heavy (a live demo, search, an AI preview) using an environment variable or a config row you can flip without a deploy. If you want the full pattern, MakerHunt has a guide on [shipping risky changes behind feature flags](https://makerhunt.io/studio/how-to-ship-risky-changes-behind-feature-flags).

## How do you load test a side project without breaking your host's rules?

A short load test shows where things break before strangers find out. Read your host's policy first, because many forbid load testing their platform. Vercel's [load testing policy](https://vercel.com/kb/guide/what-s-vercel-s-policy-regarding-load-testing-deployments) says it is only permitted on Enterprise plans and that unannounced tests may get your IPs blocked. Netlify's [scope of support](https://www.netlify.com/support-scope/) puts load testing under a custom contract with a week's notice. Cloudflare's [Workers limits page](https://developers.cloudflare.com/workers/platform/limits/) warns that many requests from a few IPs can trigger its abuse protection. Never load test third-party APIs, including your AI provider.

What you can do is test your own code: run the production build on your laptop or a VPS rented for an hour, point it at a copy of your database, and stub out paid APIs. Then use an open-source tool:

- [k6](https://grafana.com/docs/k6/latest/testing-guides/test-types/spike-testing/), which has a spike-test pattern: ramp up fast, no plateau, ramp down.
- [hey](https://github.com/rakyll/hey), a small command-line tool; something like hey -z 30s -c 20 http://localhost:3000/ runs 20 concurrent workers for 30 seconds.
- [oha](https://github.com/hatoo/oha), a hey-style load generator with a live terminal view.
- [autocannon](https://github.com/mcollina/autocannon), an HTTP benchmarking tool written in Node.js.

Start low and step up. Watch error rate, response time as concurrency rises, and database connections. The useful result is not a big number; it is the first thing that breaks.

## How do you keep a spike from turning into a scary bill?

Set budget alerts and spend caps before you share anything. The SideHunt post on [keeping side project bills under $20](https://sidehunt.io/studio/how-to-keep-your-side-project-monthly-bills-under-20) covers the settings; here are the spike-specific parts.

Know which way your plan fails. On Vercel's [Hobby plan](https://vercel.com/docs/plans/hobby), exceeding a usage limit usually means waiting until 30 days have passed to use that feature again, and Hobby is for non-commercial personal use. On Vercel Pro, [Spend Management](https://vercel.com/docs/spend-management) can notify you, call a webhook or pause production, but Vercel checks every few minutes, so usage can run past your amount. Netlify's free plan [pauses your projects](https://docs.netlify.com/manage/accounts-and-billing/billing/resume-paused-projects/) when you use up the monthly limit, and visitors see "Site not available" until the next cycle or an upgrade.

On paid plans, look up bandwidth and per-request pricing. Pay-per-use is great until something hammers an expensive endpoint. Researchers call that [denial of wallet](https://arxiv.org/abs/2104.08031): the service stays up and your bill takes the hit. Caps on your own endpoints are the defence.

![Long exposure of a highway at night with teal and red light trails from fast-moving traffic](https://images.pexels.com/photos/30195133/pexels-photo-30195133.jpeg?auto=compress&cs=tinysrgb&w=1200&h=800&fit=crop)

## What is your spike mode plan when you are at work?

The spike will start while you are in a meeting. Keep this plan as a note on your phone, with every step doable in five minutes from a browser:

- Check the shared page loads on mobile data, not office wifi.
- If it is slow or erroring, switch to the fallback page. A static page with one paragraph about the project and an email form. Keep it deployed at a second route so switching is a redirect, not a build.
- Turn signups into a waitlist if emails or onboarding are the bottleneck. "We're letting people in in batches" is fine.
- Flip off heavy features with the switch you set up earlier.
- Have one helper on standby, a friend who can read your logs.

Alerts that tell you the site is struggling are a separate job; the SideHunt guide to [monitoring a side project during your day job](https://sidehunt.io/studio/how-to-monitor-a-side-project-during-your-day-job) covers that side.

## How do you turn spike visitors into something that lasts?

- Put email capture above the fold on the shared page: one field, one button, one line about what they get.
- Give one clear next step, not four competing links.
- Add a short "if you came from..." note answering the question the thread is asking.
- Measure the source. Make sure your analytics shows referrers and signups for that page; the SideHunt guide to [analytics you'll actually check](https://sidehunt.io/studio/how-to-set-up-analytics-for-a-side-project-youll-actually-check) keeps it small.
- Reply in the thread where the link was shared, as a person, answering questions.

## What should you check the day after the spike?

The next evening, check:

- The bill and usage dashboards for every service on your trace.
- Errors and timeouts during the spike window.
- Signups and email captures by source, not just visits.
- What broke or nearly broke, and which spike mode steps you used.

Write a short note: what held, what failed, what you will change. The next spike is easier with it.

## Which traps catch builders during a traffic spike?

Trap

Why it hurts

Do this instead

Upgrading to a bigger server in a panic

The bottleneck is usually the database or an API, not CPU

Trace the request and fix the slow step

Caching a page that shows user data

One visitor's details shown to everyone

Cache only logged-out pages; mark the rest private

Running a demo AI call for every visitor

Costs scale with readers, not customers

Show a saved example; call the model after signup

Shipping a fix in the middle of the spike

A bad deploy is worse than a slow page

Use the fallback page and switches; fix tonight

Only counting visits

You learn nothing about who stayed

Count emails and signups by source

## A made-up example: Leocadia and Pebbleroll

This example is invented, and so are its numbers. Leocadia is a pharmacist who climbs on weekends. Her side project, Pebbleroll, logs bouldering sessions and has one popular public page: a climbing grade conversion chart she expects to be shared in a big climbing community.

Her trace found three problems: the chart was server-rendered from the database on every view, a view counter wrote a row per visit, and a "describe this problem" box called an AI model for anyone, logged in or not.

Over two evenings she pre-rendered the chart, deleted the counter, moved the AI box behind signup with five calls a day per account, switched to the pooled database string, and added an email form under the chart. A hey run on a rented VPS against a database copy showed signup slowing first, because it sent the confirmation email inside the request, so she moved it to a background job.

In this made-up scenario the link lands on a Tuesday morning while she is at work. The chart loads on her phone, so she does nothing until lunch. Her next-day note: chart held, signups held, 41 email captures from the community link, and the email cap was closer than she liked, so "switch to waitlist" goes into her spike plan.

## A 7-day plan to prepare your website for launch traffic

Day

Task

Done when

1

List spike pages and trace one request each

Weak-point table filled in

2

Make the shared pages static or cached

Page served from CDN, no database call per view

3

Resize images, move heavy widgets off shared pages

Page loads fast on mobile data

4

Pooled database string, remove per-visit writes, cap paid calls

No expensive call runs for anonymous visitors

5

Small load test on your own build

You know the first thing that breaks

6

Spend alerts, fallback page, feature switches

Each switch tested once

7

Email capture, one next step, spike mode note on your phone

A friend can follow the note without you

Timings are suggestions. If you only have one evening, do days 1, 2 and 6.

## FAQ

### Will Vercel, Netlify or Cloudflare free plans survive the Hacker News front page?

Static files on a CDN are the part least likely to fall over from Hacker News front page traffic; the risk is the dynamic parts and your plan's limits. Read the limit pages for your plan: Vercel Hobby usually makes you wait 30 days to use a feature again after you exceed its limit, Netlify Free pauses projects until the next cycle, and on Cloudflare the Workers Free plan has a daily limit of 100,000 requests that also covers Pages Functions. Plain static assets are the safest thing to serve.

### Should I upgrade my hosting plan before launch?

Only if your plan's failure mode is a pause you cannot accept, or your project is commercial and the free plan does not allow that. A cheap shared page usually helps more than a bigger plan.

### What is the hug of death?

It is the informal name for a small site going down after a popular site links to it, also called the Slashdot effect. The traffic is welcome; the site simply was not built for that many visitors at once.

### Do I need a load balancer or Kubernetes for a traffic spike?

No. For a side project, caching the landing page, pooling database connections and capping paid calls do far more than new infrastructure you would then have to maintain on weekends.

## Get the boring parts ready, then enjoy the spike

A traffic spike is a gift if the page stays up and asks for an email. Do the trace, make the shared page cheap, put switches on the expensive parts and keep the plan on your phone. And when you want people who browse side projects on purpose to find yours, list it on [SideHunt](https://sidehunt.io/).

## Links

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_HTML version: https://sidehunt.io/studio/how-to-get-your-side-project-ready-for-a-traffic-spike_