Bot Traffic Is On the Rise: How Web Devs Can Manage Bandwidth Strain

AI training bots, search engine crawlers, and content scrapers now make up a meaningful share of crawl requests hitting websites. Reports already show that automated bots are rivaling or overtaking human traffic. In fact, Imperva’s 2025 analysis cites that 51% of all web traffic in 2024 came from bots, with AI accelerating the trend.

That surge in automated traffic affects the cost of operation, as well as the user experience (UX), of your site. And it’s not hypothetical. In a recent Clutch survey, 42% of small businesses reported performance or website bandwidth strain from bot traffic in the last 12 months. Alleviating the strain requires a layered approach that filters obvious bot traffic, rate-limits aggressive crawlers, and serves cached responses on heavy endpoints, so real users aren’t competing with scrapers and AI crawlers for finite resources.

In this article, we'll discuss how web devs can combine preventative controls with protective enforcement to preserve site performance, protect compute and egress spend, and maintain a smooth experience for real users. Let's get started.

The Growing Challenge of Bot Traffic

The strain comes from many kinds of automated traffic. Understanding the main types of bots and their impact helps focus the fixes.

Types of Bots

Not all bots are bad, and lumping them together creates blind spots. Let’s break down the four main types of bots:

• AI training crawlers: Examples include OpenAI GPTBot and Anthropic ClaudeBot. They fetch public pages for model training or to assist users during queries. OpenAI transparently publishes GPTBot’s documentation and robots.txt directives, and Anthropic explains how site owners can allow or restrict its bots (and distinguishes ClaudeBot from the Claude-User agent that fetches content during user prompts).
• Scrapers and content harvesters: These bots copy content or extract prices and inventory. They often hit the same endpoints repeatedly and spike bandwidth.
• Malicious bots: Automated malicious bots attempt credential stuffing, spam form submissions, and inventory hoarding. They aim to disrupt users or abuse business logic.
• Legitimate bots: These are search engine crawlers and uptime monitors that support discovery and reliability. Legitimate bots usually follow robots.txt rules and rate limits.

All these automated bots together create a messy traffic mix on your website.

The Impact of Bot Traffic on Small Business Websites

For small sites, heavy bot traffic turns into real costs and slow pages.

• Increased hosting bills: Bots drive up CDN egress, origin requests, and database calls, which pushes you into higher tiers or overage fees.
• Throttled bandwidth: Many plans cap monthly transfer. Bot surges hit that cap and trigger throttling or rate limits that slow delivery for everyone.
• Degraded user experience: Pages start loading slower, actions time out, and checkouts fail more often, which leads to lost sessions and revenue.

To tackle this, a few media organizations had publicly blocked AI crawlers after seeing a sustained load without benefit. For instance, The New York Times, CNN, and ABC disallowed GPTBot in 2023, which put a spotlight on the cost/benefit calculation at scale. If large publishers with hefty CDNs take that stance, it’s no surprise smaller teams get caught off guard when aggressive crawling starts to look like a low-grade DDoS.

How Bot Traffic Causes Bandwidth Strain

Bandwidth strain starts with resource consumption. Repeated, concurrent fetches of the same heavy endpoints create needless egress and CPU churn. These types of fetches include:

• Product search
• Content feeds
• Uncompressed media

Add that up with recursive link-following, and you’re shipping gigabytes of duplicate bytes while the website bandwidth meter climbs up.

The next visible effect is performance bottlenecks. When bots own the queue, latency rises for everyone else. Slow page loads raise bounce rates and suppress conversion. Even if you’re tuned for throughput, head-of-line blocking from unthrottled crawls will show up in p95–p99 metrics first, then in user complaints.

There’s a financial impact, as well. Cloud egress and CDN fees scale linearly with bytes you don’t actually need to serve. Teams may report unpleasant surprises when scrapers loop on JSON APIs or download full-resolution assets that were never meant for automated retrieval. Bots already represent more than half of the total traffic, and without intervention, that bandwidth load will push infrastructure spending up.

Finally comes the opportunity cost. When the bandwidth is saturated, your legitimate sessions lose capacity, search bots that do matter get throttled, and the team spends time firefighting these issues rather than shipping meaningful products.

How Web Devs Can Manage Bandwidth More Effectively

Countermeasures work best in layers. It's best to start with clear signals, then back them with rate limits, smart caching, and layered detection. The goal isn’t to ban all automation; it’s about channeling useful bots and throttling the rest so that user experience isn't negatively impacted.

Optimize robots.txt / LLMs.txt Policies

Robots.txt remains a basic control for reputable crawlers. Define allow and disallow rules for GPTBot and Claude agents so crawl behavior matches your policy.

As mentioned earlier, OpenAI clearly documents how to allow or block GPTBot in robots.txt. For such cases, devs often start with a scoped allowlist for directories that make sense for discovery, and disallow the rest.

Beyond robots, LLMs.txt has emerged as a proposed standard to guide AI crawlers with more nuance, such as describing what’s useful, preferred formats, or rate guidance. While not a standard and not universally honored, it’s gaining momentum across developer communities and CMS ecosystems. For now, you can treat it as advisory. Treat robots.txt as guidance for good bots, but don't rely on it as an enforcement tool to stop abusive traffic.

Operationally, here are a few practical points to consider:

• Publish precise user-agent blocks or allowances (e.g., User-agent: GPTBot).
• Keep the file small and cacheable.

Pair policy with server-side controls. Some agents ignore directives, so plan for enforcement beyond signals. DataDome’s 2025 Global Bot Security Report, for instance, argues that static directives alone won’t deter modern AI-driven bots.

Set Crawl Rate Limits

Not every bot respects Crawl-delay, and Google ignores it, too. This is expected because enforcement belongs at your edge. To enforce your crawl policy, devs can rate-limit by IP, AS (Autonomous System), or user-agent group, and return 429s with a Retry-After header when thresholds trip. CDNs and edge platforms make this implementation straightforward:

• Vercel exposes a “Block AI Bots” firewall template you can adapt for GPTBot and peers.
• Cloudflare, Fastly, and Akamai offer rate controls that tie to bot scores or request characteristics, such as method, path, JA3 fingerprints, and cookie presence.

However, it's advisable to keep rate policies distinct from DDoS modes so you can tune limits for sustained, polite-looking crawls that still drain website bandwidth.

Implement Caching Strategies

Caching is one of the most affordable performance and bandwidth control measures when you design for it.

Here are three practical moves to reduce origin hits from bot traffic:

1. Normalize URLs so trivial query differences don’t cause cache misses. If /product?id=123&ref=a and /product?id=123&ref=b return the same JSON, strip or ignore ref at the edge.
2. Adopt stale-while-revalidate to serve warm responses while refreshing in the background. In this way, caches keep serving humans (and even bots) without hammering the origin.
3. Publish lightweight, bot-friendly representations, such as compressed JSON and static snapshots for routes that attract scraping. If a bot insists on crawling, let it fetch cheap bytes.

Even 1 to 5 seconds of TTL (Time to Live) on read-heavy endpoints turns hundreds of near-simultaneous requests into a single origin call.

Use CDNs Wisely

A CDN only helps if it actually serves the traffic. Here's how to push more responses to the edge:

• Serve static assets and cacheable HTML from the edge with sensible expiration times.
• Vary the cache only on headers that change the response, such as Cookie.
• Cut origin hits by fixing cache gaps on popular routes and keeping cache keys consistent.

Most CDNs also let you classify traffic and set per-class policy, which is useful when grouping known training crawlers, scrapers, and legitimate search bots. If a bot is cooperative, you can serve from a dedicated, highly cached path. If it’s aggressive, apply lower limits or block at the edge outright.

Brands that deployed commercial bot solutions at the CDN/WAF layer report both performance gains and lower transfer. For example, HUMAN’s ZALORA case study shows an approximately 30% reduction in hosting and bandwidth costs after filtering out automated sessions.

Monitor Logs

You already have the data: edge logs, WAF logs, and CDN analytics. Direct them to a time-series store and build quick looks for:

• New or spiking User-Agents and unexpected robots.txt hits
• ASN shifts (sudden concentration in hosting providers)
• Path heatmaps weighted by bytes, not just hits
• Status code deltas (401/403 patterns reveal credential-stuffing probes)

Cloudflare Radar’s new AI bot insights are useful as a benchmark for what classes of AI crawlers show up by industry. You can compare your mix to what they report.

Use Bot Detection Tools

Homegrown filters help, but they won’t catch sophisticated automation that spoofs browsers and farms residential IPs. That's where commercial offerings become useful. They add multi-signal detection, such as behavioral analysis, browser and device fingerprinting, IP reputation, ASN weighting, and JS instrumentation. Here are a few common options to choose from:

• Cloudflare Bot Management: Packed with WAF and Workers
• DataDome: Client-side signals and API protection. One case study shows a 75% drop in total bot traffic
• HUMAN: Formerly White Ops, ensures that every digital interaction is authentic, secure, and human
• Netacea: Publishes ROI models and cost-of-bots research

Many bots now mimic human patterns or ignore static directives entirely, so combining detection with enforcement beats policy-only approaches.

Utilize WAFs and Firewalls

This is where you stop bot traffic that refuses to play nice.

• Build rules to block by IP ranges, ASN, data center providers known for automated activity, and suspicious patterns (e.g., rapid traversal of detail pages without referrers).
• Keep a quarantine list with timed expirations to avoid permanent over-blocks.
• For emerging AI crawlers, publish and reference your allow/deny lists in version control to make changes auditable.

When an agent repeatedly ignores robots.txt or LLMs.txt, move up the stack: 403 at the edge, then country or ASN blocks if needed.

For instance, some reports highlight that ClaudeBot continues to crawl despite robots.txt restrictions. Given the risk of noncompliance, build your defenses on controls you can enforce.

Best Practices for Long-Term Site Health

So, how do you stop bot traffic? Here are the key best practices to protect website bandwidth and performance without cutting off discovery or partners:

• Don’t block all bots: Legitimate crawlers (search engines, uptime checks) drive discovery and reliability. Keep them allowed, but scope access to what’s useful and cacheable.
• Regularly update bot detection rules: Rotate IP lists, tighten signature rules, and adjust behavioral thresholds based on new scraping patterns in your logs.
• Stay informed about new AI crawlers and published IP lists: Monitor vendor documentation, such as OpenAI GPTBot updates and Anthropic’s Claude agents, and industry trackers for new identifiers.
• Combine automated defenses with human monitoring: Automated tools catch the obvious, but humans notice anomalies in referrers, dwell time, and session shape. Confirm with log samples before broad blocks.
• Document bandwidth incidents to refine policies over time: Keep a short post-incident template: which agents, which paths, byte totals, mitigation steps, and what to codify in robots.txt, WAF, and cache rules. Over time, this can help build a standard policy across your organization.

You can treat best practices as a base review item. But as bot traffic evolves, so should your defenses.

Allocate Bandwidth Like a Budget

Bot traffic is a structural component of the web now. However, not all bot traffic is bad. For instance, Google, ChatGPT, and Perplexity’s search crawler may bring referral traffic and citations, while other scrapers may be pure bandwidth cost.

As a result, the solution can't be a single "block all" switch. Instead, it should be a practical mix of signals, controls, caching, and enforcement that keeps UX fast and makes bots cheap to serve. For dev teams, that layered approach protects performance, reins in egress, and reserves capacity for the sessions that move the business forward.

Your policies should reflect that trade, and your tech stack should enforce it.

About the Author

Hannah Hicklen Content Marketing Manager at Clutch

Hannah Hicklen is a content marketing manager who focuses on creating newsworthy content around tech services, such as software and web development, AI, and cybersecurity. With a background in SEO and editorial content, she now specializes in creating multi-channel marketing strategies that drive engagement, build brand authority, and generate high-quality leads. Hannah leverages data-driven insights and industry trends to craft compelling narratives that resonate with technical and non-technical audiences alike. 

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