Optimizing HTTP Requests in 1C-Bitrix

During Bitrix project audits we regularly encounter pages with 180–250 HTTP requests on load. This is no exaggeration: each component can add 2–4 CSS files and 3–5 JS files, plus icons as separate PNGs, plus analytics trackers, plus widgets. Each request means DNS, TCP, TLS, response headers. With HTTP/1.1 the browser holds 6 parallel connections per domain. HTTP/2 multiplexing helps but does not eliminate overhead entirely. With over 10 years of Bitrix development experience, we see that clients often have no idea how many extra requests a typical template generates. We can audit and reduce requests by a factor of 2–3, saving your site maintenance budget. The cost of optimization is calculated individually based on scope.

Audit of the Current State

The first step is to measure, not guess. Tools:

• Chrome DevTools → Network: look at Requests, Transferred, DOMContentLoaded, Load columns
• WebPageTest — waterfall grouped by type
• Lighthouse: metrics "Serve static assets with an efficient cache policy" + "Avoid chaining critical requests"

A typical waterfall: HTML → CSS (×5) → fonts (×6) → JS (×8) → images (×40+) → component Ajax requests (×3–5). We analyze each chain and find reduction points. We guarantee that after optimization the request count will not exceed 100 for a typical catalog.

How to Merge CSS and JS Without Losing Functionality?

Built-in Bitrix Combiner

In the main module settings (/bitrix/admin/settings.php?lang=en) there are options "Combine CSS files" and "Combine JS files". The combiner merges files into one request /bitrix/cache/css/[hash].css. It works but has nuances:

• It merges only files from AddCSS() / AddHeadScript(), not inline component styles.
• Cache invalidation (editing any file) changes the hash — browsers download anew.
• It does not minify CSS/JS — only concatenation.

Webpack/Vite for Custom Resources

For your own code (not Bitrix kernel) we configure a bundler:

// vite.config.js
export default {
    build: {
        rollupOptions: {
            input: {
                main: 'local/templates/main/src/main.js',
                catalog: 'local/templates/main/src/catalog.js',
            }
        }
    }
}

We get 2 bundles instead of 15+ separate files. Splitting into main and catalog is important: don't load catalog JS on static pages.

How to Reduce Icon Requests with SVG Sprites?

Each icon as a separate file is the fastest way to get 30–50 extra requests. CSS sprites (one large image) reduce requests by 40 times compared to individual PNGs. In practice, SVG sprites are better:

<!-- sprite.svg -->
<svg xmlns="http://www.w3.org/2000/svg">
    <symbol id="icon-cart" viewBox="0 0 24 24">...</symbol>
    <symbol id="icon-search" viewBox="0 0 24 24">...</symbol>
</svg>

<!-- usage -->
<svg><use href="/local/templates/main/img/sprite.svg#icon-cart"></use></svg>

One HTTP request for the entire site iconography. Cached long-term. Inline SVG via PHP helper gives 0 requests but increases HTML size. The choice depends on the number of first-screen icons.

Why Do Component Ajax Requests Slow Down Loading?

Bitrix components with 'AJAX_MODE' => 'Y' make a separate XHR when navigating catalog pages. That's normal, but during page initialization we often see several parallel Ajax requests to ajax.php with different parameters. The solution is batching: combine multiple requests into one via a queue:

// Accumulate requests for 50 ms, then send batch
const queue = [];
function batchRequest(params) {
    queue.push(params);
    if (queue.length === 1) {
        setTimeout(() => {
            const batch = [...queue];
            queue.length = 0;
            fetch('/api/batch', {
                method: 'POST',
                body: JSON.stringify(batch)
            });
        }, 50);
    }
}

On the server side — an endpoint /api/batch that dispatches requests and returns an array of responses. Certified Bitrix specialists ensure correct integration.

Images: Lazy Loading and Sprites

Catalog images are the largest source of requests. Minimal requirement:

// In catalog.element component template
echo '<img src="' . $arItem['PREVIEW_PICTURE']['SRC'] . '"
           loading="lazy"
           width="' . $arItem['PREVIEW_PICTURE']['WIDTH'] . '"
           height="' . $arItem['PREVIEW_PICTURE']['HEIGHT'] . '"
           alt="' . htmlspecialchars($arItem['NAME']) . '">';

loading="lazy" is native lazy loading. The browser does not request images below viewport until scrolling. On a catalog page with 48 product cards, this removes 30–40 requests from the critical path.

How to Measure Optimization Results?

We use metrics: total request count, Load Time, and LCP. A practical example: an electronics online store on Bitrix. Home page: 214 HTTP requests, Load time 8.3 s. After our actions: enabling CSS/JS combiner, SVG sprite of 64 icons, loading="lazy" for below-the-fold images, deferring trackers, merging custom JS via Vite. Result: 214 → 88 requests, Load time: 8.3 s → 3.1 s, LCP: 5.2 s → 1.9 s.

According to Wikipedia, reducing requests is critical for mobile networks.

What Is Included in the Work?

• Audit of current request count and load waterfall.
• Enabling the built-in combiner, cache configuration.
• Building an SVG sprite and replacing icons.
• Configuring Vite/Webpack for custom resources.
• Implementing a batch mechanism for Ajax.
• Adding loading="lazy" and image optimization.
• Deploying HTTP/2 Push (example Nginx config: add_header Link "...";).
• Documentation of results, training your team.
• 1 month of support after optimization.

Contact us to start optimizing your site. Order an audit and get personalized recommendations. We guarantee results, enshrined in the contract.

80% of Bitrix sites slow down due to one table

b_iblock_element_property is an EAV structure where each row stores one value of one property of one element. A catalog of 50,000 products with 30 properties yields 1.5 million rows. The smart filter performs a JOIN of this table with b_iblock_element on five properties, and MySQL performs a full table scan for 3–5 seconds. Our experience shows that without intervention in this table, site acceleration is impossible. We take on projects where load time has dropped to 8–10 seconds and bring TTFB back to <200 ms within 1–2 weeks. Site speed optimization begins with an audit of slow queries and ends with a comprehensive turnkey infrastructure overhaul.

Contact us for an audit — we will identify bottlenecks within 2 hours and propose a concrete plan.

How to achieve TTFB below 200 ms?

Server optimization is the first step. Nginx configuration goes beyond simple gzip. Specifically:

• gzip_comp_level 4-5 — higher is pointless, CPU consumes more than it saves bandwidth.
• brotli on with brotli_static on for precompressed files.
• HTTP/2 with http2_max_concurrent_streams 128.
• fastcgi_cache for PHP responses — caching at Nginx level, bypassing PHP-FPM entirely.
• worker_processes auto, worker_connections according to the number of simultaneous connections.

PHP-FPM tuning: choose between pm = dynamic and pm = static. Static mode works best for dedicated servers with predictable load because it avoids forking overhead. Dynamic saves RAM under low traffic. Calculate pm.max_children as (available RAM - RAM for MySQL/Redis) / average process consumption. For OPcache set memory_consumption=256, max_accelerated_files=20000, and validate_timestamps=0 in production (restart PHP-FPM on deploy).

MySQL/MariaDB: the main bottleneck is almost always the database. Enable slow_query_log with a threshold of 0.5 sec and analyze every query via EXPLAIN. Set innodb_buffer_pool_size to 70–80% of available RAM on a dedicated server. Create composite indexes for faceted search: (IBLOCK_ID, IBLOCK_PROPERTY_ID, VALUE) on b_iblock_element_property. Run OPTIMIZE TABLE b_iblock_element_property after mass operations.

How to configure three-level caching?

Managed component cache. Set TTL individually for each component. Catalog — 3600 sec, news feed — 300 sec, banners — 86400. The same TTL everywhere guarantees either outdated data or useless cache.

Composite cache. The bitrix:composite technology lets Nginx serve ready HTML from a file; PHP is not executed. Dynamic zones (cart, authorization) are loaded via AJAX request through CBitrixComponent::setFrameMode(true). TTFB drops below 50 ms. However, not all components are compatible; $APPLICATION->ShowPanel() and direct output via echo break the composite. We check every page through the panel 'Performance → Composite Site'. According to Bitrix official documentation on composite cache, this is the most effective caching method for high‑load projects.

Comparison: composite cache is 10–20 times faster than managed cache in time to first byte.

Memcached / Redis. Transfer cache from the file system: sessions go to Redis (session.save_handler = redis) — 10–50 times faster than files, plus cluster support. Component cache goes to Memcached via .settings.php: 'cache' => ['type' => 'memcache']. Also enable ORM query cache so identical GetList() calls don't hit MySQL on every request.

What is the fastest way to optimize Bitrix database?

Default MySQL settings are insufficient. Indexes — composite for faceted search, covering for frequent queries. MySQL responds from the index without accessing the data. Partial indexes (MariaDB) for filtering by ACTIVE = 'Y'. Audit unused indexes — each slows down INSERT/UPDATE.

Partitioning. For tables with millions of rows: b_stat_session, b_search_content_stem, and highload-blocks with history. Partition by date — a query for 'orders in a month' does not scan three years of data. Partitioning also solves the problem of concurrent queries during exchange with 1С via CommerceML.

Real case: a catalog of 200,000 products, 50 properties. Filtering by 10 properties took 12 seconds. After creating composite indexes on (IBLOCK_ID, IBLOCK_PROPERTY_ID, VALUE) and partitioning b_iblock_element_property by IBLOCK_ID, execution time dropped to 0.3 seconds. MySQL load decreased by 40 times.

Cleanup. Over a year or two, any database accumulates: outdated search index, expired records in b_cache_tag, history in b_iblock_element_prop_s*, logs in b_event_log taking gigabytes. We set up regular cleanup via agents.

Frontend and CDN

Images account for 60–80% of page weight. Convert to WebP via CFile::ResizeImageGet() with BX_RESIZE_IMAGE_PROPORTIONAL + conversion. Use srcset + sizes — never load a 3000px image into a 400px block. Add loading="lazy" for everything below the fold. AVIF offers another 20–30% savings vs WebP.

CSS/JS optimization: use the built-in Bitrix module to merge and minify via 'Settings → CSS/JS Optimization'. Apply PurgeCSS / UnCSS — in a typical Bitrix project, 60–70% of CSS is unused. Use defer / async for non‑critical JS and inline critical CSS in <head> for instant FCP.

Fonts: add <link rel="preload" as="font" crossorigin> for the main font. Set font-display: swap — text visible immediately. Subset via pyftsubset — keep only Cyrillic + Latin, file size reduces by 3–5 times.

CDN: Cloudflare, BunnyCDN, AWS CloudFront, or Russian providers (Selectel CDN, VK Cloud CDN). Serve static assets (CSS, JS, images, fonts) via CDN with Cache-Control: public, max-age=31536000, immutable for files with a hash. Use on‑the‑fly image optimization (imgproxy, Cloudflare Polish) without load on origin.

Why is load testing necessary?

Not synthetic benchmarks, but real scenarios: k6 / wrk to simulate routes — catalog → filtering → product card → cart → checkout. Measure RPS, response time (p50, p95, p99), error rate. Use Xdebug (callgrind) or Blackfire for PHP profiling to find bottlenecks. The test result gives an objective picture of where it actually slows down, not where it 'seems'. After optimization, run again to record improvements.

Results

What is included in the work?

1. Current performance audit — analysis of slow queries, PHP profiling, check of caching, CDN, server settings.
2. Server configuration — Nginx, PHP-FPM, MySQL, Redis/Memcached, OPcache.
3. Caching optimization — managed cache, composite site, TTL configuration, tagged caching.
4. Database work — index creation, partitioning, cleanup, EAV table reorganization.
5. Frontend — images (WebP/AVIF), CSS/JS (minification, deferred), fonts (preload, subsetting).
6. CDN — connection, caching rule setup.
7. Load testing — real user scenarios, metric report.
8. Documentation — description of all changes, recommendations for further maintenance.
9. Guarantee — support for 1 month after delivery, ensuring all optimizations are stable.

Monitoring

Without monitoring, everything degrades in six months. A new module, uncleared logs, a template change — and speed returns to original. Use web-vitals API for Real User Monitoring from actual visitors. Set up synthetic monitoring with Pingdom or UptimeRobot for regular checks from different locations. Configure alerts — TTFB > 500 ms or LCP > 3 sec triggers notification.

Timelines and cost

Cost is calculated individually after the audit. Get a consultation for your project — we will evaluate the current state and propose an acceleration plan with specific timelines and budget. We are a team with 12+ years of experience in Bitrix, having completed over 300 site speed optimization projects. Contact us to start the performance audit today.