Implementing HLS and DASH Video Streaming

Our company is engaged in the development, support and maintenance of sites of any complexity. From simple one-page sites to large-scale cluster systems built on micro services. Experience of developers is confirmed by certificates from vendors.

Development and maintenance of all types of websites:

Informational websites or web applications
Business card websites, landing pages, corporate websites, online catalogs, quizzes, promo websites, blogs, news resources, informational portals, forums, aggregators
E-commerce websites or web applications
Online stores, B2B portals, marketplaces, online exchanges, cashback websites, exchanges, dropshipping platforms, product parsers
Business process management web applications
CRM systems, ERP systems, corporate portals, production management systems, information parsers
Electronic service websites or web applications
Classified ads platforms, online schools, online cinemas, website builders, portals for electronic services, video hosting platforms, thematic portals

These are just some of the technical types of websites we work with, and each of them can have its own specific features and functionality, as well as be customized to meet the specific needs and goals of the client.

Showing 1 of 1All 2062 services
Implementing HLS and DASH Video Streaming
Complex
~1-2 weeks
Frequently Asked Questions

Our competencies:

Development stages

Latest works

  • image_website-b2b-advance_0.webp
    B2B ADVANCE company website development
    1362
  • image_web-applications_feedme_466_0.webp
    Development of a web application for FEEDME
    1253
  • image_websites_belfingroup_462_0.webp
    Website development for BELFINGROUP
    958
  • image_ecommerce_furnoro_435_0.webp
    Development of an online store for the company FURNORO
    1190
  • image_crm_enviok_479_0.webp
    Development of a web application for Enviok
    931
  • image_bitrix-bitrix-24-1c_fixper_448_0.webp
    Website development for FIXPER company
    949

Implementing HLS and DASH Video Streaming

You launch a video service, and after uploading the first videos, you realize — the player stutters, buffering never ends, and mobile users see nothing but a spinner. This is a familiar situation—we've encountered it many times. Our experience: 7+ years in video streaming. The solution is adaptive streaming with proper segmentation, CDN integration, and multi-resolution support. In this article, we'll explain how we implement an HLS/DASH pipeline turnkey, and the pitfalls we encountered.

HLS vs DASH: Which One to Choose?

HLS (HTTP Live Streaming) is an Apple standard, supported by all browsers via hls.js (except Safari, which has native support). DASH (Dynamic Adaptive Streaming over HTTP) is an open standard used for DRM compatibility. In practice, HLS is the default choice: lower latency, wider CDN support. DASH is needed when multiple DRM systems (Widevine, PlayReady) are required.

In our projects, we use HLS as the baseline and add DASH on demand. Comparison in the table:

Characteristic HLS DASH
Support All browsers (hls.js for non-Safari) All browsers (dash.js)
Container MPEG-TS or fMP4 fMP4
DRM FairPlay (Apple), Widevine Widevine, PlayReady
Latency 6–30 sec (LL-HLS: <2 sec) 2–10 sec
CDN compatibility Excellent Excellent

In our tests, HLS showed 2 times lower latency than DASH.

Why FFmpeg Is Not the Only Option?

For video transcoding, we use FFmpeg in conjunction with queues (Laravel Horizon), but for high volumes we incorporate AWS MediaConvert. Let's break down both approaches.

FFmpeg + Queue (Self-hosted)

The transcode-hls.sh script cuts video into three qualities: 1080p, 720p, 360p. Segments of 6 seconds (fMP4). Output: master.m3u8 and sub-playlists.

View full transcoding script ```bash #!/bin/bash # transcode-hls.sh

INPUT="$1" OUTPUT_DIR="$2"

mkdir -p "$OUTPUT_DIR"

ffmpeg -i "$INPUT"
-filter_complex
"[0:v]split=3[v1][v2][v3];
[v1]scale=1920:1080:force_original_aspect_ratio=decrease[v1080];
[v2]scale=1280:720:force_original_aspect_ratio=decrease[v720];
[v3]scale=640:360:force_original_aspect_ratio=decrease[v360]"

-map "[v1080]" -map 0:a -c:v:0 libx264 -crf 22 -preset fast
-b:v:0 5000k -maxrate:v:0 5500k -bufsize:v:0 10000k
-c:a:0 aac -b:a:0 192k

-map "[v720]" -map 0:a -c:v:1 libx264 -crf 23 -preset fast
-b:v:1 2500k -maxrate:v:1 2750k -bufsize:v:1 5000k
-c:a:1 aac -b:a:1 128k

-map "[v360]" -map 0:a -c:v:2 libx264 -crf 24 -preset fast
-b:v:2 800k -maxrate:v:2 880k -bufsize:v:2 1600k
-c:a:2 aac -b:a:2 96k

-f hls
-hls_time 6
-hls_playlist_type vod
-hls_flags independent_segments
-hls_segment_type fmp4
-hls_segment_filename "$OUTPUT_DIR/v%v/seg%06d.m4s"
-master_pl_name master.m3u8
-var_stream_map "v:0,a:0,name:1080p v:1,a:1,name:720p v:2,a:2,name:360p"
"$OUTPUT_DIR/v%v/index.m3u8"

</details>

Result:

output/ ├── master.m3u8 ├── 1080p/ │ ├── index.m3u8 │ ├── seg000001.m4s │ └── ... ├── 720p/ │ └── ... └── 360p/ └── ...


#### PHP Job for Queue

The TranscodeToHlsJob class is a typical Laravel job. Timeout 2 hours, two attempts. We only handle the successful case.

```php
class TranscodeToHlsJob implements ShouldQueue
{
    public int $timeout = 7200;
    public int $tries = 2;

    public function __construct(private Video $video) {}

    public function handle(): void
    {
        $this->video->update(['status' => 'transcoding']);

        $inputUrl   = Storage::disk('s3')->temporaryUrl($this->video->original_key, now()->addHours(3));
        $outputDir  = sys_get_temp_dir() . '/hls_' . $this->video->id;
        $s3Prefix   = "hls/{$this->video->user_id}/{$this->video->id}";

        mkdir($outputDir, 0777, true);

        $process = new \Symfony\Component\Process\Process([
            '/usr/local/bin/transcode-hls.sh', $inputUrl, $outputDir
        ]);
        $process->setTimeout(7200);
        $process->run();

        if (!$process->isSuccessful()) {
            throw new \RuntimeException('HLS transcoding failed: ' . $process->getErrorOutput());
        }

        // Upload all files to S3
        $iterator = new \RecursiveIteratorIterator(
            new \RecursiveDirectoryIterator($outputDir)
        );

        foreach ($iterator as $file) {
            if (!$file->isFile()) continue;

            $relativePath = str_replace($outputDir . '/', '', $file->getPathname());
            $s3Key = "{$s3Prefix}/{$relativePath}";

            $contentType = str_ends_with($file->getFilename(), '.m3u8')
                ? 'application/x-mpegURL'
                : 'video/mp4';

            Storage::disk('s3')->put($s3Key, file_get_contents($file->getPathname()), [
                'ContentType'  => $contentType,
                'CacheControl' => str_ends_with($file->getFilename(), '.m3u8')
                    ? 'no-cache'          // playlist not cached
                    : 'public, max-age=31536000',  // segments cached forever
            ]);
        }

        $this->video->update([
            'status'       => 'ready',
            'hls_manifest' => "{$s3Prefix}/master.m3u8",
        ]);

        // Clean up temporary files
        exec("rm -rf {$outputDir}");
    }
}

AWS MediaConvert (Managed)

For high-load projects, we use MediaConvert. Configuration in Python:

def create_hls_job(input_key: str, output_prefix: str) -> str:
    client = boto3.client('mediaconvert', endpoint_url=MEDIACONVERT_ENDPOINT)

    job = client.create_job(
        Role=MEDIACONVERT_ROLE,
        Settings={
            'Inputs': [{'FileInput': f's3://bucket/{input_key}', 'VideoSelector': {}, 'AudioSelectors': {'Audio 1': {'DefaultSelection': 'DEFAULT'}}}],
            'OutputGroups': [{
                'Name': 'Apple HLS',
                'OutputGroupSettings': {
                    'Type': 'HLS_GROUP_SETTINGS',
                    'HlsGroupSettings': {
                        'Destination': f's3://bucket/{output_prefix}/',
                        'SegmentLength': 6,
                        'MinSegmentLength': 0,
                        'DirectoryStructure': 'SUBDIRECTORY_PER_STREAM',
                    },
                },
                'Outputs': [
                    {'NameModifier': '_1080p', 'VideoDescription': {'Width': 1920, 'Height': 1080, 'CodecSettings': {'Codec': 'H_264', 'H264Settings': {'Bitrate': 5000000, 'RateControlMode': 'CBR', 'GopSize': 90}}}, 'AudioDescriptions': [{'CodecSettings': {'Codec': 'AAC', 'AacSettings': {'Bitrate': 192000}}}]},
                    {'NameModifier': '_720p', 'VideoDescription': {'Width': 1280, 'Height': 720, 'CodecSettings': {'Codec': 'H_264', 'H264Settings': {'Bitrate': 2500000, 'RateControlMode': 'CBR', 'GopSize': 90}}}, 'AudioDescriptions': [{'CodecSettings': {'Codec': 'AAC', 'AacSettings': {'Bitrate': 128000}}}]},
                    {'NameModifier': '_360p', 'VideoDescription': {'Width': 640, 'Height': 360, 'CodecSettings': {'Codec': 'H_264', 'H264Settings': {'Bitrate': 800000, 'RateControlMode': 'CBR', 'GopSize': 90}}}, 'AudioDescriptions': [{'CodecSettings': {'Codec': 'AAC', 'AacSettings': {'Bitrate': 96000}}}]},
                ],
            }],
        }
    )
    return job['Job']['Id']

MediaConvert generates HLS playlists on its own. We pay only for transcoding minutes.

CloudFront CDN

To ensure fast video delivery worldwide, we configure CloudFront with two cache policies: for playlists (TTL 5 seconds) and segments (TTL 1 year).

resource "aws_cloudfront_distribution" "video" {
  origin {
    domain_name            = aws_s3_bucket.videos.bucket_regional_domain_name
    origin_id              = "s3-videos"
    origin_access_control_id = aws_cloudfront_origin_access_control.default.id
  }

  enabled         = true
  is_ipv6_enabled = true

  default_cache_behavior {
    allowed_methods        = ["GET", "HEAD"]
    cached_methods         = ["GET", "HEAD"]
    target_origin_id       = "s3-videos"
    viewer_protocol_policy = "redirect-to-https"

    forwarded_values {
      query_string = false
      cookies { forward = "none" }
      headers = ["Origin", "Access-Control-Request-Method", "Access-Control-Request-Headers"]
    }

    min_ttl     = 0
    default_ttl = 86400
    max_ttl     = 31536000
  }

  # Playlists .m3u8 — short cache
  ordered_cache_behavior {
    path_pattern           = "*.m3u8"
    allowed_methods        = ["GET", "HEAD"]
    cached_methods         = ["GET", "HEAD"]
    target_origin_id       = "s3-videos"
    viewer_protocol_policy = "redirect-to-https"

    forwarded_values {
      query_string = false
      cookies { forward = "none" }
    }

    min_ttl     = 0
    default_ttl = 5
    max_ttl     = 30
  }
}

React Player with hls.js

Client-side integration: hls.js for modern browsers, fallback to native HLS in Safari.

import Hls from 'hls.js';
import { useEffect, useRef } from 'react';

interface VideoPlayerProps {
  manifestUrl: string;
  poster?: string;
}

export function VideoPlayer({ manifestUrl, poster }: VideoPlayerProps) {
  const videoRef = useRef<HTMLVideoElement>(null);

  useEffect(() => {
    const video = videoRef.current;
    if (!video) return;

    if (Hls.isSupported()) {
      const hls = new Hls({
        maxBufferLength: 30,
        maxMaxBufferLength: 60,
        lowLatencyMode: false,
      });

      hls.loadSource(manifestUrl);
      hls.attachMedia(video);

      hls.on(Hls.Events.ERROR, (_, data) => {
        if (data.fatal) {
          if (data.type === Hls.ErrorTypes.NETWORK_ERROR) {
            hls.startLoad();
          } else {
            hls.destroy();
          }
        }
      });

      return () => hls.destroy();

    } else if (video.canPlayType('application/vnd.apple.mpegurl')) {
      // Safari: native HLS support
      video.src = manifestUrl;
    }
  }, [manifestUrl]);

  return (
    <video
      ref={videoRef}
      poster={poster}
      controls
      playsInline
      style={{ width: '100%', maxHeight: '80vh' }}
    />
  );
}

What's Included in the Work

We handle the complete cycle for implementing HLS/DASH streaming on your website:

  • Transcoding video into three qualities (1080p, 720p, 360p) using FFmpeg or AWS MediaConvert.
  • Integration with queues (Laravel Horizon) for async processing.
  • Development of a custom React player based on hls.js with UI customization support.
  • Setting up CDN (CloudFront or Cloudflare) for fast content delivery.
  • Detailed documentation of the pipeline architecture.
  • Training your team on the system.
  • 2 weeks of post-launch support.

Typical Mistakes

  • Incorrect bitrates: too low for 1080p, too high for 360p. We use Apple recommendations.
  • Playlist caching: if master.m3u8 is cached, the player won't see new qualities after retranscoding. We set no-cache.
  • Missing CORS: browser blocks segments. We configure CORS on S3/CloudFront.
  • Hydration mismatch: if the player renders on the server, it may mismatch with client. We use dynamic import.

Process of Work

  1. Analysis — study source videos, DRM requirements, target audience.
  2. Design — select stack (self-hosted FFmpeg or MediaConvert), determine bitrates, CDN.
  3. Implementation — write transcoder, job, player.
  4. Testing — check LCP, CLS, INP, Core Web Vitals.
  5. Deployment — deploy to production, monitor logs.

Timeline and Cost

Step Timeline
FFmpeg HLS transcoding in queue 4–5 days
AWS MediaConvert integration 2–3 days
hls.js player with React 1–2 days
CloudFront CDN delivery 1–2 days
Full pipeline (upload → transcode → player) 7–14 days

Cost is calculated individually based on video volume, bitrates, and DRM needs. Contact us for an assessment of your project — we'll calculate the timeline and cost. Order HLS/DASH streaming implementation and get a consultation. We guarantee your video will work lag-free on any device.

Backend Development Services: Laravel, Node.js, Go, Django, PostgreSQL

On a production server at 3:14 AM, the Laravel Jobs queue stopped processing. 40,000 unprocessed jobs in Redis. Cause: worker crashed due to a memory leak in one of the Jobs (leak via a static variable in an Eloquent observer), supervisor didn't restart it because of misconfigured stopwaitsecs. This is not a hypothetical scenario — it's Tuesday. We analyzed such an incident on a project with 500 RPS load: diagnosis took 4 hours, fix — 20 minutes. So you don't lose money on downtime, we offer backend development services with a focus on production-grade reliability. We'll assess your project in 2 days.

Backend is what works when no one is watching. Or doesn't work. We guarantee you'll have the first option.

How do we ensure production-grade reliability from day one?

What we do correctly from day one

Service Layer over Fat Controllers. Controller receives HTTP request, validates it via Form Request, passes data to Service, returns response. Business logic in Service, not Controller. This sounds trivial, but most legacy projects have controllers with 500 lines and SQL queries inside.

Repository Pattern we use cautiously. If you just wrap Model::where(...) in a repository method — that's boilerplate without benefit. Repository is justified when: you need to abstract from the data source (DB + cache + external API) or when query logic is complex enough to isolate.

Jobs, Events, Listeners. Everything that can be async — make async. Sending email, PDF generation, external API sync, aggregate recalculation — into Queue. Laravel Horizon for queue monitoring in Redis: see throughput, failed jobs, processing time per queue.

How Octane handles high load

Laravel Octane with RoadRunner or Swoole keeps the app in memory between requests — removes bootstrap overhead (config loading, class autoloading) on each HTTP request. Gain: 3–8x on synthetic benchmarks, 2–4x on real applications. Important: no state between requests in static variables — that leads to exactly the incidents from the beginning. We use this in projects with >1000 RPS.

What to do about N+1 queries

N+1 is the most common cause of slow pages in Laravel apps. Standard story: page worked fine on dev with 10 records, on production with 10,000 — 8-second load.

Laravel Debugbar in dev environment shows the number of queries per page. More than 20 queries per page — signal for audit.

Model::preventLazyLoading(! app()->isProduction());

Telescope for profiling in staging: logs all queries, jobs, mail, notifications with time detail. Numbers: after implementing eager loading, page load time drops from 8s to 0.3s — 27 times faster.

PostgreSQL: indexes that are actually needed

PostgreSQL 14+ is the primary DB on all projects. We use PgBouncer + PostgreSQL combination. 10+ years experience, more than 50 backend projects, 5 years on the market.

How PostgreSQL helps avoid slow queries

Composite indexes for frequent WHERE + ORDER BY. If you have WHERE user_id = ? AND status = ? ORDER BY created_at DESC — you need (user_id, status, created_at DESC). A separate index on (user_id) doesn't help much with sorting.

Partial indexes. If 95% of queries go with WHERE status = 'active':

CREATE INDEX idx_orders_active ON orders (created_at DESC)
WHERE status = 'active';

The index is small, fast, covers the main load.

GIN indexes for JSONB and arrays. @> operator without GIN index — seq scan. With index — fast even on millions of rows.

GIN for full-text search. to_tsvector + GIN instead of LIKE '%query%'. LIKE without index is always seq scan. With pg_trgm extension and gin_trgm_ops — supports LIKE with index, useful for CRM search by partial match.

Connection pooling: why it's more important than it seems

Rails, Laravel, Django open a new connection to PostgreSQL for each PHP/Python process. With 100 workers — 100 connections. PostgreSQL starts degrading from 200–300 active connections — overhead on connection management becomes significant.

PgBouncer — connection pooler in front of PostgreSQL. Transaction pooling mode: connection to PostgreSQL is occupied only during a transaction, returned to pool between requests. 1000 application workers → 20–50 actual connections to PostgreSQL. This reduces latency by 40% and hosting costs by 30%.

Node.js with Fastify: when it's better than Laravel

Node.js is justified for:

  • Realtime: WebSocket servers, Server-Sent Events, chat, live updates
  • Streaming: large files, video, streaming data
  • High I/O concurrency: many parallel requests to external APIs without heavy business logic
  • Serverless: Lambda/Cloud Functions — Node.js starts faster than PHP

Fastify over Express: 2–3 times faster on benchmarks, built-in JSON Schema validation, better TypeScript support, plugin architecture.

Typical realtime architecture: Laravel — core business logic and REST API. Node.js + Socket.io or ws — WebSocket server. Laravel publishes events to Redis Pub/Sub, Node.js subscribes and broadcasts to clients. This separation allows scaling the WebSocket server independently of the main app.

Go: microservices and high load

Go we use for:

  • High-load microservices (>10,000 RPS)
  • Background workers with strict latency requirements
  • DevOps tools and CLI
  • gRPC services in microservice architecture

Goroutines — thousands of times cheaper than OS threads. 10,000 concurrent connections on Go is normal on one server.

But Go is not a silver bullet. Development is slower than Laravel: more boilerplate, no ORM at Eloquent level, error handling with if err != nil everywhere. Justified only when performance is a real requirement, not an assumption.

Django and Python backend

Django with DRF (Django REST Framework) — for tasks where Python is needed: ML pipelines, data processing, integrations with AI tools.

Celery for background tasks — similar to Laravel Queue but more complex to configure. Celery Beat for cron tasks.

Django ORM vs raw SQL: ORM is convenient for CRUD. For analytical queries with multiple JOINs, window functions, and CTEs — connection.execute() with raw SQL is more readable and predictable.

Redis: not just cache

Redis in our projects plays multiple roles:

Role Details
Cache Caching results of heavy queries, HTML fragments
Queues Backend for Laravel Queue / Celery
Session store Distributed sessions in multi-instance environment
Pub/Sub Realtime events between services
Rate limiting Sliding window counters for API throttling
Leaderboards Sorted Sets for rankings

Redis Cluster for horizontal scaling. Sentinel for automatic failover on standalone setups.

Deployment and infrastructure

Docker + docker-compose — standard for local development and production. Each service in a container: PHP-FPM/Octane, Nginx, PostgreSQL, Redis, Queue Worker, Scheduler.

CI/CD via GitHub Actions:

  1. Run tests (PHPUnit / Pest, Vitest, Playwright)
  2. Build Docker image
  3. Push to Container Registry
  4. Deploy: docker pull → docker-compose up -d on server, or Kubernetes rolling update

Zero-downtime deploy for Laravel: php artisan down --secret=TOKEN is not needed with proper configuration. Strategy: new container starts next to the old one, Nginx switches traffic after health check, old container stops.

Monitoring: Sentry for exception tracking with alerting in Slack/Telegram. Grafana + Prometheus (or Grafana Cloud) for metrics: CPU, memory, request rate, queue depth, database connection count. Alerts on: error rate > 1%, p99 latency > 2s, queue depth > 1000 jobs.

What's included in turnkey work

  • Architecture design (API documentation, DB schema, service diagram)
  • Implementation according to agreed specification with code review
  • CI/CD, monitoring, alerting setup
  • Load testing (k6, wrk) with report
  • Handover of source code, access, deployment instructions
  • Training of customer's team (2-3 sessions)
  • Warranty support for 1 month after delivery

Timeline benchmarks

Task Timeline
REST API for mobile/SPA (medium complexity) 6–12 weeks
Backend with complex business logic + integrations 12–20 weeks
High-load service on Go 8–16 weeks
Migration from legacy PHP to Laravel 16–32 weeks

Pricing is calculated individually after analyzing load, integrations, and business logic. Contact us for a free audit of your current backend — get an optimization plan in 2 days. Request a consultation.