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• Stream ffmpeg transcoding result to S3

  7 juin 2019, par mabead

  I want to transcode a large file using FFMPEG and store the result directly on AWS S3. This will be done inside of an AWS Lambda that has limited tmp space so I can’t store the transcoding result locally and then upload it to S3 in a second step. I won’t have enough tmp space. I therefore want to store the FFMPEG output directly on S3.

  I therefore created a S3 pre-signed url that allows ’PUT’ :

  var outputPath = s3Client.GetPreSignedURL(new Amazon.S3.Model.GetPreSignedUrlRequest
  
  {
  
      BucketName = "my-bucket",
  
      Expires = DateTime.UtcNow.AddMinutes(5),
  
      Key = "output.mp3",
  
      Verb = HttpVerb.PUT,
  
  });

  I then called ffmpeg with the resulting pre-signed url :

  ffmpeg -i C:\input.wav -y -vn -ar 44100 -ac 2 -ab 192k -f mp3 https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550427237&Signature=%2BE8Wc%2F%2FQYrvGxzc%2FgXnsvauKnac%3D

  FFMPEG returns an exit code of 1 with the following output :

  ffmpeg version N-93120-ga84af760b8 Copyright (c) 2000-2019 the FFmpeg developers
  
    built with gcc 8.2.1 (GCC) 20190212
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libdav1d --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enable-libaom --enable-libmfx --enable-amf --enable-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --enable-dxva2 --enable-avisynth --enable-libopenmpt
  
    libavutil      56. 26.100 / 56. 26.100
  
    libavcodec     58. 47.100 / 58. 47.100
  
    libavformat    58. 26.101 / 58. 26.101
  
    libavdevice    58.  6.101 / 58.  6.101
  
    libavfilter     7. 48.100 /  7. 48.100
  
    libswscale      5.  4.100 /  5.  4.100
  
    libswresample   3.  4.100 /  3.  4.100
  
    libpostproc    55.  4.100 / 55.  4.100
  
  Guessed Channel Layout for Input Stream #0.0 : stereo
  
  Input #0, wav, from 'C:\input.wav':
  
    Duration: 00:04:16.72, bitrate: 3072 kb/s
  
      Stream #0:0: Audio: pcm_s32le ([1][0][0][0] / 0x0001), 48000 Hz, stereo, s32, 3072 kb/s
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (pcm_s32le (native) -> mp3 (libmp3lame))
  
  Press [q] to stop, [?] for help
  
  Output #0, mp3, to 'https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550427237&Signature=%2BE8Wc%2F%2FQYrvGxzc%2FgXnsvauKnac%3D':
  
    Metadata:
  
      TSSE            : Lavf58.26.101
  
      Stream #0:0: Audio: mp3 (libmp3lame), 44100 Hz, stereo, s32p, 192 kb/s
  
      Metadata:
  
        encoder         : Lavc58.47.100 libmp3lame
  
  size=     577kB time=00:00:24.58 bitrate= 192.2kbits/s speed=49.1x    
  
  size=    1109kB time=00:00:47.28 bitrate= 192.1kbits/s speed=47.2x    
  
  [tls @ 000001d73d786b00] Error in the push function.
  
  av_interleaved_write_frame(): I/O error
  
  Error writing trailer of https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550427237&Signature=%2BE8Wc%2F%2FQYrvGxzc%2FgXnsvauKnac%3D: I/O error
  
  size=    1143kB time=00:00:48.77 bitrate= 192.0kbits/s speed=  47x    
  
  video:0kB audio:1144kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
  
  [tls @ 000001d73d786b00] The specified session has been invalidated for some reason.
  
  [tls @ 000001d73d786b00] Error in the pull function.
  
  [https @ 000001d73d784fc0] URL read error:  -5
  
  Conversion failed!

  As you can see, I have a URL read error. This is a little surprising to me since I want to output to this url and not read it.

  Anybody know how I can store directly my FFMPEG output directly to S3 without having to store it locally first ?

  Edit 1
  I then tried to use the -method PUT parameter and use http instead of https to remove TLS from the equation. Here’s the output that I got when running ffmpeg with the -v trace option.

  ffmpeg version N-93120-ga84af760b8 Copyright (c) 2000-2019 the FFmpeg developers
  
    built with gcc 8.2.1 (GCC) 20190212
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libdav1d --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enable-libaom --enable-libmfx --enable-amf --enable-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --enable-dxva2 --enable-avisynth --enable-libopenmpt
  
    libavutil      56. 26.100 / 56. 26.100
  
    libavcodec     58. 47.100 / 58. 47.100
  
    libavformat    58. 26.101 / 58. 26.101
  
    libavdevice    58.  6.101 / 58.  6.101
  
    libavfilter     7. 48.100 /  7. 48.100
  
    libswscale      5.  4.100 /  5.  4.100
  
    libswresample   3.  4.100 /  3.  4.100
  
    libpostproc    55.  4.100 / 55.  4.100
  
  Splitting the commandline.
  
  Reading option '-i' ... matched as input url with argument 'C:\input.wav'.
  
  Reading option '-y' ... matched as option 'y' (overwrite output files) with argument '1'.
  
  Reading option '-vn' ... matched as option 'vn' (disable video) with argument '1'.
  
  Reading option '-ar' ... matched as option 'ar' (set audio sampling rate (in Hz)) with argument '44100'.
  
  Reading option '-ac' ... matched as option 'ac' (set number of audio channels) with argument '2'.
  
  Reading option '-ab' ... matched as option 'ab' (audio bitrate (please use -b:a)) with argument '192k'.
  
  Reading option '-f' ... matched as option 'f' (force format) with argument 'mp3'.
  
  Reading option '-method' ... matched as AVOption 'method' with argument 'PUT'.
  
  Reading option '-v' ... matched as option 'v' (set logging level) with argument 'trace'.
  
  Reading option 'https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D' ... matched as output url.
  
  Finished splitting the commandline.
  
  Parsing a group of options: global .
  
  Applying option y (overwrite output files) with argument 1.
  
  Applying option v (set logging level) with argument trace.
  
  Successfully parsed a group of options.
  
  Parsing a group of options: input url C:\input.wav.
  
  Successfully parsed a group of options.
  
  Opening an input file: C:\input.wav.
  
  [NULL @ 000001fb37abb180] Opening 'C:\input.wav' for reading
  
  [file @ 000001fb37abc180] Setting default whitelist 'file,crypto'
  
  Probing wav score:99 size:2048
  
  [wav @ 000001fb37abb180] Format wav probed with size=2048 and score=99
  
  [wav @ 000001fb37abb180] Before avformat_find_stream_info() pos: 54 bytes read:65590 seeks:1 nb_streams:1
  
  [wav @ 000001fb37abb180] parser not found for codec pcm_s32le, packets or times may be invalid.
  
      Last message repeated 1 times
  
  [wav @ 000001fb37abb180] All info found
  
  [wav @ 000001fb37abb180] stream 0: start_time: -192153584101141.156 duration: 256.716
  
  [wav @ 000001fb37abb180] format: start_time: -9223372036854.775 duration: 256.716 bitrate=3072 kb/s
  
  [wav @ 000001fb37abb180] After avformat_find_stream_info() pos: 204854 bytes read:294966 seeks:1 frames:50
  
  Guessed Channel Layout for Input Stream #0.0 : stereo
  
  Input #0, wav, from 'C:\input.wav':
  
    Duration: 00:04:16.72, bitrate: 3072 kb/s
  
      Stream #0:0, 50, 1/48000: Audio: pcm_s32le ([1][0][0][0] / 0x0001), 48000 Hz, stereo, s32, 3072 kb/s
  
  Successfully opened the file.
  
  Parsing a group of options: output url https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D.
  
  Applying option vn (disable video) with argument 1.
  
  Applying option ar (set audio sampling rate (in Hz)) with argument 44100.
  
  Applying option ac (set number of audio channels) with argument 2.
  
  Applying option ab (audio bitrate (please use -b:a)) with argument 192k.
  
  Applying option f (force format) with argument mp3.
  
  Successfully parsed a group of options.
  
  Opening an output file: https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D.
  
  [http @ 000001fb37b15140] Setting default whitelist 'http,https,tls,rtp,tcp,udp,crypto,httpproxy'
  
  [tcp @ 000001fb37b16c80] Original list of addresses:
  
  [tcp @ 000001fb37b16c80] Address 52.216.8.203 port 80
  
  [tcp @ 000001fb37b16c80] Interleaved list of addresses:
  
  [tcp @ 000001fb37b16c80] Address 52.216.8.203 port 80
  
  [tcp @ 000001fb37b16c80] Starting connection attempt to 52.216.8.203 port 80
  
  [tcp @ 000001fb37b16c80] Successfully connected to 52.216.8.203 port 80
  
  [http @ 000001fb37b15140] request: PUT /output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D HTTP/1.1
  
  Transfer-Encoding: chunked
  
  User-Agent: Lavf/58.26.101
  
  Accept: */*
  
  Connection: close
  
  Host: landr-distribution-reportsdev-mb.s3.amazonaws.com
  
  Icy-MetaData: 1
  
  Successfully opened the file.
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (pcm_s32le (native) -> mp3 (libmp3lame))
  
  Press [q] to stop, [?] for help
  
  cur_dts is invalid (this is harmless if it occurs once at the start per stream)
  
  detected 8 logical cores
  
  [graph_0_in_0_0 @ 000001fb37b21080] Setting 'time_base' to value '1/48000'
  
  [graph_0_in_0_0 @ 000001fb37b21080] Setting 'sample_rate' to value '48000'
  
  [graph_0_in_0_0 @ 000001fb37b21080] Setting 'sample_fmt' to value 's32'
  
  [graph_0_in_0_0 @ 000001fb37b21080] Setting 'channel_layout' to value '0x3'
  
  [graph_0_in_0_0 @ 000001fb37b21080] tb:1/48000 samplefmt:s32 samplerate:48000 chlayout:0x3
  
  [format_out_0_0 @ 000001fb37b22cc0] Setting 'sample_fmts' to value 's32p|fltp|s16p'
  
  [format_out_0_0 @ 000001fb37b22cc0] Setting 'sample_rates' to value '44100'
  
  [format_out_0_0 @ 000001fb37b22cc0] Setting 'channel_layouts' to value '0x3'
  
  [format_out_0_0 @ 000001fb37b22cc0] auto-inserting filter 'auto_resampler_0' between the filter 'Parsed_anull_0' and the filter 'format_out_0_0'
  
  [AVFilterGraph @ 000001fb37b0d940] query_formats: 4 queried, 6 merged, 3 already done, 0 delayed
  
  [auto_resampler_0 @ 000001fb37b251c0] picking s32p out of 3 ref:s32
  
  [auto_resampler_0 @ 000001fb37b251c0] [SWR @ 000001fb37b252c0] Using fltp internally between filters
  
  [auto_resampler_0 @ 000001fb37b251c0] ch:2 chl:stereo fmt:s32 r:48000Hz -> ch:2 chl:stereo fmt:s32p r:44100Hz
  
  Output #0, mp3, to 'https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D':
  
    Metadata:
  
      TSSE            : Lavf58.26.101
  
      Stream #0:0, 0, 1/44100: Audio: mp3 (libmp3lame), 44100 Hz, stereo, s32p, delay 1105, 192 kb/s
  
      Metadata:
  
        encoder         : Lavc58.47.100 libmp3lame
  
  cur_dts is invalid (this is harmless if it occurs once at the start per stream)
  
      Last message repeated 6 times
  
  size=     649kB time=00:00:27.66 bitrate= 192.2kbits/s speed=55.3x    
  
  size=    1207kB time=00:00:51.48 bitrate= 192.1kbits/s speed=51.5x    
  
  av_interleaved_write_frame(): Unknown error
  
  No more output streams to write to, finishing.
  
  [libmp3lame @ 000001fb37b147c0] Trying to remove 47 more samples than there are in the queue
  
  Error writing trailer of https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D: Error number -10054 occurred
  
  size=    1251kB time=00:00:53.39 bitrate= 192.0kbits/s speed=51.5x    
  
  video:0kB audio:1252kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
  
  Input file #0 (C:\input.wav):
  
    Input stream #0:0 (audio): 5014 packets read (20537344 bytes); 5014 frames decoded (2567168 samples); 
  
    Total: 5014 packets (20537344 bytes) demuxed
  
  Output file #0 (https://my-bucket.s3.amazonaws.com/output.mp3?AWSAccessKeyId=AKIAJDSGJWM63VQEXHIQ&Expires=1550695990&Signature=dy3RVqDlX%2BlJ0INlDkl0Lm1Rqb4%3D):
  
    Output stream #0:0 (audio): 2047 frames encoded (2358144 samples); 2045 packets muxed (1282089 bytes); 
  
    Total: 2045 packets (1282089 bytes) muxed
  
  5014 frames successfully decoded, 0 decoding errors
  
  [AVIOContext @ 000001fb37b1f440] Statistics: 0 seeks, 2046 writeouts
  
  [http @ 000001fb37b15140] URL read error:  -10054
  
  [AVIOContext @ 000001fb37ac4400] Statistics: 20611126 bytes read, 1 seeks
  
  Conversion failed!

  So it looks like it is able to connect to my S3 pre-signed url but I still have the Error writing trailer error coupled with a URL read error.

• Revision 3265 : On passe un nouvel argument possible au formulaire permettant de lui ...

  18 avril 2010, par kent1 — Log

  On passe un nouvel argument possible au formulaire permettant de lui indiquer directement quel est le tri actuel Dans le cas d’une page recherche, on ajoute un critère de tri qui est points (pertinence)

• Google Analytics Privacy Issues : Is It Really That Bad ?

  2 juin 2022, par Erin

  If you find yourself asking : “What’s the deal with Google Analytics privacy ?”, you probably have some second thoughts. 

  Your hunch is right. Google Analytics (GA) is a popular web analytics tool, but it’s far from being perfect when it comes to respecting users’ privacy. 

  This post helps you understand tremendous Google Analytics privacy concerns users, consumers and regulators expressed over the years.

  In this blog, we’ll cover :

  What Does Google Analytics Collect About Users ? 

  To understand Google Analytics privacy issues, you need to know how Google treats web users’ data. 

  By default, Google Analytics collects the following information : 

  • Session statistics — duration, page(s) viewed, etc. 
  • Referring website details — a link you came through or keyword used. 
  • Approximate geolocation — country, city. 
  • Browser and device information — mobile vs desktop, OS usage, etc. 

  Google obtains web analytics data about users via two means : an on-site Google Analytics tracking code and cookies.

  A cookie is a unique identifier (ID) assigned to each user visiting a web property. Each cookie stores two data items : unique user ID and website name. 

  With the help of cookies, web analytics solutions can recognise returning visitors and track their actions across the website(s).

  

  • First party cookies are generated by one website and collect user behaviour data from said website only. 
  • Third-party cookies are generated by a third-party website object (for example, an ad) and can track user behaviour data across multiple websites. 

  As it’s easy to imagine, third-party cookies are a goldmine for companies selling online ads. Essentially, they allow ad platforms to continue watching how the user navigates the web after clicking a certain link. 

  Yet, people have little clue as to which data they are sharing and how it is being used. Also, user consent to tracking across websites is only marginally guaranteed by existing Google Analytics controls. 

  Why Third-Party Cookie Data Collection By GA Is Problematic 

  Cookies can transmit personally identifiable information (PII) such as name, log in details, IP address, saved payment method and so on. Some of these details can end up with advertisers without consumers’ direct knowledge or consent.

  Regulatory frameworks such as General Data Protection Regulation (GDPR) in Europe and California Consumer Privacy Act (CCPA) emerged as a response to uncontrolled user behaviour tracking.

  Under regulatory pressure, Big Tech companies had to adapt their data collection process.

  Apple was the first to implement by-default third-party blocking in the Safari browser. Then added a tracking consent mechanism for iPhone users starting from iOS 15.2 and later. 

  Google, too, said it would drop third-party cookie usage after The European Commission and UK’s Competition and Markets Authority (CMA) launched antitrust investigations into its activity. 

  To shake off the data watchdogs, Google released a Privacy Sandbox — a set of progressive tech, operational and compliance changes for ensuring greater consumer privacy. 

  Google’s biggest promise : deprecate third-party cookies usage for all web and mobile products. 

  Originally, Google promised to drop third-party cookies by 2022, but that didn’t happen. Instead, Google delayed cookie tracking depreciation for Chrome until the second half of 2023. 

  Why did they push back on this despite hefty fines from regulators ?

  Because online ads make Google a lot of money.

  In 2021, Alphabet Inc (parent company of Google), made $256.7 billion in revenue, of which $209.49 billion came from selling advertising. 

  Lax Google Analytics privacy enforcement — and its wide usage by website owners — help Google make those billions from collecting and selling user data. 

  How Google Uses Collected Google Analytics Data for Advertising 

  Over 28 million websites (or roughly 85% of the Internet) have Google Analytics tracking codes installed. 

  Even if one day we get a Google Analytics version without cookies, it still won’t address all the privacy concerns regulators and consumers have. 

  Over the years, Google has accumulated an extensive collection of user data. The company’s engineers used it to build state-of-the-art deep learning models, now employed to build advanced user profiles. 

  Deep learning is the process of training a machine to recognise data patterns. Then this “knowledge” is used to produce highly-accurate predictive insights. The more data you have for model training — the better its future accuracy will be. 

  Google has amassed huge deposits of data from its collection of products — GA, YouTube, Gmail, Google Docs and Google Maps among others. Now they are using this data to build a third-party cookies-less alternative mechanism for modelling people’s preferences, habits, lifestyles, etc. 

  Their latest model is called Google Topics. 

  This comes only after Google’s failed attempt to replace cookie-based training with Federated Learning of Cohorts (FLoC) model. But the solution wasn’t offering enough user transparency and user controls among other issues.

  

  Google Topics promises to limit the granularity of data advertisers get about users. 

  But it’s still a web user surveillance method. With Google Topics, the company will continue collecting user data via Chrome (and likely other Google products) — and share it with advertisers. 

  Because as we said before : Google is in the business of profiting off consumers’ data. 

  Two Major Ways Google Takes Advantage of Customer Data

  Every bit of data Google collects across its ecosystem of products can be used in two ways :

  • For ad targeting and personalisation 
  • To improve Google’s products 

  The latter also helps the former. 

  Advanced Ad Personalisation and Targeting

  GA provides the company with ample data on users’ 

  • Recent and frequent searches 
  • Location history
  • Visited websites
  • Used apps 
  • Videos and ads viewed 
  • Personal data like age or gender 

  The company’s privacy policy explicitly states that :
  

  

  Google also admits to using collected data to “measure the effectiveness of advertising” and “personalise content and ads you see on Google.” 

  But there are no further elaborations on how exactly customers’ data is used — and what you can do to prevent it from being shared with third parties. 

  In some cases, Google also “forgets” to inform users about its in-product tracking.

  Journalists from CNBC and The New York Times independently concluded that Google monitors users’ Gmail activity. In particular, the company scans your inbox for recent purchases, trips, flights and bills notifications. 

  While Google says that this information isn’t sold to advertisers (directly), they still may use the “saved information about your orders in other Google services”. 

  Once again, this means you have little control or knowledge of subsequent data usage. 

  Improving Product Usability 

  Google has many “arms” to collect different data points — from user’s search history to frequently-travelled physical routes. 

  They also reserve the right to use these insights for improving existing products. 

  Here’s what it means : by combining different types of data points obtained from various products, Google can pierce a detailed picture of a person’s life. Even if such user profile data is anonymised, it is still alarmingly accurate. 

  Douglas Schmidt, a computer science researcher at Vanderbilt University, well summarised the matter : 

  “[Google’s] business model is to collect as much data about you as possible and cross-correlate it so they can try to link your online persona with your offline persona. This tracking is just absolutely essential to their business. ‘Surveillance capitalism’ is a perfect phrase for it.”

  Google Data Collection Obsession Is Backed Into Its Business Model 

  OK, but Google offers some privacy controls to users ? Yes. Google only sees and uses the information you voluntarily enter or permit them to access. 

  But as the Washington Post correspondent points out :

  “[Big Tech] companies get to set all the rules, as long as they run those rules by consumers in convoluted terms of service that even those capable of decoding the legalistic language rarely bother to read. Other mechanisms for notice and consent, such as opt-outs and opt-ins, create similar problems. Control for the consumer is mostly an illusion.”

  Google openly claims to be “one of many ad networks that personalise ads based on your activity online”. 

  The wrinkle is that they have more data than all other advertising networks (arguably combined). This helps Google sell high-precision targeting and contextually personalised ads for billions of dollars annually.

  Given that Google has stakes in so many products — it’s really hard to de-Google your business and minimise tracking and data collection from the company.
  

  They are also creating a monopoly on data collection and ownership. This fact makes regulators concerned. The 2021 antitrust lawsuit from the European Commission says : 

  “The formal investigation will notably examine whether Google is distorting competition by restricting access by third parties to user data for advertising purposes on websites and apps while reserving such data for its own use.”

  In other words : By using consumer data to its unfair advantage, Google allegedly shuts off competition.

  But that’s not the only matter worrying regulators and consumers alike. Over the years, Google also received numerous other lawsuits for breaching people’s privacy, over and over again. 

  Here’s a timeline : 

  • 2019 : UK citizens issued a class action suit against Google for imposing cookies to override users’ privacy settings in the Safari browser. 
  • 2020 : US citizens pushed for a $5 billion class-action suit for tracking their activity through browsers set in “private” mode.
  • 2022 : Another class-action lawsuit in the US for deceptive privacy controls and unconsented location data tracking by Google mobile apps. 
  • 2022 : Google reached a $100 million class-action settlement for breaching Illinois biometrics privacy laws in Google Photos. 

  Separately, Google has a very complex history with GDPR compliance. 

  How Google Analytics Contributes to the Web Privacy Problem 

  Google Analytics is the key puzzle piece that supports Google’s data-driven business model. 

  If Google was to release a privacy-focused Google Analytics alternative, it’d lose access to valuable web users’ data and a big portion of digital ad revenues. 

  Remember : Google collects more data than it shares with web analytics users and advertisers. But they keep a lot of it for personal usage — and keep looking for ways to share this intel with advertisers (in a way that keeps regulators off their tail).

  For Google Analytics to become truly ethical and privacy-focused, Google would need to change their entire revenue model — which is something they are unlikely to do.

  Where does this leave Google Analytics users ? 

  In a slippery territory. By proxy, companies using GA are complicit with Google’s shady data collection and usage practice. They become part of the problem.

  In fact, Google Analytics usage opens a business to two types of risks : 

  • Reputational. 77% of global consumers say that transparency around how data is collected and used is important to them when interacting with different brands. That’s why data breaches and data misuse by brands lead to major public outrages on social media and boycotts in some cases. 
  • Legal. EU regulators are on a continuous crusade against Google Analytics 4 (GA4) as it is in breach of GDPR. French and Austrian watchdogs ruled the “service” illegal. Since Google Analytics is not GDPR compliant, it opens any business using it to lawsuits (which is already happening).

  But there’s a way out.

  Choose a Privacy-Friendly Google Analytics Alternative 

  Google Analytics is a popular web analytics service, but not the only one available. You have alternatives such as Matomo. 

  Our guiding principle is : respecting privacy.

  Unlike Google Analytics, we leave data ownership 100% in users’ hands. Matomo lets you implement privacy-centred controls for user data collection.

  Plus, you can self-host Matomo On-Premise or choose Matomo Cloud with data securely stored in the EU and in compliance with GDPR.

  The best part ? You can try our ethical alternative to Google Analytics for free. No credit card required ! Start your free 21-day trial now. 

  21 day free trial. No credit card required.

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