Cloud Computing:
Cloud computing, is a kind of Internet-based computing that provides shared processing resources and data to computers and other devices on demand. It is a model for enabling ubiquitous, on-demand access to a shared pool of configurable computing resources wiki or as our friend google says that it is The practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer.
What this post aims to do:
But there are tones of resources online where you would find more desciption what I will be trying to achieve with this post is to build a working model/example to depeer understanding of this concept.Check the daigram below it represent a sample real world cloud computing application. we will try to explore the part where the worker(which can be your app interacting with ec2 part) is just us triggering by calling a function generate_burned_watermark_screener.
we will take on other parts (like celery alongwith rabbitmq and circus which are not mentioned in the diagram for maintaining the simplicity) of the diagram in comming posts.
Things this post assumes you know:
As we will try to develope a system which will perform transcoding i.e a computing task (similar to zenoders transcoding or aws’s transcoding for details please refer to some previous articles) over cloud and for this we will be using some shell scripts and python library for aws called boto. Moreover we will also be using aws cli for this purpose, so without a due lets do some coding.
Sections:
We will divide our objective into several parts:
- Use a cloud infrastructure(EC2 in our case) to do some work/computing (transcoding)
- Get the inputs from source(s3 in our case) and save them to destination(again s3 in our case)
- automate the workflow
Pre requisites:
Now to accomplish the first part i.e to get the transcoding done with watermarks on ec2 we will get an ec2 instance and connect to it with the help of aws console then we will install ffmpeg and awscli on it moreover we will then copy following scripts aws_credentials.sh , copy_log.sh and encoding_script_watermarked.sh this ec2 instance. Also I am using a font inside this folder Aaargh/Aaargh.ttf you can use any font once you link to it properly.
we will be using ffmpeg for transcoding. Before moving further and installing ffmpeg you have to be sure that you have the necessary libraries by checking if the ffmpeg build is right for example for our purposes you can install ffmpeg
sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get dist-upgrade
sudo apt-get install ffmpeg
credits to source
we will aso be using aws cli to copy files from and to s3
#install pip
sudo apt-get install python-pip
#aws interaction with s3 with awscli==1.10.8
pip install awscli
once you have all the necessary scripts on the ec2 instance you can create and image for this instance, image-id from which we can use later on The scripts will handle the actual transcoding and copying of files
Now comes the part where you automate the transcoding and get an instance up whenever you like and transcode the video we will use python and boto for this for this part we will use ec2_instance_switch.py script and then we can just call the python shell.
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python manage.py shell
from ec2_instance_switch import generate_burned_watermark_screener
generate_burned_watermark_screener()
if everything went fine you should see your instance getting up which you can check from ec2 console too , It will copy the original file (for now assumed to be mp4) to ec2 and then burn the watermark text at desiered position with hls (adaptive streaming enabled) and then save it back on s3 and give us the link for final master index file. After the transcoding is done it will close the instance and save the logs on s3 for future refrence it will also save the time it took for different transcode versions to complete.
Code Files which you will need:
aws_credentials.sh:
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#!/bin/bash
export AWS_ACCESS_KEY_ID='your_aws_key'
export AWS_SECRET_ACCESS_KEY='your_aws_secret'
export AWS_DEFAULT_REGION='your_aws_region'
copy_logs.sh:
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#!/bin/bash
source ./aws_credentials.sh
# help text displayed at various times to guide user how to invoke the bash script
helptext="$(basename "$0") [-h] [-f p v] -- program to get burned in watermark hls videos with master list with ffmpeg logs
e.g mutliple word argument processor:
time bash copy_logs.sh --projectid=3631 --mothervideoid="3799" --videoid="3798" -server="your_bucket_name"
e.g with log files:
(time bash copy_logs.sh -p="3631" -m="3799" -v="3800" -s="your_bucket_name") 2>> encoding_logs.log
where:
-h show this help text
-p project id
-s server
-m mother video id
-v video id"
#for parsing command line arguments
#Display message incase no arguments are supplied
if [[ $# -eq 0 ]] ; then
echo "please provide necessary arguments check help text for guidance:" >> encoding_logs.log
echo $helptext >> encoding_logs.log
exit 0
fi
for i in "$@"
do
case $i in
-p=*|--projectid=*)
INPUT_PROJECT_ID="${i#*=}"
shift # past argument=value
;;
-v=*|--videoid=*)
INPUT_VIDEO_ID="${i#*=}"
shift # past argument=value
;;
-m=*|--mothervideoid=*)
INPUT_MOTHER_VIDEO="${i#*=}"
shift # past argument=value
;;
-s=*|--server=*)
SERVER="${i#*=}"
shift # past argument=value
;;
--default)
DEFAULT=YES
shift # past argument with no value
;;
*)
echo 'please provide correct arguments check help text for guidance:'
echo $helptext
exit 0
;;
esac
done
#print the argumnets read
echo "INPUT PROJECT ID = ${INPUT_PROJECT_ID}"
echo "INPUT VIDEO ID = ${INPUT_VIDEO_ID}"
echo "INPUT MOTHER VIDEO ID = ${INPUT_MOTHER_VIDEO}"
echo "SERVER NAME = ${SERVER}"
#setting the values for script as per input values
export PROJECT_ID=${INPUT_PROJECT_ID}
export VIDEO_ID=${INPUT_VIDEO_ID}
export SERVER_NAME=${SERVER}
export MOTHER_VIDEO_ID=${INPUT_MOTHER_VIDEO}
echo $AWS_ACCESS_KEY_ID
#this is the place where from you copy the original video which will be transcoded you can alter it as per your need
aws s3 cp encoding_logs.log s3://$SERVER_NAME/$PROJECT_ID/video/$MOTHER_VIDEO_ID/$VIDEO_ID/
#stop instance
export AWS_DEFAULT_REGION='us-east-1e'
export InstanceId=`curl http://169.254.169.254/latest/meta-data/instance-id;echo`
aws ec2 stop-instances --instance-ids ${InstanceId} --region us-east-1
ec2_instance_switch.py:
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import boto
import time
import json
import simplejson
import datetime
from boto.s3.connection import S3Connection
from django.conf import settings
# AWS credentials
aws_key = settings.AWS_ACCESS_KEY_ID
aws_secret = settings.AWS_SECRET_ACCESS_KEY
def get_conection():
conn = boto.connect_ec2(aws_key, aws_secret)
return conn
def get_watermark_position(video):
#based on the parent video watermark position choose one from below
#1.Bottom left
#2.Bottom center
#3.Bottom right
#4.Middle left
#5.Middle center
#6.Middle right
#7.Top left
#8.Top center
#9.Top right
# you can get it for other positions too
if video.watermark_pos == 'top':
burned_position = '8'
elif video.watermark_pos == 'middle':
burned_position = '5'
elif video.watermark_pos == 'bottom':
burned_position = '2'
else:
print("This value of watermark position not known, using default")
burned_position = '2'
return burned_position
def get_video_duration(video):
#add the watermark and send the time for both the full length burned watermark and also add the position for the visible watermark
try:
# you must have video duration in milliseconds
video_duration_in_ms=56000
miliseconds = int(video_duration_in_ms)
hours, milliseconds = divmod(miliseconds, 3600000)
minutes, milliseconds = divmod(miliseconds, 60000)
seconds = float(milliseconds) / 1000
burnedin_end_time = "%i:%02i:%06.3f" % (hours, minutes, seconds)
#'0:00:52.254'
return burnedin_end_time
except Exception as durexecp:
print(durexecp)
def get_video_details(video):
try:
#get base file
#some_s3_link/test_file.mo4
original_base_file = video.original_url.split('/')[-1]#test_file.mp4
#get watermark position
burned_position = get_watermark_position(video)
#get video durations
burnedin_end_time = get_video_duration(video)
return original_base_file,burned_position, burnedin_end_time
except Exception as vnaexp:
print('Some issue occured while getting video details')
print(vnaexp)
def keyexistsonS3(key):
conn = S3Connection(aws_secret_access_key=aws_secret,aws_access_key_id=aws_key)
bucket = conn.get_bucket(settings.AWS_BUCKET_NAME, validate=True)
try:
# Will hit the API to check if it exists.
possible_key = bucket.get_key(key)
if possible_key:
return True
else:
return False
except Exception as e:
return False
def transcode_request_for_ec2(watermark_text,mother_video):
mother_video_id =str(mother_video.id)
new_video = mother_video
new_video.pk = None #django shuould set it
new_video.save()
project_id = str(new_video.project.id)
#for simple test you can just input these values, new video has most details same as old one except the watermarking
original_base_file, burned_position, hidden_position, burnedin_end_time, h_burnedin_start_time, h_burnedin_end_time = get_video_details(new_video)
video_id = str(new_video.id)
bucket_name = settings.AWS_BUCKET_NAME
# Connect to EC2
conn = get_conection()
#we can add a parameter to check which formats we need in future
BOOTSTRAP_SCRIPT = """#!/bin/bash -ex
exec > >(tee /var/log/user-data.log|logger -t user-data -s 2>/dev/console) 2>&1
echo BEGIN
date
cd /home/ubuntu/
pwd
while [ ! -f ./encoding_script_watermarked.sh ]; do sleep 2;echo "loading script..."; done
echo "script loaded"
((time bash ./encoding_script_watermarked.sh -p='%(PROJECT_ID)s' -m='%(MOTHER_VIDEO_ID)s' -v='%(VIDEO_ID)s' -f='%(FILE_NAME)s' -b="%(BURNED_END_TIME)s" -a="%(BURNED_POSITION)s" -w="%(WATERMARK_TEXT)s" -s='%(BUCKET_NAME)s') &>> encoding_logs.log; bash ./copy_logs.sh -p='%(PROJECT_ID)s' -m='%(MOTHER_VIDEO_ID)s' -v='%(VIDEO_ID)s' -s='%(BUCKET_NAME)s')
echo END
"""
burned_end_time= str(burnedin_end_time)
startup = BOOTSTRAP_SCRIPT % {
'PROJECT_ID': project_id,
'VIDEO_ID': video_id,
'FILE_NAME': original_base_file,
'BURNED_END_TIME': burned_end_time,
'BURNED_POSITION': burned_position,
'WATERMARK_TEXT': watermark_text,
'MOTHER_VIDEO_ID':mother_video_id,
'BUCKET_NAME': bucket_name}
print(startup)
instance_reservation = conn.run_instances(
image_id="ami-ac3640c1",# use the ami for the image which we created earlier
instance_type="c3.xlarge",#instance type you want to use
key_name="your_key_file",
security_groups=["ffmpeg-test-security-group"],
user_data=startup
)
instance = instance_reservation.instances[0]
print(instance)
#wait till the instance is not running
while instance.state != 'running':
print ('...instance is %s' % instance.state)
time.sleep(10)
instance.update()
#tag instcance once its running
instance_name = str(mother_video_id)+'-'+str(video_id)+'-'+str(datetime.datetime.now())
print(instance_name)
instance.add_tag("Name",instance_name)
#now the instance is running we should check for processed data in s3 after some avegare time
#wait till instance has not stopped
while instance.state != 'stopped':
print ('...instance is %s' % instance.state)
time.sleep(10)
instance.update()
#check if the files are present on s3, .ts files , index files and master file
if keyexistsonS3(project_id+'/video/'+mother_video_id+'/'+video_id+'/'+'master_'+project_id+'_'+video_id+'.m3u8'):
master_url_tobe_saved = 'https://'+str(settings.AWS_BUCKET_NAME)+'.s3.amazonaws.com/'+project_id+'/video/'+mother_video_id+'/'+video_id+'/'+'master_'+project_id+'_'+video_id+'.m3u8'
print(master_url_for_hls_video)
else:
#if not then process failed and we can retry and report and should never terminate the instance, also get a failuer mail
print('some s3 files are missing something went haywire with instance %s' % instance)
return None
def generate_burned_watermark_screener():
#I am using a video object here for simplicity
mother_video_id ="3627"
watermark_text ="Ec2 test 104"
mother_video = Videos.objects.get(id=mother_video_id)
#generate the burned watermark video
print('calling ec2')
#pdb.set_trace()
burned_video = transcode_request_for_ec2(watermark_text,mother_video)
print('got the video')
print(burned_video)
encoding_script_watermarked.sh
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#!/bin/bash
source ./aws_credentials.sh
# help text displayed at various times to guide user how to invoke the bash script
helptext="$(basename "$0") [-h] [-f p v] -- program to get burned in watermark hls videos with master list with ffmpeg
e.g mutliple word argument processor:
time bash encoding_script_watermarked.sh --projectid="3631" --videoid="3798" --videofile="3631_6.mp4" -server="your_bucket"
with log files:
9time bash encoding_script_watermarked.sh -p="3631" -m="3799" -v="3800" -f="3631_6.mp4" -b="0:00:52.254" -i="0:00:17.418" -z="0:00:17.433" -a="5" -c="6" -w="this is test watermark text" -s="your_bucket") 2>> encoding_logs.log
where:
-h show this help text
-f link to video, file name
-p project id
-s server
-b burned watermark end time
-a burned watermakr position
-w watermakr text
-m mother video id
-v video id"
#for parsing command line arguments
#Display message incase no arguments are supplied
if [[ $# -eq 0 ]] ; then
echo "please provide necessary arguments check help text for guidance:" >> encoding_logs.log
echo $helptext >> encoding_logs.log
exit 0
fi
for i in "$@"
do
case $i in
-f=*|--videofile=*)
INPUT_VIDEO_FILE_KEY="${i#*=}"
shift # past argument=value
;;
-p=*|--projectid=*)
INPUT_PROJECT_ID="${i#*=}"
shift # past argument=value
;;
-v=*|--videoid=*)
INPUT_VIDEO_ID="${i#*=}"
shift # past argument=value
;;
-b=*|--burnedendtime=*)
INPUT_BURNED_END_TIME="${i#*=}"
shift # past argument=value
;;
-a=*|--burnedposition=*)
INPUT_BURNED_POSITION="${i#*=}"
shift # past argument=value
;;
-w=*|--watermarktext=*)
INPUT_WATERMARK_TEXT="${i#*=}"
shift # past argument=value
;;
-m=*|--mothervideoid=*)
INPUT_MOTHER_VIDEO="${i#*=}"
shift # past argument=value
;;
-s=*|--server=*)
SERVER="${i#*=}"
shift # past argument=value
;;
--default)
DEFAULT=YES
shift # past argument with no value
;;
*)
echo 'please provide correct arguments check help text for guidance:'
echo $helptext
exit 0
;;
esac
done
{
#print the argumnets read
echo "INPUT VIDEO FILE = ${INPUT_VIDEO_FILE_KEY}"
echo "INPUT PROJECT ID = ${INPUT_PROJECT_ID}"
echo "INPUT VIDEO ID = ${INPUT_VIDEO_ID}"
echo "INPUT MOTHER VIDEO ID = ${INPUT_MOTHER_VIDEO}"
echo "SERVER NAME = ${SERVER}"
#for dynamically creating .ass file
echo "INPUT BURNED WATERMARK END TIME = ${INPUT_BURNED_END_TIME}"
echo "INPUT BURNED WATERMARK POSITION = ${INPUT_BURNED_POSITION}"
echo "INPUT WATERMARK TEXT = ${INPUT_WATERMARK_TEXT}"
#setting the values for script as per input values
export PROJECT_ID=${INPUT_PROJECT_ID}
export VIDEO_ID=${INPUT_VIDEO_ID}
export SERVER_NAME=${SERVER}
export INPUT_LINK=${INPUT_VIDEO_FILE_KEY}
export MOTHER_VIDEO_ID=${INPUT_MOTHER_VIDEO}
#for dynamically creating .ass file
export BURNED_END_TIME=${INPUT_BURNED_END_TIME}
export BURNED_POSITION=${INPUT_BURNED_POSITION}
export WATERMARK_TEXT=${INPUT_WATERMARK_TEXT}
#creating .ass file dynamically for generating different watermarks and it also gives on control on styling as mentioned below
cat << EOF > "dynamic_subtitle_"$VIDEO_ID".ass"
[Script Info]
; Script generated by FFmpeg/Lavc57.24.103
ScriptType: v4.00+
PlayResX: 384
PlayResY: 288
[V4+ Styles]
Format: Name, Fontname, Fontsize, PrimaryColour, SecondaryColour, OutlineColour, BackColour, Bold, Italic, Underline, StrikeOut, ScaleX, ScaleY, Spacing, Angle, BorderStyle, Outline, Shadow, Alignment, MarginL, MarginR, MarginV, Encoding
Style: Default,Arial,16,&H99999999,&H99999999,&H0,&H0,0,0,0,0,100,100,0,0,1,0,0,$BURNED_POSITION,10,10,10,0
[Events]
Format: Layer, Start, End, Style, Name, MarginL, MarginR, MarginV, Effect, Text
Dialogue: 0,0:00:00.00,$BURNED_END_TIME,Default,,0,0,0,,$WATERMARK_TEXT
EOF
echo "copying original from s3 ..." >> encoding_logs.log
#download the file from s3 and parse it for name, for now assuming that the file is mp4
(time aws s3 cp s3://$SERVER_NAME/$PROJECT_ID/video/$INPUT_LINK . ) &>> encoding_logs.log
#set downloaded file as the input for transcoding
export INPUT_VIDEO_FILE=$INPUT_LINK
#check if all the necessary arguments are present, note spacing is important in bash ( as Bash uses spaces to tokenise scripts)
if [[ PROJECT_ID != "" && VIDEO_ID != "" && INPUT_VIDEO_FILE != "" && SERVER_NAME != "" ]]
then
#starting notifications
echo "The ffmpeg encoding is starting \n"
echo "encoding for $PROJECT_ID for video id $VIDEO_ID has beengg started using input file $INPUT_VIDEO_FILE \n" >> encoding_logs.log
#for -profile:v details are here- https://trac.ffmpeg.org/wiki/Encode/H.264, for other options check, ffmpeg -h
echo "temp directory for video to be saved in s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/" >> encoding_logs.log
#make directory if not present
mkdir -p "s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/"
#360 version
echo ffmpeg -i $INPUT_VIDEO_FILE -profile:v baseline -level 4.0 -vf "scale=-2:360,subtitles='dynamic_subtitle_'$VIDEO_ID'.ass':force_style='FontName=Aaargh/Aaargh.ttf,PrimaryColour=&H664c4c4c" -start_number 0 -hls_time 10 -hls_list_size 0 -f hls s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/$VIDEO_ID"_360_.m3u8"
echo "starting encoding ..." >> encoding_logs.log
#360 version
(time ffmpeg -i $INPUT_VIDEO_FILE -profile:v baseline -level 4.0 -vf "scale=-2:360,subtitles='dynamic_subtitle_'$VIDEO_ID'.ass':force_style='FontName=Aaargh/Aaargh.ttf,PrimaryColour=&H664c4c4c" -start_number 0 -hls_time 10 -hls_list_size 0 -f hls s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/$VIDEO_ID"_360_.m3u8" && echo "360 version:" >> encoding_logs.log ) 2>> encoding_logs.log &
#480 version
(time ffmpeg -i $INPUT_VIDEO_FILE -profile:v baseline -level 4.0 -vf "scale=-2:480,subtitles='dynamic_subtitle_'$VIDEO_ID'.ass':force_style='FontName=Aaargh/Aaargh.ttf,PrimaryColour=&H664c4c4c" -start_number 0 -hls_time 10 -hls_list_size 0 -f hls s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/$VIDEO_ID"_480_.m3u8" && echo "480 version" >> encoding_logs.log) 2>> encoding_logs.log &
#720 version
(time ffmpeg -i $INPUT_VIDEO_FILE -profile:v baseline -level 4.0 -vf "scale=-2:720,subtitles='dynamic_subtitle_'$VIDEO_ID'.ass':force_style='FontName=Aaargh/Aaargh.ttf,PrimaryColour=&H664c4c4c" -start_number 0 -hls_time 10 -hls_list_size 0 -f hls s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/$VIDEO_ID"_720_.m3u8" && echo "720 version" >> encoding_logs.log ) 2>> encoding_logs.log &
#1080 version
(time ffmpeg -i $INPUT_VIDEO_FILE -profile:v baseline -level 4.0 -vf "scale=-2:1080,subtitles='dynamic_subtitle_'$VIDEO_ID'.ass':force_style='FontName=Aaargh/Aaargh.ttf,PrimaryColour=&H664c4c4c" -start_number 0 -hls_time 10 -hls_list_size 0 -f hls s3_temp/your_bucket/$PROJECT_ID/videos/$VIDEO_ID/$VIDEO_ID"_1080_.m3u8" && echo "1080 version" >> encoding_logs.log ) 2>> encoding_logs.log &
echo "The ffmpeg encoding has ended\n" >> encoding_logs.log
#creating a master playlist for hls videos for adaptive streaming
cat << EOF > "s3_temp/your_bucket/"$PROJECT_ID/videos/$VIDEO_ID/master_$PROJECT_ID"_"$VIDEO_ID".m3u8"
#EXTM3U
#EXT-X-STREAM-INF:PROGRAM-ID=1,BANDWIDTH=1128000,RESOLUTION=640x360,CODECS="avc1.42001e,mp4a.40.2"
${VIDEO_ID}_360_.m3u8
#EXT-X-STREAM-INF:PROGRAM-ID=1,BANDWIDTH=1803000,RESOLUTION=854x480,CODECS="avc1.42001f,mp4a.40.2"
${VIDEO_ID}_480_.m3u8
#EXT-X-STREAM-INF:PROGRAM-ID=1,BANDWIDTH=3138000,RESOLUTION=1280x720,CODECS="avc1.42001f,mp4a.40.2"
${VIDEO_ID}_720_.m3u8
#EXT-X-STREAM-INF:PROGRAM-ID=1,BANDWIDTH=4865000,RESOLUTION=1920x1080,CODECS="avc1.420028,mp4a.40.2"
${VIDEO_ID}_1080_.m3u8
EOF
#uploading files to s3
echo "uploading processed files to s3 ..." >> encoding_logs.log
(time aws s3 cp s3_temp/$SERVER_NAME/$PROJECT_ID/videos/$VIDEO_ID/ s3://$SERVER_NAME/$PROJECT_ID/video/$MOTHER_VIDEO_ID/$VIDEO_ID/ --recursive) 2>> encoding_logs.log
else
echo "Please provide the necessart arguments"
echo $helptext >> encoding_logs.log
fi
} || {
echo "some error occured while runing transcoding bash script"
}
So thus you have now trancoded the video over cloud . Congratulations you have completed your cloud computing 101 lesson !