Hi
user
Admin Login:
Username:
Password:
Name:
Scaling python services - the Spotify way.
--client
pygotham
--show
pygotham_2012
--room The_Spotify_Room_Room_6 1041 --force
Next: 1 Large scale collaborative filtering
show more...
Marks
Author(s):
Kinshuk Mishra
Location
The Spotify Room: Room 6
Date
jun Sat 09
Days Raw Files
Start
13:00
First Raw Start
error-in-template
Duration
00:50:00
Offset
None
End
13:50
Last Raw End
Chapters
Total cuts_time
None min.
raw-playlist
raw-mp4-playlist
encoded-files-playlist
mp4
svg
png
assets
release.pdf
Scaling_python_services_the_Spotify_way.json
logs
Admin:
episode
episode list
cut list
raw files day
marks day
marks day
image_files
State:
---------
borked
edit
encode
push to queue
post
richard
review 1
email
review 2
make public
tweet
to-miror
conf
done
Locked:
clear this to unlock
Locked by:
user/process that locked.
Start:
initially scheduled time from master, adjusted to match reality
Duration:
length in hh:mm:ss
Name:
Video Title (shows in video search results)
Emails:
email(s) of the presenter(s)
Released:
has someone authorised pubication
Unknown
Yes
No
Normalise:
Channelcopy:
m=mono, 01=copy left to right, 10=right to left, 00=ignore.
Thumbnail:
filename.png
Description:
markdown
The talk will focus on the techniques Spotify employs to scale several services like playlist, radio, ads, etc to offer the complete music experience around the clock to millions of users. We will talk about how we scale horizontally by making our services stateless, by smartly caching and sharding data and several other tricks like using SRV DNS records for service discovery.
Comment:
production notes
Rf filename:
root is .../show/dv/location/, example: 2013-03-13/13:13:30.dv
Sequence:
get this:
check and save to add this
Veyepar
Video Eyeball Processor and Review