SlideShare una empresa de Scribd logo
1 de 23
1
building lightning fast apps
over CF and BOSH
2
Leading the commercial Redis market
Founded in 2011; GA in 02/2013
2,200+ paying customers; 50,000+ DBs; 100+ new
DBs/day
2nd largest contributor to open source Redis
Raised $13M - Bain/Carmel/Strategic/Angels
Offices in Santa Clara and Tel-Aviv
In a nutshell
3
Redis Cloud Memcached Cloud
Our offering
Fully-managed cloud services.
On-prem server license - soon.
3
4
Launching
Redis Labs Cluster
with BOSH
5
Why Redis ?
6
The newest NoSQL create by Salvatore Sanfilippo (@antirez)
The fastest data store available today (served entirely from
RAM)
Among the top 3 databases chosen by developers
Much more than a simple key/value - Strings, Hashes, Lists,
Sets, Sorted Set, LUA, transactions, Bits operations
Strong use cases, dynamic community, large eco-system
Redis
7
100msec =
Fast apps requirements
max E2E response time, under any
load
50msec = average Internet latency
50msec = required app response time (includes
processing & multi DB accesses)
1msec = required DB response time
The only database to meet requirement=
8
DB performance comparison
@<1msec
@<1msec
@<1msec
@<20msec
@<10-50msec
@<10-50msec
@<100msec
@<100msec
@>100msec
9
Timeline
Followers
Caching
Messaging
Geo search
Leaderboards
Job management
RT analytics
Verticals & main use cases
Online
advertising
Social Gaming Financial
Services
10
• Multi-TB in memory
• ~ 300,000 reads/sec
• ~ 5,000*N writes/sec
N - # of followers
Twitter
Every Timeline
(800 tweets per user)
is on Redis
11
• 20TB+ in memory
• ~ 6,000,000 reads/sec
• ~ 600,000 writes/sec
Weibo (Chinese Twitter)
• Counting
• Reverse cache
• Top 10 lists
• Last Index
• Relational list/Message Queue
• Fast transactions w/ LUA
12
Pinterest
Object graph:
• Per user (Sorted Set w/ timestamp as score)
 store the users followed (explicit+ implicit)
 store the user’s followers (explicit+implicit)
• Per board
 Redis Hash for storing explicit followers
 Redis Set for storing explicit unfollowers
13
Stack Overflow
Three levels of cache:
• Local cache (no persistence)
 sessions, and pending view count updates
• Site cache
 hot question id lists, users acceptance rates..
• Global cache
 Inboxes, API usage quotas, …
14
Github
• Redis is used for routing info
• Matching user repositories to server names
15
Hipchat
• Which users are in which room
• Who is online
• XMPP server balancing
16
Youporn
Most data is found in Hashes with ordered Sets used to know
what data to show
(1) ZinterStore on:
{videos:filters:release}{videos:filters:orientation:straight}
{videos:filters:categories(id)}{videos:ordering:rating}
(2) Perform a ZRANGE to get the pages we want and get the list
of video_ids back
(3) Start pipelining to get all the videos from Hashes
17
Snapchat
• 500+ instances
• 15-50TB
• Running on GCE
400M messages/day
18
Why Redis Labs ?
19
Infinite seamless scalability
True high-availability
Stable top performance
Zero management
Users choose us because..
20
We invested a lot…
• 20+ man-years spent on R&D
• 15 Redis experts on team
Optimal Redis deployment environment
• [BOSH] Bootstrapping Redis Labs cluster (over EC2)
• [Redis Labs Console] Create a plan & set CF Credentials
• [CF]: Create & bind service
• Show a working app (try.redis)
• SSO
The Demo
22
Questions ?
23
Thank You

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How to Build a High Performance Application Using Cloud Foundry and Redis (Cloud Foundry Summit 2014)

Notas del editor

  1. 20 13 Cont ributer
  2. You probably ask yourself why Redis
  3. Choozen
  4. At bottom An at the top is Redis
  5. Let’s run through it quickly
  6. What are the benefits of using us You performance can vary quite a bit