Acunu is developing an enterprise Cassandra appliance called Castle that aims to simplify Cassandra deployment and management. Castle includes a storage engine optimized for large disks and workloads, and allows for high density on commodity hardware. It also features fast disk rebuilds through its shared memory architecture. Acunu provides a web UI called the Control Center to configure, monitor, and troubleshoot Castle without deep Cassandra expertise. Acunu performs extensive automated testing of Castle to ensure reliability.
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Next Generation Cassandra
1. Next Generation
Cassandra
Tom Wilkie
Founder & VP Engineering, Acunu
3. Cassandra needs a team
Installing, con鍖guring and deploying
Automating management operations
Monitoring and alerting $ $ $
$
Testing and 鍖xing bugs
Tuning the garbage collector
Tweaking the storage engine
3
4. Acunu: your enterprise Cassandra Appliance
Data driven applications Web UI
Apache Cassandra
Control
Center
Acunu Storage Engine
Con鍖gured and tuned OS
Commodity Hardware
4
6. Castle: Built for Big Data
Storage engine optimized for large slow disks,
many cores, Big Data workloads
Enterprise density on commodity hardware
Lightning disk rebuilds:10x faster than RAID
Shared memory interface
Castle
keys
Userspace
Acunu Kernel
userspace
interface
values
In-kernel
async, shared
memory ring workloads
shared buffers
kernelspace
Streaming interface
interface
range key buffered key buffered
queries insert value insert get value get
Doubling Arrays Opensource (GPLv2, MIT
doubling array
mapping layer
for user libraries)
insert Bloom 鍖lters
queues key
get
arrays x
range arrays
queries management
http://goo.gl/gzihe
key
insert merges
http://bitbucket.org/acunu
Arrays
mapping layer
modlist btree
key Version tree
Loadable Kernel Module,
insert btree
key
get
btree
targeting CentOSs 2.6.18
range
queries value arrays
6
Cache
apping &
http://www.acunu.com/
ng layer
"Extent" layer
prefetc
extent block
extent cache
10. Control Center
The new UI has been critical in helping us work out what is wrong in our code
The new UI has been critical in helping us work out
what is wrong in our code
- Matt Miller, TellyBug
12. 13,000 tests per day
1.1 million tests per release
3.5k machine days of testing
for each release
12
13. Short, unit tests
Distributed tests
Data integrity tests
Tests for common, long running operations
(bootstrap, decommission, backup, restore etc)
Failure simulation
Resource usage tests
(checking memory and cpu consumption)
Long running performance tests
13
18. Turnkey Cassandra
No need to master the internals
No tuning required
No need for a committer on staff