Instaclustr provides Cassandra as a service running in the cloud on AWS and Azure. It allows companies to focus on their applications instead of managing Cassandra infrastructure. Instaclustr's fully managed service handles deploying and operating Cassandra clusters in the cloud at global scale. An advertising company was able to improve the performance of their application serving targeted ads by moving their Cassandra cluster to Instaclustr's cloud service for flexibility and reduced management burden.

1. Cassandra in the Cloud
Adam Zegelin
Co-founder and VP of Engineering @ Instaclustr.
Sydney Tech Day
instaclustr.com
@Instaclustr

2. Instaclustr
• Instaclustr provides Cassandra-as-a-Service in the cloud.
• Aussie startup, based out of Canberra.
Our CTO, Ben Bromhead, recently opened our Silicon Valley office. We’re soon to open an
office in London.
• Real production experience — several customers in production.
• Currently run on Amazon Web Services, Microsoft Azure in private beta.
In discussion with Google and IBM, more to come.
• DataStax are investors & partners.

3. • Ben and myself started as a different company — data hosting &
market-place, running in the cloud.
• As a startup we wanted to use Cassandra in the cloud alongside
our app, but not host & manage it
• Founded Instaclustr — now our full focus
• Instaclustr: Focus on writing your app, not managing database
infrastructure

4. C* Model
• One database, many servers
• All servers (nodes) participate in the cluster
• Decentralised
• Need more capacity? Add more servers!
• Multiple servers ≣ built in redundancy

5. 100,000
ops/sec
200,000
ops/sec
400,000
ops/sec

6. client
0
4
28
0
4
28
client

7. Hosting C*
• Traditional — servers, racks, data centres
• Cloud — unlimited* compute resources
• Hybrid/cloud bursting — overflow into the cloud

8. Traditional Model
• Buy or rent your own servers
• Manage hardware & software deployments and updates
• Slow time to market
• In-flexible
• Buy enough hardware to handle peak load upfront
• Requires good capacity planning
• Co-locate in a data centre
Or build your own if your big enough (or have certain requirements)

9. ☁
• Pay for what you use
• Hardware is no-longer a concern
• Almost instant-on compute resources
< 1 minute boot time
• Flexible
• Scale up and down with load
• Respond quickly to changes in capacity requirements

10. ☁
• Node replacement is easy
• Global Deployments
C* nodes with data replica + app instance close to your users.
• Redundancy — not all your eggs in one basket
Availability zones, regions, providers
• Split workloads — one DC for the app, one DC for analytics
Reduce the performance impact of data analytics on user facing nodes

11. Hybrid/Cloud Bursting
• C* nodes in your own data centre and C* nodes in the cloud
• Both are C* replicated data centres
• Live backups & fail-over — faster data recovery
• On-demand extra capacity for planed peak loads
• Periodic computationally expensive analytics jobs

12. Amazon Web Services
• Largest cloud provider — well supported (documentation, community,
value-add services)
• Multiple regions — Sydney, APAC, US, Europe
• Node sizes to fit all C* use cases
• SSD-backed nodes
• Virtual Private Clouds
• VPNs and VPC peering for isolated access

13. Gotchas
• Buggy APIs
• Noisy neighbours
• Data sovereignty & security

14. C* + ☁ + Instaclustr
• We run C* for metrics and log storage
Also dog-fooding
• The scale of this cluster — both performance & storage — will grow
as we manage more nodes
More nodes = more data + more ops/sec
• Improved dev & testing — Every developer can run their own copy
of our app + the monitoring cluster, on-demand

15. Case Study
• Advertising company — recording click metrics and serve targeted advertisements
• Requires < 10 ms response time from C*
• Originally managed it themselves
• Managing their app and the C* cluster was a burden on their engineering team
• Switched over to Instaclustr
• Instaclustr + Cloud + C* is flexible.
Their performance requirements changed and the cloud & C* allowed us to change the underlying virtual
machines. In production. At runtime.

16. Thank you!
adam@instaclustr.com ∙ @zegelin