This document discusses the journey of a company moving from a Microsoft-based infrastructure to using open source NoSQL databases like Cassandra and Aerospike to handle increasing data and performance needs. It describes initial experiments with Cassandra that showed promise but eventually led to performance issues as data and request volumes grew. An evaluation of Aerospike demonstrated significantly better consistent performance and simplified operations, leading to it replacing Cassandra in production. Lessons learned include regularly evaluating technology choices and being open to alternatives as needs change over time.

2. ABOUT
Simple developer
In DSP team
Real time auction engine for Ads

3. BUSINESS CASE
A lot of users
A lot of data
Real time decision making
Based on data we have

4. CONTENT
We are living with Cassandra already more than
26000 hours and counting
I picked up random moments from our interesting
marriage
Sometimes sleepless nights
A lot of intense days
Some experience gained hopefully
Come by and discuss things

5. I was born

6. Went to school

7. Finished university

8. Something special has happened

9. LET’S STORE COOKIE PROFILES FIRST
Search for fast, scalable storage
Capable of storing big amount of data
And handle write intense workload
Please, not SQL Server again?

10. OH, NO-SQL YOU SAY
Cassandra!
Let’s do some benchmarks and compare!… with
what?
Ok… let’s bring it home

11. HAPPY MOMENT
Adform was mainly Microsoft based company
First open source project in company
First “Linux first” piece of software
First COOL tech
Started to adopt other open source / not Microsoft
solutions afterwards

12. MICROSOFT BASED…
No Linux experience etc.
Let’s run on windows  as it’s written in JAVA
All services was written in .NET
…and no libraries for .NET at all
Virtualization…

13. HAPPY MOMENT
It’s very fun to invent things
In house .NET client with failover, load balancing,
dynamic node discovery

14. FINALLY UP AND RUNNING
3 (+-) years ago started in PROD with version 0.7
beta 2
Everything was running smooth with few gigs of
data
Hardware had a lot of spare capacity
Were proud NO SQL experts 

15. DSP KICKS IN
Decision to start DSP project
Data in Cassandra for decision making
A lot of frontend servers
More reads and
… 20 ms. per requests SLA

16. 20 MS
20 MS – GAME CHANGER
OK when you can allow 100 MS for part of the
requests

17. SAD MOMENT
Move from Windows to Linux
Move from virtual to bare metal
“Smart” in house Cassandra client
Data access tuning for ex. Dynamic snitch
Optimizing memory usage
Code base optimized on data access
Data in RAM
GC tuning
Compaction tuning
Consultancy

18. SAD MOMENT
Fat nodes
Stability

19. RESULTED IN
A lot of DEV time spent
On tracking changes in new Cassandra
releases
Tweaking configuration
Monitoring compactions, read stages etc.
Thinking about further optimizations
…but…
Experience was extracted 

20. AND ON TOP
Scale 4x times!!!
Maybe it’s time to search for alternatives
Fast read access
CONSISTENT read access
Fat nodes
Low time on maintenance
.NET “compatible”

21. AEROSPIKE
Aerospike?
Not open source at that time
Quite amount of money
Promises looks too good
Everyone skeptical
But let’s give a shot

22. SHOT
POC cluster
2 nodes, SSD based, consumer grade discs
Shadow workload
No tweaking
“FAT” nodes

23. SHOT
Forgot all skepticism in one week
POC became PROD
Disc load >90%
5 month no problems
99% < 10ms consistent performance
Simpler, easier to maintain code base
Focus on business

24. JUST IN CASE
So we are running on proprietary piece of software
But.. data model, access patterns are compatible
with most nosql’s
Just in case 
It’s already open source 

25. CASSANDRA
Cassandra still in toolbox
To maintain knowledge base
And it’s great
For less time restricted workloads
Write workloads
Other cases

26. THE END
When you feel that someone becomes too big part
of your life
In not pleasant way
Search for alternatives
Love ends in 3 years
Data model is important
Read documentation (limitations etc.)
I don’t know – maybe there is more

27. NUMBERS
2 storage servers
1 TB of data
120 000 reads
8 000 writes
42 client servers