2. agenda
introduction to kafka
kafka @ finn.no
101* mistakes
questions
“From a certain point onward
there is no longer any turning
back. That is the point that
must be reached.”
― Franz Kafka, The Trial
3. Top 5
1. no consideration of data on the
inside vs outside
2. schema not externally defined
3. same config for every
client/topic
4. 128 partitions as default config
5. running on 8 overloaded nodes
4. FINN.no
2nd largest website in norway
classified ads ( Ebay, Zillow in one)
60 millions pageviews a day
80 microservices
130 developers
1000 deploys to production a week
6 minutes from commit to deploy
(median)
8. #kafkasummit @spjelkavik @audunstrand
in the beginning ...
Architecture governance board decided to use RabbitMQ as message queue.
Kafka was installed for a proof of concept, after developers spotted it januar 2013.
9. #kafkasummit @spjelkavik @audunstrand
2013 - POC
“High” volume
Stream of classified ads
Ad matching
Ad indexed
mod05
zk
kafka
mod07
zk
kafka
mod01
zk
kafka
mod03
zk
kafka
mod06
zk
kafka
mod08
zk
kafka
mod02
zk
kafka
mod04
zk
kafka
dc 1
dc 2
Version 0.8.1
4 partitions
common client
java library
thrift
10. #kafkasummit @spjelkavik @audunstrand
2014 - Adoption and
complaining
low volume/ high
reliability
Ad Insert
Product Orchestration
Payment
Build Pipeline
click streams
mod05
zk
kafka
mod07
zk
kafka
mod01
zk
kafka
mod03
zk
kafka
mod06
zk
kafka
mod08
zk
kafka
mod02
zk
kafka
mod04
zk
kafka
dc 1
dc 2
Version 0.8.1
4 partitions
experimenting
with
configuration
common java
library
16. Pattern
Language
why is it a mistake
what is the consequence
what is the correct solution
what has finn.no done
17. Top 5
1. no consideration of data on the
inside vs outside
2. schema not externally defined
3. same config for every
client/topic
4. 128 partitions as default config
5. running on 8 overloaded nodes
20. #kafkasummit @spjelkavik @audunstrand
what is the consequence
direct reads across services/domains is quite normal in legacy and/or enterprise
systems
coupling makes it hard to make changes
unknown and unwanted coupling has a cost
Kafka had no security per topic - you must add that yourself
21. #kafkasummit @spjelkavik @audunstrand
what is the correct solution
Consider what is data on the inside, versus data on the outside
Convention for what is private data and what is public data
If you want to change your internal representation often, map it before publishing it
publicly (Anti corruption layer)
24. #kafkasummit @spjelkavik @audunstrand
why is it a mistake
data and code needs separate versioning strategies
version should be part of the data
defining schema in a java library makes it more difficult to access data from non-
jvm languages
very little discoverability of data, people chose other means to get their data
difficult to create tools
25. #kafkasummit @spjelkavik @audunstrand
what is the consequence
development speed outside jvm has been slow
change of data needs coordinated deployment
no process for data versioning, like backwards compatibility checks
difficult to create tooling that needs to know data format, like data
lake and database sinks
26. #kafkasummit @spjelkavik @audunstrand
what is the correct solution
confluent.io platform has a separate schema registry
apache avro
multiple compatibility settings and evolutions strategies
connect
Take complexity out of the applications
27. #kafkasummit @spjelkavik @audunstrand
what has finn.no done
still using java library, with schemas in builders
confluent platform 2.0 is planned for the next step, not (just) kafka 0.9
29. #kafkasummit @spjelkavik @audunstrand
why is it a mistake
Historically - One Big Database with Expensive License
Database world - OLTP and OLAP
Changed with Open Source software and Cloud
Tried to simplify the developer's day with a single config
Kafka supports very high throughput and highly reliable
30. #kafkasummit @spjelkavik @audunstrand
what is the consequence
Trade off between throughput and degree of reliability
With a single configuration - the last commit wins
Either high throughput, and risk of loss - or potentially too slow
31. #kafkasummit @spjelkavik @audunstrand
what is the correct solution
Understand your use cases and their needs!
Use proper pr topic configuration
Consider splitting / isolation
32. #kafkasummit @spjelkavik @audunstrand
Defaults that are quite reliable
Exposing configuration variables in the client
Ask the questions;
● at least once delivery
● ordering - if you partition, what must have strict ordering
● 99% delivery - is that good enough?
● what level of throughput is needed
what has finn.no done
33. #kafkasummit @spjelkavik @audunstrand
Configuration
Configuration for production
● Partitions
● Replicas (default.replication.factor)
● Minimum ISR (min.insync.replicas)
● Wait for acknowledge when producing messages (request.required.acks, block.on.buffer.full)
● Retries
● Leader election
Configuration for consumer
● Number of threads
● When to commit (autocommit.enable vs consumer.commitOffsets)
36. #kafkasummit @spjelkavik @audunstrand
why is it a mistake
partitions are kafkas way of scaling consumers, 128 partitions can handle 128
consumer processes
in 0.8; clusters could not reduce the number of partitions without deleting data
highest number of consumers today is 20
37. #kafkasummit @spjelkavik @audunstrand
what is the consequence
our 0.8 cluster was configured with 128 partitions as default, for all topics.
many partitions and many topics creates many datapoints that must be coordinated
zookeeper must coordinate all this
rebalance must balance all clients on all partitions
zookeeper and kafka went down (may 2015)
Users could note create ads for two days
38. #kafkasummit @spjelkavik @audunstrand
what is the correct solution
small number of partitions as default
increase number of partitions for selected topics
understand your use case (throughput target)
reduce length of transactions on consumer side
Max partitions on a broker => 1500 advised in our case - we had 38k
http://www.confluent.io/blog/how-to-choose-the-number-of-topicspartitions-in-a-kafka-cluster/
41. #kafkasummit @spjelkavik @audunstrand
why is it a mistake
Kafka was set up by Ops for a proof of concept - not for hardened production use
By coincidence we had 8 nodes for kafka, the same 8 nodes for zookeeper
Zookeeper is dependent on a majority quorum, low latency between nodes
The 8 nodes were NOT dedicated - in fact - they were overloaded already
42. #kafkasummit @spjelkavik @audunstrand
what is the consequence
Zookeeper recommends 3 nodes for normal usage, 5 for high, and any more is
questionable
More nodes leads to longer time for finding consensus, more communication
If we get a split between data centers, there will be 4 in each
You should not run Zk between data centers, due to latency and outage
possibilities
43. #kafkasummit @spjelkavik @audunstrand
what is the correct solution
Have an odd number of Zookeeper nodes - preferrably 3, at most 5
Don’t cross data centers
Check the documentation before deploying serious production load
Don’t run a sensitive service (Zookeeper) on a server with 50 jvm-based services,
300% over committed on RAM
Watch GC times
44. #kafkasummit @spjelkavik @audunstrand
what has finn.no done
dc 1
dc 2
broker05
zk
kafka
broker01
zk
kafka
broker03
zk
kafka
broker04
zk
kafka
broker02
zk
kafka
Version 0.8.2
5-20 partitions
multiple
configurations
47. #kafkasummit @spjelkavik @audunstrand
References / Further reading
Designing data intensive systems, Martin Kleppmann
Data on the inside - data on the outside, Pat Helland
I Heart Logs, Jay Kreps
The Confluent Blog, http://confluent.io/
Kafka - The definitive guide
https://cwiki.apache.org/confluence/display/KAFKA/Kafka+papers+and+presentations
http://www.finn.no/apply-here
http://www.schibsted.com/en/Career/
48. “It's only because of
their stupidity that
they're able to be so
sure of themselves.”
― Franz Kafka, The
Trial
Audun Fauchald Strand
@audunstrand
Henning Spjelkavik
@spjelkavik
http://www.finn.no/apply-here
http://www.schibsted.com/en/Career/
Q?
49. #kafkasummit @spjelkavik @audunstrand
Runner up
Using pre-1.0 software
Have control of topic creation
Kafka is storage - treat it like one also ops-wise
Client side rebalancing, misunderstood
Commiting on all consumer threads, believing that you only commited on one