The document discusses deploying Flink jobs as Docker containers in a production environment, emphasizing the need for repeatable builds and packaging jobs like services. It outlines the necessary steps for building and executing Docker containers that handle configuration and job management within a YARN cluster. Future improvements could include making the approach independent of YARN and exploring other resource management tools like Kubernetes.

1. Deploying Flink Jobs
as Docker Containers
Dominik Bruhn - Director of Platform Engineering Relayr
Flink Forward Sep 12-14 2017 Berlin

2. Who am I?
● Director of Platform Engineering
● At Relayr
○ Industrial IOT Platform
○ Real Time Sensor Data is processed, stored, analyzed and presented
● Contributor to Apache Flink

3. Production
Production
What is this talk about?
Source
Flink Job Production???

4. What are the Requirements?
● Streaming Jobs
● Endless Jobs
● Deployed in Multiple Environments (Configuration Files)
● Single Deployed Artefact
● Deploy to YARN (EMR) cluster
● Repeatable Builds

5. What is the Idea?
“If it behaves like a service, package it like a service”
● Docker Container contains the Job + Flink + Some
scripting
● Docker Container submits and monitors the Flink Job in
the YARN cluster.
● Actual computation happens in the YARN cluster
● Docker Container stays attached to the job

6. Steps Necessary I - Building
Source
Flink Job
Docker
ContainerCompile
Test
Package
Upload

7. Packaging
● Result from compliation: Job Fat JAR
○ Exclude Flink from the Fat JAR
● Package into a Docker Container:
○ Java
○ Apache Flink Distribution
○ Job Fat JAR
○ Configuration File (Templates)
○ If needed: Utilities for Configuration Fetching
○ Entrypoint Shell Script

8. Steps Necessary II - Executing
Docker
Container
Docker Runtime YARN Cluster
Flink Job
Configure
Submit
Monitor

9. What does the Container do?
1. Fetch Configuration Values + YARN Credentials
2. Get YARN Configuration
3. Update Configuration File of Job + Flink
4. List YARN Jobs, find old running
a. If found, kill
5. Find out the last savepoint on HDFS
6. Start job on YARN from savepoint
7. Stay attached to the Job

10. What do we get from this?
● Flink Job deployed as all other services
● Adapting to different environment
● Monitoring and failing like other services

11. What was left out?
● Packaging as stand alone
docker container (i.e. for
testing)
What could be done in the
future?
● Approach independent of
YARN on a stand alone Flink
cluster.
● Use other resource
management tools instead of
YARN, i.e. kubernetes.

12. Thanks for your attention!
Hiring!