1. Mario-Leander Reimer
mario-leander.reimer@qaware.de
@LeanderReimer
A Hitchhiker‘s Guide to the
Cloud Native Stack
Hamburg, 20. June 2017

2. Mario-Leander Reimer
Chief Technologist, QAware GmbH
Contact Details
Phone: +49 89 23 23 15 121
Mail: mario-leander.reimer@qaware.de
Twitter: @LeanderReimer
Github: https://github.com/lreimer
2
Developer & Architect
20+ years of experience
#CloudNativeNerd
Open Source Enthusiast

3. Let‘s talk about Cloud Native Applications.
3

4. DISRUPT
4
CLOUD NATIVE APPLICATIONS
INDUSTRIALIZE
OPEX SAVINGS
(automation & utilization)
ANTIFRAGILITYHYPERSCALE
TRAFFIC, DATA, FEATURES
DEVOPS &
CONTINUOUS DELIVERY

5. BUILT AND COMPOSED
AS MICROSERVICES
3KEYPRINCIPLES
5
CLOUD NATIVE APPLICATIONS
PACKAGED AND
DISTRIBUTED IN CONTAINERS
DYNAMICALLY
EXECUTED IN THE CLOUD

6. Robert A. Heinlein, 1966, The Moon Is a Harsh Mistress
„There ain’t no such thing
as a free lunch.“

7. 7
The 5 Cloud Commandments:
1. Everything Fails All The Time.
2. Focus on MTTR not MTTF.
3. Know the Eight Fallacies of Distributed Computing.
4. Scale out, not up.
5. Treat resources as cattle not as pets.
picture alliance / United Archive

8. Design Principles for Cloud Native Applications.
8
Design for Distribution: Containers; microservices; API driven development.
Design for Performance: Responsive; concurrent; resource efficient.
Design for Automation: Automated Dev & Ops tasks.
Design for Resiliency: Fault-tolerant and self-healing.
Design for Elasticity: Scales dynamically and reacts to stimuli.
Design for Delivery: Short roundtrips and automated provisioning.
Design for Diagnosability: Cluster-wide logs, metrics and traces.

9. Different Levels of Cloud Native Application Maturity.
9
Scales dynamically based on stimuli.
Dynamic infrastructure migration without
service downtime.
Level 3: Cloud Native
Fault tolerant and resilient design.
Metrics and monitoring built-in.
Runs anywhere. Infrastructure agnostic.
Level 2: Cloud Resilient
Consists of loosely coupled systems.
Services can be found by name.
Adheres to the 12-factor app principles.
Level 1: Cloud Friendly
No file system requirements.
Runs on virtualized hardware.
Executed as self-contained image.
Level 0: Cloud Ready
https://www.opendatacenteralliance.org/docs/architecting_cloud_aware_applications.pdf

10. The Anatomy of the Cloud Native Stack.
10
How to decouple
from physical
hardware?
How to provide the
right resources for
container execution?
How to run (containerized)
applications on a cluster?
How to automate standard
operations procedures?
What infrastructure
to provide to cloud
native applications?

12. Specific Cloud Native Stack with Spring Cloud and K8s.
12

13. (1) Microservices
(2) Containerization
(3) Composition
(4) Orchestration
The 4 Phases of Cloud Native Application Development.
13

14. Microservices

15. Niloo138, Getty Images

16. 2002
16
Buying
Registration
Items
Categories
Services

17. 2008
17
Additional
Services

18. 2011
18
Additional
Services

19. Bad News.
19
Very long
release cycles.
Limited
scalability.

20. 2016
20
Additional
Services

21. Good News.
21
1000 deployments a day …
… triggered by dev teams.
~ 100% availability
Resource efficiency
Suitable scalability
Enabled new kinds of
applications ( IoT, mobile, APIs)
to compete globally

22. WHAT DID THEY DO?

23. The obvious answer: Decomposition.
23

24. 24
Cloud Native Application Development: Components All
Along the Software Lifecycle.
DESIGN BUILD RUN
§ Complexity unit
§ Data integrity unit
§ Coherent and cohesive
features unit
§ Decoupled unit
§ Planning unit
§ Team assignment unit
§ Knowledge unit
§ Development unit
§ Integration unit
§ Release unit
§ Deployment unit
§ Runtime unit
(crash, slow-down, access)
§ Scaling unit
1:1 n:1

25. 25
Dev Components Ops Components?:1
System
Subsystems
Components
Services
Good starting point
Decomposition Trade-Offs
Microservices
Nanoservices
Macroservices
Monolith
+ More flexible to scale
+ Runtime isolation (crash, slow-down, …)
+ Independent releases, deployments, teams
+ Higher utilization possible
- Distribution debt: Latency
- Increasing infrastructure complexity
- Increasing troubleshooting complexity
- Increasing integration complexity

26. A simple Zwitscher microservices using Spring Cloud.
26
https://github.com/qaware/hitchhikers-guide-cloudnative

27. Containerization

28. Hardware vs. OS Virtualization.
28
Real Hardware
Virtual Hardware
OS
OS Libraries
Application
Real Hardware
(Virtual Hardware)
OS
OS Libraries
Application
HSI*
SCI*
Hardware Virtualization OS Virtualization
Private Copy
Shared ResourcesVirtualMachine
Container
Isolated Hardware Isolated NW-interface, process space, file system
*) HSI = Hardware Software Interface
SCI = System Call Interface
§ Less volume of private copy
§ Near zero runtime overhead
§ Short start-up time
§ Stong isolation

29. Developer‘s Perspective of the Docker Workflow.
29
$ docker build -t zwitscher-service:1.0.1 .
$ docker run --name zwitscher-service -d
-p 8080:8080 zwitscher-service:1.0.1
$ docker stop zwitscher-service
$ docker start zwitscher-service
$ docker tag zwitscher-service:1.0.1
hitchhikersguide/zwitscher-service:latest
$ docker push hitchhikersguide/zwitscher-service

30. FROM qaware/alpine-k8s-ibmjava8:8.0-3.10
MAINTAINER QAware GmbH <qaware-oss@qaware.de>
RUN mkdir -p /app
COPY build/libs/zwitscher-service-1.0.1.jar /app/zwitscher-service.jar
COPY src/main/docker/zwitscher-service.conf /app/
ENV JAVA_OPTS –Xmx256m
EXPOSE 8080
CMD /app/zwitscher-service.jar
Example Dockerfile.
30

31. Some Useful Tips on using Docker.
31
A Dockerfile is code! Treat it as 1st class citizen.
Know your base image. Size matters.
Chain RUN commands. Use intelligent layering.
Remove temporary files and directories.
Define ENV variables for important parameters.
Use one image for all your environments.
Version your images.
Use quality tools to check Dockerfiles and images.

32. Composition

33. Microservices need an Ecosystem to run in.
33
How to access
endpoints from
the outside?
How to expose
and find service
endpoints?
How to execute an
ops component?
How to call other
endpoints resilient
and responsive?
How to detect and
resolve operational
anomalies?
How to provide cluster-
wide configuration and
consensus?

34. 34

35. Conceptual View on Infrastructure Composition.
35

36. version: '3'
services:
zwitscher-consul:
...
zwitscher-service:
image: hitchhikersguide/zwitscher-service:1.0.1
environment:
- CONSUL_HOST=zwitscher-consul
- CONSUL_PORT=8500
- TWITTER_APP_ID=${TWITTER_APP_ID}
- TWITTER_APP_SECRET=${TWITTER_APP_SECRET}
depends_on:
- zwitscher-consul
ports:
- "8080:8080"
networks:
- zwitscher-net
Example docker-compose.yml
36
$ docker-compose build
$ docker-compose up –d --build
$ docker-compose logs
$ docker-compose down

37. Orchestration

38. echo "- The default provider is GCE"
export KUBERNETES_PROVIDER=gce
export KUBE_GCE_ZONE=europe-west1-d
export NUM_NODES=4
echo "- Another possible provider is AWS"
export KUBERNETES_PROVIDER=aws
export KUBE_AWS_ZONE=eu-central-1a
export NODE_SIZE=t2.small
curl -sS https://get.k8s.io | bash
Easy K8s setup: Local, Bare Metal, Cloud or Managed.
38

39. Conceptual View on Kubernetes Building Blocks.
39

40. Services are an abstraction for a logical
collection of pods.
Pods are the smallest unit of compute in
Kubernetes
Deployments are an abstraction used to
declare and update pods, RCs, …
Replica Sets ensure that the desired
number of pod replicas are running
Labels are key/value pairs used to identify
Kubernetes resources
Most important Kubernetes concepts.
40

41. Single or Multi Container Pods?
41

42. K8s Deployment Overview.
42

43. K8s-only Deployment Variation.
43

44. apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: zwitscher-service
spec:
replicas: 3
template:
metadata:
labels:
zwitscher: service
spec:
containers:
- name: zwitscher-service
image: "hitchhikersguide/zwitscher-service:1.0.1"
ports:
- containerPort: 8080
env:
- name: CONSUL_HOST
value: zwitscher-consul
Example K8s Deployment Definition.
44

45. resources:
# Define resources to help K8S scheduler
# CPU is specified in units of cores
# Memory is specified in units of bytes
# required resources for a Pod to be started
requests:
memory: "128Mi"
cpu: "250m"
# the Pod will be restarted if limits are exceeded
limits:
memory: "192Mi"
cpu: "500m"
Define Resource Constraints carefully.
45

46. # container will receive requests if probe succeeds
readinessProbe:
httpGet:
path: /admin/info
port: 8080
initialDelaySeconds: 30
timeoutSeconds: 5
# container will be killed if probe fails
livenessProbe:
httpGet:
path: /admin/health
port: 8080
initialDelaySeconds: 90
timeoutSeconds: 10
Liveness and Readiness Probes for Actuator endpoints.
46

47. apiVersion: v1
kind: Service
metadata:
name: zwitscher-service
labels:
zwitscher: service
spec:
# use NodePort here to be able to access the port on each node
# use LoadBalancer for external load-balanced IP if supported
type: NodePort
ports:
- port: 8080
selector:
zwitscher: service
Example K8s Service Definition.
47

48. Programmable MIDI Controller.
Visualizes Deployments and Pods.
Scales Deployments.
Supports K8s, OpenShift, DC/OS.
http://github.com/qaware/kubepad/
Let‘s have some fun with K8S!
48

50. No magic! Just complex technology.
50
Building distributed systems is hard!
The Cloud Native Stack hides most of the inherent complexity.
High abstraction: Boon and Bane of software development.
Developers and architects need additional skills and know-how.
Favour gradual transition over big bang cloud migration.

51. Sources and some articles to read @ home …
51
https://github.com/qaware/hitchhikers-guide-cloudnative
Der Cloud Native Stack: Mesos, Kubernetes und Spring Cloud
https://goo.gl/U5cJAU
Spring Cloud und Netflix OSS: Cloud-native Anwendungen bauen
https://goo.gl/edNlUK
Cloud-native Anwendungen mit Kubernetes
https://goo.gl/dVkoyR
Eine Einführung in Apache Mesos: Das Betriebsystem der Cloud
https://goo.gl/7SnMZA

52. Mario-Leander Reimer
mario-leander.reimer@qaware.de
@LeanderReimer github.com/lreimer
linkedin.com/qaware slideshare.net/qaware
twitter.com/qaware xing.com/qaware