Microservices, DevOps & SRE

@arafkarsh arafkarsh
ARAF KARSH HAMID
Co-Founder / CTO
MetaMagic Global Inc., NJ, USA
@arafkarsh
arafkarsh
Microservice
Architecture Series
Building Cloud Native Apps
User Stories / Agile
Architecture & Design
Testing Automation
DevOps & SRE
Part 10 of 11

Slides are color coded based on the topic colors.
Design Thinking /
Lean Startup /
Agile / Stories
1
Architecture
& Design
2
Test
Automation 3
DevOps
SRE 4
2

What is DevOps?
3
Is DevOps - A technology or collection of technologies?
Answer: NO
Is DevOps - A way of programming?
Answer: NO
is DevOps - A Process?
Answer: NO
Can you become a DevOps Engineer?
Answer: NO - its not a skill set

I am confused!
Then what is
DevOps?
4
It’s the Destination
Let the Journey Begin!!!

Application Modernization – 3 Transformations
5
Monolithic SOA Microservice
Physical
Server
Virtual
Machine
Cloud
Waterfall Agile DevOps
Source: IBM: Application Modernization > https://www.youtube.com/watch?v=RJ3UQSxwGFY
Architecture
Infrastructure
Delivery

Application Modernization – 3 Transformations
6
Monolithic SOA Microservice
Physical
Server
Virtual
Machine
Cloud
Waterfall Agile DevOps
Source: IBM: Application Modernization > https://www.youtube.com/watch?v=RJ3UQSxwGFY
Architecture
Infrastructure
Delivery
Modernization
1
2
3

Agile
Scrum (4-6 Weeks)
Developer Journey
Monolithic
Domain Driven Design
Event Sourcing and CQRS
Waterfall
Optional
Design
Patterns
Continuous Integration (CI)
6/12 Months
Enterprise Service Bus
Relational Database [SQL] / NoSQL
Development QA / QC Ops
7
Microservices
Scrum / Kanban (1-5 Days)
Mandatory
Design
Patterns
Infrastructure Design Patterns
CI
DevOps
Event Streaming / Replicated Logs
SQL NoSQL
CD
Container Orchestrator Service Mesh

Stages of DevOps Delivery Pipeline
Source: Sanjeev Sharma, IBM, DevOps for Dummies
Application Release Management
Development Build Package
Repository
Test
Environment
Stage
Environment
Production
Environment
Application Deployment Automation
Cloud Provisioning
mvn repository
npm repository
Docker hub
8

Software Specs
• Design Thinking / Lean Startup
• User Stories
• Agile - Scrum / Kanban
9
1

Three Mindsets of Product Development
Design
Thinking
Lean Agile
Source: Jonny Schneider, Thought Works
Explore the
Problem
Build the
right things
Build the
things right
Hypothesis
Validation
New Business Requirements
Product Evolutions
Agile
MVP
10

Agile Values
INDIVIDUALS AND
INTERACTIONS
OVER PROCESSESS
AND TOOLS
WORKING SOFTWARE
COMPREHENSIVE
DOCUMENTATION
OVER
CUSTOMER
COLLABORATION
OVER CONTRACT
NEGOTIATION
RESPONDING
TO CHANGE
OVER FOLLOWING A
PLAN
Source: Agile Manifesto - https://www.scrumalliance.org/resources/agile-manifesto
11

Scrum
4 – 8 People
Complete
Specs
Stories
Planned
for a
Sprint
Max
8 Hours
Max
15 Mins
Multiple
increments
within a
Sprint
1 Month
Release
12

What is Kanban
Kanban is a method for managing the creation
of products with an emphasis on
• continual delivery (Daily / Hourly) while
• not overburdening the development
team.
Like Scrum, Kanban is a process designed to
help teams work together more effectively.
Kanban is a visual management method that was developed by Toyota in
the early 1940s.
Kanban in Japanese means Card
Microsoft Xbox One
Team does multiple
Daily releases using
Kanban.
13

Three Principles of Kanban
14
Source: https://resources.collab.net/agile-101/what-is-kanban
• Visualize what you do today
(workflow): seeing all the items in
context of each other can be very
informative
• Limit the amount of work in progress
(WIP): this helps balance the flow-
based approach, so teams don’t start
and commit to too much work at once
• Enhance flow: when something is
finished, the next highest thing from
the backlog is pulled into play

Kanban Board
Backlog Work breakdown Work In Progress Done
Active Done Active Done
Track
Task blocked
due to
Dependency.
Once the
dependent
Task is ready
the blocked
task will be
moved to
Active State
To Do List
Max items in WIP must be
1.4x of total Resources
A Backlog item is broken down
to tasks and each Task should
NOT take more than 1-3 days
at max.
It’s a good practice to keep all
the tasks of similar size.
Tasks are assigned to
respective team members.
15

Similarities between Kanban and Scrum
Task Breakdown Continuous Improvement Visible Workflow
Both Scrum and Kanban supports Large Complex work to be broken down to smaller tasks and
completed efficiently. Both place high focus on Continuous Improvement and process optimization
and support a highly visible (Task) Workflows for the visibility to all the stake holders.
16

Release Cycles
17
Kanban
Preparation
Requirements
Design
Development
Testing
Release
1 – 4 Days Cycle
Scrum
1 Month (Max) Cycle
1 or 2 Weeks Cycle
also allowed

Kanban vs. Scrum
Kanban Scrum
Roles &
Responsibilities
No prescribed roles
Pre-defined roles of Scrum master,
Product owner and team member
Delivery Timelines Continuous Delivery (Daily/Hourly) Time boxed sprints (2-4 Weeks)
Delegation &
Prioritization
Work is pulled through the system
(single piece flow)
Work is pulled through the system
in batches (the sprint backlog)
Modifications Changes can be made at any time No changes allowed mid-sprint
Measurement of
Productivity
Cycle time Velocity
When to Use?
More appropriate in operational
environments with a high degree of
variability in priority
More appropriate in situations
where work can be prioritized in
batches that can be left alone
Source: https://leankit.com/learn/kanban/kanban-vs-scrum/
18

Benefits of Kanban
• Shorter cycle times can deliver features faster.
• Responsiveness to Change:
• When priorities change very frequently, Kanban is ideal.
• Balancing demand against throughput guarantees that most
the customer-centric features are always being worked.
• Requires fewer organization / room set-up changes to get
started
• Reducing waste and removing activities that don’t add value to
the team/department/organization
• Rapid feedback loops improve the chances of more motivated,
empowered and higher-performing team members
19

User Stories
• User Stories
• Behavior Driven Design
• Writing Good Stories
• Estimate and Planning
• Case Study
Theme Epic User Story Sprint
20

ShopEasy – eCommerce Portal
Theme Epic User Story Sprint
ShopEasy – eCommerce Application
1. Customer Management
2. Search Product
3. Catalogue
4. Shopping Cart
5. Order Processing
6. Payments
2. Search Product
Release 1
1. Global Search
Release 2
1. Search by Brand
2. Search by Price
Range
Release 3
1. Search by Model
2. Search by Rating
Stories
1. Global Search
2. Search by Brand
3. Search by Price
Range
4. Search by Model
5. Search by Rating
21

Epic – Customer
As a Consumer
I want to register eCommerce Portal
So that I can buy products
Role-Feature-Reason Matrix
User Story – 1 : Registration
BDD Acceptance Criteria – 1: Save User
Given The fields First Name, Last Name, DOB
Address, Email Address, Phone No.
When User enters values in the fields First
Name, Last Name, DOB Address, Email
Address, Phone No.
Then If the following fields contains values
First Name, Last Name, Address, Email
Address and Phone No.
AND Age is greater than 18
Save the Data.
BDD Acceptance Criteria – 2 : Generate Password
Given User Info Available
When Email Address is a valid email
Then Generate the password
AND Send mail with user email address as
login id the URL of the portal
AND Send Password in a separate email
address.
AND Store data on mail status as mail send
or failed.
BDD Acceptance Criteria – 3 : Resend Mail
Given User Registration mail status is available
When The Mail status is failed.
Then Send the mail again
AND stored the attempt number.
22

User Journey / Story Map & Release Cycles
Browse Products Add to Shopping Cart Select Shipping Address Confirm Order Make Payment
Catalogue Shopping Cart Order Payment
Customer
View Product
Search
User Journey
Search by Price Image Gallery Update Qty Use PayPal
R2
Global Search Product Details Add to Cart
Delete Item
Select Address Confirm Order
Pay Credit Card
Make
Payment
R1
Registration
Minimum Viable Product
Scrum Sprint Cycle
Search by Price Image Gallery Update Qty Use PayPal
Kanban Cycle: Each of the Story can be released without waiting for other stories to be completed resulting
in Shorter Releases as all the stories are independent!
23

Architecture & Design
• Capability Centric Design
• Domain Driven Design
• Event Sourcing & CQRS
• Microservices Architecture
24
2

Capability Centric Design
Business Centric Development
• Focus on Business Capabilities
• Entire team is aligned towards
Business Capability.
• From Specs to Operations – The
team handles the entire spectrum
of Software development.
• Every vertical will have its own
Code Pipeline
Front-End-Team Back-End-Team Database-Team
In a typical Monolithic way the team is
divided based on technology / skill set
rather than business functions. This leads
to not only bottlenecks but also lack of
understanding of the Business Domain.
QA Team
QA = Quality Assurance
PO = Product Owner
Vertically sliced Product Team
Front-End
Back-End
Database
Business
Capability 1
QA
Team
PO
Front-End
Back-End
Database
Business
Capability 2
QA
Team
PO
Front-End
Back-End
Database
Business
Capability n
QA
Team
PO
25

Domain Driven Design – Tactical Design
26
Source: Domain-Driven Design Reference by Eric Evans

Event Sourcing Intro
27
Standard CRUD Operations – Customer Profile – Aggregate Root
Profile
Address
Title
Profile Created
Profile
Address
New Title
Title Updated
Profile
New
Address
New Title
New Address added
Derived
Profile
Address
Notes
Notes Removed
Time T1 T2 T4
T3
Event Sourcing and Derived Aggregate Root
Commands
1. Create Profile
2. Update Title
3. Add Address
4. Delete Notes
2
Events
1. Profile Created Event
2. Title Updated Event
3. Address Added Event
4. Notes Deleted Event
3
Profile
Address
New Title
Current State of the
Customer Profile
4
Event store
Single Source of Truth
Greg
Young

User Journey / CCD / DDD / Event Sourcing & CQRS
User Journey
Bounded
Context
1
Bounded
Context
2
Bounded
Context
3
1. Bounded Contexts
2. Entity
3. Value Objects
4. Aggregate Roots
5. Domain Events
6. Repository
7. Service
8. Factory
Process
1
Commands
2
Projections
5
ES Aggregate
4
Events
3
Event Sourcing & CQRS
Domain Expert Analyst Architect QA
Design Docs Test Cases Code
Developers
Ubiquitous Language
Core
Domain
Sub
Domain
Generic
Domain
Vertically sliced Product Team
FE
BE
DB
Business
Capability 1
QA
Team
PO
FE
BE
DB
Business
Capability 2
QA
Team
PO
FE
BE
DB
Business
Capability n
QA
Team
PO
28

Microservices Characteristics
29
We can scale our operation independently, maintain
unparalleled system availability, and introduce new
services quickly without the need for massive
reconfiguration. —
Werner Vogels, CTO, Amazon Web Services
Modularity ... is to a technological economy
what the division of labor is to a
manufacturing one.
W. Brian Arthur,
author of e Nature of Technology
The key in making great and growable systems is
much more to design how its modules communicate
rather than what their internal properties and
behaviors should be.
Alan Kay, 1998 email to the Squeak-dev list
Components
via
Services
Organized around
Business
Capabilities
Products
NOT
Projects
Smart
Endpoints
& Dumb Pipes
Decentralized
Governance &
Data Management
Infrastructure
Automation
Design for
Failure
Evolutionary
Design

Shopping Portal
30
/ui
/productms
/auth
/order
Gateway
Virtual Service
Deployment / Replica / Pod Nodes
Istio Sidecar - Envoy
Load Balancer
Kubernetes
Objects
Istio Objects
Firewall
P M C
Istio Control Plane
UI Pod N5
v2
Canary
v2
User X = Canary
Others = Stable
A / B Testing using
Canary Deployment
v1 UI Pod
UI Pod
UI Pod
UI
Service
N1
N2
N2
Destination
Rule
Stable / v1
EndPoints
Internal
Load Balancers
Source:
https://github.com/meta-magic/kubernetes_workshop
Users
Product Pod
Product Pod
Product Pod
Product
Service
MySQL
Pod
N4
N3
Destination
Rule
EndPoints
Review Pod
Review Pod
Review Pod
Review
Service
N1
N4
N3
Service Call
Kube DNS
EndPoints

Deployment – Updates and rollbacks, Canary Release
D
ReplicaSet – Self Healing, Scalability, Desired State
R
Worker Node 1
Master Node (Control Plane)
Kubernetes
Architecture
31
POD
POD itself is a Linux
Container, Docker
container will run inside
the POD. PODs with single
or multiple containers
(Sidecar Pattern) will share
Cgroup, Volumes,
Namespaces of the POD.
(Cgroup / Namespaces)
Scheduler
Controller
Manager
Using yaml or json
declare the desired
state of the app.
State is stored in
the Cluster store.
Self healing is done by Kubernetes using watch loops if the desired state is changed.
POD POD POD
BE
1.2
10.1.2.34
BE
1.2
10.1.2.35
BE
1.2
10.1.2.36
BE
15.1.2.100
DNS: a.b.com 1.2
Service Pod IP Address is dynamic, communication should
be based on Service which will have routable IP
and DNS Name. Labels (BE, 1.2) play a critical role
in ReplicaSet, Deployment, & Services etc.
Cluster
Store
etcd
Key Value
Store
Pod Pod Pod
Label Selector selects pods based on the Labels.
Label
Selector
Label Selector
Label Selector
Node
Controller
End Point
Controller
Deployment
Controller
Pod
Controller
….
Labels
Internet
Firewall K8s Virtual
Cluster
Cloud Controller
For the cloud providers to manage
nodes, services, routes, volumes etc.
Kubelet
Node
Manager
Container
Runtime
Interface
Port 10255
gRPC
ProtoBuf
Kube-Proxy
Network Proxy
TCP / UDP Forwarding
IPTABLES / IPVS
Allows multiple
implementation of
containers from v1.7
RESTful yaml / json
$ kubectl ….
Port 443
API Server
Pod IP ...34 ...35 ...36
EP
• Declarative Model
• Desired State
Key Aspects
N1
N2
N3
Namespace
1
N1
N2
N3
Namespace
2
• Pods
• ReplicaSet
• Deployment
• Service
• Endpoints
• StatefulSet
• Namespace
• Resource Quota
• Limit Range
• Persistent
Volume
Kind
Secrets
Kind
• apiVersion:
• kind:
• metadata:
• spec:
Declarative Model
• Pod
• ReplicaSet
• Service
• Deployment
• Virtual Service
• Gateway, SE, DR
• Policy, MeshPolicy
• RbaConfig
• Prometheus, Rule,
• ListChekcer …
@
@
Annotations
Names
Cluster IP
Node
Port
Load
Balancer
External
Name
@
Ingress

Test Automation
• Microservices Testing strategies
• Chaos engineering
• Behavior driven development
32
3

Microservices Testing Strategies
Ubiquitous
Language
Domain
Expert
Analyst Developers
QA
Design
Docs
Test Cases
Code
E2E
Testing
Integration
Testing
Contract Testing
Component Testing
Unit Testing
Number of Tests
Speed
Cost
Time
Mike Cohen’s Testing Pyramid
Test Pyramid: https://martinfowler.com/bliki/TestPyramid.html
70%
20%
10%
33

Other Testing Strategies or Anti Patterns
Inverted Pyramid /
Ice Cream Cone Strategy
Unit Testing
Integration Testing
End 2 End
Testing
Hour Glass Strategy
70%
20%
10%
45%
45%
10%
34

Microservices Testing Strategy
Unit Testing
A unit test exercises the
smallest piece of testable
software in the application
to determine whether it
behaves as expected.
Source: https://martinfowler.com/articles/microservice-testing/#agenda
Component Testing
A component test limits the
scope of the exercised
software to a portion of the
system under test,
manipulating the system
through internal code
interfaces and using test
doubles to isolate the code
under test from other
components.
Integration Testing
An integration test verifies
the communication paths
and interactions between
components to detect
interface defects
Integration Contract Testing
An Integration Contract test is a
test at the boundary of an
external service verifying that it
meets the contract expected by a
consuming service.
End 2 End Testing
An end-to-end test verifies that a
system meets external
requirements and achieves its
goals, testing the entire system,
from end to end
Say NO to End 2 End Tests - Mike
Walker April 22, 2015. Google Test Blog
35

Microservices Testing Scenarios / Tools
36
Testing Tools
Contract Testing Scope
Integration Testing
Verifies the communication
paths and interactions between
components to detect interface
defects
Contract Testing
It is a test at the boundary of an
external service verifying that it
meets the contract expected by a
consuming service.
Payment Mock
Integration
Contract
Testing
Scope
Test Double
Montebank
Cart
Component Testing
Unit
Testing
Integration
Testing
Scope
Order
REST / HTTP or
Events / Kafka
Item ID,
Quantity,
Address..
Mock Order
Component Testing
A component test limits the
scope of the exercised
software to a portion of the
system under test.
Order
Payment
Unit
Testing
Firewall
Integration Testing Scope
REST / HTTP
Payment
Sandbox
Component
Testing
U

Shift Right – Chaos Engineering
Cloud
Chaos Monkey Randomly disables production instances
Chaos Kong
Similar to Chaos Monkey, simulates an outage of
an entire Amazon availability zone.
Doctor Monkey Kubernetes
Checks CPU load, Memory usage and removes it
from network if the health is bad.
Janitor Monkey Kubernetes Search for unused resources and disposes them.
Conformity
Monkey
Finds instances that don’t adhere to best-
practices and shuts them down.
Latency Money Service Mesh Induces Artificial delays
Security Monkey
Is an extension of Compliance Monkey. Find
security vulnerabilities and terminates offending
instances.
Source: https://github.com/Netflix/SimianArmy/wiki
Source: http://principlesofchaos.org/
37
Production Testing – Load / Stress / Performance

Behavior Driven Development
Source: https://dannorth.net/introducing-bdd/
As an insurance Broker
I want to know who my Gold Customers are
So that I sell more
Given Customer John Doe exists
When
he buys insurance ABC for
$1000 USD
Then He becomes a Gold Customer
BDD Construct
As a Customer
I want to withdraw Cash from ATM
So that I don’t have to wait in line at the bank
Given
The account is in Credit
AND the Card is Valid
AND the dispenser contains Cash
BDD Construct
When The Customer requests Cash
Then
Ensure that the Account is debited
AND Ensure cash is dispensed
AND ensure that Card is returned.
38

Features of BDD
• Focus on Behavior of the System
rather than tests.
• Collaboration between Business
Stake holders, Analysts,
Developers, QA.
• Ubiquitous Language
• Driven By Business Value
• Extends Test Driven Development
Source: https://cucumber.io/
Cucumber merges specification and
test documentation into one cohesive
whole.
39

Testing Strategy Summary
1. Unit Testing
A unit test exercises the smallest piece of testable software.
2. Component Testing
A component test limits the scope of the exercised software to a portion
of the system under test.
3. Contract Testing
It is a test at the boundary of an external service verifying that it meets the
contract expected by a consuming service
4. Integration Testing
It verifies the communication paths and interactions between components
to detect interface defects.
40

DevOps &
SITE RELIABILITY ENGINEERING
• ITIL – Service life cycle
• DEVOPS
• SRE CONCEPT
41
4

ITIL – Service Life Cycle
Source: https://www.flycastpartners.com/itil-service-lifecycle-guide/
• ITIL is a framework providing best practice
guidelines on all aspects of end to end
service management.
• It covers complete spectrum of People,
Processes, Products and use of Partners (v3).
Service is a means of delivering value to
customers by achieving customer's desired
results while working within given constraints.
Incident is defined as any disruption in IT
service.
Service Level Agreement. It is a commitment
between a service provider and a client.
42

Development & Operations
Development Team
Agility
Operations Team
Stability
Developers
Keep throwing
releases over
the wall and
get pushed
back by the
operations
team.
43

DevOps – Lean thinking
Systems of Records: Critical
Enterprise transactions and
these Apps doesn’t require
frequent changes.
Systems of Engagement: With
introduction of Rich Web Apps
and Mobiles Apps, Systems of
Records were augmented by
Systems of Engagements.
Customers directly engage with
these Apps and these Apps
requires Rapid Releases.
DevOps Return on Investment
1. Enhanced Customer Experience
2. Increased Capacity to Innovate
3. Faster time to value
44

Production Environment
Continuous Monitoring
Fully
Automated
Continuous Deployment
Shift Left – Operational Concerns
• Operations Concerns move earlier in software delivery life cycle, towards development.
• The Goal is to enable Developers and QC Team to Develop and Test the software that
behave like Production System in fully automated way.
Development Environment
Build
Build
Build
Test Environment
Continuous Integration
Unit
Testing
Component
Testing
Contract
Testing
Integration
Testing
Continuous Testing
Shift Left moves operations earlier in development cycle.
45
Stage Environment
Acceptance Testing
Pull Request / Merge
Continuous Delivery
GitOps – CD/CD

Infrastructure as a Code
• Infrastructure as a Code is a
critical capability for DevOps
• This helps the organizations to
establish a fully automated
pipeline for Continuous Delivery.
• Infra as a Code is a software defined environment to manage
the following:
• Network Topologies, Roles, Relationship, Network Policies
• Deployment Models, Workloads, Workload Policies &
Behaviors.
• Autoscaling (up & down) of the workloads
46

Stages of DevOps Delivery Pipeline
Application Release Management
Development Build Package
Repository
Test
Environment
Stage
Environment
Production
Environment
Application Deployment Automation
Cloud Provisioning
mvn repository
npm repository
Docker hub
47

5 Principles of DevOps (Philosophies)
Reduce
Organization
Silos
Capability Centric Design
Implement
Gradual
Change
Microservices Architecture
& Agile: Kanban
Leverage Tooling & Automation
CI/CD Pipeline & Container Orchestration
48
Accept
Failure as
Normal
Design for Failure
Measure
Everything
Service Mesh: Observability

class SRE implements DevOps
49
Source: https://stackify.com/site-reliability-engineering/ - https://www.redhat.com/en/topics/devops/what-is-sre

class SRE implements DevOps
Reduce
Organization
Silos
Accept
Failure as
Normal
Implement
Gradual
Change
Leverage Tooling & Automation
Measure
Everything
 Share Ownership  SLOs & Blameless PM  Canary Deployment
 Automate this years Job  Measure toil &
reliability
50
Capability Centric Design Microservices Architecture
& Agile: Kanban
CI/CD Pipeline & Container Orchestration
Design for Failure
Service Mesh: Observability

Service Levels – SLI / SLO
SLI – Service Level Indicator
For Web sites:
SLI is a Percentage of requests
responded in good health.
SLI can be a Performance Indicator:
Percentage of search results returned
under 50 milli-seconds.
SLO – Service Level Objective
SLO is a goal built around SLI. It is
usually a percentage and is tied to a
period and it is usually measured in
a number of nines. Time periods
can be last 24 hours, last week, last
30 days, current quarter etc.
uptime Last 30 Days
90%
(1 nine of uptime): Meaning you
were down for 10% of the
period. This means you were
down for three days out of the
last thirty days.
99%
(2 nines of uptime): Meaning 1%
or 7.2 hours of downtime over
the last thirty days.
99.9%
(3 nines of uptime): Meaning
0.1% or 43.2 minutes of
downtime.
99.99%
(4 nines of uptime): Meaning
0.01% or 4.32 minutes of
downtime.
99.999%
(5 nines of uptime): Meaning 26
seconds or 0.001% of downtime.
51

SRE – Concept
 Bridge the Gap between Development & Operations
 Developers wants to ship features as fast as possible
 Operations want stability in Production
 Empowers the Software Developers to own the operations of
Applications in Production.
 Site Reliability Engineers spends 50% of their time in Operations.
 SRE has a deep understanding of the application, the code, how
it runs, is configured and how it will scale.
 They monitor and manage the support apart from the
development activities.
52

SRE – Responsibilities
 Proactively monitor and review application performance
 Handle on-call and emergency support
 Ensure software has good logging and diagnostics
 Create and maintain operational runbooks
 Help triage escalated support tickets
 Work on feature requests, defects and other
development tasks
 Contribute to overall product roadmap
53

DevOps Case Studies
• NetFlix
• Spotify
54

100s Microservices
1,000s Releases / Day
10,000s Virtual Machines
100K+ User actions / Second
81 M Customers Globally
1 B Time series Metrics
10 B Hours of video streaming
every quarter
Source: NetFlix: : https://www.youtube.com/watch?v=UTKIT6STSVM
10s OPs Engineers
0 NOC
0 Data Centers
So what do NetFlix think about DevOps?
No DevOps
Don’t do lot of Process / Procedures
Freedom for Developers & be Accountable
Trust people you Hire
No Controls / Silos / Walls / Fences
Ownership – You Build it, You Run it.
55

50M Paid Subscribers
100M Active Users
60 Countries
Cross Functional Team
Full, End to End ownership of features
Autonomous
1000+ Microservices
Source: https://microcph.dk/media/1024/conference-microcph-2017.pdf
1000+ Tech Employees
120+ Teams
56

Benefits of DevOps
 Velocity
o Agile / Kanban,
o Capability Centric Design
o Domain Driven Design
o Event Sourcing & CQRS
o Microservices Architecture
Code Build Manage Learn
Idea
 Quality
o Test Automation
o Build Pipeline Automation
o Continuous Integration
o Continuous Delivery
o Continuous Deployment
People Process Tools
57

@arafkarsh arafkarsh 58
Design Patterns are
solutions to general
problems that
software developers
faced during software
development.
Design Patterns

DREAM | AUTOMATE | EMPOWER
Araf Karsh Hamid :
India: +91.999.545.8627
http://www.slideshare.net/arafkarsh
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@arafkarsh
arafkarsh

Source Code: https://github.com/MetaArivu Web Site: https://metarivu.com/ https://pyxida.cloud/

References
1. IBM: Event Driven Architecture – Mar 21, 2021
2. Martin Fowler: Event Driven Architecture – GOTO 2017
3. Greg Young: A Decade of DDD, Event Sourcing & CQRS – April 11, 2016
4. Nov 13, 2014 GOTO 2014 – Event Sourcing. By Greg Young
5. Mar 22, 2016 Building Micro Services with Event Sourcing and CQRS
6. Apr 15, 2016 YOW! Nights – Event Sourcing. By Martin Fowler
7. May 08, 2017 When Micro Services Meet Event Sourcing. By Vinicius Gomes
Kafka
1. Understanding Kafka
2. Understanding RabbitMQ
3. IBM: Apache Kafka – Sept 18, 2020
4. Confluent: Apache Kafka Fundamentals – April 25, 2020
5. Confluent: How Kafka Works – Aug 25, 2020
6. Confluent: How to integrate Kafka into your environment – Aug 25, 2020
7. Kafka Streams – Sept 4, 2021
8. Kafka: Processing Streaming Data with KSQL – Jul 16, 2018
9. Kafka: Processing Streaming Data with KSQL – Nov 28, 2019
62

References
Microservices
1. Microservices Definition by Martin Fowler
2. When to use Microservices By Martin Fowler
3. GoTo: Sep 3, 2020: When to use Microservices By
Martin Fowler
4. GoTo: Feb 26, 2020: Monolith Decomposition
Pattern
5. Thought Works: Microservices in a Nutshell
6. Microservices Prerequisites
7. What do you mean by Event Driven?
8. Understanding Event Driven Design Patterns for
Microservices
Testing – TDD / BDD
1. An introduction to TDD
2. Component Software Testing
3. What is Component Testing?
4. Component Test By Martin Fowler
5. Contract Testing By Martin Fowler
6. Integration Testing By Martin Fowler
7. Testing Strategies in Microservices
Architecture
8. Practical Test Pyramid By Ham Vocke
63

References
Cloud Architecture
1. Vmware: What is Cloud Architecture?
2. Redhat: What is Cloud Architecture?
3. Cloud Computing Architecture
4. Cloud Adoption Essentials:
5. Google: Hybrid and Multi Cloud
6. IBM: Hybrid Cloud Architecture Intro
7. IBM: Hybrid Cloud Architecture: Part 1
8. IBM: Hybrid Cloud Architecture: Part 2
9. Cloud Computing Basics: IaaS, PaaS, SaaS
10. IBM: IaaS Explained
11. IBM: PaaS Explained
12. IBM: SaaS Explained
13. IBM: FaaS Explained
14. IBM: What is Hypervisor?
DevOps
1. IBM: What is DevOps?
2. IBM: Cloud Native DevOps Explained
3. IBM: Application Transformation
4. IBM: Virtualization Explained
5. What is DevOps? Easy Way
6. DevOps?! How to become a DevOps Engineer???
64

References
Databases: Big Data / Cloud Databases
1. Google: How to Choose the right database?
2. AWS: Choosing the right Database
3. IBM: NoSQL Vs. SQL
4. A Guide to NoSQL Databases
5. How does NoSQL Databases Work?
6. What is Better? SQL or NoSQL?
7. What is DBaaS?
8. NoSQL Concepts
9. Key Value Databases
10. Document Databases
11. Graph Databases
12. Column Databases
13. Row Vs. Column Oriented Databases
14. Database Indexing Explained
15. MongoDB Indexing
16. AWS: DynamoDB Global Indexing
17. AWS: DynamoDB Local Indexing
18. Google Cloud Spanner
19. AWS: DynamoDB Design Patterns
20. Cloud Provider Database Comparisons
21. CockroachDB: When to use a Cloud DB?
65

References
Docker / Kubernetes / Istio
1. IBM: Virtual Machines and Containers
2. IBM: What is a Hypervisor?
3. IBM: Docker Vs. Kubernetes
4. IBM: Containerization Explained
5. IBM: Kubernetes Explained
6. IBM: Kubernetes Ingress in 5 Minutes
7. Microsoft: How Service Mesh works in Kubernetes
8. IBM: Istio Service Mesh Explained
9. IBM: Kubernetes and OpenShift
10. IBM: Kubernetes Operators
11. 10 Consideration for Kubernetes Deployments
Istio – Metrics
1. Istio – Metrics
2. Monitoring Istio Mesh with Grafana
3. Visualize your Istio Service Mesh
4. Security and Monitoring with Istio
5. Observing Services using Prometheus, Grafana, Kiali
6. Istio Cookbook: Kiali Recipe
7. Kubernetes: Open Telemetry
8. Open Telemetry
9. How Prometheus works
10. IBM: Observability vs. Monitoring
66

References
CI / CD
1. What is Continuous Integration?
2. What is Continuous Delivery?
3. CI / CD Pipeline
4. What is CI / CD Pipeline?
5. CI / CD Explained
6. CI / CD Pipeline using Java Example Part 1
7. CI / CD Pipeline using Ansible Part 2
8. Declarative Pipeline vs Scripted Pipeline
9. Complete Jenkins Pipeline Tutorial
10. Common Pipeline Mistakes
11. CI / CD for a Docker Application
67

References
68
1. Lewis, James, and Martin Fowler. “Microservices: A Definition of This New Architectural Term”, March 25, 2014.
2. Miller, Matt. “Innovate or Die: The Rise of Microservices”. e Wall Street Journal, October 5, 2015.
3. Newman, Sam. Building Microservices. O’Reilly Media, 2015.
4. Alagarasan, Vijay. “Seven Microservices Anti-patterns”, August 24, 2015.
5. Cockcroft, Adrian. “State of the Art in Microservices”, December 4, 2014.
6. Fowler, Martin. “Microservice Prerequisites”, August 28, 2014.
7. Fowler, Martin. “Microservice Tradeoffs”, July 1, 2015.
8. Humble, Jez. “Four Principles of Low-Risk Software Release”, February 16, 2012.
9. Zuul Edge Server, Ketan Gote, May 22, 2017
10. Ribbon, Hysterix using Spring Feign, Ketan Gote, May 22, 2017
11. Eureka Server with Spring Cloud, Ketan Gote, May 22, 2017
12. Apache Kafka, A Distributed Streaming Platform, Ketan Gote, May 20, 2017
13. Functional Reactive Programming, Araf Karsh Hamid, August 7, 2016
14. Enterprise Software Architectures, Araf Karsh Hamid, July 30, 2016
15. Docker and Linux Containers, Araf Karsh Hamid, April 28, 2015

References
16. Oct 27, 2012 What I have learned about DDD Since the book. By Eric Evans
17. Mar 19, 2013 Domain Driven Design By Eric Evans
18. Jun 02, 2015 Applied DDD in Java EE 7 and Open Source World
19. Aug 23, 2016 Domain Driven Design the Good Parts By Jimmy Bogard
20. Sep 22, 2016 GOTO 2015 – DDD & REST Domain Driven API’s for the Web. By Oliver Gierke
21. Jan 24, 2017 Spring Developer – Developing Micro Services with Aggregates. By Chris Richardson
22. May 17. 2017 DEVOXX – The Art of Discovering Bounded Contexts. By Nick Tune
23. Dec 21, 2019 What is DDD - Eric Evans - DDD Europe 2019. By Eric Evans
24. Oct 2, 2020 - Bounded Contexts - Eric Evans - DDD Europe 2020. By. Eric Evans
25. Oct 2, 2020 - DDD By Example - Paul Rayner - DDD Europe 2020. By Paul Rayner

References
26. Nov 13, 2014 - GOTO 2014 – Event Sourcing. By Greg Young
27. Mar 22, 2016 - Spring Developer – Building Micro Services with Event Sourcing and CQRS
28. Apr 15, 2016 - YOW! Nights – Event Sourcing. By Martin Fowler
29. May 08, 2017 - When Micro Services Meet Event Sourcing. By Vinicius Gomes
30. July 15, 2015 – Agile is Dead : GoTo 2015 By Dave Thomas
31. Apr 7, 2016 - Agile Project Management with Kanban | Eric Brechner | Talks at Google
32. Sep 27, 2017 - Scrum vs Kanban - Two Agile Teams Go Head-to-Head
33. Feb 17, 2019 - Lean vs Agile vs Design Thinking
34. Dec 17, 2020 - Scrum vs Kanban | Differences & Similarities Between Scrum & Kanban
35. Feb 24, 2021 - Agile Methodology Tutorial for Beginners | Jira Tutorial | Agile Methodology Explained.
Agile Methodologies
70

References
1. Jul 3, 2019 – Understanding Kafka
2. Aug 8, 2019 – Understanding RabbitMQ
3. Feb 6, 2020 – An introduction to TDD
4. Aug 14, 2019 – Component Software Testing
5. May 30, 2020 – What is Component Testing?
6. Apr 23, 2013 – Component Test By Martin Fowler
7. Jan 12, 2011 – Contract Testing By Martin Fowler
8. Jan 16, 2018 – Integration Testing By Martin Fowler
9. Testing Strategies in Microservices Architecture
10. Practical Test Pyramid By Ham Vocke
71

References
SQL Vs NoSQL
36. Jun 29, 2012 – Google I/O 2012 - SQL vs NoSQL: Battle of the Backends
37. Feb 19, 2013 - Introduction to NoSQL • Martin Fowler • GOTO 2012
38. Jul 25, 2018 - SQL vs NoSQL or MySQL vs MongoDB
39. Oct 30, 2020 - Column vs Row Oriented Databases Explained
40. Dec 9, 2020 - How do NoSQL databases work? Simply Explained!
72

References
73
27. MSDN – Microsoft https://msdn.microsoft.com/en-us/library/dn568103.aspx
28. Martin Fowler : CQRS – http://martinfowler.com/bliki/CQRS.html
29. Udi Dahan : CQRS – http://www.udidahan.com/2009/12/09/clarified-cqrs/
30. Greg Young : CQRS - https://www.youtube.com/watch?v=JHGkaShoyNs
31. Bertrand Meyer – CQS - http://en.wikipedia.org/wiki/Bertrand_Meyer
32. CQS : http://en.wikipedia.org/wiki/Command–query_separation
33. CAP Theorem : http://en.wikipedia.org/wiki/CAP_theorem
34. CAP Theorem : http://www.julianbrowne.com/article/viewer/brewers-cap-theorem
35. CAP 12 years how the rules have changed
36. EBay Scalability Best Practices : http://www.infoq.com/articles/ebay-scalability-best-practices
37. Pat Helland (Amazon) : Life beyond distributed transactions
38. Stanford University: Rx https://www.youtube.com/watch?v=y9xudo3C1Cw
39. Princeton University: SAGAS (1987) Hector Garcia Molina / Kenneth Salem
40. Rx Observable : https://dzone.com/articles/using-rx-java-observable

References – Microservices – Videos
74
41. Martin Fowler – Micro Services : https://www.youtube.com/watch?v=2yko4TbC8cI&feature=youtu.be&t=15m53s
42. GOTO 2016 – Microservices at NetFlix Scale: Principles, Tradeoffs & Lessons Learned. By R Meshenberg
43. Mastering Chaos – A NetFlix Guide to Microservices. By Josh Evans
44. GOTO 2015 – Challenges Implementing Micro Services By Fred George
45. GOTO 2016 – From Monolith to Microservices at Zalando. By Rodrigue Scaefer
46. GOTO 2015 – Microservices @ Spotify. By Kevin Goldsmith
47. Modelling Microservices @ Spotify : https://www.youtube.com/watch?v=7XDA044tl8k
48. GOTO 2015 – DDD & Microservices: At last, Some Boundaries By Eric Evans
49. GOTO 2016 – What I wish I had known before Scaling Uber to 1000 Services. By Matt Ranney
50. DDD Europe – Tackling Complexity in the Heart of Software By Eric Evans, April 11, 2016
51. AWS re:Invent 2016 – From Monolithic to Microservices: Evolving Architecture Patterns. By Emerson L, Gilt D. Chiles
52. AWS 2017 – An overview of designing Microservices based Applications on AWS. By Peter Dalbhanjan
53. GOTO Jun, 2017 – Effective Microservices in a Data Centric World. By Randy Shoup.
54. GOTO July, 2017 – The Seven (more) Deadly Sins of Microservices. By Daniel Bryant
55. Sept, 2017 – Airbnb, From Monolith to Microservices: How to scale your Architecture. By Melanie Cubula
56. GOTO Sept, 2017 – Rethinking Microservices with Stateful Streams. By Ben Stopford.
57. GOTO 2017 – Microservices without Servers. By Glynn Bird.

References – DevOps / SRE (Site Reliability Engineering)
75
58. Amazon: https://www.youtube.com/watch?v=mBU3AJ3j1rg
59. NetFlix: https://www.youtube.com/watch?v=UTKIT6STSVM
60. DevOps and SRE: https://www.youtube.com/watch?v=uTEL8Ff1Zvk
61. SLI, SLO, SLA : https://www.youtube.com/watch?v=tEylFyxbDLE
62. DevOps and SRE : Risks and Budgets : https://www.youtube.com/watch?v=y2ILKr8kCJU
63. SRE @ Google: https://www.youtube.com/watch?v=d2wn_E1jxn4

1. Simoorg : LinkedIn’s own failure inducer framework. It was designed to be easy to extend and
most of the important components are plug‐ gable.
2. Pumba : A chaos testing and network emulation tool for Docker.
3. Chaos Lemur : Self-hostable application to randomly destroy virtual machines in a BOSH-
managed environment, as an aid to resilience testing of high-availability systems.
4. Chaos Lambda : Randomly terminate AWS ASG instances during business hours.
5. Blockade : Docker-based utility for testing network failures and partitions in distributed
applications.
6. Chaos-http-proxy : Introduces failures into HTTP requests via a proxy server.
7. Monkey-ops : Monkey-Ops is a simple service implemented in Go, which is deployed into an
OpenShift V3.X and generates some chaos within it. Monkey-Ops seeks some OpenShift
components like Pods or Deployment Configs and randomly terminates them.
8. Chaos Dingo : Chaos Dingo currently supports performing operations on Azure VMs and VMSS
deployed to an Azure Resource Manager-based resource group.
9. Tugbot : Testing in Production (TiP) framework for Docker.
Testing tools

Microservices, DevOps & SRE

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