This document outlines a deployment strategy for deploying a company's software updates. It includes an agenda, deployment overview, challenges of modern applications, and descriptions of common deployment techniques like rolling deployments, blue/green deployments, and canary deployments. Best practices and considerations for post-deployment monitoring are also discussed. Comparisons are made between the different deployment strategies on factors like downtime, ability to test with real traffic, targeted users, cloud costs, rollback capabilities, and complexity.

1. Deployment Strategy
Yo u r C o m p a n y N a m e
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2. 2
AGENDA
Company Software Updates Deployment Strategy
Routing Techniques
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01
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03
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3. Content
3
Deployment Overview01
Challenges of Modern Applications02
Rolling Deployments03
Rolling Deployment Use Case04
Blue/Green Deployments05
Blue/Green Deployment Use Case06
Routing Techniques09
Canary Deployments07
Post-Deployment Monitoring12
Canary Deployment Use Case08
Deployment Strategies Comparisons11
Deployment Best Practices10
DEPLOYMENT
STRATEGY

4. Deployment Overview
DEPLOYMENT OVERVIEW
Number of Sites or Release Recipients Target Deployments Target Group Scheduled Dates
<Identify the number & location (if applicable) of the sites/ release
recipients for the software application/system>
Initial Deployment <Site/Release Recipients> <Month/Year>
General Availability Release <Site/Release Recipients> <Month/Year>
4
DEPLOYMENT APPROACH
Description
<Describe the deployment approach that will be used for deploying the software application/system>
Benefits (Tangible & Intangible) & Risks
<Describe tangible & intangible benefits realized from the recommended approach>
Assumptions
<List any assumptions associated with the deployment approach>
ASSUMPTIONS
Risks
<List any associated with the deployment approachRISKS
&

5. Challenges of Modern Applications
This slide covers challenges faced by the modern applications
5
One of the most important challenges faced by a web-facing
application is the ability to handle a large number of concurrent users
Modern applications need to be able to handle large amounts of data
Lack of handling failures gracefully without any data loss or interruptions
of internet traffic
is bot generated, half of which is attributed to “bad” bots.52%
Unfortunately,
of organizations
can’t make a clear distinction between good and bad bots.79%
Listed here are some
of the challenges
faced by modern
applications. User
can add according to
their requirements
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6. Deployment Strategy - Rolling Deployments
In this slide we have covered rolling deployment architecture
6
Both Nodes running…. Both Nodes running….Patching 2nd Node….Patching 1st Node….
During that time, new and old versions will coexist without affecting functionality or user experience
In a rolling deployment, an application’s new version gradually replaces the old one
The actual deployment happens over a period of time
This slide covers
rolling deployments
nodes model and its
working, user can
edit according to his
requirements
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7. Rolling Deployment Pattern
The old version is shown in blue and the new version is shown in green across each server in the cluster
7
State 0
State 1
State 2
Final State
The original applications were deployed in containers, the
upgrade can tackle one container at a time
Each container is modified to download the latest image from
the app vendor’s site
Old Version New Version
This slide covers the
rolling deployment pattern
i.e. how new version
upgrades or modified
without affecting existing
users, user can alter
according to their
requirements

8. Rolling Deployment Use Case
8
This slide shows the deployment of the application to PROD environment in four phases
We will deploy the application to the PROD environment in four phases:
Deploy only to
the DB tier
and verify the
DB upgrade
Deploy to a few resources in
the App and Web tiers and
verify that the application was
deployed successfully
Deploy to a few
more resources in
the App tier based
on some rules
Deploy to
the
remaining
resources
P H AS E
1 2 3 4
the Web
App
DB tiers
TheApplicationconsistsof
ThreeTiers
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This slide covers the use
of rolling deployment in
PROD environment with
in different phases. User
can alter according to his
requirements

9. Deployment Strategy - Blue-Green, Red-Black or A/B Deployment
This slide explains the functioning of blue green deployment strategy
9
U S E R S
R o u t e r
All Users
Web Server Application Server Database Server
Web Server Application Server Database Server
Old Version
New Version
Two identical production environments work in parallel
The Blue/Green Deployment strategy will be used
with dynamic cloud environments
There are two physically separate environments. At any
time, only one of these environments is live, serving all of
the production traffic
While new versions of the applications are deployed to the
second (blue) environment, the first environment (green) is
serving production traffic
This slide covers the
functioning of blue green
deployment environment,
while new version is
deployed the older one
serves the traffic. User can
alter according to their
requirements
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10. Blue-Green, Red-Black or A/B Deployment Pattern
This slide covers the two identical production environments works in parallel
10
› One is the currently-running production environment receiving all user
traffic (depicted as Blue)
› The other is a clone of it, but idle (Green)
› Both use the same database back-end and app configuration
› The new version of the application is deployed in the green
environment & tested for functionality and performance
› Once the testing results are successful, application traffic is routed
from blue to green
› Green then becomes the new production
Load Balancer
User Traffic
Load Balancer
User Traffic
Code Version 1 Code Version 2 Code Version 1 Code Version 2
Currently Running
Clone
Below shown are the
blue green environment
deployment pattern.
Which user can alter
according to his
requirements
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11. Blue-Green, Red-Black or A/B Deployment Use Case
This slide covers how to create blue and green deployment strategy as blue green are two physically separated environments, and can be configured in the Electric Flow environment model
11
Creating Four Environments
(DEV, QA, BLUE, and GREEN)
Mapping the Environments to the Shopping Cart Application
Select the Shopping Cart application, and map the application tiers to the
corresponding environment tiers in DEV, QA, BLUE, and GREEN
Creating a Pipeline
with Three Stages
Create a pipeline with three stages
called DEV, QA and PROD
Creating Three Tasks for the PROD stage
In PROD stage, create three tasks:
Number Task Name Description
1 DeployShoppingCart
This is another process task similar to what is in the DEV and QA stages that the environment name is parameterized.
The system will automatically switch deployments between the BLUE and GREEN environments
2 CertifyDeployment This is a manual step to review and certify the deployment
3 CompletePostCertificationTasks
This is an automation task to run any post certification tasks such as updating the load balancer and switching the
environment in preparation for the next pipeline run (for example, update the TargetENV parameter)
Listed here are the blue
green strategy deployment
use case i.e.
Modelling of the blue green
environment through these
steps and tasks. User can
alter according to their
requirements

12. Blue-Green, Red-Black or A/B Deployment Use Case Cont.
12
In this slide we have covered pipeline for the blue green deployment
Running the Pipeline
Before running the pipeline, the GREEN environment is serving all
of the production traffic, and the BLUE environment is ready to be
upgraded to the new software version
Before starting the Deployment,
› We have to set Rolling/TargetEnv property to the first
environment to which we want to deploy on the project.
› RollingDeploy/TargetEnv will be set to BLUE because the
GREEN environment is currently catering to end-user traffic
Setting the property value to GREEN will ensure that the next deployment will happen to the GREEN
environment while the BLUE environment serves all of the production traffic
The pipeline will start at the DEV stage and continue to the PROD stage
Once the deployment reaches the PROD stage, the application process task will deploy to the BLUE environment based
on the property value $[/myProject/RollingDeploy/TargetEnv], which was set to BLUE at the beginning of the run
Once the deployment task has completed, there is a manual step to functionally verify the deployment
If there was a need for some automated testing, those tasks can easily be added to the pipeline stage
Once the deployment completes successfully, switch the user traffic to the BLUE servers, & update the
RollingDeploy/TargetEnv property to GREEN
When the Pipeline starts:
This slide covers
before staring and
starting steps for the
blue green
deployment. User can
alter according to his
requirements

13. Deployment Strategy - Canary Deployment
13
This slide explains about the working of canary deployment environment
U S E R S
Web Server Application Server Database Server
Web Server Application Server Database Server
Old Version
New Version
R o u t e r
Most Users
95%
Some Users
5%
One environment is handling the production traffic. During deployment time, new versions are applied to
the second inactive environment similar to a blue/green deployment
Once the second environment with the newer version is satisfactorily tested, a portion of the end-user traffic is
diverted to it
The first environment runs the old production version of the applications and bears the majority of the traffic while
the second environment runs the new version of the applications and caters to a small portion of the traffic
This is a way to test the new version with live traffic, and if everything looks fine, all the traffic can be diverted
to the new version, or if there are issues with the new version, the older version can be kept instead
This technique
is an advanced
variation of the
Blue/Green
Deployment
In this slide we cover
canary deployment
environment working by
testing new version
without deleting the old
one. User can alter
according to their
requirements.
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14. Canary Deployment Pattern
In this slide we cover phased approach for canary deployment
14
Canary Deployment is like blue-green, except it’s more risk-averse
Instead of switching from blue
to green in one step, we use a
PHASED APPROACH
› Deploy a new application code in a small part of the production infrastructure
› Once the application is signed off for release, only a few users are routed to it. This minimizes any impact.
› No errors reported, the new version can gradually roll out to the rest of the infrastructure
User Traffic
Load Balancer
Code Version 1
Most Users Few Users
Code Version 2
Majority Infrastructure
User Traffic
Load Balancer
Code Version 2
All Infrastructure
This slide covers phased
approach for canary
deployment, in which new
version roll out to the rest
of the infrastructure when
no error reported. User
can alter according to their
requirements

15. Canary Deployment Use Case
15
This slide shows the canary deployment use, that how application deployed in subset of servers
The purpose of a canary deployment is to deploy an application to a small set of servers for validation by
a subset of users
Once user validation is complete, the application is rolled out to a larger set of servers
This is very similar to blue/green deployments where you can model separate environments and use
pipelines to control deployments to higher-order environments
The key difference with canary deployments is that part of the traffic is routed to the environment with
the latest version
USE
CASE
This slide covers that how
canary deployment is to
deploy an application to a
small set of servers. User
can alter according to his
requirements
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16. Routing Techniques:
This Slide Shows Various Techniques For Routing New Users
16
Basing routing on the
source IP range;
Releasing the application in
specific geographic regions;
Exposing internal users to the canary deployment
before allowing external user access;
Using an application logic to unlock new features to specific users and groups.
This logic is removed when the application goes live for the rest of the users
Listed are the routing
techniques for testing the
new versions of the
application. User can alter
according to his
requirements

17. Deployment Best Practices
This slide explains the best practices to minimize the deployment risks
17
Use Standard Operating
Environments (SOEs)
Ensure environment
consistency. You can use
tools like Vagrant and
Packer for development
workstations and servers
Use a
Deployment Checklist
An item on the checklist may
be to "backup all databases
only after app services have
been stopped" to prevent
data corruption
Adopt Continuous
Integration (CI)
CI ensures code checked
into the feature branch of a
code repository merges with
its main branch only after it
has gone through a series
of dependency checks, unit
and integration tests, and a
successful build
Adopt Continuous
Delivery (CD)
With CD, the CI-built
code artifact is
packaged and always
ready to be deployed
in one or more
environments
Enable Automated
Rollbacks for Deployments
that fail health checks,
whether due to availability
or error rate issues
This slide covers the best
practices for the
deployments techniques
which user can follow
before deployments and
can alter according to their
requirements
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18. Strategy
Zero
Downtime
Real Traffic
Testing
Targeted
Users
Cloud
Cost
Rollback
Duration
Negative
Impact on User
Complexity of
Setup
Rolling Deployment
The old version is shown in blue & the new
version is shown in green across each
server in the cluster
BLUE / GREEN
Version B is released alongside version A,
then the traffic is switched to version B
CANARY
Version B is released to a subset of users,
then proceed to a full rollout
A / B TESTING
Version B is released to a subset of users
under specific condition
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Deployment Strategies Comparisons
This slide shows the comparison of deployment strategies on different bases
18
Listed are the deployment
strategies comparisons on
the bases of cost, start-up,
time etc. User can alter
according to their
requirements
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19. Post-Deployment Monitoring (1/2)
This slide covers the post deployment monitoring framework
19
ApplicationPerformanceManagement
› Agentless (RUM) – [First]
› Multiple Protocol Anlytics
› Synthetic Probes & Robots
› APM Value : 80% comes from the EUE
› Agentless is low risk (Port Mirroring)
• Quick Implementation < 2 Days
› Robots = Availability & low vol. trends
End User
Experience
› Trans, Path Snapshots
› Bottom Up/ Top Down
› Monitor Cloud Apps
› Better service dependency mappings
• Understanding how network topologies
interact with application architecture
› Change impact assessment
Runtime
Application Architecture
› User-defined Transactions
› URL / Page Definitions
› 8 to 12 high level groups
› Meaningful SLAs to the Business
strengthen trust with Business
› Provide early warning trend reports
Business
Transactions
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Dimensions Area of Focus Potential Benefits
This slide covers
dimensions, area of focus
etc. to monitor
performance after
deployment. User can
alter according to his
requirements
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20. Post-Deployment Monitoring (2/2)
This slide covers the post deployments monitoring dashboard to measure performance
20
6.01%
21.19%
72.79%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Frustrated
Tolerated
Satisfied
89.3
4.9
3.2
2.2
0.4
401 500 403 400 422
Avg.
Response Time
Failed
Requests
HTTP
Failure Codes
0
50
100
150
200
250
Jan (12:00
pm)
Feb (6:00
pm)
Mar (12:00
am)
Apr (6:00
am)
May (12:00
pm)
Jun (6:00
pm)
Jul (12:00
am)
Aug (6:00
am)
Sep (12:00
pm)
Oct (6:00
pm)
Nov (12:00
am)
Dec (6:00
am)
Expressjs
Remote HTTP Calls
Postgres
Rendering
Remote HTTP Calls
86.18 ms from 14 : 15 till 15 : 10
160.24 ms
Overall Avg
7 ms
Expressjs
37.43 ms
Remote HTTP Calls
7.59 ms
Postgres
6 ms
Rendering
0
200
400
600
Jan
(12:00
pm)
Feb
(6:00
pm)
Mar
(12:00
am)
Apr
(6:00
am)
May
(12:00
pm)
Jun
(6:00
pm)
Jul
(12:00
am)
Aug
(6:00
am)
Sep
(12:00
pm)
Oct
(6:00
pm)
Nov
(12:00
am)
Dec
(6:00
am)
0%
2%
4%
6%
Jan
(12:00
pm)
Feb
(6:00
pm)
Mar
(12:00
am)
Apr
(6:00
am)
May
(12:00
pm)
Jun
(6:00
pm)
Jul
(12:00
am)
Aug
(6:00
am)
Sep
(12:00
pm)
Oct
(6:00
pm)
Nov
(12:00
am)
Dec
(6:00
am)
10 K Failed Requests
2 % Failure Rate
Response Time
Transaction Throughput HTTP Failure Rate
Experience
0.5M Requests
0.1 sec Apdex Threshold
0.83 Apdex Score
160.24 ms 0.5 M
Total Requests
10 K 2 %
Failure Rate
This slide shows the
KPIs and metrices to
measure performance
after deployment. User
can alter according to
their requirements

21. Deployment Strategy Icons Slide
21

22. 22
Additional Slides

23. Stacked Bar
23
50%
65%
-15%
-9%
40%
50%
-19%
-2%
-30% -20% -10% 0% 10% 20% 30% 40% 50% 60% 70%
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and changes automatically based
on data. Just left click on it and
select “Edit Data”.
Product 01
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and changes automatically based
on data. Just left click on it and
select “Edit Data”.
Product 02
Product 01
Product 02

24. Clustered Bar Chart
24
15
25
10
25
50
20
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and changes automatically based
on data. Just left click on it and
select “Edit Data”.
Product 01
This graph/chart is linked to excel,
and changes automatically based
on data. Just left click on it and
select “Edit Data”.
Product 02
Product 02
Product 01

25. Puzzle
25
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01 02
03

26. 26
About us
Preferred by Many
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Value Client
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Target Audience
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27. 27
Mission
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Vision
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Goals
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Our
Mission

28. Timeline
28
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6 Jul 2015
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8 Aug 2017
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15 Sep 2019
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22 Oct 2016
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12 Nov 2018
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27 Dec 2020

29. Target
29
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30. Financial
30
Net Income
$345
Deposits
$423
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31. 31
Thank
You
Address
# street number, city, state
Contact Number
0123456789
Email Address
email address123@gmail.com