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DevOpsis a combination of
software development (dev)
and operations (ops). It is
defined as a software
engineering methodology that
aims to integrate the work of
development teams and
operations teams by facilitating
a culture of collaboration and
shared responsibility.
(Source: Gitlab.com)
What is DevOps? And Why Use DevOps?
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DevOps is more than just CI / CD
Code Build Integrate Test Release Deploy Operate
Agile Development
Continuous Integration
Continuous Delivery
Continuous Deployment
DevOps
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DevOps on AWS
CI/CD Services
CodePipeline
Builds, tests, and deploys code change based on
release process models defined.
CodeBuild
Fully managed build service that compiles source code,
runs tests, and produces packages ready to deploy.
CodeDeploy
Automates code deployments to any instance
including EC2 and on-premises.
CodeStar
Provides a unified interface to manage software
delivery from a single place.
Infrastructure as a Code
CloudFormation
Provides an easy way to create and manage
collection of AWS resources.
OpsWorks
Configuration management service that uses Chef, an
automation platform that treats server configs as code.
Systems Manager
Management service that helps to collect software
inventory, apply OS patches, create system images.
Config
Provides AWS resource inventory, configuration history,
configuration change notifications to enable security,
governance.
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DevOps on Azure
Azure Boards
Deliver value to your users faster using
proven agile tools to plan, track, and
discuss work across your teams.
Azure Pipelines
Build, test, and deploy with CI/CD that
works with any language, platform, and
cloud. Connect to GitHub or any other Git
provider and deploy continuously.
Azure Repos
Get unlimited, cloud-hosted private Git
repos and collaborate to build better code
with pull requests and advanced file
management.
Azure Test Plans
Test and ship with confidence using manual
and exploratory testing tools.
Azure Artifacts
Create, host, and share packages with your
team, and add artifacts to your CI/CD
pipelines with a single click.
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Developer’s
View
QA Stage
Push Code
Backlog &
Work Items
Azure Build
Pipeline (CI)
Azure Release
Pipeline (CD)
Trigger Build
Publish
Artifacts
Azure
Artifacts
Pull
Artifacts
Trigger Release
Build Job
Get Source
Install Tools
(Optional)
Build Solution
Run Tests
(Optional)
Package Artifacts
Publish Artifacts
Deploy to Dev
Deploy to QA
Prod Stage
Deploy to
Staging Slot
Swap Staging
and Prod Slots
Approvals &
Gates
Approvals &
Gates
Azure Boards
Azure Repos
(Git)
Dev Stage
Developer
Visual
Studio
Visual Studio
Code
App Service
Prod Staging Slot
Production Slot
Dev
QA
Web App
Web App
Web App
Web App
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What is SRE (Site Reliability Engineering)?
STEP 1
Monitor – Log metrics on key
functionalities for reliability and
scalability
STEP 2
Visualize – represent findings
graphically and identify bottlenecks
STEP 3
Remediate – find solutions and
execute effectively
STEP 4
Improve – be vigilant and uphold the
principal of zero downtime
Why do you need SRE?
Term originated at Google and is
now used everywhere
Wikipedia Definition:
Site reliability engineering (SRE)
is a set of principles and
practices that incorporates
aspects of software engineering
and applies them to
infrastructure and operations
problems. The main goals are to
create scalable and highly
reliable software systems.
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Benefits of Site Reliability Engineering
Reduce product /
service downtime
Bridges the gaps
between platform
design, development, &
operations
Increased security &
compliance
Automation /
human error impact
reduction
Understanding the
process end-to-end for
better outcomes
Create
observability
into service
health
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SRE Maturity Model
•Predictive Event Management
•Automated Self Healing Repairs
•New Environments on Demand
(Immutable pre-defined blueprints)
•Provision for new initiatives (Error, Risk, and Toil)
•Impact assessment for changes
•Experiments with Non-Prod followed by Production
•Canary/Blue-Green Deployments
•Measure and Model Main Signals (Error, Traffic, Latency, and Failover)
•Measure and Model Metrics like MTTR, MTBF, MTTA etc.
•Mainly Logging
•Basic KPIs (Performance, Reliability etc.)
Self Service
Self Healing
Automated Impact
Assessment
Chaos Engineering
Improved Telemetry
Basic Observability
Stage 1
Stage 2
Stage 3
Security & Compliance
01
02
03
04
05
06
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DevOps and SRE Recap
ObservabilityProactive remediation
Full automation
Playbooks / runbooks
ITIL based Incident
management
Fault tolerant design
KPIs Knowledge base
Standardization
Continuous
improvement
Blameless
post-mortems
Error quota,
SLI/SLA/SLO
Microservices design
DevOps tools
configuration
Deployments and
rollbacks
API contracts CI/CD pipelines
SRE DevOps
Chaos engineering