In DevOps we are used to talking about application velocity. But velocity without a framework is short lived and potentially creates more risk than benefit. Code-to-Cloud visibility is the practice of making sure engineering teams have visibility across the entire SDLC in depth and breadth. With code-to-cloud visibility organizations understand the impact of application development from feature definition to it running in production. Join Splunker Chris Riley as he explores: The importance of aligning application visibility with your application tech stack How to enable code-to-cloud visibility practices Deeper understanding of DevSecOps, Pipeline Analytics, and Observability

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Code-To-Cloud
Visibility:
A Framework for
DevOps
Success

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Chris Riley
DevOps & DevRel Advocate
@HoardingInfo

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Is DevOps just about
Velocity

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Developers
Quality
Engineers
DevOps Engineers
SRE & Ops
Developers
Plan/
CODE
BUILD TEST RELEASE DEPLOY OPERATE MONITOR RESPOND
End
dev insights
End
quality insights
End
prod insights
InfoSec
Visibility Silos

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Code-to-Cloud Visibility
SDLC: Health, Security, KPIs
Breadth
Depth
Plan/
CODE
BUILD TEST RELEASE DEPLOY OPERATE MONITOR RESPOND
Incident Response
Full-Stack Monitoring

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Why?
Retain & Optimize Lift & Shift Re-Factor Re-Architect /
Cloud-Native
DEV OPS DEV OPS DEV OPS DEV OPS
Cloud Managed e.g. RDS,
DynamoDB, SaaS
Cloud First Architecture
Tightly Coupled Apps,
Slow Deployment Cycles
Primarily using
Cloud IaaS
More Modular, but
Dependent App Components
Loosely Coupled Microservices,
and Serverless Functions
VM VM VM
VM VM VM VM VM VM
Private Public
VM VM VM VM VM VM
Private Public Private Public

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Pipeline
Analytics Observability
DevS cOps

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Use Cases of Pipeline Analytics

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Monitor – Meet your SLO
• Infra Metrics: Memory, CPU, Disk, Network IO
• Status Up/Down
• RED – Rate, Error, Duration

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Audit – Stop bad actors
• Requests by policy/entity
• Auth by type/method
• Request by IP
• Request by URI
• Request/Auth Denials

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Measure – Know the meaning of good
• DORA Metrics:
• Deployment Frequency (DF)
• Lead Time for Changes (MLT)
• Change Failure Rate (CFR)
• Time to Recover/Restore (MTTR)
• And more:
• Work in Progress (WIP)
• Cost of Downtime
• Amount of un-planned work
• Activity by Repo/Artifact
• Branch aging summary
• Say/Do

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Build more secure
applications
Secure the
application factory
Secure applications
in production
The use cases of DevSecOps

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Characteristics of DevSecOps
Integrated Using
Automation
Shift Security Left At DevOps Speed
Test
Code Build Release Operate

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Site Reliability Engineers(SRE)
Security
Secure apps in prod
Secure the app factory
DevOps Engineers
Site Reliability Engineers(SRE)
Security
CIO, CTO, CISO
Make your DevSecOps practice visible
Developers
Quality Engineers
DevOps Engineers
Build more secure apps
The practice is not one-size-fits-all

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SIEM
Observability
Incident Response
Secure apps in prod
Secure the app factory
Pipeline Analytics
SIEM
Pipeline Analytics
Make your DevSecOps practice visible
Pipeline Analytics
Build more secure apps
The practice is not one-size-fits-all

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The Dimensions of Observability

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The Data of Observability
• Getting data in –
• The right data – Metrics, Logs, Traces and Spans
• Data resolution – Cardinality, Full-Fidelity

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Infrastructure
Infrastructure
APM / Infrastructure
APM
DEM / APM
DEM
Infrastructure
Networking
Application Infrastructure
Backend
API
Front End
Application Logic
APM / Infrastructure
Security - SIEM
Delivery Chain – Pipeline Analytics

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The Practice of Observability
Application Performance Mentoring (APM)
Infrastructure Monitoring
Real-User Monitoring (RUM)
Logs
Incident Response

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is your
Code-To-Cloud

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Thank You!
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