Manual Monitoring Slows Deployment and Introduces Risk How often do you update your applications? “We deploy multiple times per day” seems to be the new badge of honor for DevOps. But what you don’t often hear about are the problems caused by process acceleration as a result of continuous integration and continuous deployment (CI/CD). Rapid introduction of performance problems and errors Rapid introduction of new endpoints causing monitoring issues Lengthy root cause analysis as number of services expand When implementing CI/CD, ANY manual intervention slows down the entire pipeline. You can’t achieve complete CI/CD without automating your monitoring processes (just like you did for integration, testing, and deployment).

1. Monitoring at the Speed of DevOps
Why Continuous Deployment and
Continuous Monitoring Make a Winning Pair

2. Today’s Speakers
• Docker Captain
• Docker Meetup Organizer
• DevOpsDays Nashville Organizer
• 14+ years in software development
• 4+ years Docker experience
@notsureifkevin
• 10+ years APM expertise
• Highly Experienced in Customer
Success
• Authority on Web Based
Technology and Enterprise
Applications
Kevin Crawley
Developer Evangelist
Hugh Brien
Sr. Solutions Architect
hughbrien

3. Agenda
• State of DevOps Today
• Problems Caused by CI/CD
• Reasons for CI/CD Challenges
• Requirements for Automatic Monitoring
• The Solution: Instana Automatic Monitoring
• Instana Demo
• Q&A

4. State of DevOps Today
• High Performance vs Low Performance
Organizations
• How you implement cloud infrastructure
matters
• Software Delivery & Operational
Performance (SDO) unlocks competitive
advantages
• Outsourcing by function hurts performance.
• Key technical practices – like monitoring and
observability – drive high performance

5. Software Delivery Performance - Throughput
Measuring the velocity of your application delivery organization

6. Software Delivery Performance - Stability
Measuring the resiliency of your application delivery organization

7. High Performance vs Low Performance Organizations
High Performers
• Deployments:
> 1 hour and < 1 day
• Lead Time for Changes:
> 1 day and < 1 week
• MTTR:
< 1 day
• Change Failure Rate:
0-15%
Low Performers
• Deployments:
Once per week/month
• Lead Time for Changes:
> 1 month and <6 months
• MTTR:
> 1 week and < 1 month
• Change Failure Rate:
46-60%
https://puppet.com/resources/whitepaper/state-of-devops-report

8. Problems Caused by CI/CD
• Generally Accepted Fact:
Successful CI/CD requires monitoring and observability in test & production
• As more companies embark on CI/CD unique problems are surfacing
• Rapid introduction of performance problems and errors
• Rapid introduction of new endpoints causing monitoring issues
• Lengthy root cause analysis as number of services expand

9. Reason For CI/CD Challenges
• More software is updated or added more frequently on more infrastructure
• Good for business, difficult on conventional monitoring tools
• Most monitoring tools employ many, if not all, of the following processes:
• Manually write data collectors
• Manually instrument code for tracing
• Manually configure data collectors
• Manually discover dependencies
• Manually decide how to correlate data
• Manually build dashboards to visualize correlation
• Manually configure alerting rules and thresholds
• Manually build data collection to store your metrics

10. Impact of “Manual Monitoring” on CI/CD
No Automation Poor Visibility No Speed
Unhappy Customers Lost Revenue

11. Speed Requires Automation
• CI/CD automates your software delivery process
• Manual steps slow you down!
GitHub
Puppet Labs
Chef
Selenium
Kubernetes
Jenkins

12. Requirements for Automatic Monitoring
• Zero or Minimal Configuration for the Automatic Discovery
of Infrastructure and Software Components
• Automatic instrumentation and tracing of every
component in your application
• Pre-existing alerts for supported technologies and
frameworks
• High resolution metrics and analytics to power Machine
Learning Algorithms
Automated continuous monitoring will keep your
continuous deployment pipelines flowing smoothly and
efficiently.

13. Instana Automatic Monitoring
Instana Agent:
• One agent deployed once per host
• Continuous automatic discovery of technology
• Automatic metric collection
• Automatic tracing
• Automatic dependency mapping
Continuous real time discovery and monitoring of ALL components
Automatic
No Plugins
No Configuration

14. DevOps Demands Automatic
Don’t slow down
Let the robot do the work!
Automation
Detect
Capture
Analyse (AI)
Actionable Information
Optimisations
Troubleshooting
Accelerate Delivery
Incidents

15. "Observability aims to provide highly granular
insights into the behavior of systems along with
rich context, perfect for debugging purposes."
Cindy Sridharan
Observability: The New Requirement

16. Deep Performance Analysis
• Rise in Latency and
Processing Time
• DBO causing log(n) rise
in latency and processing
• Application Trace to
Database led us to the
offending endpoint
• Fix deployed and
improvement observed
immediately (Next Slide)

17. Immediate Feedback

18. It’s time to change your
perspective on monitoring
DEMO