Mastering Continuous Resiliency in Cloud: Chaos Engineering No one likes downtime. It can be detrimental in today’s competitive environment. It isn’t cheap either. Many companies have been using traditional DR strategies. However, their testing is costly, limited, and complex. In the modern agile environment, the latest DR exercise becomes invalid not long after it is done and there’s a greater variety of disruptions that can occur. In this demo, we’ll explore how to use chaos engineering techniques to: quantify reliability and resiliency, gain valuable insights, and build systems that can withstand the unexpected. By applying these practices, you can gain confidence, prove resiliency, and be sure you are ready to face the unexpected. Our speaker is Alexander Snegovoy, Lead of DevOps & Cloud Center of Competence at DataArt. Alex spearheads DataArt’s drive toward innovation, with more than 10 years of professional experience across the financial services, healthcare, travel, and IoT industries. After joining DataArt as a software engineer in 2016, he became a leading member of the DevOps & Cloud Center of Competence. His role also includes identifying and communicating technology trends, cementing alliances and strategic partnerships with other companies, and coaching and mentoring new talent.

2. New York USA
London UK
Munich Germany
Zug Switzerland
Chaos Engineering

3. $336,000/hour is the average cost
of downtime (as per Gartner’s report)
01

4. Last year AWS experienced 2
Availability-Zone level outages in
Ohio Region
02

5. It’s a Journey
• Introduce manual
experiments to
verify a hypothesis
• Execute in the
Development
Environment
• Reliability raises in
priorities and
enables confidence
in the product
• Introduce multiple
experiments
• Integrate Experiments
into SDLC
• Execute in Staging/Pre-
Prod environments
• Define “steady
state”
• Ensure
observability is in
place to confirm the
steady state
• Formulate a
hypothesis to
challenge the
steady state
• Run experiments in
Production
• Automatically
execute random
experiments
Crawl Run
Walk Innovate
Reliability Assurance 5

6. What are the mechanisms
6
• Bash + Python as a solution for everything
• ChaosMesh
• LitmusChaos and Harness
• Gremlin

7. The harder it is to disrupt the
steady state, the more confidence
we have
03

8. Goal is to verify that a system
does work, rather than validate
how it works
04

9. Demo Time!