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Fabian Stäber, Instana
Monitoring in a
Microservices World
@fstabr
Docker's Impact on Software Architecture
Application
Service Service
Service
Service
Service
Service
Impact on Monitoring
Some things become easier
● Health checks are commodity
● Runtime platforms provide information on service orchestration
Some things become harder
● Dynamically changing environments
● Health checks are not sufficient to represent the application state
Metrics
What is it: Time Series Data
Which challenges does it solve:
SLO-based alerting, root cause
analysis
Watch out for: Aggregate
horizontally, relate vertically,
automation
Distributed Tracing
What is it: Distributed Call Tree
Which challenges does it solve:
Distributed system behavior, root
cause analysis
Watch out for: Automation,
grouping, overlay networks
Service Service
Service
Service
Service
Service
A "simple" example
Latency, 99th percentile:
120ms
What's an application?
Latency derived from
distributed tracing data
Navigate traces and metrics
for root cause analysis
Link additional data like
continuous profiles
Attach application
logs to slow calls
Organizational Challenges
● Continuous delivery / continuous
deployment
● New Roles: DevOps, SRE
● New requirements and
responsibilities for existing roles
○ Software developers own the
infrastructure deeper than ever
before
Summary
● Docker enables dynamic distributed scalable polyglot applications
● Requires new approach to monitoring
○ Automate as much as possible
○ Use new data like metrics and distributed traces
● Adapt your teams and roles to the new world
Fabian Stäber, Instana
@fstabr

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Monitoring in a Microservices World

  • 1. Fabian Stäber, Instana Monitoring in a Microservices World @fstabr
  • 2. Docker's Impact on Software Architecture Application Service Service Service Service Service Service
  • 3. Impact on Monitoring Some things become easier ● Health checks are commodity ● Runtime platforms provide information on service orchestration Some things become harder ● Dynamically changing environments ● Health checks are not sufficient to represent the application state
  • 4. Metrics What is it: Time Series Data Which challenges does it solve: SLO-based alerting, root cause analysis Watch out for: Aggregate horizontally, relate vertically, automation
  • 5. Distributed Tracing What is it: Distributed Call Tree Which challenges does it solve: Distributed system behavior, root cause analysis Watch out for: Automation, grouping, overlay networks Service Service Service Service Service Service
  • 6. A "simple" example Latency, 99th percentile: 120ms What's an application? Latency derived from distributed tracing data Navigate traces and metrics for root cause analysis Link additional data like continuous profiles Attach application logs to slow calls
  • 7. Organizational Challenges ● Continuous delivery / continuous deployment ● New Roles: DevOps, SRE ● New requirements and responsibilities for existing roles ○ Software developers own the infrastructure deeper than ever before
  • 8. Summary ● Docker enables dynamic distributed scalable polyglot applications ● Requires new approach to monitoring ○ Automate as much as possible ○ Use new data like metrics and distributed traces ● Adapt your teams and roles to the new world