the way to distributed tracing · 2018. 11. 5. · what is this talk about understand the concepts...
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DISTRIBUTED TRACINGTHE WAY TO
WHO ARE WE?
▸ Frank Pfleger@frankpflegerfrank@trasier.com
▸ Lukasz Pielak@lukaszpielaklukasz@trasier.com
WHAT IS THIS TALK ABOUT
▸ Understand the concepts
▸ The way to Distributed Tracing
▸ Beyond Distributed Tracing
LOGGING
LOGGING
PULL REQUEST
REVIEWER CHANGES
AUTHOR CHANGES
LOGGING
LOGGING
Source: https://www.baeldung.com/mdc-in-log4j-2-logback
LOGGING
Source: https://www.baeldung.com/mdc-in-log4j-2-logback
LOGGING
LOGGING - MDC
Source: https://www.baeldung.com/mdc-in-log4j-2-logback
TRACEABILITY OF SOFTWARE
MONOLITHIC ARCHITECTURE
TRACEABILITY OF SOFTWARE
MONOLITHIC ARCHITECTURE▸ Components tightly coupled
▸ Difficult maintenance
▸ Long time to build
▸ Big bang release
TRACEABILITY OF SOFTWARE
MICROSERVICES
TRACEABILITY OF SOFTWARE
▸ Difficult error detection (multiple hosts / pods)
▸ Increased latency
▸ Service versioning
▸ MDC thread scoped
MICROSERVICES
TRACEABILITY OF SOFTWARE
MDC CONTEXT PROPAGATION
TK TK TK
TKTK
TK
TK
TK TK
DISTRIBUTED TRACING
DISTRIBUTED TRACING
BRINGING EVENTS IN
CAUSAL ORDER IN
DISTRIBUTED ENVIRONMENT
DISTRIBUTED TRACING
Span TracerTrace Context(span id, trace id)
Trace
DEMO
DISTRIBUTED TRACING
WHY DISTRIBUTED TRACING?
▸ Latency visualization
▸ Service dependency visualization
▸ Hidden architecture revealed
▸ Error analysis
▸ Infrastructure check
▸ Version check
▸ Trace Context
▸ Clock skew / synchronization
▸ Performance and stability
▸ Data ingestion and storage
▸ Data retention
▸ GDPA
DISTRIBUTED TRACING
PROBLEMS OF DISTRIBUTED TRACING
SERVICE B
SERVICE A
Latency measurement points
Host 1
Host 2
CORRELATE LOG ENTRIES
TRACE COMMUNICATION BETWEEN SERVICES
USE DISTRIBUTED TRACING
USE TRACE-ID IN THE MDC
THE WAY TO DISTRIBUTED TRACING
BOOKING PAYMENT
USER INTERFACE Live Reporting(Performance monitoring)
OFFER
DATASTORE BigData Store(High-Performance / Indexing)
WEBS
HOP
Context propagation(Service Instrumentation)
Common language(Specification / Trace-Context)
COLLECTOR Decoupled Reporter(Asynchronous collecting)
TOOLING LANDSCAPE
DEMO
APM - PROVIDERSSUPPORT FOR OPENTRACING ENABLES
BEYONDDISTRIBUTED TRACING
BEYOND DISTRIBUTED TRACING
BUSINESS TRACING EASY BUG TRIAGE
REPLAY CONVERSATIONS MOCK SERVICES
BUSINESS ANALYSIS PREDICTIVE ANALYSIS
BUSINESS TRACING
CONVERSATION AS A WHOLE
BUSINESS TRACING
CONVERSATION AS A WHOLE
BUSINESS TRACING
CONVERSATION AS A WHOLE
DEMO
THE POINT IS, YOU CAN NEVER BE TOO GREEDY.
Donald Trump
BUSINESS TRACING
BEYOND DISTRIBUTED TRACING
BUSINESS TRACING EASY BUG TRIAGE
REPLAY CONVERSATIONS MOCK SERVICES
BUSINESS ANALYSIS PREDICTIVE ANALYSIS
BEYOND DISTRIBUTED TRACING
BUSINESS TRACING EASY BUG TRIAGE
REPLAY CONVERSATIONS MOCK SERVICES
BUSINESS ANALYSIS PREDICTIVE ANALYSIS
BEYOND DISTRIBUTED TRACING
REPLAY CONVERSATIONS
BOOKING PAYMENT
OFFER
WEBS
HOP
DATASTORE
BEYOND DISTRIBUTED TRACING
REPLAY CONVERSATIONS
BOOKING PAYMENT
OFFER
WEBS
HOP
DATASTORE
REPLAY-ENGINE
BEYOND DISTRIBUTED TRACING
BUSINESS TRACING EASY BUG TRIAGE
REPLAY CONVERSATIONS MOCK SERVICES
BUSINESS ANALYSIS PREDICTIVE ANALYSIS
PAYMENT
BEYOND DISTRIBUTED TRACING
MOCK SERVICES
BOOKING
OFFER
WEBS
HOP
PAYMENT-MOCK
DATASTORE
BEYOND DISTRIBUTED TRACING
BUSINESS TRACING EASY BUG TRIAGE
REPLAY CONVERSATIONS MOCK SERVICES
BUSINESS ANALYSIS PREDICTIVE ANALYSIS
BEYOND DISTRIBUTED TRACING
BUSINESS ANALYSIS
BOOKING PAYMENT
OFFER
WEBS
HOP
DATASTORE
ANALYZER
USER INTERFACE
BEYOND DISTRIBUTED TRACING
BUSINESS TRACING EASY BUG TRIAGE
REPLAY CONVERSATIONS MOCK SERVICES
BUSINESS ANALYSIS PREDICTIVE ANALYSIS
TRY EXISTING SOLUTIONS REUSABLE TRACE CONTEXT
CONSIDER THE VALUE OF YOUR DATA
Q & MAYBE A ;-)
▸ Lukasz Pielak@lukaszpielaklukasz@trasier.com
▸ Frank Pfleger@frankpflegerfrank@trasier.com
▸ OpenTracing
▸ https://opentracing.io
▸ OpenCensus
▸ https://opencensus.io
▸ Zipkin
▸ https://zipkin.io
▸ Jaeger
▸ https://jaegertracing.io
▸ Trasier
▸ https://trasier.com
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