The document discusses monitoring containerized applications and microservices using Amazon CloudWatch Container Insights and Amazon CloudWatch Anomaly Detection. Container Insights provides fully managed monitoring of compute capacity, ad hoc analytics, and application tracing. Anomaly Detection enables self-learning of normal metric behavior, accounts for seasonality, and provides dynamic alerting of abnormal system behavior. Both services help provide observability of containerized applications.

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Monitoring with container insights & anomaly
detection
Greg Eppel
Global Solutions Architect
CloudWatch & X-Ray
AWS
S V C 3 0 8

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Topics
Monitoring
Observability
Container insights
Anomaly detection
Demo

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Reactive monitoring
Blissful ignorance
Confusion
Stress
False hope
Desperation
Enlightenment

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Monitoring must evolve
Monolithic to
microservice
Short-lived
resources
^Devices
^Data
Faster release
velocity

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Metrics
What: Numeric representation of data measured over
intervals of time
Why: Useful for identifying trends, mathematical
modeling, and prediction

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Logs
What: Immutable, timestamped record of discrete
events that happened over time
Why: Useful for uncovering emergent and
unpredictable behavior

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Traces
What: Representation of a series of related distributed
events that encode the end-to-end request flow
through a distributed system
Why: Provides visibility into both the path traversed by
a request as well as the structure of a request

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Observability
This is the goal

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Observability is the goal
These are the tools

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Amazon CloudWatch
Container Insights (Preview)
Enables you to monitor, isolate, and diagnose your containerized
applications and microservices environments
1. Fully managed automated summary/analysis of compute capacity
2. Ad hoc analytics capability
3. Application tracing observability

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Amazon CloudWatch
Anomaly Detection (Preview)
Enables developers, operators and systems engineers to
automate, accelerate, and improve the detection and alerting of
abnormal system and application behavior.
1. Self-learning metric behavior
2. Aware of seasonality
3. Dynamic alarming

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Container Insights: Takeaways
1. Fully managed automated summary/analysis of compute capacity
2. Ad hoc analytics capability
3. Application tracing observability

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Anomaly detection: Takeaways
1. Self-learning metric behavior
2. Aware of seasonality
3. Dynamic alarming

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http://aws.amazon.com/cloudwatch/getting-started

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Thank you!
S U M M I T © 2019, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Greg Eppel
geppel@amazon.com