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Managing Quality of Service for
Containerized Microservice Applications
• Michael Krumm, Product Manager
• 1.5 yrs, Sales Engineer, AppDynamics
• 1 yr, Software Consultant, BMC Software
• 2.5 yrs, Department Manager and Head of IT,
Hospital



• Pete Abrams, Founder & COO
• 2 yrs, VP Innovation, AppDynamics
• 4 yrs, VP Channel Sales, AppDynamics
• 10 yrs, sales and marketing at Sun Microsystems
• 5 yrs, VP Marketing, Netcontinuum
Speaker Bios
From: How Microservices Have a Macro Affect on APM, June, 2016
The Challenge of MicroServices for APM
Instana is a Gartner Cool Vendor 2016: 

Availability and Performance
“Microservice architectures bring new complexity, in terms
of scale and dynamism, to assessing the status of the
application environment.”
Cameron Haight, Chief of Research, Infrastructure and Operations at Gartner, Inc.
• written in different languages

• maintained independently

• deployed automatically

• terminated after use 

• invoked on demand

• scaled dynamically
No longer rigid, hard wired blocks of functionality
but rather Business Processes made from the interactions of
the multitude of (micro)services
What are MicroService Applications?
USER
Applications are:
Modern systems are built with resilience.
The new QoS challenge is the dynamism
and interactions, 

not so much the piece parts.
Cluster
?
The Microservice Technology Stack
?
ServicesHost Container Middleware
Host Container Middleware Cluster
CPU high Load to high GC Overhead (JVM) Re-Balancing
Alert
?
Traditional Monitoring Creates Too Many Alarms
Code Exceptions/Errors
?
Services
An issue with a component probably does not
affect the Quality of (micro)Service
Alert Alert Alert ???
The Challenge of monitoring MicroServices based Applications
Cluster
Host
Container
Middleware
Service USER
?
?
• deep, diverse technology stacks
• complex, unpredictable service interactions
• constantly changing everything
• scale, even small systems have 100s of parts
GOAL:
Quality of (micro)Service Management:
In Production,
With Minimal Impact,
and Zero Configuration
A modern application is the
usage patterns of microservices
Monitoring those services is
required to manage the
application
USER
Monitoring With Instana
Management by Incident
Incidents report all correlated
changes and issues
Quality of the (micro) Services
‣ Incidents are raised when quality
is impacted
‣ Quality is defined by KPI’s:
‣ Throughput
‣ Latency
‣ Error Rate
‣ Saturation
‣ KPI health is determined by
machine learning
Curated Expert Knowledge =
component health understanding
Component Health Reported within Incidents
The Dynamic Graph
Search Product Trace
Index A
ES Cluster
Spring Boot
JVM
Process
Container
Host
ES Node
JVM
Process
Container
Host
ES Node
JVM
Process
Container
Host
ES Node
JVM
Process
Container
Host
ES Node
JVM
Process
Container
Host
Zone
Zone
App A
A model to correlate
relationships and
interaction
One Agent 

per Host
One Sensor per
active component
Trace messages
between
microservices
Sensor Repository
Agent
Knowledge Engine
Elasticsearch
sensor
Tomcat sensor
JVM sensor
Linux sensor
Auto Discovery / Auto Update
Communication
Local

Sensor Memory
&
Contextual 

Compression
Immediate, Automatic and Continuous Discovery of Components and Dependencies
1 SECOND RESOLUTION
Others
Instana collects 1 second resolution data. Data viewed as 1 minute running average.
Aggregation = loss of information | Dynamic applications demand high resolution data
Demo Application „The Shop“
• Online Shop with simulated traffic
• total of 22 Services
• Languages
• Java, PHP, Node.js
• Components
• Docker
• Marathon
• Springboot
• Cassandra, Elasticsearch, MySQL, MongoDB
• RabbitMQ, Kafka, Redis, Memcached
• nginx, HAProxy
• and more…
A day with Instana
• Ops is notified about an Incident
• Identify and understand the issue
• Work on remediation
Demo
• Runtime behavior and architecture in production
• Identify code improvement opportunities
• Troubleshoot performance and errors
• Understand deployment impact in seconds
Value to Developers
• Full Stack visibility and navigation - infrastructure to
application to trace and back
• Automatic and intelligent Incident management
• Real time insights and comparison
Value to Operations
• Understand service usage
• Manage service performance
• Identify improvements
• Prioritize based on impact
Value to Product Owner
Q & A
Data Ingestion &

Health Calculation
Sensor Data
Realtime Stream
Processing
Incident
Detection
Alerting
Quality of Service
Dependency
Health
Metrics
3D Map
Dynamic Knowledge
Graph
API & CLI
Configuration
Instana Processing Pipeline
3 seconds from sensing to alerting
Sensor Availability
Sensors:
Supported Technologies
Tracing:
Data Retention
• Metrics Data Retention
‣ 1 second data granularity is stored for 10 minutes
- 5 seconds for 24 hours
- 60 seconds for 1 month
- 300 seconds/5 minutes for 3 months
- 3600 seconds/1 hours forever
• Graph/Configuration Data Retention
‣ each change of the Graph is kept forever
• Events Data Retention
‣ each event is kept forever
Instana, Inc. Proprietary and Confidential 27
Instana 

Knowledge

EngineSensor Data
On-Prem Instana Service
3D Map
On-Prem Deployment
Usage Billing Data
Instana
Monitoring
User
Management
Updates
Customer’s Data Center
Instana Cloud
Authentication + HTTPS
Ad

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Managing Quality of Service for Containerized Microservice Applications

  • 1. Managing Quality of Service for Containerized Microservice Applications
  • 2. • Michael Krumm, Product Manager • 1.5 yrs, Sales Engineer, AppDynamics • 1 yr, Software Consultant, BMC Software • 2.5 yrs, Department Manager and Head of IT, Hospital
 
 • Pete Abrams, Founder & COO • 2 yrs, VP Innovation, AppDynamics • 4 yrs, VP Channel Sales, AppDynamics • 10 yrs, sales and marketing at Sun Microsystems • 5 yrs, VP Marketing, Netcontinuum Speaker Bios
  • 3. From: How Microservices Have a Macro Affect on APM, June, 2016 The Challenge of MicroServices for APM Instana is a Gartner Cool Vendor 2016: 
 Availability and Performance “Microservice architectures bring new complexity, in terms of scale and dynamism, to assessing the status of the application environment.” Cameron Haight, Chief of Research, Infrastructure and Operations at Gartner, Inc.
  • 4. • written in different languages
 • maintained independently
 • deployed automatically
 • terminated after use 
 • invoked on demand
 • scaled dynamically No longer rigid, hard wired blocks of functionality but rather Business Processes made from the interactions of the multitude of (micro)services What are MicroService Applications? USER Applications are:
  • 5. Modern systems are built with resilience. The new QoS challenge is the dynamism and interactions, 
 not so much the piece parts.
  • 6. Cluster ? The Microservice Technology Stack ? ServicesHost Container Middleware
  • 7. Host Container Middleware Cluster CPU high Load to high GC Overhead (JVM) Re-Balancing Alert ? Traditional Monitoring Creates Too Many Alarms Code Exceptions/Errors ? Services An issue with a component probably does not affect the Quality of (micro)Service Alert Alert Alert ???
  • 8. The Challenge of monitoring MicroServices based Applications Cluster Host Container Middleware Service USER ? ? • deep, diverse technology stacks • complex, unpredictable service interactions • constantly changing everything • scale, even small systems have 100s of parts
  • 9. GOAL: Quality of (micro)Service Management: In Production, With Minimal Impact, and Zero Configuration
  • 10. A modern application is the usage patterns of microservices Monitoring those services is required to manage the application USER Monitoring With Instana
  • 11. Management by Incident Incidents report all correlated changes and issues
  • 12. Quality of the (micro) Services ‣ Incidents are raised when quality is impacted ‣ Quality is defined by KPI’s: ‣ Throughput ‣ Latency ‣ Error Rate ‣ Saturation ‣ KPI health is determined by machine learning
  • 13. Curated Expert Knowledge = component health understanding Component Health Reported within Incidents
  • 14. The Dynamic Graph Search Product Trace Index A ES Cluster Spring Boot JVM Process Container Host ES Node JVM Process Container Host ES Node JVM Process Container Host ES Node JVM Process Container Host ES Node JVM Process Container Host Zone Zone App A A model to correlate relationships and interaction
  • 15. One Agent 
 per Host One Sensor per active component Trace messages between microservices Sensor Repository Agent Knowledge Engine Elasticsearch sensor Tomcat sensor JVM sensor Linux sensor Auto Discovery / Auto Update Communication Local
 Sensor Memory & Contextual 
 Compression Immediate, Automatic and Continuous Discovery of Components and Dependencies
  • 16. 1 SECOND RESOLUTION Others Instana collects 1 second resolution data. Data viewed as 1 minute running average. Aggregation = loss of information | Dynamic applications demand high resolution data
  • 17. Demo Application „The Shop“ • Online Shop with simulated traffic • total of 22 Services • Languages • Java, PHP, Node.js • Components • Docker • Marathon • Springboot • Cassandra, Elasticsearch, MySQL, MongoDB • RabbitMQ, Kafka, Redis, Memcached • nginx, HAProxy • and more…
  • 18. A day with Instana • Ops is notified about an Incident • Identify and understand the issue • Work on remediation
  • 19. Demo
  • 20. • Runtime behavior and architecture in production • Identify code improvement opportunities • Troubleshoot performance and errors • Understand deployment impact in seconds Value to Developers
  • 21. • Full Stack visibility and navigation - infrastructure to application to trace and back • Automatic and intelligent Incident management • Real time insights and comparison Value to Operations
  • 22. • Understand service usage • Manage service performance • Identify improvements • Prioritize based on impact Value to Product Owner
  • 23. Q & A
  • 24. Data Ingestion &
 Health Calculation Sensor Data Realtime Stream Processing Incident Detection Alerting Quality of Service Dependency Health Metrics 3D Map Dynamic Knowledge Graph API & CLI Configuration Instana Processing Pipeline 3 seconds from sensing to alerting
  • 26. Data Retention • Metrics Data Retention ‣ 1 second data granularity is stored for 10 minutes - 5 seconds for 24 hours - 60 seconds for 1 month - 300 seconds/5 minutes for 3 months - 3600 seconds/1 hours forever • Graph/Configuration Data Retention ‣ each change of the Graph is kept forever • Events Data Retention ‣ each event is kept forever
  • 27. Instana, Inc. Proprietary and Confidential 27 Instana 
 Knowledge
 EngineSensor Data On-Prem Instana Service 3D Map On-Prem Deployment Usage Billing Data Instana Monitoring User Management Updates Customer’s Data Center Instana Cloud Authentication + HTTPS
  翻译: