Managing Quality of Service for Containerized Microservice Applications

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Information about Managing Quality of Service for Containerized Microservice Applications

Published on November 17, 2016

Author: JulesPierreLouis

Source: slideshare.net

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

25. Sensor Availability Sensors: Supported Technologies Tracing:

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

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