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Optimizing Your Container Environment: Monitor Your Pets and Cattle
Real-time Log Management and Analytics Built for the Cloud.
ServicesApplications
OperatingSystem
VirtualMachine
Hypervisor Machine
Containers are changing how software development and operations teams design, build and monitor systems. These containers - or “pets” and “cattle” - need consistent monitoring and optimization.
Containerization of environments regularly results in systems with large numbers of dynamic and ephemeral instances that autoscale to meet demands on system load.
GROWTH AND POPULARITY Docker Container Downloads
(in Millions)
December 2014 April 2015 June 2015
4xin six months
SECOND-MOST POPULAR OPEN SOURCE PROJECT
(Survey of more than 550 respondents conducted by Linux.com and The New Stack)
Fewer respondents said they contribute to Docker but it’s the project everyone said they want to
contribute to more.
0
50
100
150
200
250
300
350
400
KVMDockerOpenstack
Google's data centers and
applications are 100% container-
based — spinning up 2 billion
containers per week
The potential of container technology to unseat VMs threatens the market for products sold by Citrix, VMware, Dell, Hewlett-Packard, IBM and Microsoft.
$4B MARKET THREATENED
Amazon, Google, IBM, and Microsoft have all partnered with Docker and are building their own container-based solutions.
“Why is it such a big deal? Because it means genuine application
portability -- using lightweight packages instead of full VMs.“
Eric Knorr, InfoWorld
CONTAINER TYPES: PETS AND CATTLE
PetsContainers With Very Short Life Spans
• Require great attention
• Given actual names
• Unique and procured individually
• Sad if they die
• Common pets include MSSQLdatabases, SharePoint, legacy apps, and Unix systems
CONTAINER TYPES: PETS AND CATTLE
CattleContainers With Long Uptimes
• Look after themselves
• Don't have specific names - given numbers
• Managed in herds
• Can be simply replaced if they die
• Standardized
CONTAINER PROBLEMS + SOLUTIONSContainer Health: 6 Questions DevOps Need to Answer
How do you monitor your container’s resource utilization?
How do you get insight into the current and historical state of clusters?
How do you preempt container performance issues?
Do you know when a container dies or gets paused?
Are you able to see if a container went down in retrospect when troubleshooting?
How easy is it for you to capture CPU, network and memory utilization per container?
A specialized Docker container for log collection and monitoring
Centralized logging
capabilities for Docker
environments
Container-level resource usage
statistics such as CPU, Memory, Network, etc.
Monitoring Tools: Out-of-the-box saved searches, tags, (real-time) alerts and data visualizations
Preventive Tools:
Proactive alerts
CONTAINER CARE SOLVED: MONITORING
LOGGING ON DOCKER
The Logentries container is a dedicated logging container that runs alongside your existing Docker containers. Using Logentries you can collect and monitor container-level stats and logs from within each container and easily scale to collect logs from new containers without requiring additional configuration.
• Automatically collect, monitor and analyze container-level logs and stats
• Automatically scale your container environment without configuration
• Easily correlate container-level logs, stats, Docker API events, and host metrics
+
Sources: • InfoWorld, “9 key enterprise tech trends for 2015 and beyond” • WSJ, “Software Firms Scramble to Jump Into Containers” • James Thomason, “2015 Year of the Whale and other disruptive trends in IT” • SiliconAngle, “Open source: Docker’s secret sauce | #DockerCon” • Docker, “About Docker”
Additional Resources: • The State of Logging on Docker •
https://blog.logentries.com/2014/03/the-state-of-logging-on-docker/ • What is the Docker Stats API •
https://blog.logentries.com/2015/02/what-is-the-docker-stats-api/ • Docker Log Management Using Fluentd •
http://jasonwilder.com/blog/2014/03/17/docker-log-management-using-fluentd/
• How to Centralize Logs from CoreOS Clusters • https://blog.logentries.com/2015/03/how-to-centralize-logs-from-coreos-clusters/