Monitoring ECS and Dynamic Infrastructure

Containers and other forms of dynamic infrastructure can prove challenging to monitor.  How do you define normal, when your infrastructure is intentionally in motion and change from minute to minute? Join us as we discuss proven strategies for monitoring your containerized infrastructure on AWS and ECS.

Transcript

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Ilan Rabinovitch Monitoring in Motion Monitoring Containers and ECS
2. $ finger ilan@datadog [datadoghq.com] Name: Ilan Rabinovitch Role: Director, Technical Community 
 Interests: * Open Source * Large scale web operations * Monitoring and Metrics * Planning FL/OSS and DevOps Events (SCALE, TXLF, DevOpsDays, and more…)
3. • SaaS based infrastructure monitoring • Focus on modern infrastructure • Cloud, Containers, Micro Services • Processing nearly a trillion data points per day • Intelligent Alerting Datadog Overview
4. Operating Systems, Cloud Providers (AWS), Containers, Web Servers, Datastores, Caches, Queues and more... Monitor Everything
6. $ cat ~/.plan 1. Introduction: Why Containerize? 2. How: Collecting Docker and ECS Metrics 3. Finding the Signal: How do we know what to monitor? 4. Practice: Fitting it all together on ECS
7. Why Containerization?
8. More info at: www.datadoghq.com/docker-adoption/
9. Why Containers? • Avoid Dependency Hell
10. Why Containers? • Avoid Dependency Hell • Single Artifact Deployments
12. Source: http://bit.ly/1SvvbuP Why Containers?
13. Source: http://bit.ly/1RQRsXW
14. Source: http://bit.ly/1qFylWK • Avoid Dependency Hell • Single Artifact Deployments • Quick, Low Cost Provisioning Why Containers?
15. Source: Datadog
16. ECS - Elastic Container Services • Automatically manages and schedules your containers as ‘tasks’
 • Ensures tasks are always running based on your parameters • Integration with load balancing and routing via ELB.
17. Monitoring in Motion How do you define and monitor for normal when everything is changing around you? Between ECS and Containers you now have: • Containers moving between hosts. • Changing ports • and other changes underneath your feet.
18. Adding up the numbers… Docker Status API: 220+ Metrics per container
19. Adding up the numbers… Docker Status API: 223+ Metrics per container ECS CloudWatch Metrics: 4 per cluster + 2 per service
20. Adding up the numbers… Docker Status API: 223+ Metrics per container ECS CloudWatch Metrics: 4 per cluster + 2 per service OS Metrics: 100~ per instance
21. Docker Status API: 223+ Metrics per container ECS CloudWatch Metrics: 4 per cluster + 2 per service OS Metrics: 100~ per instance App Metrics: 50~ Adding up the numbers…
23. Adding up the numbers… OS Metrics: 100~ per instance Docker Status API: 223+ Metrics per container ECS CloudWatch Metrics: 4 per cluster + 2 per service App Metrics: 50~ Metrics Overload!
25. Host Centric
26. Service Centric
27. Avoiding Gaps
29. Tags All the Way Down
30. Moving from statements to tag based queries “Monitor all containers running image web in region us-west-2 across all availability zones that use more than 1.5x the average memory on c3.xlarge”
31. Monitoring 101
34. Collecting data is cheap;
 not having it when you need it can be expensive
35. Instrument all the things!
37. Monitoring 101: tl;dr Edition More Details at: http://www.datadoghq.com/blog/monitoring-101-alerting/
38. tl;dr - Data Types
39. Examples: NGINX - Metrics Work Metrics:
 Requests Per Second • Dropped Connections • Request Time • Error Rates Resource Metrics: • Disk I/O • Memory • CPU • Queue Length
40. Examples: NGINX - Events • Configuration Change • Code Deployment • Service Started / Stopped • etc
41. When to let a sleeping engineer lie?
42. When to alert?
43. Recurse until you find root cause
44. Getting at the Metrics • ECS vs Docker • Work Metrics vs Resource Metrics
45. Resource Metrics Utilization: • CPU (user + system) • memory • i/o • network traffic Saturation • throttling • swap Error • Network Errors 
 (receive vs transmit)
46. Docker and ECS Events • Starting / Stopping Containers • Auto-scaled Underlying Instances
48. CloudWatch and ECS Resources CPUReservation MemoryReservation CPUUtilization MemoryUtilization
49. How do we get at the upper layers?
50. Getting at the Metrics CPU METRICS MEMORY METRICS I/O METRICS NETWORK METRICS pseudo-files Yes Yes Some Yes, in 1.6.1+ stats command Basic Basic No Basic API Yes Yes Some Yes
51. Pseudo-files • Provide visibility into container metrics via the file system. • Generally under: 
 /cgroup/<resource>/docker/$CONTAINER_ID/ 
 or
 /sys/fs/cgroup/<resource>/docker/$CONTAINER_ID/

52. Pseudo-files: CPU Metrics $ cat /sys/fs/cgroup/cpuacct/docker/$CONTAINER_ID/cpuacct.stat > user 2451 # time spent running processes since boot > system 966 # time spent executing system calls since boot $ cat /sys/fs/cgroup/cpu/docker/$CONTAINER_ID/cpu.stat > nr_periods 565 # Number of enforcement intervals that have elapsed > nr_throttled 559 # Number of times the group has been throttled > throttled_time 12119585961 # Total time that members of the group were throttled (12.12 seconds) Pseudo-files: CPU Throttling
53. Docker API • Detailed streaming metrics as JSON HTTP socket
 $ curl -v --unix-socket /var/run/docker.sock http://localhost/containers/ 28d7a95f468e/stats

54. STATS Command # Usage: docker stats CONTAINER [CONTAINER...] $ docker stats $CONTAINER_ID CONTAINER CPU % MEM USAGE/LIMIT MEM % NET I/O BLOCK I/O ecb37227ac84 0.12% 71.53 MiB/490 MiB 14.60% 900.2 MB/275.5 MB 266.8 MB/872.7 MB
55. Side Car Containers
56. Agents and Daemons • Ideally we’d want to schedule an agent or daemon on each node via ECS Tasks.
 • Current Work Arounds: 1. Bake it into your image. 2. Install on each host at provision time. 3. Automate with User Scripts and Launch Configs
57. Grant Privileges via IAM $ aws iam create-role \
 --role-name ecs-monitoring \
 --assume-role-policy-document file://trust.policy $ aws iam put-role-policy --role-name ecs-monitoring
 --policy-name ecs-monitoring-policy
 --policy-document file://ecs.policy $ aws iam create-instance-profile 
 --instance-profile-name ECSNode $ aws iam add-role-to-instance-profile \ --instance-profile-name ECSNode \
 --role-name ecs-monitoring
58. Create A User Script
59. Auto-Scale! $ aws autoscaling create-launch-configuration 
 --launch-configuration MyECSCluster --key-name my-key 
 --image-id AMI_ID --instance-type INSTANCE_TYPE 
 --user-data file://launch-script.txt --iam-instance-profile IAM_ROLE
60. Aren’t we still missing a layer?
61. Open Questions • Where is my container running? • What is the capacity of my cluster? • What port is my app running on? • What’s the total throughput of my app? • What’s its response time per tag? (app, version, region) • What’s the distribution of 5xx error per container?
62. Service Discovery Docker API ECS & CloudWatch Monitoring Agent Container A O A O Containers List & Metadata Additional Metadata (Tags, etc) Config Backend Integration Configurations Host Level Metrics
63. Custom Metrics • Instrument custom applications
 • You know your key transactions best.
 • Use async protocols like Etys’ STATSD
64. Source: http://bit.ly/1NoW6aj
65. Thank You