Cloud Native Night August 2016, Munich: Talk by Julius Volz (@juliusvolz, Co-founder at Prometheus). Join our Meetup: www.meetup.com/cloud-native-muc Abstract: This talk is on monitoring dynamic cloud environments with Prometheus.

1. Prometheus
Cloud Monitoring with Prometheus
Julius Volz, August 2016

2. Prometheus
Monitoring system and TSDB:
● instrumentation
● metrics collection and storage
● querying
● alerting
● dashboarding / graphing / trending
Made for dynamic cloud environments!
What is Prometheus?
https://prometheus.io

3. Prometheus
● raw log / event collection
● request tracing
● “magic” anomaly detection
● durable long-term storage
● automatic horizontal scaling
● user / auth management
What does Prometheus NOT do?

4. Prometheus
● Started in 2012 at SoundCloud by Matt and Julius
● Inspired by Google’s monitoring tools
● Motivation
○ needed to monitor dynamic cloud environment
○ unsatisfying data models, querying, and efficiency in
existing approaches
Origin

5. Prometheus
Architecture

6. Prometheus
Four main improvements
1. Multi-dimensional data model (like OpenTSDB).
2. Powerful query language (the same for exploring, graphing, alerting).
3. Efficient data collection (yes, it's pull, not push).
4. Operational simplicity (unlike OpenTSDB).

7. Prometheus
Multi-dimensional data model
api_http_requests_total{method="GET", endpoint="/api/tracks", status="200"} 2034834

8. Prometheus
Powerful query language
topk(3, sum(rate(bazooka_instance_cpu_time_seconds_total[5m])) by (app, proc))
sort_desc(sum(bazooka_instance_memory_limit_bytes -
bazooka_instance_memory_usage_bytes) by (app, proc))

9. Prometheus
Efficient data collection
1000s of targets.
800,000 samples per second.
Millions of time series.
On a single monitoring server.
Running many servers is easy, too…
Pull, not push.

10. Prometheus
Operational simplicity
● written in Go
● static binary
● not clustered

11. Prometheus
Expression browser

12. Prometheus
Built-in graphing

13. Prometheus
Grafana Support

14. Prometheus
Challenges in Dynamic Environments
● on-demand VMs (EC2, Azure, GCP, ...)
● dynamically scheduled service instances
(Kubernetes, Docker Swarm, ...)
● microservices
⇨ many services, dynamic hosts, and ports
How to make sense of this mess?

15. Prometheus
Monitoring Dynamic Environments
● Use service discovery
○ ...to know what should be there
○ ...to pull metrics
○ ...to add metadata to metrics
● Focus on services, not machines

16. Prometheus
Architecture

17. Prometheus
...with Prometheus
● configure service in Prometheus
○ automatic discovery and scraping
● map host, port, service etc. into
dimensions
● query language enables:
○ service-level aggregation
○ instance-level drill-down
○ precise alerting

18. Prometheus
Prometheus <3 Kubernetes
● Borg -> Kubernetes
● Borgmon -> Prometheus
● both use labels
● Prometheus supports Kubernetes SD
● Kubernetes has Prometheus metrics

19. Prometheus
Demo?

20. Prometheus
Thanks!
Q&A