Prometheus seems to be unstoppable and has come to be the monitoring solution of choice for time series data in microservices. This talk compares the pros and cons of running it yourself vs having it run for you in the cloud. I prepared these slides for the meet up talk https://www.meetup.com/Cloud-Native-Computing-Berlin/events/235329061/

1. Prometheus – on-site vs in-the-cloud
David Kaltschmidt @davkals

3. What is Prometheus
Timeseries DB
Borgmon (Google) for the rest of us
Open source
Cloud Native Foundation

4. Like Uber, but for Uber
Graphite + StatsD
stats.api-server.tracks.post.500 -> 93
InfluxDB
OpenTSDB

5. Get started
$ docker run -p 9090:9090 prom/prometheus
time="2016-11-16T00:51:06Z" level=info msg="Starting prometheus (version=1.2.1,
branch=master, revision=dd66f2e94b2b662804b9aa1b6a50587b990ba8b7)" source="main.go:75"
time="2016-11-16T00:51:06Z" level=info msg="Build context (go=go1.7.1,
user=root@fd9b0daff6bd, date=20161010-15:58:23)" source="main.go:76"
time="2016-11-16T00:51:06Z" level=info msg="Loading configuration file /etc/prometheus/
prometheus.yml" source="main.go:247"
time="2016-11-16T00:51:07Z" level=info msg="Loading series map and head chunks..."
source="storage.go:354"
time="2016-11-16T00:51:07Z" level=info msg="0 series loaded." source="storage.go:359"
time="2016-11-16T00:51:07Z" level=warning msg="No AlertManagers configured, not dispatching
any alerts" source="notifier.go:176"

6. Kubernetes
AWS
…
Bigger setup

7. Prometheus and Kubernetes: A Perfect Match
Prometheus and Kubernetes: Deploying
https://www.weave.works/blog/
Prometheus and Kubernetes: Monitoring Your Applications
Prometheus and Kubernetes: Monitoring Your Infrastructure

8. Dimensional data
stats.api-server.tracks.post.500 -> 93
VS
api_server_http_requests_total{
job=“apiserver”, instance=“<sample1>”,
method=“POST”, handler=“/tracks",
status=“500"} -> 34
https://prometheus.io/docs/practices/naming/

9. PromQL
http_requests_total{job="apiserver",
handler=“/api/comments"}[5m]
sum(rate(http_requests_total[5m])) by (job)
topk(3,
sum(
rate(instance_cpu_time_ns[5m])
) by (app, proc)
)

10. UI: Expression browser

11. UI: Grafana

12. Where does my data live?
Indexes on LevelDB
One file per time-series on disk

13. Prometheus in the cloud
API compatible
Keep query language
Throughput on par
https://github.com/weaveworks/cortex

14. Retriever
scraping
your jobs
Your DC
Weave Cloud
Frontend,
Authenticator
Distributor
Ingester
Distributor…
IngesterIngester
DynamoDB S3

15. Re-use your local Prometheus
remote_write:
url: https://cloud.weave.works/api/prom/push
basic_auth:
password: <redacted>
Retriever

16. DEMO
https://cloud.weave.works

17. Why not just run my own
Well, you kind of are.
But Cloud…

18. Reuse your Grafana
• Type: Prometheus
• Url: https://cloud.weave.works/api/prom
• Access: Direct
• Http Auth: Basic Auth
• User: user (this is ignored, but must be non-empty)
• Password: (the same one your retrieval agent uses)

19. Wanted: Feedback for UI
Decide on Grafana integration
vs
something else

20. We’re hiring!
London BerlinSan Francisco

21. David Kaltschmidt @davkals
Sign up at https://cloud.weave.works/
$ kubectl -n kube-system apply -f
‘https://cloud.weave.works/k8s/cortex.yaml?t=...'
https://github.com/weaveworks/cortex
Try It Out!
Questions?