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Scaling Prometheus to a Million Machines
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Scaling Prometheus to a Million Machines
1.
Breaking Prometheus Scaling prometheus to
a million machines
2.
About Me • Technical
Lead Digital Ocean • Microservices in GO Book • Lives in Bangkok
3.
Dark Days • Graphite •
InfluxDB • OpenTSDB (*sigh*)
4.
Manual Prometheus
5.
Manual Issues • Lots
of Prometheus servers • Mismatched versions • New machines = update config • Missing matches
6.
Consul + Prometheus
= Peanut butter + Jelly
7.
8.
Datacenter wide 10,000s of
nodes Stage 2:
9.
Prometheus Per Region Prometheus Grafana Prometheus
Prometheus Prometheus Prometheus Prometheus
10.
I/O Problems • Modify
retention windows • Drop metrics from node_exporter • Larger and larger machines
11.
Tuning options storage.local.retention storage.local.memory-chunks storage.local.max-chunks-to-persist storage.local.checkpoint-interval storage.local.checkpoint-dirty-series-limit
12.
Sharding
13.
14.
rate(node_cpu{instance=“server12345.digitalocean.com:9100”}[2m]) Shard on red Prometheus
Proxy
15.
Alert Manager
16.
Shard Problems • Shard
redistribution • Over provisioning • Data loss • Limited data windows
17.
Kafka Bus
18.
19.
Million VMs
20.
Digital Ocean Agent • Installable
Metrics Agent • Authenticated Push Gateway • “Reverse node exporter”
21.
Query Api • Customer
facing API • GRPC / Json • Authenticated per customer • Prometheus queries
22.
https://github.com/digitalocean/vulcan Introducing Vulcan
23.
Vulcan • Prometheus Api •
Cassandra storage • Kafka incoming • Standard Scrapers
24.
Cassandra Store
25.
Downsampling • In memory
shared promethues • Driven from data in kafka • Reusable for Alerting
26.
Downsampling / Alerting
27.
Future • New Scrape
Sources (Kafka) • Per series expiry TTLs • Plugin Storage Model (In Memory) • Alerting High Availability
28.
Questions? We’re Hiring! Matthew Campbell hyper@hyperworks.nu @kanwisher github.com/mattkanwisher
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