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What Goes Wrong with Language Definitions and How to Improve the Situation
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Microsoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdf
WSO2CON2024 - It's time to go Platformless
WSO2CON2024 - It's time to go Platformless
Metrics: where and how
1.
Metrics: where and
how graphite-oriented story
2.
• Vsevolod Polyakov •
Platform Engineer at Grammarly
3.
Graphite All whisper-based systems
4.
Default graphite architecture
5.
what? • RRD-like (gram.ly/gfsx) •
so.it.is.my.metric → /so/it/is/my/metric.wsp • Fixed retention (by namepattern) • Fixed size (actually no)
6.
Retention and size •
1s:1d → 1 036 828 bytes • 10s:10d → 1 036 828 bytes • 1s:365d → 378 432 028 bytes (1 TB ~ 3 000) • 10s:365d → 37 843 228 bytes (1 TB ~ 30 000) whisper calc
7.
Retention and size •
10s:30d,1m:120d,10m:365d → 4 564 864 bytes • 240 864 metrics in 1 TB • aggregation: average, sum, min, max, and last. • can be assign per metric
8.
How • terraform (https://www.terraform.io/) •
docker (https://www.docker.com/) • ansible (https://www.ansible.com/) • rocker (https://github.com/grammarly/rocker) • rocker-compose (https://github.com/grammarly/rocker-compose)
9.
Default graphite architecture
10.
carbon-cache.py • single-core • many
options in config file • default link
11.
architecture carbon-cache.py
12.
Start load testing •
m4.xlarge instance (4 CPU, 16 GB ram, 256 GB disk EBS gp2) • retentions = 1s:1d • MAX_CACHE_SIZE, MAX_UPDATES_PER_SECOND, MAX_CR • defaults • almost 1.5h to get limit :(
13.
carbon-cache.py cache size
→ 75k reqs
14.
15.
16.
results • 75 000
reqs max • 60 000 reqs flagman speed • IO :(
17.
Try to tune! •
WHISPER_SPARSE_CREATE = true (don’t allocate space on creation) non-linear IO load. • CACHE_WRITE_STRATEGY = sorted (default)
18.
cache size 1k
→ 195k reqs
19.
results • 120 000
reqs flagman speed • cache flush problem :(
20.
Try to tune! •
CACHE_WRITE_STRATEGY = max will give a strong flush preference to frequently updated metrics and will also reduce random file-io.
21.
from 1k to
150k
22.
results • 90 000
reqs flagman speed • cache flush problem :(
23.
Try to tune! •
CACHE_WRITE_STRATEGY = naive just flush. Better with random IO.
24.
from 45k to
135k
25.
results • 120 000
reqs flagman speed • still CPU
26.
sorted max naive
27.
• Maybe it’s
IO EBS limitation? → 512 GB disk. • No.
28.
go-carbon • multi-core single
daemon • written in golang • not many options to tune :( link
29.
Start load testing •
m4.xlarge instance (4 CPU, 16 GB ram, 256 GB disk EBS gp2) • retentions = 1s:1d • max-size = 0 • max-updates-per-second = 0 • almost 1h to get limit :(
30.
1k → 130k
reqs ~3k/min
31.
32.
results • 120 000
reqs flagman speed • but it’s without sparse. • try to implement
33.
try to tune! remaining
:= whisper.Size() - whisper.MetadataSize() whisper.file.Seek(int64(remaining-1), 0) whisper.file.Write([]byte{0}) chunkSize := 16384 zeros := make([]byte, chunkSize) for remaining > chunkSize { // if _, err = whisper.file.Write(zeros); err != nil { // return nil, err // } remaining -= chunkSize } if _, err = whisper.file.Write(zeros[:remaining]); err != nil { return nil, err }
34.
180 000 reqs
!
35.
36.
try to tune! •
max update operation = 1500
37.
results • TLDR 210
000 - 240 000 reqs flagman speed • 31 000 000 cache size!
38.
39.
try to tune! •
max update operation = 0 • input-buffer = 400 000
40.
results • 270 000
reqs flagman speed • 10-20 million req cache size!
41.
42.
try to tune! •
vm.dirty_background_ratio=40 • vm.dirty_ratio=60
43.
300 000 reqs
44.
results • 300 000
reqs flagman speed • 180k+ reqs ±without cache
45.
Re:Lays
46.
Default graphite architecture
47.
arch forward
48.
arch namedregexp
49.
arch hash
50.
arch hash replicafactor:
2
51.
carbon-relay.py • twisted based •
native
52.
Start load testing •
c4.xlarge instance (4 CPU, 7.5 GB ram) • ~1 Gb lan • default parameters • hashing • 10 connections
53.
WTF!
54.
carbon-relay-ng • golang-based • web-panel •
live-updates • aggregators • spooling link
55.
<150 000 reqs
56.
carbon-c-relay • written in
C • advanced cluster management
57.
from 100 000
to 1 600 000 reqs
58.
1 400 000
flagman speed. Or not?
59.
So… go-carbon + carbon-c-relay
= ♡
60.
BTW. influx, 130k
reqs on cluster
61.
influx
62.
openTSDB single instance +
hbase cluster = upto 150k reqs
63.
ALSO • zipper: • https://github.com/grobian/carbonserver •
https://github.com/grobian/carbonwriter • https://github.com/dgryski/carbonzipper • https://github.com/dgryski/carbonapi • https://github.com/dgryski/carbonmem • https://github.com/jssjr/carbonate
64.
plans • Cyanite, retest •
newTS • openTSDB tuninig • zipper tuning
65.
feel free to
ask • Vsevolod Polyakov • ctrlok@gmail.com • skype: ctrlok1987 • github.com/ctrlok • twitter.com/ctrlok • slack: HangOps • Gitter: dev_ua/devops • skype: DevOps from Ukraine
Editor's Notes
последние 2,5 года работаю в граммарли разрабатываем крутые штуки, надо писать много метрик, бла бла бла
очень простой, все знают. Можно сказать стандарт индустрии для метрик
простота быстро читать, быстро писать
отключил логи, у амазона странные EBS
если кеш не сбрасывается то это плохо
скорость записи — большими кусками создаются файлы
линейная скорость чтения
отключил логи, у амазона странные EBS
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