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Serverless log analytics with Amazon Kinesis
SteamhausKELK ON AWS
Who am I?
Rob Greenwood
Tech Director @ Steamhaus
Logging is difficult
No centralised logging
User needs OS
knowledge
Distribution
Of keys
Enemy of
autoscaling
Log
rotation
Users download
logs unnecessarily
Doesn’t scale
To many servers
Slow to
find issues
Alerting

is hard
Sshing to
servers :(
SteamhausKELK ON AWS
ELK is awesomE
SteamhausKELK ON AWS
ELK on ec2
SteamhausKELK ON AWS
KELK on AWS
• Low maintenance - No ec2, Uses entirely AWS serverless technologies and services
• ALB, Cloudfront and Cloudtrail logs are ingested as well as EC2 logs
• Logs are archived in S3 for long term storage, and indexed in Elasticsearch for short term analytics
• Automated with Terraform
• Open source
Kinesis: buffering and delivering instance logs
Elasticsearch: Indexing and log storage
Lambda: processing and delivering S3 logs
Kibana: Search and analytics
SteamhausKELK ON AWS
How does it work?
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
SteamhausKELK ON AWS
Automation

code
Sample
Web Stack
VPC
ALB
EC2
Logging

Stack
Kinesis
Elasticsearch

Service
Lambda
S3
CloudfrontPython
Terraform
Do try this at home!
github.com/steamhaus/kelk-example
SteamhausKELK ON AWS
Callouts from the build
• It’s not production ready, built for readability
• Nailing iam and bucket policies can take a while!
• Testing lambda - create a test event in the UI
• Use Terraform, rinse and repeat
SteamhausKELK ON AWS
Any Questions..?
Thank you :)
Contact us



hello@steamhaus.co.uk

0161 820 2020

@steamhausmcr
Locate us
Fourways House

57 Hilton Street 

Manchester M1 2EJ

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Serverless log analytics with Amazon Kinesis