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Logs: Etsy’s Journey to Elastic Cloud
Migrating a legacy logging system to Elasticsearch service on Elastic Cloud
Stefano Vita <svita@etsy.com>
Agenda
1
Overview
2
Why?
3
How?
4
What did go well?
5
What we wish we knew?
Etsy is the global
marketplace for
unique and
creative goods. It’s
home to a universe
of special,
extraordinary
items, from unique
handcrafted pieces
to vintage
treasures.
Use cases of
Elasticsearch
• Convenient way to analyze log events
• Alerting
• Reporting
Logging numbers
8 Tb 70k 1.6k
Data Indexed
daily
Events
ingested every
second
Hosts sending
logs to the
pipeline
Etsy’s Decision to Migrate and Key
Considerations
Why migrate Etsy’s
logging system? ● Etsy was migrating entirely to
Google Cloud
● Elasticsearch is a complex system
that requires specialized knowledge
(especially in a logging use case)
● Elasticsearch 2.4 old and
unmaintained (EOL date was
02/2018)
A few reasons...
Why migrate Etsy’s
logging system? ● Alert fatigue for the whole team
● Maintaining Elasticsearch infra is
NOT observability
● Data center shutdown
A few reasons...
Key considerations
Migration must not impact
developers’ day-to-day
work
Business as usual
Migration must be time
efficient (data center
shutdown)
Time
Migration must reduce
infrastructure
management from the
team
Reduce TOIL
Process Options
1. Move all logs to Elasticsearch
service on Elastic Cloud
2. Move only critical logs to
Elasticsearch service on Elastic
Cloud
3. Move to our Google Cloud
infrastructure using ECE (Elastic
Cloud Enterprise)
4. Move to our Google Cloud
infrastructure manually
Alternatives
● Splunk
● Stackdriver
● <name logging solution>
Considerations:
● Too many intrusive solutions for
developers
● We didn’t want to throw away the
Elasticsearch knowledge we built
over the year
● Not enough time to prototype and
roll out a change that big
Challenges
● Move stack from 2.4 to 7.x
○ Logstash 2.x can’t talk to
Elasticsearch > 6.x
○ Identify and replace
deprecated settings in
Elasticsearch
○ Learn new features
○ Deploy changes safely
● Keep two systems running in
parallel for some time
Migration Timeline
03/2018
Gathered cluster size
and wrote first options
draft
Prod data
migrated;
Beta testing
started!
10/2019
Users fully migrated to the
new setup
01/202012/2018
Finalized
options
Contract
signed!
03/201902/2019
Prepared
migration
plan
06/2019
Dev data
migrated
Migration Successes
● Met our deadline
● Elastic support and consultants are helpful
● Happy developers
● Returning teams
Migration Successes
● Better observability into the stack
● Easier and safer management of indices and logstash pipelines
● Create, grow and shrink clusters is way easier
● Better isolation of the stream of data
What we wished we knew?
● Sizing an ES cluster is an art
○ One needs to consider volume AND throughput
● Noisy neighbors
● Support SLAs are not ideal when developing
○ Initial response on SEV3 is 1 business day
● Elastic Cloud is not just an endpoint
○ We are still responsible for indices management
What’s next?
● Improvement on the logging pipeline
● Analyze use cases and recommend best practices in Etsy
Thank You
Stefano Vita

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Migrating a legacy logging system: Etsy’s journey to Elastic Cloud

  • 1. Logs: Etsy’s Journey to Elastic Cloud Migrating a legacy logging system to Elasticsearch service on Elastic Cloud Stefano Vita <svita@etsy.com>
  • 2. Agenda 1 Overview 2 Why? 3 How? 4 What did go well? 5 What we wish we knew?
  • 3. Etsy is the global marketplace for unique and creative goods. It’s home to a universe of special, extraordinary items, from unique handcrafted pieces to vintage treasures.
  • 4. Use cases of Elasticsearch • Convenient way to analyze log events • Alerting • Reporting
  • 5. Logging numbers 8 Tb 70k 1.6k Data Indexed daily Events ingested every second Hosts sending logs to the pipeline
  • 6. Etsy’s Decision to Migrate and Key Considerations
  • 7. Why migrate Etsy’s logging system? ● Etsy was migrating entirely to Google Cloud ● Elasticsearch is a complex system that requires specialized knowledge (especially in a logging use case) ● Elasticsearch 2.4 old and unmaintained (EOL date was 02/2018) A few reasons...
  • 8. Why migrate Etsy’s logging system? ● Alert fatigue for the whole team ● Maintaining Elasticsearch infra is NOT observability ● Data center shutdown A few reasons...
  • 9. Key considerations Migration must not impact developers’ day-to-day work Business as usual Migration must be time efficient (data center shutdown) Time Migration must reduce infrastructure management from the team Reduce TOIL
  • 10. Process Options 1. Move all logs to Elasticsearch service on Elastic Cloud 2. Move only critical logs to Elasticsearch service on Elastic Cloud 3. Move to our Google Cloud infrastructure using ECE (Elastic Cloud Enterprise) 4. Move to our Google Cloud infrastructure manually
  • 11. Alternatives ● Splunk ● Stackdriver ● <name logging solution> Considerations: ● Too many intrusive solutions for developers ● We didn’t want to throw away the Elasticsearch knowledge we built over the year ● Not enough time to prototype and roll out a change that big
  • 12. Challenges ● Move stack from 2.4 to 7.x ○ Logstash 2.x can’t talk to Elasticsearch > 6.x ○ Identify and replace deprecated settings in Elasticsearch ○ Learn new features ○ Deploy changes safely ● Keep two systems running in parallel for some time
  • 13. Migration Timeline 03/2018 Gathered cluster size and wrote first options draft Prod data migrated; Beta testing started! 10/2019 Users fully migrated to the new setup 01/202012/2018 Finalized options Contract signed! 03/201902/2019 Prepared migration plan 06/2019 Dev data migrated
  • 14. Migration Successes ● Met our deadline ● Elastic support and consultants are helpful ● Happy developers ● Returning teams
  • 15. Migration Successes ● Better observability into the stack ● Easier and safer management of indices and logstash pipelines ● Create, grow and shrink clusters is way easier ● Better isolation of the stream of data
  • 16. What we wished we knew? ● Sizing an ES cluster is an art ○ One needs to consider volume AND throughput ● Noisy neighbors ● Support SLAs are not ideal when developing ○ Initial response on SEV3 is 1 business day ● Elastic Cloud is not just an endpoint ○ We are still responsible for indices management
  • 17. What’s next? ● Improvement on the logging pipeline ● Analyze use cases and recommend best practices in Etsy