The document discusses tactics for optimizing costs on Elasticsearch Service. It outlines various strategies like utilizing optimized deployment templates, adjusting availability zones, implementing data rollups, setting up ILM policies to rollover data and reduce shards, applying ILM and snapshot management policies, and preparing for an annual commitment by optimizing deployment size based on use case. Implementing these different optimization techniques could help reduce costs by up to half depending on the deployment and use case.

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Cost Optimization on
Elasticsearch Service
Tom Lawler - Team Lead, Customer Success

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Forward-Looking Statements

3. Agenda
• Understanding Cloud Costs
• Cost Optimization in Elasticsearch service
• Preparing for Annual

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Understanding
Cloud Costs

5. Hourly Rate
Summary & Architecture
• Hourly rate
– Based Cloud Provider,
region, template, zones
and size
– Free tier for Kibana, ML,
APM

6. Billing & Account
Activity
Overview of Account Activity
• Upgrade Subscription
• Update Billing Information
• Download Invoices
• See Month to date activity

7. Invoice
Reviewing Infra costs and
DTS costs
• DTS costs
– Data out
– Internode
– Snapshot Storage
– Snapshot API
• Infrastructure

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Cost Optimization in
Elasticsearch Service

9. Elasticsearch Service
Optimization
Tactics for Cost Optimization
Deployment Infrastructure
Utilising deployment templates for use case
optimisation
Availability Zones
Increase of decrease availability zones.
Roll ups
Summarize data into high-level time buckets
Setting up ILM policies
Rollover data and reduce shards
Index Management
Apply ILM policies
Snapshot Management
Optimise snapshot frequency & retention
depending on use case

10. Deployment
Infrastructure
Tactics for Cost Optimization
What is it?
Templates with varying infrastructure set ups
across providers.
When should I use it?
Depending on the nature of your deployment.
How much can I save?
It could help you up to half the costs
associated with a deployment if you optimise
the your setup.

11. Hot-warm + ILM
What is it?
A hot-warm cluster lets you store
infrequently accessed data (warm) on
cheaper hardware while frequently queried
data (hot) resides on performant hardware.
When should I use it?
Great for time-series data like logs, metrics,
and traces.
How much can I save?
It depends on how much data you decide to
retain in the hot tier vs sending to the warm
tier.
Tactics for Cost Optimization

12. Data Rollups
What is it?
Let’s you summarize data into high-level
time buckets, letting you save on storage
costs.
When should I use it?
Great for data that doesn’t require low-level
granularity over time like metrics.
How much can I save?
It depends on how much data you decide to
summarize.
Tactics for Cost Optimization

13. Tactics for Cost Optimization
Availability Zones
What is it?
The ability to adjust the number of zones
your data i available in in case of failure.
When should I use it?
In production at least 2 zones should be
used. For dev/test 1 is sufficient.
How much can I save?
Each additional zone is a replica of the
primary zones so 2 zones = 2x the cost.

14. ILM Policy
What is it?
A policy that defines the parameters by
which you can roll over data. Data can be
moved to warm or to delete.
When should I use it?
They should be used when your data
retention policy dictates.
How much can I save?
Optimising data retention could allow you to
scale your deployments up and down. It can
also help with DTS costs.
Tactics for Cost Optimization

15. Index Management
Tactics for Cost Optimization
What is it?
An easy to use UI for managing indexes
within Kibana.
When should I use it?
When you need to delete indices, apply ILM
policies or update mappings.
How much can I save?
Optimising data retention could allow you to
scale your deployments up and down. It can
also help with DTS costs.

16. • Create Snapshot Policy
• Apply to desired Indices
• Nominate external repository
Snapshot
Management
Tactics for Cost Optimization
What is it?
A Kibana UI which allows you to create and
manage your snapshots.
When should I use it?
When you use case dictates.
How much can I save?
Depending on use case you can save on
storage costs by managing frequency and
retention.

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Preparing for Annual

18. Preparing for annual
Steps to take as you consider an annual commitment
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Use use case and
data retention to
define deployment
type
Identify which
features you need
and select
subscription level
Optimize
deployment size
using Elastic
guidance
Size the
deployment after
optimisation
5
Test in production
with peace of
mind

19. Get in touch!

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Thank You!