2. Get started at https://aws.amazon.com/elasticsearch-service/
Amazon Search Services
Amazon
CloudSearch
Amazon
Elasticsearch
Service
3. Get started at https://aws.amazon.com/elasticsearch-service/
Open Source Distributed Index
Managed Service using Elasticsearch and Kibana
Fully managed; Zero admin
Highly Available and Reliable
RESTful API for easy integration
Amazon
Elasticsearch
Service
4. Get started at https://aws.amazon.com/elasticsearch-service/
Amazon Elasticsearch Service Leading Use Cases
Log Analytics &
Operational Monitoring
• Monitor the performance of
applications, web servers, and
hardware
• Easy to use, powerful data
visualization tools to detect
issues quickly
• Dig into logs in an intuitive,
fine-grained way
• Kibana provides fast, easy
visualization
Search
• Application or website provides
search capabilities over diverse
documents
• Tasked with making this knowledge
base searchable and accessible
• Text matching, faceting, filtering,
fuzzy search, auto complete,
highlighting, and other search
features
• Query API to support application
search
5. Leading enterprises trust Amazon Elasticsearch
Service for their search and analytics applications
Media &
Entertainment
Online
Services
Technology Other
6. Get started at https://aws.amazon.com/elasticsearch-service/
Adobe Developer Platform (Adobe I/O)
P R O B L E M
• Cost effective monitor
for XL amount of log
data
• Over 200,000 API calls
per second at peak -
destinations, response
times, bandwidth
• Integrate seamlessly
with other components
of AWS eco-system.
SOLU TION
• Log data is routed with
Amazon Kinesis to
Amazon Elasticsearch
Service, then
displayed using AES
Kibana
• Adobe team can easily
see traffic patterns and
error rates, quickly
identifying anomalies
and potential
challenges
B E N E F I T S
• Management and
operational simplicity
• Flexibility to try out
different cluster config
during dev and test
Amazon
Kinesis
Streams
Spark Streaming
Amazon
Elasticsearch
Service
Data
Sources
1
7. Get started at https://aws.amazon.com/elasticsearch-service/
McGraw Hill Education
P R O B L E M
• Supporting a wide catalog
across multiple services in
multiple jurisdictions
• Over 100 million learning
events each month
• Tests, quizzes, learning
modules begun / completed
/ abandoned
S O L U T I O N
• Search and analyze test
results, student/teacher
interaction, teacher
effectiveness, student
progress
• Analytics of applications
and infrastructure are now
integrated to understand
operations in real time
B E N E F I T S
• Confidence to scale
throughout the school year.
From 0 to 32TB in 9 months
• Focus on their business, not
their infrastructure
8. Get started at https://aws.amazon.com/elasticsearch-service/
Easy to Use
Deploy a production-ready Elasticsearch
cluster in minutes
Simplifies time-consuming management
tasks such as software patching, failure
recovery, backups, and monitoring
Open
Get direct access to the Elasticsearch
open-source API
Fully compatible with the open source
Elasticsearch API, for all code and
applications
Secure
Secure Elasticsearch clusters with AWS
Identity and Access Management (IAM)
policies with fine-grained access control
access for users and endpoints
Automatically applies security patches
without disruption, keeping Elasticsearch
environments secure
Available
Provides high availability using Zone
Awareness, which replicates data between
two Availability Zones
Monitors the health of clusters and
automatically replaces failed nodes,
without service disruption
AWS Integrated
Integrates with Amazon Kinesis Firehose,
AWS IOT, and Amazon CloudWatch Logs for
seamless data ingestion
AWS CloudTrail for auditing, AWS Identity
and Access Management (IAM) for
security, and AWS CloudFormation for
cloud orchestration
Scalable
Scale clusters from a single node up to 20
nodes
Configure clusters to meet performance
requirements by selecting from a range of
instance types and storage options
including SSD-powered EBS volumes
Amazon Elasticsearch Service Benefits
9. Get started at https://aws.amazon.com/elasticsearch-service/
Easy to use and scalable
AWS SDK
AWS CLI
AWS
CloudFormation
Elastic Load
Balancing
AWS IAM
Amazon
CloudWatch
AWS CloudTrail
10. Get started at https://aws.amazon.com/elasticsearch-service/
Open
• Drop-in replacement
• Zero-change, no-risk
migration to or from open
source Elasticsearch
11. Get started at https://aws.amazon.com/elasticsearch-service/
Secure
• Control access based on
originating IP or Principal
• Mix policies to provide
application access and
Kibana access
• Use IAM roles to provide
access for other services
12. Get started at https://aws.amazon.com/elasticsearch-service/
Available
Amazon Elasticsearch Service cluster
1
3
Instance 1
2
1 2
Instance 2
3
2
1
Instance 3
Availability Zone 1 Availability Zone 2
2
1
Instance 4
3
3
15. Get started at https://aws.amazon.com/elasticsearch-service/
Firehose delivery architecture with
transformations
intermediate
Amazon S3
bucket
backup S3 bucket
source records
data source
source records
Amazon Elasticsearch
Service
Firehose
delivery stream
transformed
records transformed
records
transformation failure
delivery failure
16. Get started at https://aws.amazon.com/elasticsearch-service/
Repository Search
• File metadata and
possibly file contents
for traditional search
• Lambda to keep the
repository current
• Good for up to ~60TB
of metadata/source
data (current limits)
See also: Indexing S3 Metadata blog post by Amit Sharma
18. Get started at https://aws.amazon.com/elasticsearch-service/
What to do with a terabyte of logs?
19. Get started at https://aws.amazon.com/elasticsearch-service/
Visualize it with Kibana 5!
20. Get started at https://aws.amazon.com/elasticsearch-service/
Scripting with Amazon Elasticsearch Service
Scripting is fully supported using the Painless language.
With scripts you can
• Change the precedence of search results
• Delete index fields by query
• Modify search results to return specific fields
• Alter elements in a field
Painless is explicitly designed for Elasticsearch and is both
performant and secure.
21. Get started at https://aws.amazon.com/elasticsearch-service/
Ingest Pipelines and Processors
When you index documents, you can specify a pipeline.
The pipeline can have a series of processors that
pre-process the data before indexing.
Twenty processors are available, some are simple:
{ "append":
{ "field": "field1"
"value": ["item2", "item3", "item4"] } }
Others are more complex, like the Grok processor for
regex with aliased expressions.
23. Get started at https://aws.amazon.com/elasticsearch-service/
Shrink and Rollover
Shrink an index to a single shard:
POST source_index/_shrink/target_index
Very useful for time-series indexes once ingestion is done!
Rollover an index based on number of documents:
POST logs_index/_rollover
{ "conditions": {"max_docs": 100000 } }
24. Get started at https://aws.amazon.com/elasticsearch-service/
Supported Elasticsearch 5 Plugins
• Smart Chinese Analysis plugin
• Stempel Polish Analysis plugin
• Ingest Processor Attachment plugin
• Ingest Geoip Processor Plugin
• Ingest User Agent Processor plugin
• Mapper Murmur3 Plugin
中文
Polskie
25. Get started at https://aws.amazon.com/elasticsearch-service/
Testing Ingest Performance
• Load generator
• m4.large, single process, single thread
• Amazon Elasticsearch Service
• 1 instance, 1 primary, no replicas, EBS gp2 storage
• Data
• 1.8m apache web log lines, comprising 196 MB
• _bulk API calls with 10K lines per call
• Monitoring data gathered from load generator process
and from the Amazon Elasticsearch Service domain
26. Get started at https://aws.amazon.com/elasticsearch-service/
Amazon Elasticsearch
Service with v2.3 Engine
Instance Avg Index Docs/sec
m3.medium 3.93 ms 2811
m3.2xlarge 11.83 ms 3966
r3.large 8.87 ms 3932
r3.8xlarge 10.58 ms 4404
I2.2xlarge 11.2 ms 5305
Ingest Performance Test Results
Instance Avg Index Docs/sec
m3.medium 3.12 ms 3629
m3.2xlarge 11.1 ms 5816
r3.large 8.76 ms 7221
r3.8xlarge 9.59 ms 7726
I2.2xlarge 10.3 ms 9676
Amazon Elasticsearch
Service with v5.1 Engine
Up to 82% more documents per second!
27. Get started at https://aws.amazon.com/elasticsearch-service/
Migrating from v2.3 to v5.1
The easy way:
1. Create a new Amazon Elasticsearch Service v5.1 cluster
2. Snapshot your v2.3 indexes
3. Restore the indexes to the v5.1 cluster
… but this won’t get most of the benefits of v5.1
There are many breaking changes in v5, documented at
https://www.elastic.co/guide/en/elasticsearch/reference/5.1/breaking-changes.html
28. Get started at https://aws.amazon.com/elasticsearch-service/
Three Things to Remember
• Amazon Elasticsearch Service is a drop-in replacement
for new and existing Elasticsearch workloads
• Deploy, manage, and scale Elasticsearch more easily in
the AWS cloud
• Support for Elasticsearch 5.1 brings scripting, additional
plugins and additional performance to Amazon
Elasticsearch Service
29. Get started at https://aws.amazon.com/elasticsearch-service/
Find out more:
https://aws.amazon.com/elasticsearch-service/
AWS Centralized Logging:
https://aws.amazon.com/answers/logging/centralized-logging/
Elasticsearch at the AWS Database Blog:
https://aws.amazon.com/blogs/database/category/elasticsearch/
Or ask your Solutions Architect!
Amazon
Elasticsearch
Service
Hinweis der Redaktion
200k peak during testing
10k rps on average spike to 200k
3 billion records in ES right now
No lock in
Instance: Which instance type for the cluster
Avg Index: The millis that the cluster reports spending on indexing, divided by the number of docs indexed in that time period
Docs/s: The kibana average of the document delta across the test as reported by cluster APIs.
Time: rounded to the nearest 30s.