Learn about the strategic feature areas of the Elastic Stack—Elasticsearch, a data engine like no other, and Kibana, the window into the Elastic Stack.
The session will cover:
Bringing data into the Elastic Stack
Storing data
Analyzing data
Acting on data
UiPath Community: Communication Mining from Zero to Hero
Why Elastic for log analytics, APM, and security
1. ElasticON Solution Series -
Why Elastic?
Sajjad Ahmed, Elasticsearch Product Lead
Vijay Doshi, Kibana Product Lead
Transforming Data into Insights
2. Safe Harbor
Statement
This presentation includes forward-looking
statements that are subject to risks and
uncertainties. Actual results may differ materially
as a result of various risk factors included in the
reports on the Forms 10K, 10Q, and 8K, and in
other filings we make with the SEC from time to
time. Elastic undertakes no obligation to update
any of these forward-looking statements.
4. Use cases emerged
Log analytics
Infrastructure metrics
Service uptime
Threat hunting
Website search
Cross company
resource search
eCommerce search
Incident Response
Real user monitoring
5. Search Observe Protect
Use cases emerged
Log analytics
Application performance monitoring
Infrastructure metrics
Service uptime
Threat hunting
Endpoint protection
Website search
In-app search
Cross company
resource search
eCommerce search
customer support
portal
Synthetic monitoring
Threat prevention
Threat Detection
Incident Response
Response hunting
Security monitoring
Business Analytics
Real user monitoring
Network Traffic Mapping
6. Log analytics
Application performance monitoring
Infrastructure metrics
Service uptime
Threat hunting
Endpoint protection
Website search
In-app search
Cross company
resource search
eCommerce search
customer support
portal
Synthetic monitoring
Threat prevention
Threat Detection
Incident Response
Response hunting
Security monitoring
Business Analytics
Real user monitoring
Elastic Enterprise Search Elastic Security
Elastic Observability
Network Traffic Mapping
Solutions created
35. Schema on write
Speed, Scale,
Relevance
Schema on read
Flexibility
Data you understand
and use
Best For
New Data Sources
Handling Changes
Enable New Workflows
Good For
36.
37. Runtime Fields Use cases
Get a jump start on your data
• Spend less time setting up the index and
more time searching.
• Extract and calculate new fields on the fly.
• Convert to indexed fields as needed for
optimal performance.
38. Quickly adapt to changes in your data
Runtime Fields Use cases
• Data is constantly evolving.
• Changes can break your index mappings.
• Dynamically create runtime fields without
reindexing.
• Eliminate the need to fix mappings and
reindex your data.
39. Give current fields a fresh coat of paint
Runtime Fields Use cases
• Find new ways to analyze already
indexed data by creating a runtime
field using any combination of
existing fields.
• Empower end users to perform their
own analyses without overriding
others or requiring admin support.
40. Fix errors quickly reducing downtime to production
Runtime Fields Use cases
• Mistakes made in index mappings are no
longer costly.
• Shadow incorrectly indexed fields with
runtime fields.
• Eliminate the need to fix mappings and
reindex your data.