From 85f1d7acffa516729014d863c7440e07a22573bc Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Mon, 26 Aug 2024 17:42:28 +0200 Subject: [PATCH 01/14] First draft of what is elasticsearch rewrite --- docs/reference/intro.asciidoc | 224 +++++++++------------------------- 1 file changed, 57 insertions(+), 167 deletions(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 3fc23b44994a7..4db507fb8ea6a 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -1,180 +1,74 @@ [[elasticsearch-intro]] == What is {es}? -_**You know, for search (and analysis)**_ -{es} is the distributed search and analytics engine at the heart of -the {stack}. {ls} and {beats} facilitate collecting, aggregating, and -enriching your data and storing it in {es}. {kib} enables you to -interactively explore, visualize, and share insights into your data and manage -and monitor the stack. {es} is where the indexing, search, and analysis -magic happens. +https://github.com/elastic/elasticsearch[{es}] is a distributed, RESTful search and analytics engine, scalable data store, and vector database built in Java on top of the Apache Lucene library. +Use {es} to search, index, store, and analyze data of all shapes and sizes in near real-time. -{es} provides near real-time search and analytics for all types of data. Whether you -have structured or unstructured text, numerical data, or geospatial data, -{es} can efficiently store and index it in a way that supports fast searches. -You can go far beyond simple data retrieval and aggregate information to discover -trends and patterns in your data. And as your data and query volume grows, the -distributed nature of {es} enables your deployment to grow seamlessly right -along with it. +[TIP] +==== +{es} has a lot of features. Explore the full list on the https://www.elastic.co/elasticsearch/features[product webpage^]. +==== -While not _every_ problem is a search problem, {es} offers speed and flexibility -to handle data in a wide variety of use cases: +{es} is the heart of the the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. -* Add a search box to an app or website -* Store and analyze logs, metrics, and security event data -* Use machine learning to automatically model the behavior of your data in real - time -* Use {es} as a vector database to create, store, and search vector embeddings -* Automate business workflows using {es} as a storage engine -* Manage, integrate, and analyze spatial information using {es} as a geographic - information system (GIS) -* Store and process genetic data using {es} as a bioinformatics research tool +{es} is used for a wide and growing range of use cases. Here are a few examples: -We’re continually amazed by the novel ways people use search. But whether -your use case is similar to one of these, or you're using {es} to tackle a new -problem, the way you work with your data, documents, and indices in {es} is -the same. +* *Monitor log and event data*. Store and analyze logs, metrics, and security event data for operational insights and SIEM. +* *Build search applications*. Add search capabilities to apps or websites and build enterprise search engines over your organization's internal data sources. +* *Vector database*. Store and search vectorized data, create vector embeddings with built-in and third-party NLP models. +* *Retrieval augmented generation (RAG)*. Use {es} as a retrieval engine to augment Generative AI models. +* *Application and security monitoring*. Monitor and analyze application performance and security data effectively. +* *Machine learning*. Use machine learning to automatically model the behavior of your data in real time. -[[documents-indices]] -=== Data in: documents and indices - -{es} is a distributed document store. Instead of storing information as rows of -columnar data, {es} stores complex data structures that have been serialized -as JSON documents. When you have multiple {es} nodes in a cluster, stored -documents are distributed across the cluster and can be accessed immediately -from any node. - -When a document is stored, it is indexed and fully searchable in <>--within 1 second. {es} uses a data structure called an -inverted index that supports very fast full-text searches. An inverted index -lists every unique word that appears in any document and identifies all of the -documents each word occurs in. - -An index can be thought of as an optimized collection of documents and each -document is a collection of fields, which are the key-value pairs that contain -your data. By default, {es} indexes all data in every field and each indexed -field has a dedicated, optimized data structure. For example, text fields are -stored in inverted indices, and numeric and geo fields are stored in BKD trees. -The ability to use the per-field data structures to assemble and return search -results is what makes {es} so fast. - -{es} also has the ability to be schema-less, which means that documents can be -indexed without explicitly specifying how to handle each of the different fields -that might occur in a document. When dynamic mapping is enabled, {es} -automatically detects and adds new fields to the index. This default -behavior makes it easy to index and explore your data--just start -indexing documents and {es} will detect and map booleans, floating point and -integer values, dates, and strings to the appropriate {es} data types. - -Ultimately, however, you know more about your data and how you want to use it -than {es} can. You can define rules to control dynamic mapping and explicitly -define mappings to take full control of how fields are stored and indexed. - -Defining your own mappings enables you to: - -* Distinguish between full-text string fields and exact value string fields -* Perform language-specific text analysis -* Optimize fields for partial matching -* Use custom date formats -* Use data types such as `geo_point` and `geo_shape` that cannot be automatically -detected - -It’s often useful to index the same field in different ways for different -purposes. For example, you might want to index a string field as both a text -field for full-text search and as a keyword field for sorting or aggregating -your data. Or, you might choose to use more than one language analyzer to -process the contents of a string field that contains user input. - -The analysis chain that is applied to a full-text field during indexing is also -used at search time. When you query a full-text field, the query text undergoes -the same analysis before the terms are looked up in the index. - -[[search-analyze]] -=== Information out: search and analyze - -While you can use {es} as a document store and retrieve documents and their -metadata, the real power comes from being able to easily access the full suite -of search capabilities built on the Apache Lucene search engine library. - -{es} provides a simple, coherent REST API for managing your cluster and indexing -and searching your data. For testing purposes, you can easily submit requests -directly from the command line or through the Developer Console in {kib}. From -your applications, you can use the -https://www.elastic.co/guide/en/elasticsearch/client/index.html[{es} client] -for your language of choice: Java, JavaScript, Go, .NET, PHP, Perl, Python -or Ruby. +This is just a sample of search, observability, and security use cases enabled by {es}. +Refer to our https://www.elastic.co/customers/success-stories[customer success stories] for concrete examples across a range of industry verticals. +// Link to demos, search labs chatbots [discrete] -[[search-data]] -==== Searching your data - -The {es} REST APIs support structured queries, full text queries, and complex -queries that combine the two. Structured queries are -similar to the types of queries you can construct in SQL. For example, you -could search the `gender` and `age` fields in your `employee` index and sort the -matches by the `hire_date` field. Full-text queries find all documents that -match the query string and return them sorted by _relevance_—how good a -match they are for your search terms. - -In addition to searching for individual terms, you can perform phrase searches, -similarity searches, and prefix searches, and get autocomplete suggestions. - -Have geospatial or other numerical data that you want to search? {es} indexes -non-textual data in optimized data structures that support -high-performance geo and numerical queries. - -You can access all of these search capabilities using {es}'s -comprehensive JSON-style query language (<>). You can also -construct <> to search and aggregate data -natively inside {es}, and JDBC and ODBC drivers enable a broad range of -third-party applications to interact with {es} via SQL. +[[elasticsearch-intro-elastic-stack]] +.What is the Elastic Stack? +******************************* +The Elastic Stack refers to the suite of products enabled by {es}: + +* https://www.elastic.co/guide/en/kibana/current/index.html[Kibana]. A UI for visualizing and exploring data in {es}. +* https://www.elastic.co/guide/en/logstash/current/introduction.html[Logstash]. A server-side data processing pipeline for ingesting and transforming data from multiple sources and indexing into {es}. +* https://www.elastic.co/guide/en/fleet/current/fleet-overview.html[Fleet and Elastic Agent.] Elastic Agents is a single, unified way to add monitoring for logs, metrics, and other types of data to a host. Fleet is a central place to configure and monitor your Elastic Agents. +* https://www.elastic.co/guide/en/beats/libbeat/current/beats-reference.html[Beats]. Lightweight data shippers for sending data from edge machines to {es}. +* https://www.elastic.co/guide/en/observability/current/apm.html[APM]. Monitor the performance of your applications. +* https://www.elastic.co/guide/en/elasticsearch/hadoop/current/float.html[{es} Hadoop]. Use {es} as a Hadoop input/output format. + +https://www.elastic.co/guide/en/starting-with-the-elasticsearch-platform-and-its-solutions/current/stack-components.html[Learn more about the Elastic Stack]. +******************************* +// TODO: Remove once we've moved Stack Overview to a subpage? [discrete] -[[analyze-data]] -==== Analyzing your data - -{es} aggregations enable you to build complex summaries of your data and gain -insight into key metrics, patterns, and trends. Instead of just finding the -proverbial “needle in a haystack”, aggregations enable you to answer questions -like: - -* How many needles are in the haystack? -* What is the average length of the needles? -* What is the median length of the needles, broken down by manufacturer? -* How many needles were added to the haystack in each of the last six months? - -You can also use aggregations to answer more subtle questions, such as: - -* What are your most popular needle manufacturers? -* Are there any unusual or anomalous clumps of needles? - -Because aggregations leverage the same data-structures used for search, they are -also very fast. This enables you to analyze and visualize your data in real time. -Your reports and dashboards update as your data changes so you can take action -based on the latest information. - -What’s more, aggregations operate alongside search requests. You can search -documents, filter results, and perform analytics at the same time, on the same -data, in a single request. And because aggregations are calculated in the -context of a particular search, you’re not just displaying a count of all -size 70 needles, you’re displaying a count of the size 70 needles -that match your users' search criteria--for example, all size 70 _non-stick -embroidery_ needles. +[[elasticsearch-intro-deploy]] +=== Deployment options + +To use {es}, you need a running instance of the {es} service. +You can deploy {es} in various ways: + +* https://elastic.co/guide/en/cloud/current/ec-getting-started.html[*Elastic Cloud*]. {es} is available as part of our hosted Elastic Stack offering, deployed in the cloud with your provider of choice. Sign up for a https://cloud.elastic.co/registration[14 day free trial]. +* https://elastic.co/guide/en/cloud-enterprise/current/Elastic-Cloud-Enterprise-overview.html[*Elastic Cloud Enterprise*]. Deploy Elastic Cloud on public or private clouds, virtual machines, or your own premises. +* https://elastic.co/guide/en/cloud-on-k8s/current/k8s-overview.html[*Elastic Cloud on Kubernetes*]. Deploy Elastic Cloud on Kubernetes. +* https://www.elastic.co/docs/current/serverless[*Elastic Cloud Serverless* (technical preview)]. Create serverless projects for autoscaled and fully-managed {es} deployments. Sign up for a https://cloud.elastic.co/serverless-registration[14 day free trial]. +* <>. Install, configure, and run {es} on your own premises. ++ +[TIP] +==== +If you just want to get started quickly with a minimal local setup, refer to <>. +==== [discrete] -[[more-features]] -===== But wait, there’s more - -Want to automate the analysis of your time series data? You can use -{ml-docs}/ml-ad-overview.html[machine learning] features to create accurate -baselines of normal behavior in your data and identify anomalous patterns. With -machine learning, you can detect: +[[elasticsearch-next-steps]] +=== Learn more -* Anomalies related to temporal deviations in values, counts, or frequencies -* Statistical rarity -* Unusual behaviors for a member of a population - -And the best part? You can do this without having to specify algorithms, models, -or other data science-related configurations. +* <>. A beginner's guide to deploying your first {es} instance, indexing data, and running queries. +* https://elastic.co/webinars/getting-started-elasticsearch[Webinar: Introduction to {es}]. Register for our live webinars to learn directly from {es} experts. +* https://www.elastic.co/guide/en/elasticsearch/client/index.html[Client libraries]. Choose from a variety of official and community-supported clients to work with {es} in your preferred programming language. +* Visit Elastic Search Labs for tutorials that AI-powered search using the latest {es} features. +** Follow our tutorial https://www.elastic.co/search-labs/tutorials/search-tutorial/welcome[to build a hybrid search solution in Python]. +** Check out the https://github.com/elastic/elasticsearch-labs?tab=readme-ov-file#elasticsearch-examples--apps[`elasticsearch-labs` repository] for a range of Python notebooks and apps for various use cases. [[scalability]] === Scalability and resilience: clusters, nodes, and shards @@ -255,13 +149,9 @@ create secondary clusters to serve read requests in geo-proximity to your users. the active leader index and handles all write requests. Indices replicated to secondary clusters are read-only followers. -[discrete] -[[admin]] -==== Care and feeding - As with any enterprise system, you need tools to secure, manage, and monitor your {es} clusters. Security, monitoring, and administrative features that are integrated into {es} enable you to use {kibana-ref}/introduction.html[{kib}] as a control center for managing a cluster. Features like <> and <> -help you intelligently manage your data over time. +help you intelligently manage your data over time. \ No newline at end of file From 1c2eb0d8837b88dc8009f6bbd5610bdc5fdbb309 Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Mon, 26 Aug 2024 17:49:02 +0200 Subject: [PATCH 02/14] Move clients link --- docs/reference/intro.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 4db507fb8ea6a..8e24d726b7baa 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -31,6 +31,7 @@ Refer to our https://www.elastic.co/customers/success-stories[customer success s The Elastic Stack refers to the suite of products enabled by {es}: * https://www.elastic.co/guide/en/kibana/current/index.html[Kibana]. A UI for visualizing and exploring data in {es}. +* https://www.elastic.co/guide/en/elasticsearch/client/index.html[Client libraries]. Work with {es} in your preferred programming language. * https://www.elastic.co/guide/en/logstash/current/introduction.html[Logstash]. A server-side data processing pipeline for ingesting and transforming data from multiple sources and indexing into {es}. * https://www.elastic.co/guide/en/fleet/current/fleet-overview.html[Fleet and Elastic Agent.] Elastic Agents is a single, unified way to add monitoring for logs, metrics, and other types of data to a host. Fleet is a central place to configure and monitor your Elastic Agents. * https://www.elastic.co/guide/en/beats/libbeat/current/beats-reference.html[Beats]. Lightweight data shippers for sending data from edge machines to {es}. @@ -65,7 +66,6 @@ If you just want to get started quickly with a minimal local setup, refer to <>. A beginner's guide to deploying your first {es} instance, indexing data, and running queries. * https://elastic.co/webinars/getting-started-elasticsearch[Webinar: Introduction to {es}]. Register for our live webinars to learn directly from {es} experts. -* https://www.elastic.co/guide/en/elasticsearch/client/index.html[Client libraries]. Choose from a variety of official and community-supported clients to work with {es} in your preferred programming language. * Visit Elastic Search Labs for tutorials that AI-powered search using the latest {es} features. ** Follow our tutorial https://www.elastic.co/search-labs/tutorials/search-tutorial/welcome[to build a hybrid search solution in Python]. ** Check out the https://github.com/elastic/elasticsearch-labs?tab=readme-ov-file#elasticsearch-examples--apps[`elasticsearch-labs` repository] for a range of Python notebooks and apps for various use cases. From 8b794e999e1786deb0610ff994255ea0676f7262 Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Mon, 26 Aug 2024 17:49:24 +0200 Subject: [PATCH 03/14] Remove backlinks --- docs/reference/modules/shard-ops.asciidoc | 2 +- docs/reference/search/search-your-data/near-real-time.asciidoc | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/reference/modules/shard-ops.asciidoc b/docs/reference/modules/shard-ops.asciidoc index c0e5ee6a220f0..fdca5c898a3f7 100644 --- a/docs/reference/modules/shard-ops.asciidoc +++ b/docs/reference/modules/shard-ops.asciidoc @@ -1,7 +1,7 @@ [[shard-allocation-relocation-recovery]] === Shard allocation, relocation, and recovery -Each <> in Elasticsearch is divided into one or more <>. +Each index in Elasticsearch is divided into one or more <>. Each document in an index belongs to a single shard. A cluster can contain multiple copies of a shard. Each shard has one distinguished shard copy called the _primary_, and zero or more non-primary copies called _replicas_. The primary shard copy serves as the main entry point for all indexing operations. The operations on the primary shard copy are then forwarded to its replicas. diff --git a/docs/reference/search/search-your-data/near-real-time.asciidoc b/docs/reference/search/search-your-data/near-real-time.asciidoc index 46a996c237c38..47618ecd9fd7a 100644 --- a/docs/reference/search/search-your-data/near-real-time.asciidoc +++ b/docs/reference/search/search-your-data/near-real-time.asciidoc @@ -2,7 +2,7 @@ [[near-real-time]] === Near real-time search -The overview of <> indicates that when a document is stored in {es}, it is indexed and fully searchable in _near real-time_--within 1 second. What defines near real-time search? +When a document is stored in {es}, it is indexed and fully searchable in _near real-time_--within 1 second. What defines near real-time search? Lucene, the Java libraries on which {es} is based, introduced the concept of per-segment search. A _segment_ is similar to an inverted index, but the word _index_ in Lucene means "a collection of segments plus a commit point". After a commit, a new segment is added to the commit point and the buffer is cleared. From f138524fcb52e41a749634191cc06fbe1266c5ab Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Mon, 26 Aug 2024 18:01:18 +0200 Subject: [PATCH 04/14] Make link text conform --- docs/reference/intro.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 8e24d726b7baa..d7cd72018da05 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -66,7 +66,7 @@ If you just want to get started quickly with a minimal local setup, refer to <>. A beginner's guide to deploying your first {es} instance, indexing data, and running queries. * https://elastic.co/webinars/getting-started-elasticsearch[Webinar: Introduction to {es}]. Register for our live webinars to learn directly from {es} experts. -* Visit Elastic Search Labs for tutorials that AI-powered search using the latest {es} features. +* https://www.elastic.co/search-labs[Elastic Search Labs]. Tutorials and blogs that explore AI-powered search using the latest {es} features. ** Follow our tutorial https://www.elastic.co/search-labs/tutorials/search-tutorial/welcome[to build a hybrid search solution in Python]. ** Check out the https://github.com/elastic/elasticsearch-labs?tab=readme-ov-file#elasticsearch-examples--apps[`elasticsearch-labs` repository] for a range of Python notebooks and apps for various use cases. From 3062ac98d98e4b18643a1e4e86ae8abd2b4512ab Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Mon, 26 Aug 2024 18:36:13 +0200 Subject: [PATCH 05/14] Add back indices page --- docs/reference/intro.asciidoc | 52 +++++++++++++++++++++++++++++++++++ 1 file changed, 52 insertions(+) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index d7cd72018da05..1aa3cc03d16b2 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -70,6 +70,58 @@ If you just want to get started quickly with a minimal local setup, refer to <>--within 1 second. {es} uses a data structure called an +inverted index that supports very fast full-text searches. An inverted index +lists every unique word that appears in any document and identifies all of the +documents each word occurs in. + +An index can be thought of as an optimized collection of documents and each +document is a collection of fields, which are the key-value pairs that contain +your data. By default, {es} indexes all data in every field and each indexed +field has a dedicated, optimized data structure. For example, text fields are +stored in inverted indices, and numeric and geo fields are stored in BKD trees. +The ability to use the per-field data structures to assemble and return search +results is what makes {es} so fast. + +{es} also has the ability to be schema-less, which means that documents can be +indexed without explicitly specifying how to handle each of the different fields +that might occur in a document. When dynamic mapping is enabled, {es} +automatically detects and adds new fields to the index. This default +behavior makes it easy to index and explore your data--just start +indexing documents and {es} will detect and map booleans, floating point and +integer values, dates, and strings to the appropriate {es} data types. + +You can define rules to control dynamic mapping and explicitly +define mappings to take full control of how fields are stored and indexed. + +Defining your own mappings enables you to: + +* Distinguish between full-text string fields and exact value string fields +* Perform language-specific text analysis +* Optimize fields for partial matching +* Use custom date formats +* Use data types such as `geo_point` and `geo_shape` that cannot be automatically +detected + +It’s often useful to index the same field in different ways for different +purposes. For example, you might want to index a string field as both a text +field for full-text search and as a keyword field for sorting or aggregating +your data. Or, you might choose to use more than one language analyzer to +process the contents of a string field that contains user input. + +The analysis chain that is applied to a full-text field during indexing is also +used at search time. When you query a full-text field, the query text undergoes +the same analysis before the terms are looked up in the index. + [[scalability]] === Scalability and resilience: clusters, nodes, and shards ++++ From 56cfb44370c2c89f7d952aff023e00ee88d5c8ff Mon Sep 17 00:00:00 2001 From: Liam Thompson <32779855+leemthompo@users.noreply.github.com> Date: Tue, 27 Aug 2024 10:33:14 +0200 Subject: [PATCH 06/14] Use attributes MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: István Zoltán Szabó --- docs/reference/intro.asciidoc | 4 ++-- docs/reference/modules/shard-ops.asciidoc | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 1aa3cc03d16b2..ce8ad57c6f065 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -9,7 +9,7 @@ Use {es} to search, index, store, and analyze data of all shapes and sizes in ne {es} has a lot of features. Explore the full list on the https://www.elastic.co/elasticsearch/features[product webpage^]. ==== -{es} is the heart of the the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. +{es} is the heart of the the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. {es} is used for a wide and growing range of use cases. Here are a few examples: @@ -18,7 +18,7 @@ Use {es} to search, index, store, and analyze data of all shapes and sizes in ne * *Vector database*. Store and search vectorized data, create vector embeddings with built-in and third-party NLP models. * *Retrieval augmented generation (RAG)*. Use {es} as a retrieval engine to augment Generative AI models. * *Application and security monitoring*. Monitor and analyze application performance and security data effectively. -* *Machine learning*. Use machine learning to automatically model the behavior of your data in real time. +* *Machine learning*. Use {ml} to automatically model the behavior of your data in real-time. This is just a sample of search, observability, and security use cases enabled by {es}. Refer to our https://www.elastic.co/customers/success-stories[customer success stories] for concrete examples across a range of industry verticals. diff --git a/docs/reference/modules/shard-ops.asciidoc b/docs/reference/modules/shard-ops.asciidoc index fdca5c898a3f7..7854633e8be9f 100644 --- a/docs/reference/modules/shard-ops.asciidoc +++ b/docs/reference/modules/shard-ops.asciidoc @@ -1,7 +1,7 @@ [[shard-allocation-relocation-recovery]] === Shard allocation, relocation, and recovery -Each index in Elasticsearch is divided into one or more <>. +Each index in {es} is divided into one or more <>. Each document in an index belongs to a single shard. A cluster can contain multiple copies of a shard. Each shard has one distinguished shard copy called the _primary_, and zero or more non-primary copies called _replicas_. The primary shard copy serves as the main entry point for all indexing operations. The operations on the primary shard copy are then forwarded to its replicas. From 69612acd91f91cb252a08c6687467855011c4dc7 Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 10:23:31 +0200 Subject: [PATCH 07/14] Review feedback, add back deleted pages, refactor --- docs/reference/intro.asciidoc | 132 +++++++++++++++++++++++++++------- 1 file changed, 108 insertions(+), 24 deletions(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 1aa3cc03d16b2..80042127a5f86 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -1,21 +1,22 @@ [[elasticsearch-intro]] == What is {es}? -https://github.com/elastic/elasticsearch[{es}] is a distributed, RESTful search and analytics engine, scalable data store, and vector database built in Java on top of the Apache Lucene library. -Use {es} to search, index, store, and analyze data of all shapes and sizes in near real-time. +https://github.com/elastic/elasticsearch[{es}] is a distributed search and analytics engine, scalable data store, and vector database built on Apache Lucene. +It's optimized for speed and relevance on production-scale workloads. +Use {es} to search, index, store, and analyze data of all shapes and sizes in near real time. [TIP] ==== {es} has a lot of features. Explore the full list on the https://www.elastic.co/elasticsearch/features[product webpage^]. ==== -{es} is the heart of the the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. +{es} is the heart of the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. {es} is used for a wide and growing range of use cases. Here are a few examples: -* *Monitor log and event data*. Store and analyze logs, metrics, and security event data for operational insights and SIEM. -* *Build search applications*. Add search capabilities to apps or websites and build enterprise search engines over your organization's internal data sources. -* *Vector database*. Store and search vectorized data, create vector embeddings with built-in and third-party NLP models. +* *Monitor log and event data*. Store logs, metrics, and event data for observability and security information and event management (SIEM). +* *Build search applications*. Add search capabilities to apps or websites, or build enterprise search engines over your organization's internal data sources. +* *Vector database*. Store and search vectorized data, and create vector embeddings with built-in and third-party natural language processing (NLP) models. * *Retrieval augmented generation (RAG)*. Use {es} as a retrieval engine to augment Generative AI models. * *Application and security monitoring*. Monitor and analyze application performance and security data effectively. * *Machine learning*. Use machine learning to automatically model the behavior of your data in real time. @@ -28,15 +29,14 @@ Refer to our https://www.elastic.co/customers/success-stories[customer success s [[elasticsearch-intro-elastic-stack]] .What is the Elastic Stack? ******************************* -The Elastic Stack refers to the suite of products enabled by {es}: +{es} is the core component of the Elastic Stack, a suite of products for collecting, storing, searching, and visualizing data. * https://www.elastic.co/guide/en/kibana/current/index.html[Kibana]. A UI for visualizing and exploring data in {es}. * https://www.elastic.co/guide/en/elasticsearch/client/index.html[Client libraries]. Work with {es} in your preferred programming language. * https://www.elastic.co/guide/en/logstash/current/introduction.html[Logstash]. A server-side data processing pipeline for ingesting and transforming data from multiple sources and indexing into {es}. -* https://www.elastic.co/guide/en/fleet/current/fleet-overview.html[Fleet and Elastic Agent.] Elastic Agents is a single, unified way to add monitoring for logs, metrics, and other types of data to a host. Fleet is a central place to configure and monitor your Elastic Agents. +* https://www.elastic.co/guide/en/fleet/current/fleet-overview.html[Fleet and Elastic Agent.] Elastic Agent is a single, unified way to add monitoring for logs, metrics, and other types of data to a host. Fleet is a central place to configure and monitor your Elastic Agents. * https://www.elastic.co/guide/en/beats/libbeat/current/beats-reference.html[Beats]. Lightweight data shippers for sending data from edge machines to {es}. * https://www.elastic.co/guide/en/observability/current/apm.html[APM]. Monitor the performance of your applications. -* https://www.elastic.co/guide/en/elasticsearch/hadoop/current/float.html[{es} Hadoop]. Use {es} as a Hadoop input/output format. https://www.elastic.co/guide/en/starting-with-the-elasticsearch-platform-and-its-solutions/current/stack-components.html[Learn more about the Elastic Stack]. ******************************* @@ -49,29 +49,36 @@ https://www.elastic.co/guide/en/starting-with-the-elasticsearch-platform-and-its To use {es}, you need a running instance of the {es} service. You can deploy {es} in various ways: +* <>. Get started quickly with a minimal local Docker setup. * https://elastic.co/guide/en/cloud/current/ec-getting-started.html[*Elastic Cloud*]. {es} is available as part of our hosted Elastic Stack offering, deployed in the cloud with your provider of choice. Sign up for a https://cloud.elastic.co/registration[14 day free trial]. -* https://elastic.co/guide/en/cloud-enterprise/current/Elastic-Cloud-Enterprise-overview.html[*Elastic Cloud Enterprise*]. Deploy Elastic Cloud on public or private clouds, virtual machines, or your own premises. -* https://elastic.co/guide/en/cloud-on-k8s/current/k8s-overview.html[*Elastic Cloud on Kubernetes*]. Deploy Elastic Cloud on Kubernetes. * https://www.elastic.co/docs/current/serverless[*Elastic Cloud Serverless* (technical preview)]. Create serverless projects for autoscaled and fully-managed {es} deployments. Sign up for a https://cloud.elastic.co/serverless-registration[14 day free trial]. + +**Advanced deployment options** + * <>. Install, configure, and run {es} on your own premises. -+ -[TIP] -==== -If you just want to get started quickly with a minimal local setup, refer to <>. -==== +* https://elastic.co/guide/en/cloud-enterprise/current/Elastic-Cloud-Enterprise-overview.html[*Elastic Cloud Enterprise*]. Deploy Elastic Cloud on public or private clouds, virtual machines, or your own premises. +* https://elastic.co/guide/en/cloud-on-k8s/current/k8s-overview.html[*Elastic Cloud on Kubernetes*]. Deploy Elastic Cloud on Kubernetes. [discrete] [[elasticsearch-next-steps]] === Learn more +Here are some resources to help you get started: + * <>. A beginner's guide to deploying your first {es} instance, indexing data, and running queries. * https://elastic.co/webinars/getting-started-elasticsearch[Webinar: Introduction to {es}]. Register for our live webinars to learn directly from {es} experts. * https://www.elastic.co/search-labs[Elastic Search Labs]. Tutorials and blogs that explore AI-powered search using the latest {es} features. ** Follow our tutorial https://www.elastic.co/search-labs/tutorials/search-tutorial/welcome[to build a hybrid search solution in Python]. ** Check out the https://github.com/elastic/elasticsearch-labs?tab=readme-ov-file#elasticsearch-examples--apps[`elasticsearch-labs` repository] for a range of Python notebooks and apps for various use cases. +[[how-elasticsearch-works]] +=== How {es} works + +This page outlines some fundamental {es} concepts and features, including how data is stored, indexing capabilities, search and analysis features, scalability, and disaster recovery options. + +[discrete] [[documents-indices]] -=== Documents and indices +==== Documents and indices {es} is a distributed document store. Instead of storing information as rows of columnar data, {es} stores complex data structures that have been serialized @@ -122,11 +129,82 @@ The analysis chain that is applied to a full-text field during indexing is also used at search time. When you query a full-text field, the query text undergoes the same analysis before the terms are looked up in the index. +[discrete] +[[search-analyze]] +==== Information out: search and analyze + +While you can use {es} as a document store and retrieve documents and their +metadata, the real power comes from being able to easily access the full suite +of search capabilities built on the Apache Lucene search engine library. + +{es} provides a simple, coherent REST API for managing your cluster and indexing +and searching your data. For testing purposes, you can easily submit requests +directly from the command line or through the Developer Console in {kib}. From +your applications, you can use the +https://www.elastic.co/guide/en/elasticsearch/client/index.html[{es} client] +for your language of choice: Java, JavaScript, Go, .NET, PHP, Perl, Python +or Ruby. + +[discrete] +[[search-data]] +===== Searching your data + +The {es} REST APIs support structured queries, full text queries, and complex +queries that combine the two. Structured queries are +similar to the types of queries you can construct in SQL. For example, you +could search the `gender` and `age` fields in your `employee` index and sort the +matches by the `hire_date` field. Full-text queries find all documents that +match the query string and return them sorted by _relevance_—how good a +match they are for your search terms. + +In addition to searching for individual terms, you can perform phrase searches, +similarity searches, and prefix searches, and get autocomplete suggestions. + +Have geospatial or other numerical data that you want to search? {es} indexes +non-textual data in optimized data structures that support +high-performance geo and numerical queries. + +You can access all of these search capabilities using {es}'s +comprehensive JSON-style query language (<>). You can also +construct <> to search and aggregate data +natively inside {es}, and JDBC and ODBC drivers enable a broad range of +third-party applications to interact with {es} via SQL. + +[discrete] +[[analyze-data]] +===== Analyzing your data + +{es} aggregations enable you to build complex summaries of your data and gain +insight into key metrics, patterns, and trends. Instead of just finding the +proverbial “needle in a haystack”, aggregations enable you to answer questions +like: + +* How many needles are in the haystack? +* What is the average length of the needles? +* What is the median length of the needles, broken down by manufacturer? +* How many needles were added to the haystack in each of the last six months? + +You can also use aggregations to answer more subtle questions, such as: + +* What are your most popular needle manufacturers? +* Are there any unusual or anomalous clumps of needles? + +Because aggregations leverage the same data-structures used for search, they are +also very fast. This enables you to analyze and visualize your data in real time. +Your reports and dashboards update as your data changes so you can take action +based on the latest information. + +What’s more, aggregations operate alongside search requests. You can search +documents, filter results, and perform analytics at the same time, on the same +data, in a single request. And because aggregations are calculated in the +context of a particular search, you’re not just displaying a count of all +size 70 needles, you’re displaying a count of the size 70 needles +that match your users' search criteria--for example, all size 70 _non-stick +embroidery_ needles. + +[discrete] [[scalability]] -=== Scalability and resilience: clusters, nodes, and shards -++++ -Scalability and resilience -++++ +==== Scalability and resilience {es} is built to be always available and to scale with your needs. It does this by being distributed by nature. You can add servers (nodes) to a cluster to @@ -155,7 +233,7 @@ interrupting indexing or query operations. [discrete] [[it-depends]] -==== It depends... +===== Shard size and number of shards There are a number of performance considerations and trade offs with respect to shard size and the number of primary shards configured for an index. The more @@ -183,7 +261,7 @@ testing with your own data and queries]. [discrete] [[disaster-ccr]] -==== In case of disaster +===== Disaster recovery A cluster's nodes need good, reliable connections to each other. To provide better connections, you typically co-locate the nodes in the same data center or @@ -201,9 +279,15 @@ create secondary clusters to serve read requests in geo-proximity to your users. the active leader index and handles all write requests. Indices replicated to secondary clusters are read-only followers. +[discrete] +[[admin]] +===== Security, management, and monitoring + As with any enterprise system, you need tools to secure, manage, and monitor your {es} clusters. Security, monitoring, and administrative features that are integrated into {es} enable you to use {kibana-ref}/introduction.html[{kib}] as a control center for managing a cluster. Features like <> and <> -help you intelligently manage your data over time. \ No newline at end of file +help you intelligently manage your data over time. + +Refer to <> for more information. \ No newline at end of file From 757f9c1f6ffe7d7e11a01f0b9126ac0a60f7ef6e Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 11:46:13 +0200 Subject: [PATCH 08/14] =?UTF-8?q?Revert=20merging=20subpages=20which=20bre?= =?UTF-8?q?aks=20backlinks=20=F0=9F=98=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/reference/intro.asciidoc | 24 ++++++++---------------- 1 file changed, 8 insertions(+), 16 deletions(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 729b22a289461..f8b0315f7c27e 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -71,14 +71,8 @@ Here are some resources to help you get started: ** Follow our tutorial https://www.elastic.co/search-labs/tutorials/search-tutorial/welcome[to build a hybrid search solution in Python]. ** Check out the https://github.com/elastic/elasticsearch-labs?tab=readme-ov-file#elasticsearch-examples--apps[`elasticsearch-labs` repository] for a range of Python notebooks and apps for various use cases. -[[how-elasticsearch-works]] -=== How {es} works - -This page outlines some fundamental {es} concepts and features, including how data is stored, indexing capabilities, search and analysis features, scalability, and disaster recovery options. - -[discrete] [[documents-indices]] -==== Documents and indices +=== Documents and indices {es} is a distributed document store. Instead of storing information as rows of columnar data, {es} stores complex data structures that have been serialized @@ -129,9 +123,8 @@ The analysis chain that is applied to a full-text field during indexing is also used at search time. When you query a full-text field, the query text undergoes the same analysis before the terms are looked up in the index. -[discrete] [[search-analyze]] -==== Information out: search and analyze +=== Search and analyze While you can use {es} as a document store and retrieve documents and their metadata, the real power comes from being able to easily access the full suite @@ -147,7 +140,7 @@ or Ruby. [discrete] [[search-data]] -===== Searching your data +==== Searching your data The {es} REST APIs support structured queries, full text queries, and complex queries that combine the two. Structured queries are @@ -172,7 +165,7 @@ third-party applications to interact with {es} via SQL. [discrete] [[analyze-data]] -===== Analyzing your data +==== Analyzing your data {es} aggregations enable you to build complex summaries of your data and gain insight into key metrics, patterns, and trends. Instead of just finding the @@ -202,9 +195,8 @@ size 70 needles, you’re displaying a count of the size 70 needles that match your users' search criteria--for example, all size 70 _non-stick embroidery_ needles. -[discrete] [[scalability]] -==== Scalability and resilience +=== Scalability and resilience {es} is built to be always available and to scale with your needs. It does this by being distributed by nature. You can add servers (nodes) to a cluster to @@ -233,7 +225,7 @@ interrupting indexing or query operations. [discrete] [[it-depends]] -===== Shard size and number of shards +==== Shard size and number of shards There are a number of performance considerations and trade offs with respect to shard size and the number of primary shards configured for an index. The more @@ -261,7 +253,7 @@ testing with your own data and queries]. [discrete] [[disaster-ccr]] -===== Disaster recovery +==== Disaster recovery A cluster's nodes need good, reliable connections to each other. To provide better connections, you typically co-locate the nodes in the same data center or @@ -281,7 +273,7 @@ secondary clusters are read-only followers. [discrete] [[admin]] -===== Security, management, and monitoring +==== Security, management, and monitoring As with any enterprise system, you need tools to secure, manage, and monitor your {es} clusters. Security, monitoring, and administrative features From bde3ccee2f53b0afa14167a123dee455ddf9aeb2 Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 11:48:46 +0200 Subject: [PATCH 09/14] Restore link --- docs/reference/modules/shard-ops.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/modules/shard-ops.asciidoc b/docs/reference/modules/shard-ops.asciidoc index 7854633e8be9f..429168c92a751 100644 --- a/docs/reference/modules/shard-ops.asciidoc +++ b/docs/reference/modules/shard-ops.asciidoc @@ -1,7 +1,7 @@ [[shard-allocation-relocation-recovery]] === Shard allocation, relocation, and recovery -Each index in {es} is divided into one or more <>. +Each <> in Elasticsearch is divided into one or more <>. Each document in an index belongs to a single shard. A cluster can contain multiple copies of a shard. Each shard has one distinguished shard copy called the _primary_, and zero or more non-primary copies called _replicas_. The primary shard copy serves as the main entry point for all indexing operations. The operations on the primary shard copy are then forwarded to its replicas. From 832eb3f055ecaa2188280e79b969ed512bb4acdd Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 11:48:58 +0200 Subject: [PATCH 10/14] Fix the the --- docs/reference/intro.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index f8b0315f7c27e..15fc929b9cb1f 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -10,7 +10,7 @@ Use {es} to search, index, store, and analyze data of all shapes and sizes in ne {es} has a lot of features. Explore the full list on the https://www.elastic.co/elasticsearch/features[product webpage^]. ==== -{es} is the heart of the the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. +{es} is the heart of the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. {es} is used for a wide and growing range of use cases. Here are a few examples: From 9ec671883821c13f32f35570249eff163a1350d8 Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 11:53:46 +0200 Subject: [PATCH 11/14] Delete whitespace --- docs/reference/modules/shard-ops.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/modules/shard-ops.asciidoc b/docs/reference/modules/shard-ops.asciidoc index 429168c92a751..3089875008168 100644 --- a/docs/reference/modules/shard-ops.asciidoc +++ b/docs/reference/modules/shard-ops.asciidoc @@ -1,7 +1,7 @@ [[shard-allocation-relocation-recovery]] === Shard allocation, relocation, and recovery -Each <> in Elasticsearch is divided into one or more <>. +Each <> in Elasticsearch is divided into one or more <>. Each document in an index belongs to a single shard. A cluster can contain multiple copies of a shard. Each shard has one distinguished shard copy called the _primary_, and zero or more non-primary copies called _replicas_. The primary shard copy serves as the main entry point for all indexing operations. The operations on the primary shard copy are then forwarded to its replicas. From dcf50505342e44f1135148cbc8e50f9b66ee3800 Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 11:54:28 +0200 Subject: [PATCH 12/14] Restore single whitespace to remove noise because this file is unchanged --- docs/reference/modules/shard-ops.asciidoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/reference/modules/shard-ops.asciidoc b/docs/reference/modules/shard-ops.asciidoc index 3089875008168..c0e5ee6a220f0 100644 --- a/docs/reference/modules/shard-ops.asciidoc +++ b/docs/reference/modules/shard-ops.asciidoc @@ -1,7 +1,7 @@ [[shard-allocation-relocation-recovery]] === Shard allocation, relocation, and recovery -Each <> in Elasticsearch is divided into one or more <>. +Each <> in Elasticsearch is divided into one or more <>. Each document in an index belongs to a single shard. A cluster can contain multiple copies of a shard. Each shard has one distinguished shard copy called the _primary_, and zero or more non-primary copies called _replicas_. The primary shard copy serves as the main entry point for all indexing operations. The operations on the primary shard copy are then forwarded to its replicas. From 238ec7d08b9c3371036c4c61d926fd3bc11d6cbc Mon Sep 17 00:00:00 2001 From: Liam Thompson Date: Wed, 28 Aug 2024 18:45:51 +0200 Subject: [PATCH 13/14] Trim Stack callout, use URL attributes where possible --- docs/reference/intro.asciidoc | 20 ++++++-------------- 1 file changed, 6 insertions(+), 14 deletions(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 15fc929b9cb1f..256428698671b 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -1,7 +1,7 @@ [[elasticsearch-intro]] == What is {es}? -https://github.com/elastic/elasticsearch[{es}] is a distributed search and analytics engine, scalable data store, and vector database built on Apache Lucene. +{es-repo}[{es}] is a distributed search and analytics engine, scalable data store, and vector database built on Apache Lucene. It's optimized for speed and relevance on production-scale workloads. Use {es} to search, index, store, and analyze data of all shapes and sizes in near real time. @@ -10,7 +10,7 @@ Use {es} to search, index, store, and analyze data of all shapes and sizes in ne {es} has a lot of features. Explore the full list on the https://www.elastic.co/elasticsearch/features[product webpage^]. ==== -{es} is the heart of the <> and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. +{es} is the heart of the {estc-welcome-current}/stack-components.html[Elastic Stack] and powers the Elastic https://www.elastic.co/enterprise-search[Search], https://www.elastic.co/observability[Observability] and https://www.elastic.co/security[Security] solutions. {es} is used for a wide and growing range of use cases. Here are a few examples: @@ -30,14 +30,6 @@ Refer to our https://www.elastic.co/customers/success-stories[customer success s .What is the Elastic Stack? ******************************* {es} is the core component of the Elastic Stack, a suite of products for collecting, storing, searching, and visualizing data. - -* https://www.elastic.co/guide/en/kibana/current/index.html[Kibana]. A UI for visualizing and exploring data in {es}. -* https://www.elastic.co/guide/en/elasticsearch/client/index.html[Client libraries]. Work with {es} in your preferred programming language. -* https://www.elastic.co/guide/en/logstash/current/introduction.html[Logstash]. A server-side data processing pipeline for ingesting and transforming data from multiple sources and indexing into {es}. -* https://www.elastic.co/guide/en/fleet/current/fleet-overview.html[Fleet and Elastic Agent.] Elastic Agent is a single, unified way to add monitoring for logs, metrics, and other types of data to a host. Fleet is a central place to configure and monitor your Elastic Agents. -* https://www.elastic.co/guide/en/beats/libbeat/current/beats-reference.html[Beats]. Lightweight data shippers for sending data from edge machines to {es}. -* https://www.elastic.co/guide/en/observability/current/apm.html[APM]. Monitor the performance of your applications. - https://www.elastic.co/guide/en/starting-with-the-elasticsearch-platform-and-its-solutions/current/stack-components.html[Learn more about the Elastic Stack]. ******************************* // TODO: Remove once we've moved Stack Overview to a subpage? @@ -50,14 +42,14 @@ To use {es}, you need a running instance of the {es} service. You can deploy {es} in various ways: * <>. Get started quickly with a minimal local Docker setup. -* https://elastic.co/guide/en/cloud/current/ec-getting-started.html[*Elastic Cloud*]. {es} is available as part of our hosted Elastic Stack offering, deployed in the cloud with your provider of choice. Sign up for a https://cloud.elastic.co/registration[14 day free trial]. -* https://www.elastic.co/docs/current/serverless[*Elastic Cloud Serverless* (technical preview)]. Create serverless projects for autoscaled and fully-managed {es} deployments. Sign up for a https://cloud.elastic.co/serverless-registration[14 day free trial]. +* {cloud}/ec-getting-started-trial.html[*Elastic Cloud*]. {es} is available as part of our hosted Elastic Stack offering, deployed in the cloud with your provider of choice. Sign up for a https://cloud.elastic.co/registration[14 day free trial]. +* {serverless-docs}/general/sign-up-trial[*Elastic Cloud Serverless* (technical preview)]. Create serverless projects for autoscaled and fully-managed {es} deployments. Sign up for a https://cloud.elastic.co/serverless-registration[14 day free trial]. **Advanced deployment options** * <>. Install, configure, and run {es} on your own premises. -* https://elastic.co/guide/en/cloud-enterprise/current/Elastic-Cloud-Enterprise-overview.html[*Elastic Cloud Enterprise*]. Deploy Elastic Cloud on public or private clouds, virtual machines, or your own premises. -* https://elastic.co/guide/en/cloud-on-k8s/current/k8s-overview.html[*Elastic Cloud on Kubernetes*]. Deploy Elastic Cloud on Kubernetes. +* {ece-ref}/Elastic-Cloud-Enterprise-overview.html[*Elastic Cloud Enterprise*]. Deploy Elastic Cloud on public or private clouds, virtual machines, or your own premises. +* {eck-ref}/k8s-overview.html[*Elastic Cloud on Kubernetes*]. Deploy Elastic Cloud on Kubernetes. [discrete] [[elasticsearch-next-steps]] From acc90b56deaf45604d93355183504d09edc4a643 Mon Sep 17 00:00:00 2001 From: Liam Thompson <32779855+leemthompo@users.noreply.github.com> Date: Thu, 29 Aug 2024 09:38:51 +0200 Subject: [PATCH 14/14] Fix hyphens Co-authored-by: marciw <333176+marciw@users.noreply.github.com> --- docs/reference/intro.asciidoc | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/reference/intro.asciidoc b/docs/reference/intro.asciidoc index 256428698671b..cd9c126e7b1fd 100644 --- a/docs/reference/intro.asciidoc +++ b/docs/reference/intro.asciidoc @@ -22,7 +22,7 @@ Use {es} to search, index, store, and analyze data of all shapes and sizes in ne * *Machine learning*. Use {ml} to automatically model the behavior of your data in real-time. This is just a sample of search, observability, and security use cases enabled by {es}. -Refer to our https://www.elastic.co/customers/success-stories[customer success stories] for concrete examples across a range of industry verticals. +Refer to our https://www.elastic.co/customers/success-stories[customer success stories] for concrete examples across a range of industries. // Link to demos, search labs chatbots [discrete] @@ -43,11 +43,11 @@ You can deploy {es} in various ways: * <>. Get started quickly with a minimal local Docker setup. * {cloud}/ec-getting-started-trial.html[*Elastic Cloud*]. {es} is available as part of our hosted Elastic Stack offering, deployed in the cloud with your provider of choice. Sign up for a https://cloud.elastic.co/registration[14 day free trial]. -* {serverless-docs}/general/sign-up-trial[*Elastic Cloud Serverless* (technical preview)]. Create serverless projects for autoscaled and fully-managed {es} deployments. Sign up for a https://cloud.elastic.co/serverless-registration[14 day free trial]. +* {serverless-docs}/general/sign-up-trial[*Elastic Cloud Serverless* (technical preview)]. Create serverless projects for autoscaled and fully managed {es} deployments. Sign up for a https://cloud.elastic.co/serverless-registration[14 day free trial]. **Advanced deployment options** -* <>. Install, configure, and run {es} on your own premises. +* <>. Install, configure, and run {es} on your own premises. * {ece-ref}/Elastic-Cloud-Enterprise-overview.html[*Elastic Cloud Enterprise*]. Deploy Elastic Cloud on public or private clouds, virtual machines, or your own premises. * {eck-ref}/k8s-overview.html[*Elastic Cloud on Kubernetes*]. Deploy Elastic Cloud on Kubernetes.