Fixes directives + other edits

jmikell821 · jmikell821 · commit 8895ccf0708c · 2025-09-09T17:59:47.000-04:00
diff --git a/get-started/introduction.md b/get-started/introduction.md
@@ -20,28 +20,28 @@ Refer to the following table for a quick reference of which solution you may nee
 | Monitor data for anomalous activity, detect, prevent, and respond to security incidents | [{{elastic-sec}}](/solutions/security.md) | SOC teams, security analysts, IT security admins |
 
 :::{tip}
-Check out our [customer success stories](https://www.elastic.co/customers/success-stories) to learn how various organizations are utilizing our products for their specific business needs.
+Check out our [customer success stories](https://www.elastic.co/customers/success-stories) to learn how various organizations utilize our products for their specific business needs.
 :::
 
-Each of our solutions is available as a fully-managed {{serverless-short}} project or a self-managed deployment. Refer to [deployment options](../get-started/deployment-options.md) to learn about these options. 
+Each of our solutions is available as a fully managed {{serverless-short}} project or a self-managed deployment. Refer to [deployment options](../get-started/deployment-options.md) to learn about these options. 
 
 ## Elastic {{observability}} 
 
 ### Overview [observability-overview]
 
-Elastic {{observability}} provides unified observability across applications and infrastructure. It brings together logs, metrics, application traces, user experience data, and more into a single, integrated platform. This consolidation allows for powerful, cross-referenced analysis, enabling teams to move from detecting issues to understanding their root causes with speed and efficiency. By leveraging the search and analytics capabilities of {{es}}, it offers a holistic view of system behavior.
+Elastic {{observability}} provides unified observability across applications and infrastructure. It combines logs, metrics, application traces, user experience data, and more into a single, integrated platform. This consolidation allows for powerful, cross-referenced analysis, enabling teams to move from detecting issues to understanding their root causes with speed and efficiency. By leveraging the search and analytics capabilities of {{es}}, it offers a holistic view of system behavior.
 
 Elastic {{observability}} embraces open standards like OpenTelemetry for flexible data collection, and offers scalable, cost-efficient data retention with tiered storage.
 
 ### {{observability}} use cases [observability-use-cases]
 
-Apply Elastic {{observability}} to a wide range of scenarios to improve operational awareness and system reliability. 
+Apply Elastic {{observability}} to various scenarios to improve operational awareness and system reliability. 
 :::{dropdown} Use cases
 * **Log Monitoring and Analytics:** Centralize and analyze petabytes of log data from any source. This enables quick searching, ad-hoc queries with ES|QL, and visualization with prebuilt dashboards to diagnose issues.
 * **Application Performance Monitoring (APM):** Gain code-level visibility into application performance. By collecting and analyzing traces with native OTel support, teams can identify bottlenecks, track errors, and optimize the end-user experience.
 * **Infrastructure Monitoring:** Monitor metrics from servers, virtual machines, containers, and serverless environments with over 400 out-of-the-box integrations, including OpenTelemetry. This provides deep insights into resource utilization and overall system health.
 * **Digital Experience Monitoring:**
-  * **Real User Monitoring (RUM):** Capture and analyze data on how real users are interacting with web applications to improve perceived performance.
+  * **Real User Monitoring (RUM):** Capture and analyze data on how real users interact with web applications to improve perceived performance.
   * **Synthetic Monitoring:** Proactively simulate user journeys and API calls to test application availability and functionality.
   * **Uptime Monitoring:** Continuously check the status of services and applications to ensure they are available.
 * **Universal Profiling:** Gain visibility into system performance and identify expensive lines of code without application instrumentation, helping to increase CPU efficiency and reduce cloud spend.
@@ -60,28 +60,28 @@ At the heart of Elastic {{observability}} are several key concepts that enable i
 * OpenTelemetry: Elastic Observability offers first-class, production-grade support for OpenTelemetry. This allows organizations to use vendor-neutral instrumentation and stream native OTel data without proprietary agents, leveraging the Elastic Distribution of OpenTelemetry (EDOT).
 * AIOps and AI Assistant: Leverages predictive analytics and an LLM-powered AI Assistant to reduce the time required to detect, investigate, and resolve incidents. This includes zero-config anomaly detection, pattern analysis, and the ability to surface correlations and root causes.
 * Alerting and Cases: A built-in feature for creating rules to detect complex conditions and trigger actions. It allows teams to stay aware of potential issues and use Cases to track investigation details, assign tasks, and collaborate on resolutions.
-* Service Level Objectives (SLOs): A framework for defining and monitoring the reliability of a service. Elastic Observability allows for the creation and tracking of SLOs to ensure that performance targets are being met.
+* Service Level Objectives (SLOs): A framework for defining and monitoring the reliability of a service. Elastic Observability allows for creating and tracking SLOs to ensure that performance targets are being met.
 :::
 
 ## {{elastic-sec}} 
 
 ### Overview 
 
-{{elastic-sec}} is a unified security solution that integrates SIEM (Security Information and Event Management), endpoint security, and cloud security into a single platform so you can detect, prevent, and respond to cyber threats across your entire environment in near real time. Elastic Security leverages {{es}} powerful platform for its searching and analytic capabilities, and {{kib}} for its visualization features. By combining prevention, detection, and response capabilities, {{elastic-sec}} helps your organization reduce the risk of successful attacks. 
+{{elastic-sec}} is a unified security solution that integrates SIEM (Security Information and Event Management), endpoint security, and cloud security into a single platform so you can detect, prevent, and respond to cyber threats across your entire environment in near real time. Elastic Security leverages {{es}}'s powerful platform for its searching and analytic capabilities, and {{kib}} for its visualization features. By combining prevention, detection, and response capabilities, {{elastic-sec}} helps your organization reduce the risk of successful attacks. 
 
-Install {{elastic-sec}} on one of our Elastic-managed Cloud deployments or on your own self-managed infrastructure.  
+Install {{elastic-sec}} on one of our Elastic-managed Cloud deployments or your own self-managed infrastructure.  
 
 ### {{elastic-sec}} use cases 
 
-Use {{elastic-sec}} for a wide variety of security needs to ensure your systems are protected from the latest threats.
+Use {{elastic-sec}} for numerous security needs to ensure your systems are protected from the latest threats.
 
 :::{dropdown} Use cases
-* **SIEM:** {{elastic-sec}} acts as a modern SIEM that provides a centralized platform for ingesting, analyzing, and managing security data from various sources. 
+* **SIEM:** {{elastic-sec}} is a modern SIEM that provides a centralized platform for ingesting, analyzing, and managing security data from various sources. 
 * **Third-party integration support:** Ingest data from a variety of tools and data sources so you can centralize your security data.
 * **Threat detection and analytics:** Identify unknown threats by enabling prebuilt or custom detection rules, automatically detect anomalous activity with built-in machine learning jobs, or proactively search for threats using our powerful threat hunting and interactive visualization tools. 
 * **Automatic migration:** Migrate SIEM rules from other platforms to {{elastic-sec}}. 
 * **Endpoint protection and threat prevention:** Automatically stop cybersecurity attacks—such as malware and ransomware—before damage and loss can occur.
-* **AI-powered features:** Elastic Security leverages generative AI to help enhance threat detection, assist with incident response, and day-to-day security operations. For example, the AI Assistant can summarize alerts, identify relevant information, suggest investigation steps, and even generate complex queries from natural language input.
+* **AI-powered features:** Elastic Security leverages generative AI to help enhance threat detection, assist with incident response, and day-to-day security operations. For example, the AI Assistant can summarize alerts, identify relevant information, suggest investigation steps, and generate complex queries from natural language input.
 * **Custom dashboards and visualizations:** Create custom dashboards and visualizations to gain insights into security events.
 * **Cloud Security:** {{elastic-sec}} provides the following cloud features:
   * **Cloud Security Posture Management (CSPM) and Kubernetes Security Posture Management (KSPM):** Check cloud service configurations against security benchmarks to identify and resolve misconfigurations that can be exploited.
@@ -95,16 +95,16 @@ Before diving into setup and configuration, familiarize yourself with the founda
 
 :::{dropdown} Concepts
 
-* {{agent}}: A single, unified way to add monitoring for logs, metrics, and other types of data to a host. Elastic Agent can also protect hosts from security threats, query data from operating systems, forward data from remote services or hardware. 
+* {{agent}}: A single, unified way to add monitoring for logs, metrics, and other types of data to a host. Elastic Agent can also protect hosts from security threats, query data from operating systems, and forward data from remote services or hardware. 
 * {{elastic-defend}}: {{elastic-sec}}'s Endpoint Detection and Response (EDR) tool that protects endpoints from malicious activity. {{elastic-defend}} uses a combination of techniques like machine learning, behavioral analysis, and prebuilt rules to detect, prevent, and respond to threats in real-time.
 * {{elastic-endpoint}}: The installed component that performs {{elastic-defend}}'s threat monitoring and prevention capabilities. 
 * Detection engine: The framework that detects threats by using rules to search for suspicious events in data sources and generating alerts when those rules meet the defined criteria.  
-* Detection rules: Sets of conditions that identify potential threats and malicious activities. Rules analyze various data sources, including logs and network traffic, to detect anomalies, suspicious behaviors, or known attack patterns. {{elastic-sec}} ships out-the-box prebuilt rules, or you can create your own custom rules. 
-* Alerts: A notification that's generated when a rule’s criteria is met. You can then investigate an alert to dive into deeper details.  
+* Detection rules: Sets of conditions that identify potential threats and malicious activities. Rules analyze various data sources, including logs and network traffic, to detect anomalies, suspicious behaviors, or known attack patterns. {{elastic-sec}} ships out-of-the-box prebuilt rules, or you can create your own custom rules. 
+* Alerts: A notification that's generated when a rule’s criteria are met. You can then investigate an alert to dive into deeper details.  
 * Machine learning and anomaly detection: Anomaly detection jobs identify anomalous events or patterns in your data. Use these with machine learning detection rules to generate alerts when behavior deviates from normal activity.
 * Entity analytics: A threat detection feature that combines the power of Elastic’s detection engine and machine learning capabilities to identify unusual user behaviors across hosts, users, and services. Entity analytics uses a risk scoring engine to calculate a risk score, which is evaluated at a recurring interval. 
-* Cases: A tool that allows you to collect and share information about security issues. Opening a case allows you to track key investigation details and collect alerts in a central location. You can also send cases to external systems.
-* Timeline: A threat hunting tool that allows you to investigate security events so you can gather and analyze data related to alerts or suspicious activity. You can add events to Timeline from various sources, build custom queries, and even import/export a Timeline to collaborate and share. 
+* Cases: A tool that allows you to collect and share information about security issues. Opening a case lets you track key investigation details and collect alerts in a central location. You can also send cases to external systems.
+* Timeline: A threat hunting tool that allows you to investigate security events so you can gather and analyze data related to alerts or suspicious activity. You can add events to Timeline from various sources, build custom queries, and import/export a Timeline to collaborate and share. 
 * Security posture management: Includes two Cloud Security features–Cloud Security Posture Management (CSPM) and Kubernetes Security Posture Management (KSPM)--that help you evaluate the services and resources in your cloud environment, such as storage, compute, IAM, and more — against security guidelines defined by the Center for Internet Security (CIS). These features help you identify and remediate configuration risks in your environment. 
 * AI Assistant: A generative AI-powered tool that helps with tasks like alert investigation, incident response, and query generation. It utilizes natural language processing and knowledge retrieval to provide context-aware assistance, summarize threats, suggest next steps, and automate workflows. Use AI Assistant to better understand and respond to security incidents.
 :::
@@ -119,33 +119,33 @@ Before diving into setup and configuration, familiarize yourself with the founda
 Use {{es}} for a wide range of business needs.   
 
 :::{dropdown} Use cases
-* **Full-text search:** Quickly find specific words or phrases within large volumes of text-based data, such as documents, articles, or product descriptions. Documents and search queries are transformed to enable returning relevant results instead of exact term matches. 
-* **Semantic search:** Go beyond keyword matching to understand the user's intent. This helps your search engine to recognize what users mean, not just what they type, by understanding synonyms and related concepts.
+* **Full-text search:** Find specific words or phrases within large volumes of text-based data, such as documents, articles, or product descriptions. Documents and search queries are transformed to enable returning relevant results instead of exact term matches. 
+* **Semantic search:** Go beyond keyword matching to understand the user's intent. Understanding synonyms and related concepts helps your search engine recognize what users mean, not just what they type.
 * **Hybrid search:** Get the best of both worlds by combining traditional keyword search with modern, meaning-based vector search. This ensures your users get the most accurate and relevant results every time.
-* **Vector database:** Search for data based on its meaning and context, not just keywords. This allows you to find similar items, like pictures that have the same style or songs with a similar vibe, by understanding the underlying concepts.
-* **Retrieval Augmented Generation (RAG):** Connect your generative AI applications (like chatbots) to your own private data. This allows your AI to provide more accurate, up-to-date, and relevant answers based on your proprietary information.
-* **Geospatial search:** Build location-aware features into your applications. This allows you to do things like find all available services within a certain radius, calculate the distance between two points, or identify which delivery routes are most efficient.
+* **Vector database:** Search for data based on its meaning and context, not just keywords. Understanding the underlying concepts allows you to find similar items, like pictures with the same style or songs with a similar vibe.
+* **Retrieval Augmented Generation (RAG):** Connect your generative AI applications (like chatbots) to your private data. This allows your AI to provide more accurate, up-to-date, and relevant answers based on your proprietary information.
+* **Geospatial search:** Build location-aware features into your applications. This allows you to do things like find all available services within a certain radius, calculate the distance between two points, or identify the most efficient delivery routes.
 :::
 
 ### {{es}} core concepts [search-concepts]
 Before you decide what type of search to use with {{es}} or bring in your data, familiarize yourself with the following {{es}} concepts.
 
-:::{dropdown} Concepts
+::::{dropdown} Concepts
 
 * **Index:** A collection of documents with similar characteristics that are uniquely identified by a name or an alias. The name is used to target the index in search queries and other operations.
  **Field:** The smallest individual unit of data within a document. It represents a specific property or attribute of the data you're indexing (for example, title, author, date, summary, etc.). Fields are critical for indexing, as they determine how data is analyzed and stored to enable efficient searching.
 * **Document:** Any structured data encoded in JSON. {{es}} organizes and stores data into documents. 
-* **Primary shard:** A self-contained Lucene index that contains some or all data for an index. Shards allow {{es}} to horizontally scale by splitting an index's data into smaller, manageable partitions, therefore improving performance. Each document in an index belongs to one primary shard.
+* **Primary shard:** A self-contained Lucene index that contains some or all data for an index. Shards allow {{es}} to scale horizontally by splitting an index's data into smaller, manageable partitions, improving performance. Each document in an index belongs to one primary shard.
 * **Replica:** A copy of a primary shard. Replicas maintain redundant copies of your data across the nodes in your cluster. This protects against hardware failure and increases capacity to serve read requests like searching or retrieving a document.
 * **Node:** A single running instance of the {{es}} server. 
 * **Cluster:** A collection of one or more nodes that holds all your data and provides indexing and search capabilities across all nodes. {{es}} clusters feature primary and replica shards to provide failover in the case of a node going down. When a primary shard goes down, the replica takes its place.
   :::{note}
-  If you're running {{es}} on a serverless deployment, you don't have to worry a bout shards, nodes or clusters. Elastic manages these for you. 
+  If you're running {{es}} on a serverless deployment, you don't have to worry a bout shards, nodes, or clusters. Elastic manages these for you. 
   :::
-* **Mapping:** The process that defines how a document and the fields it contains are stored and indexed.
-* **Client:** Software or an application designed to facilitate communication and interaction with an {{es}} cluster. It enables applications written in various programming languages to send requests to {{es}}, process the response, then push that data into the cluster. 
+* **Mapping:** The process that defines how a document and its fields  are stored and indexed.
+* **Client:** Software or an application that facilitates communication and interaction with an {{es}} cluster. It enables applications written in various programming languages to send requests to {{es}}, process the response, and then push that data into the cluster. 
 
-:::
+::::
 
 <!--TBD: Call out how solutions map to Serverless project types? -->
 <!-- Content moved from the-stack.md
