Merge branch 'main' into release-rs-gilboa

Author: rrelledge

build/components/example.py

@@ -14,7 +14,9 @@
     'java-sync': '@Test',
     'java-async': '@Test',
     'java-reactive': '@Test',
-    'c#': r'\[Fact]|\[SkipIfRedis\(.*\)]'
+    'c#': r'\[Fact]|\[SkipIfRedis\(.*\)]',
+    'c#-sync': r'\[Fact]|\[SkipIfRedis\(.*\)]',
+    'c#-async': r'\[Fact]|\[SkipIfRedis\(.*\)]'
 }
 PREFIXES = {
     'python': '#',
@@ -25,6 +27,8 @@
     'java-reactive': '//',
     'go': '//',
     'c#': '//',
+    'c#-sync': '//',
+    'c#-async': '//',
     'redisvl': '#',
     'php': '//',
     'rust': '//',

build/local_examples.py

@@ -34,7 +34,7 @@
     'python': 'Python',
     'node.js': 'Node.js',
     'go': 'Go',
-    'c#': 'C#',
+    'c#': 'C#-Sync',
     'java': 'Java-Sync',  # Default to sync, could be overridden
     'php': 'PHP',
     'redisvl': 'RedisVL',
@@ -72,6 +72,11 @@ def get_client_name_from_language_and_path(language: str, path: str) -> str:
             return 'Rust-Async'
         if 'rust-sync' in path:
             return 'Rust-Sync'
+    if language == 'c#':
+        if 'async' in path:
+            return 'C#-Async'
+        if 'sync' in path:
+            return 'C#-Sync'
     # Default behavior for all languages (and Java fallback)
     return get_client_name_from_language(language)
 

config.toml

@@ -45,7 +45,7 @@ tagManagerId = "GTM-TKZ6J9R"
 gitHubRepo = "https://github.com/redis/docs"
 
 # Display and sort order for client examples
-clientsExamples = ["Python", "Node.js", "Java-Sync", "Java-Async", "Java-Reactive", "Go", "C#", "RedisVL", "PHP", "Rust-Sync", "Rust-Async"]
+clientsExamples = ["Python", "Node.js", "Java-Sync", "Java-Async", "Java-Reactive", "Go", "C#-Sync", "C#-Async", "RedisVL", "PHP", "Rust-Sync", "Rust-Async"]
 searchService = "/convai/api/search-service"
 ratingsService = "/docusight/api/rate"
 
@@ -64,7 +64,8 @@ rdi_current_version = "1.14.1"
 "Java-async"={quickstartSlug="lettuce"}
 "Java-reactive"={quickstartSlug="lettuce"}
 "Go"={quickstartSlug="go"}
-"C#"={quickstartSlug="dotnet"}
+"C#-Sync"={quickstartSlug="dotnet"}
+"C#-Async"={quickstartSlug="dotnet"}
 "RedisVL"={quickstartSlug="redis-vl"}
 "PHP"={quickstartSlug="php"}
 "Rust-sync"={quickstartSlug="rust"}

content/develop/clients/dotnet/_index.md

@@ -36,45 +36,31 @@ dotnet add package NRedisStack
 
 ## Connect and test
 
-Connect to localhost on port 6379.
-
-```csharp
-using NRedisStack;
-using NRedisStack.RedisStackCommands;
-using StackExchange.Redis;
-//...
-ConnectionMultiplexer redis = ConnectionMultiplexer.Connect("localhost");
-IDatabase db = redis.GetDatabase();
-```
+Add the following imports to your source file:
+
+{{< clients-example set="landing" step="import" lang_filter="C#-Sync,C#-Async" >}}
+{{< /clients-example >}}
+
+Connect to localhost on port 6379. The client supports both synchronous and asynchronous commands.
+
+{{< clients-example set="landing" step="connect" lang_filter="C#-Sync,C#-Async" >}}
+{{< /clients-example >}}
 
 You can test the connection by storing and retrieving a simple string.
 
-```csharp
-db.StringSet("foo", "bar");
-Console.WriteLine(db.StringGet("foo")); // prints bar
-```
+{{< clients-example set="landing" step="set_get_string" lang_filter="C#-Sync,C#-Async" >}}
+{{< /clients-example >}}
 
 Store and retrieve a HashMap.
 
-```csharp
-var hash = new HashEntry[] { 
-    new HashEntry("name", "John"), 
-    new HashEntry("surname", "Smith"),
-    new HashEntry("company", "Redis"),
-    new HashEntry("age", "29"),
-    };
-db.HashSet("user-session:123", hash);
-
-var hashFields = db.HashGetAll("user-session:123");
-Console.WriteLine(String.Join("; ", hashFields));
-// Prints: 
-// name: John; surname: Smith; company: Redis; age: 29
-```
+{{< clients-example set="landing" step="set_get_hash" lang_filter="C#-Sync,C#-Async" >}}
+{{< /clients-example >}}
+
 ## Redis Open Source modules
 
 To access Redis Open Source capabilities, use the appropriate interface like this:
 
-```
+```cs
 IBloomCommands bf = db.BF();
 ICuckooCommands cf = db.CF();
 ICmsCommands cms = db.CMS();

content/develop/clients/dotnet/prob.md

@@ -99,15 +99,15 @@ add. The following example adds some names to a Bloom filter representing
 a list of users and checks for the presence or absence of users in the list.
 Note that you must use the `BF()` method to access the Bloom filter commands.
 
-{{< clients-example home_prob_dts bloom "C#" >}}
+{{< clients-example home_prob_dts bloom "C#-Sync" >}}
 {{< /clients-example >}}
 
 A Cuckoo filter has similar features to a Bloom filter, but also supports
 a deletion operation to remove hashes from a set, as shown in the example
 below. Note that you must use the `CF()` method to access the Cuckoo filter
 commands.
 
-{{< clients-example home_prob_dts cuckoo "C#" >}}
+{{< clients-example home_prob_dts cuckoo "C#-Sync" >}}
 {{< /clients-example >}}
 
 Which of these two data types you choose depends on your use case.
@@ -128,7 +128,7 @@ You can also merge two or more HyperLogLogs to find the cardinality of the
 [union](https://en.wikipedia.org/wiki/Union_(set_theory)) of the sets they
 represent.
 
-{{< clients-example home_prob_dts hyperloglog "C#" >}}
+{{< clients-example home_prob_dts hyperloglog "C#-Sync" >}}
 {{< /clients-example >}}
 
 The main benefit that HyperLogLogs offer is their very low
@@ -169,7 +169,7 @@ a Count-min sketch object, add data to it, and then query it.
 Note that you must use the `CMS()` method to access the Count-min
 sketch commands.
 
-{{< clients-example home_prob_dts cms "C#" >}}
+{{< clients-example home_prob_dts cms "C#-Sync" >}}
 {{< /clients-example >}}
 
 The advantage of using a CMS over keeping an exact count with a
@@ -202,7 +202,7 @@ shows how to merge two or more t-digest objects to query the combined
 data set. Note that you must use the `TDIGEST()` method to access the
 t-digest commands.
 
-{{< clients-example home_prob_dts tdigest "C#" >}}
+{{< clients-example home_prob_dts tdigest "C#-Sync" >}}
 {{< /clients-example >}}
 
 A t-digest object also supports several other related commands, such
@@ -225,5 +225,5 @@ top *k* items and query whether or not a given item is in the
 list. Note that you must use the `TOPK()` method to access the
 Top-K commands.
 
-{{< clients-example home_prob_dts topk "C#" >}}
+{{< clients-example home_prob_dts topk "C#-Sync" >}}
 {{< /clients-example >}}

content/develop/clients/dotnet/transpipe.md

@@ -37,7 +37,7 @@ versions of the standard command methods
 buffered in the pipeline and only execute when you call the `Execute()`
 method on the pipeline object.
 
-{{< clients-example pipe_trans_tutorial basic_pipe "C#" >}}
+{{< clients-example pipe_trans_tutorial basic_pipe "C#-Sync" >}}
 {{< /clients-example >}}
 
 ## Execute a transaction
@@ -47,7 +47,7 @@ instance of the `Transaction` class, call async command methods
 on that object, and then call the transaction object's 
 `Execute()` method to execute it.
 
-{{< clients-example pipe_trans_tutorial basic_trans "C#" >}}
+{{< clients-example pipe_trans_tutorial basic_trans "C#-Sync" >}}
 {{< /clients-example >}}
 
 ## Watch keys for changes
@@ -77,7 +77,7 @@ For example, the `KeyNotExists` condition aborts the transaction
 if a specified key exists or is added by another client while the
 transaction executes:
 
-{{< clients-example pipe_trans_tutorial trans_watch "C#" >}}
+{{< clients-example pipe_trans_tutorial trans_watch "C#-Sync" >}}
 {{< /clients-example >}}
 
 You can also use a `When` condition on certain individual commands to

content/develop/clients/dotnet/vecsets.md

@@ -48,22 +48,22 @@ dotnet add package Microsoft.ML
 In a new C# file, import the required classes. Note that the `#pragma`
 directive suppresses warnings about the experimental status of the vector set API:
 
-{{< clients-example set="home_vecsets" step="import" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="import" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 ## Access the model
 
 Use the `GetPredictionEngine()` helper function declared in the example below to load the model that creates the embeddings:
 
-{{< clients-example set="home_vecsets" step="model" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="model" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 The `GetPredictionEngine()` function uses two classes, `TextData` and `TransformedTextData`, 
 to specify the `PredictionEngine` model. These have a very simple definition
 and are required because the model expects the input and output to be
 passed in named object fields:
 
-{{< clients-example set="home_vecsets" step="data_classes" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="data_classes" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 Note that you must declare these classes at the end of the source file
@@ -73,15 +73,15 @@ The `GetEmbedding()` function declared below can then use this model to
 generate an embedding from a section of text and return it as a `float[]` array,
 which is the format required by the vector set API:
 
-{{< clients-example set="home_vecsets" step="get_embedding" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="get_embedding" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 ## Create the data
 
 The example data is contained a `Dictionary` object with some brief
 descriptions of famous people:
 
-{{< clients-example set="home_vecsets" step="data" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="data" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 ## Add the data to a vector set
@@ -99,7 +99,7 @@ The call to `VectorSetAdd()` also adds the `born` and `died` values from the
 original dictionary as attribute data. You can access this during a query
 or by using the [`VectorSetGetAttributesJson()`]({{< relref "/commands/vgetattr" >}}) method.
 
-{{< clients-example set="home_vecsets" step="add_data" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="add_data" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 ## Query the vector set
@@ -112,7 +112,7 @@ return elements of the set, ranked in order of similarity to the query.
 
 Start with a simple query for "actors":
 
-{{< clients-example set="home_vecsets" step="basic_query" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="basic_query" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 This returns the following list of elements (formatted slightly for clarity):
@@ -131,7 +131,7 @@ on the information contained in the embedding model.
 You can use the `Count` property of `VectorSetSimilaritySearchRequest` to limit the
 list of elements to just the most relevant few items:
 
-{{< clients-example set="home_vecsets" step="limited_query" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="limited_query" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 The reason for using text embeddings rather than simple text search
@@ -141,7 +141,7 @@ different. For example, the word "entertainer" doesn't appear in any of the
 descriptions but if you use it as a query, the actors and musicians are ranked
 highest in the results list:
 
-{{< clients-example set="home_vecsets" step="entertainer_query" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="entertainer_query" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 Similarly, if you use "science" as a query, you get the following results:
@@ -162,7 +162,7 @@ with `VectorSetSimilaritySearch()` to restrict the search further. For example,
 repeat the "science" query, but this time limit the results to people
 who died before the year 2000:
 
-{{< clients-example set="home_vecsets" step="filtered_query" lang_filter="C#" >}}
+{{< clients-example set="home_vecsets" step="filtered_query" lang_filter="C#-Sync" >}}
 {{< /clients-example >}}
 
 Note that the boolean filter expression is applied to items in the list

content/embeds/rc-heroku-add-on.md

@@ -0,0 +1,19 @@
+Deploy Redis Cloud as a Heroku add-on to enhance your applications with high-performance data storage and caching capabilities.
+
+## Overview
+
+The [Redis Cloud Heroku add-on](https://elements.heroku.com/addons/rediscloud) provides a fully managed Redis service as a Heroku add-on, making it easy to quickly add high-performance data storage to your Heroku applications. Redis Cloud on Heroku is perfect for web applications requiring fast caching, session storage, and real-time features.
+
+## Key Features
+
+- **One-Click Installation**: Easy installation through Heroku add-ons marketplace
+- **Automatic Provisioning**: Instant Redis database setup with connection credentials
+- **Heroku Integration**: Seamless integration with Heroku's platform and tooling
+- **Scaling**: Easy scaling through Heroku dashboard or CLI
+- **Monitoring**: Built-in monitoring and alerting for your Redis databases
+- **Backup & Recovery**: Automated backups and point-in-time recovery
+- **Multi-language Support**: Works with all programming languages supported by Heroku
+
+## Get started
+
+Learn how to [add Redis Cloud to Heroku applications](https://devcenter.heroku.com/articles/rediscloud).

content/integrate/NRedisStack/_index.md

@@ -16,6 +16,23 @@ type: integration
 weight: 2
 ---
 
-Connect your C#/.NET application to a Redis database using the NRedisStack client library. 
+Connect your C#/.NET application to a Redis database using the NRedisStack client library.
+
+## Overview
+
+NRedisStack is a comprehensive .NET client library for Redis that extends StackExchange.Redis with support for all Redis data structures and capabilities. It provides strongly-typed APIs for Redis data structures and advanced features, making it ideal for modern .NET applications.
+
+## Key Features
+
+- **Redis Stack (v7.4 and earlier) and Redis 8 support**: Native support for JSON, time series, and probabilistic data structures, and Redis Query Engine.
+- **Strongly Typed**: Type-safe APIs with full IntelliSense support in Visual Studio
+- **Async/Await**: Native asynchronous programming support for high-performance applications
+- **StackExchange.Redis Integration**: Built on the proven StackExchange.Redis foundation
+- **Connection Multiplexing**: Efficient connection sharing across multiple operations
+- **Cluster Support**: Full Redis Cluster support for distributed deployments
+- **Pipeline Support**: Command batching for improved throughput
+- **.NET Ecosystem**: Seamless integration with ASP.NET Core, Entity Framework, and other .NET technologies
+
+## Getting Started
 
 Refer to the complete [C#/.NET guide]({{< relref "/develop/clients/dotnet" >}}) to install, connect, and use NRedisStack.

content/integrate/aws-redis-cloud/_index.md

@@ -0,0 +1,36 @@
+---
+LinkTitle: AWS
+Title: Redis Cloud on AWS
+categories:
+- docs
+- integrate
+- rc
+description: Deploy Redis Cloud on Amazon Web Services
+group: cloud
+stack: true
+summary: Deploy and manage Redis Cloud databases on AWS with seamless integration and global availability.
+title: AWS
+type: integration
+weight: 10
+---
+
+Deploy Redis Cloud on Amazon Web Services (AWS) to leverage Redis's performance with AWS's global infrastructure and services.
+
+## Overview
+
+Redis Cloud on AWS provides a fully managed Redis service that combines the power of Redis with AWS's reliable, scalable cloud infrastructure. Deploy Redis databases across multiple AWS regions with enterprise-grade security, automatic scaling, and 24/7 monitoring.
+
+## Key Features
+
+- **VPC Peering**: Secure, private connectivity between Redis Cloud and your AWS VPC
+- **AWS Transit Gateway**: Private connectivity to multiple resources
+- **Multi-AZ Deployment**: High availability across AWS Availability Zones
+- **AWS Marketplace**: Simple billing through your existing AWS account
+- **Global Distribution**: Deploy in 12+ AWS regions worldwide
+- **Auto-scaling**: Automatic scaling based on memory usage and throughput
+- **Enterprise Security**: Data encryption, compliance certifications, and access control
+- **24/7 Monitoring**: Comprehensive monitoring and alerting capabilities
+
+## Getting Started
+
+Get started with [Redis Cloud]({{< relref "/operate/rc/rc-quickstart" >}}) on AWS to create and manage your Redis databases with step-by-step setup instructions and best practices.