Merge pull request #305709 from flang-msft/fxl---retirement-include

fxl---draft of include file for retirement

Author: Stacyrch140

articles/azure-cache-for-redis/cache-administration.md

@@ -10,6 +10,8 @@ appliesto:
 ---
 # Administration tasks for Azure Cache for Redis
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 This article describes tasks such as [rebooting](#reboot), [flushing](#flush-data) a cache,  and [Update channel and Schedule updates](#update-channel-and-schedule-updates) for your Azure Cache for Redis instances.
 
 ## Reboot

articles/azure-cache-for-redis/cache-azure-active-directory-for-authentication.md

@@ -11,6 +11,8 @@ appliesto:
 
 # Use Microsoft Entra for cache authentication
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 Azure Cache for Redis offers two methods to [authenticate](cache-configure.md#authentication) to your cache instance: access keys and Microsoft Entra.
 
 Although access key authentication is simple, it comes with a set of challenges around security and password management. For contrast, in this article, you learn how to use a Microsoft Entra token for cache authentication.

articles/azure-cache-for-redis/cache-best-practices-client-libraries.md

@@ -12,6 +12,8 @@ ms.custom: devx-track-java, devx-track-javaee, devx-track-javaee-liberty, devx-t
 
 # Client libraries
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 Azure Cache for Redis is based on the Redis open-source, in-memory data store. Redis clients for many programming languages can access Azure Redis. Your application can use any client library that's compatible with open-source Redis to connect to your Azure Redis cache.
 
 Each client library has its own API that calls Redis servers using Redis commands. The client libraries are built to communicate with any Redis server.

articles/azure-cache-for-redis/cache-best-practices-connection.md

@@ -10,6 +10,8 @@ appliesto:
 
 # Connection resilience
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 ## Retry commands
 
 Configure your client connections to retry commands with exponential backoff. For more information, see [retry guidelines](/azure/architecture/best-practices/retry-service-specific#azure-cache-for-redis).

articles/azure-cache-for-redis/cache-best-practices-development.md

@@ -14,6 +14,8 @@ appliesto:
 
 # Development
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 ## Connection resilience and server load
 
 When developing client applications, be sure to consider the relevant best practices for [connection resilience](cache-best-practices-connection.md) and [managing server load](cache-best-practices-server-load.md).

articles/azure-cache-for-redis/cache-best-practices-enterprise-tiers.md

@@ -15,6 +15,8 @@ appliesto:
 
 # What are the best practices for the Enterprise and Enterprise Flash tiers
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 Here are the best practices when using the Enterprise and Enterprise Flash tiers of Azure Cache for Redis.
 
 ## Zone Redundancy

articles/azure-cache-for-redis/cache-best-practices-kubernetes.md

@@ -11,6 +11,8 @@ appliesto:
 
 # Kubernetes-hosted client applications
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 This article provides best practices for using Azure Cache for Redis in Kubernetes-hosted client applications.
 
 ## Stagger multiple connections

articles/azure-cache-for-redis/cache-best-practices-memory-management.md

@@ -14,6 +14,8 @@ appliesto:
 
 # Memory management
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 This article describes best practices for memory management in Azure Cache for Redis.
 
 ## Choose the right eviction policy

articles/azure-cache-for-redis/cache-best-practices-performance.md

@@ -14,6 +14,8 @@ appliesto:
 
 # Performance testing
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 Testing the performance of a Redis instance can be a complicated task. The performance of a Redis instance can vary based on parameters such as the number of clients, the size of data values, and whether pipelining is being used. There also can be a tradeoff between optimizing throughput or latency.
 
 Fortunately, several tools exist to make benchmarking Redis easier. Two of the most popular tools are **[redis-benchmark](https://redis.io/docs/latest/operate/oss_and_stack/management/optimization/benchmarks/)** and **[memtier-benchmark](https://github.com/redislabs/memtier_benchmark)**. This article focuses on redis-benchmark.

articles/azure-cache-for-redis/cache-best-practices-scale.md

@@ -13,6 +13,8 @@ appliesto:
 
 # Scaling
 
+[!INCLUDE [cache-retirement-alert](includes/cache-retirement-alert.md)]
+
 ## Scaling under load
 
 While scaling a cache under load, configure your `maxmemory-reserved` setting to improve system responsiveness. For more information, see [Configure your maxmemory-reserved setting](cache-best-practices-memory-management.md#configure-your-maxmemory-reserved-setting).