fix: vale checks

docs/products/kafka/concepts/kafka-tiered-storage.md

@@ -3,6 +3,7 @@ title: Tiered storage in Aiven for Apache Kafka® overview
 ---
 
 Tiered storage in Aiven for Apache Kafka® helps you manage data more effectively by using two different storage types: local disk and remote cloud storage solutions like AWS S3, Google Cloud Storage, and Azure Blob Storage.
+
 This feature lets you allocate frequently accessed data to high-speed local disks while
 moving less critical or infrequently accessed data to more cost-effective remote storage
 solutions. You can store data on specific topics indefinitely without running out of

docs/products/kafka/concepts/tiered-storage-guarantees.md

@@ -2,8 +2,7 @@
 title: Guarantees
 ---
 
-With Aiven for Apache Kafka®'s tiered storage, there are two primary
-types of data retention guarantees: *total retention* and *local
+With Aiven for Apache Kafka®'s tiered storage, there are two primary types of data retention guarantees: *total retention* and *local
 retention*.
 
 **Total retention**: Tiered storage ensures that your data remains available up to the

docs/products/kafka/concepts/tiered-storage-how-it-works.md

@@ -1,9 +1,9 @@
 ---
 title: How tiered storage works in Aiven for Apache Kafka®
+sidebar_label: How it works
 ---
 
-Aiven for Apache Kafka® tiered storage is a feature that optimizes data
-management across two distinct storage tiers:
+Aiven for Apache Kafka® tiered storage is a feature that optimizes data management across two distinct storage tiers:
 
 -   **Local tier**: Primarily consists of faster and typically more
     expensive storage solutions like solid-state drives (SSDs).
@@ -24,8 +24,8 @@ interact with Apache Kafka in the same way, regardless of whether tiered
 storage is enabled or not.
 
 Administrators can configure tiered storage per topic by defining the
-retention period and retention bytes to specify how much data should be
-retained on the local disk instead of remote storage.
+retention period and retention bytes to specify how much data is retained on the local
+disk instead of remote storage.
 
 ## Local vs. remote data retention
 
@@ -44,19 +44,19 @@ threshold.
 Data is organized into segments, which are uploaded to remote storage
 individually. The active (newest) segment remains in local storage,
 which means that the segment size can also influence local data
-retention. For instance, if the local retention threshold is 1 GB, but
-the segment size is 2 GB, the local storage will exceed the 1 GB limit
-until the active segment is rolled over and uploaded to remote storage.
+retention. For instance, if the local retention threshold is 1 GB, but the segment
+size is 2 GB, the local storage exceeds the 1 GB limit until the active segment is
+rolled over and uploaded to remote storage.
 
 ## Asynchronous uploads and replication
 
 Data is transferred to remote storage asynchronously and does not
 interfere with the producer activity. While the Kafka broker aims to
 move data as swiftly as possible, certain conditions, such as high
-ingestion rate or connectivity issues, may cause more data to be stored
+ingestion rate or connectivity issues, can cause more data to be stored
 in the local storage than the specified local retention policy.
 
-Any data exceeding the local retention threshold will not be purged by
+Any data exceeding the local retention threshold is not be purged by
 the log cleaner until it is successfully uploaded to remote storage. The
 replication factor is not considered during the upload process, and only
 one copy of each segment is uploaded to the remote storage. Most remote

docs/products/kafka/concepts/tiered-storage-limitations.md

@@ -2,10 +2,8 @@
 title: Trade-offs and limitations
 ---
 
-The main trade-off of tiered storage is the higher latency while
-accessing and reading data from remote storage compared to local disk
-storage. While adding local caching can partially solve this problem, it
-cannot eliminate the latency completely.
+The main trade-off of tiered storage is the higher latency while accessing and reading data from remote storage compared to local disk
+storage. While adding local caching can partially solve this problem, it cannot eliminate the latency completely.
 
 ## Limitations
 

docs/products/kafka/howto/configure-topic-tiered-storage.md

@@ -2,10 +2,8 @@
 title: Enable and configure tiered storage for topics
 ---
 
-Aiven for Apache Kafka® allows you to configure tiered storage
-and set retention policies for individual topics. Learn how to configure
-tiered storage for individual topics and set local retention policies
-step by step.
+Aiven for Apache Kafka® allows you to configure tiered storage and set retention policies for individual topics. Learn how to configure
+tiered storage for individual topics and set local retention policies step by step.
 
 ## Prerequisite
 

sidebars.ts

@@ -561,7 +561,6 @@ const sidebars: SidebarsConfig = {
                     id: 'products/kafka/concepts/kafka-tiered-storage',
                   },
                   items: [
-                    'products/kafka/concepts/kafka-tiered-storage',
                     'products/kafka/concepts/tiered-storage-how-it-works',
                     'products/kafka/concepts/tiered-storage-guarantees',
                     'products/kafka/concepts/tiered-storage-limitations',