AWS documentdb documentation change
Summary
Updated documentation for Amazon DocumentDB elastic clusters with minor grammatical corrections, clarification of shard configuration (adding details about writer instance and read replicas), and consistent capitalization of 'elastic clusters'. Also added Oxford commas and improved formatting.
Security assessment
The changes are primarily grammatical improvements and clarifications about shard configuration. There is no mention of security vulnerabilities, features, or concerns in the changes.
Diff
diff --git a/documentdb/latest/developerguide/elastic-how-it-works.md index 5907156d3..80cbbd4cc 100644 --- a/documentdb/latest/developerguide/elastic-how-it-works.md +++ b/documentdb/latest/developerguide/elastic-how-it-works.md @@ -30 +30 @@ The topics in this section provide information about the mechanisms and function -Amazon DocumentDB elastic clusters use hash-based sharding to partition data across distributed storage system. Sharding, also known as partitioning, splits large data sets into small data sets across multiple nodes enabling you to scale out your database beyond vertical scaling limits. Elastic clusters use the separation, or “decoupling”, of compute and storage in Amazon DocumentDB enabling you to scale independently of each other. Rather than re-partitioning collections by moving small chunks of data between compute nodes, elastic clusters copy data efficiently within the distributed storage system. +Amazon DocumentDB elastic clusters use hash-based sharding to partition data across a distributed storage system. Sharding, also known as partitioning, splits large data sets into small data sets across multiple nodes enabling you to scale out your database beyond vertical scaling limits. Elastic clusters use the separation, or “decoupling,” of compute and storage in Amazon DocumentDB, enabling you to scale independently of each other. Rather than re-partitioning collections by moving small chunks of data between compute nodes, elastic clusters copy data efficiently within the distributed storage system. @@ -38 +38 @@ Definitions of shard nomenclature: - * **Shard** — A shard provides compute for an elastic cluster. A shard by default will have two nodes. You can configure a maximum of 32 shards and each shard can have a maximum of 64 vCPUs. + * **Shard** — A shard provides compute for an elastic cluster. It will have a single writer instance and 0–15 read replicas. By default, a shard will have two instances: a writer and a single read replica. You can configure a maximum of 32 shards and each shard instance can have a maximum of 64 vCPUs. @@ -42 +42 @@ Definitions of shard nomenclature: - * **Shard collection** — A shard collection is a collection whose data is distributed across an elastic cluster in data partitions. + * **Sharded collection** — A sharded collection is a collection whose data is distributed across an elastic cluster in data partitions. @@ -65 +65 @@ When you scale out your database by adding additional shards, Amazon DocumentDB -Amazon DocumentDB supports migrating MongoDB sharded data to elastic clusters. Offline, online and hybrid migration methods are supported. For more information, see [Migrating to Amazon DocumentDB](./docdb-migration.html). +Amazon DocumentDB supports migrating MongoDB sharded data to elastic clusters. Offline, online, and hybrid migration methods are supported. For more information, see [Migrating to Amazon DocumentDB](./docdb-migration.html). @@ -69 +69 @@ Amazon DocumentDB supports migrating MongoDB sharded data to elastic clusters. O -Amazon DocumentDB Elastic Clusters provides the ability to increase the number of shards (scale out) in your elastic cluster, and the number of vCPUs applied to each shard (scale up). You can also reduce the number of shards and compute capacity (vCPUs) as needed. +Amazon DocumentDB elastic clusters provide the ability to increase the number of shards (scale out) in your elastic cluster, and the number of vCPUs applied to each shard (scale up). You can also reduce the number of shards and compute capacity (vCPUs) as needed. @@ -79 +79 @@ Cluster-level scaling is also available. For more information, see [Scaling Amaz -Amazon DocumentDB is designed to be reliable, durable, and fault tolerant. To improve availability, elastic clusters deploys two nodes per shard placed across different Availability Zones. Amazon DocumentDB includes several automatic features that make it a reliable database solution. For more information, see [Amazon DocumentDB reliability](./how-it-works.html#how-it-works.reliability). +Amazon DocumentDB is designed to be reliable, durable, and fault-tolerant. To improve availability, elastic clusters deploy two nodes per shard placed across different Availability Zones. Amazon DocumentDB includes several automatic features that make it a reliable database solution. For more information, see [Amazon DocumentDB reliability](./how-it-works.html#how-it-works.reliability). @@ -83 +83 @@ Amazon DocumentDB is designed to be reliable, durable, and fault tolerant. To im -Amazon DocumentDB data is stored in a cluster volume, which is a single, virtual volume that uses solid state drives (SSDs). A cluster volume consists of six copies of your data, which are replicated automatically across multiple Availability Zones in a single AWS Region. This replication helps ensure that your data is highly durable, with less possibility of data loss. It also helps ensure that your cluster is more available during a failover because copies of your data already exist in other Availability Zones. For more details on storage, high availability and replication see [Amazon DocumentDB: how it works](./how-it-works.html). +Amazon DocumentDB data is stored in a cluster volume, which is a single, virtual volume that uses solid state drives (SSDs). A cluster volume consists of six copies of your data, which are replicated automatically across multiple Availability Zones in a single AWS Region. This replication helps ensure that your data is highly durable, with less possibility of data loss. It also helps ensure that your cluster is more available during a failover because copies of your data already exist in other Availability Zones. For more details on storage, high availability, and replication see [Amazon DocumentDB: how it works](./how-it-works.html). @@ -119 +119 @@ The following functional differences exist between Amazon DocumentDB 4.0 and ela - // Elastic Clusters + // Elastic clusters @@ -131 +131 @@ The following functional differences exist between Amazon DocumentDB 4.0 and ela - * In elastic clusters, the `find` commands with `$regex` and `$options` query parameters return an error: "Cannot set options in both $regex and $options". + * In elastic clusters, the `find` commands with `$regex` and `$options` query parameters return an error: "Cannot set options in both $regex and $options." @@ -146 +146 @@ In Amazon DocumentDB 4.0, `$indexOfCP` returns "0" when the `start` position is - * With elastic clusters, projection operations in `_id fields`, for example: `{"_id.nestedField" : 1}`, return documents that only include the projected field. Whereas in Amazon DocumentDB 4.0, nested field projection commands do not filter out any document. + * With elastic clusters, projection operations in `_id fields`, e.g., `{"_id.nestedField" : 1}`, return documents that only include the projected field. Meanwhile, in Amazon DocumentDB 4.0, nested field projection commands do not filter out any document.