# Amazon OpenSearch Service Amazon offering for managed OpenSearch clusters. 1. [Storage](#storage) 1. [UltraWarm storage](#ultrawarm-storage) 1. [Cold storage](#cold-storage) 1. [Operations](#operations) 1. [Migrate indexes to UltraWarm storage](#migrate-indexes-to-ultrawarm-storage) 1. [Return warm indexes to hot storage](#return-warm-indexes-to-hot-storage) 1. [Migrate indexes to Cold storage](#migrate-indexes-to-cold-storage) 1. [Best practices](#best-practices) 1. [Dedicated master nodes](#dedicated-master-nodes) 1. [Cost-saving measures](#cost-saving-measures) 1. [Further readings](#further-readings) 1. [Sources](#sources) ## Storage Clusters can be set up to use the [hot-warm architecture]. _Hot_ storage provides the fastest possible performance for indexing and searching **new** data. _Data_ nodes use **hot** storage in the form of instance stores or EBS volumes attached to each node. Indexes that are **not** actively written to (e.g., immutable data like logs), that are queried less frequently, or that don't need the hot storage's performance can be moved to _warm_ storage. Warm indexes are **read-only** unless returned to hot storage.
Aside that, they behave like any other hot index. _UltraWarm_ nodes use **warm** storage in the form of S3 and caching. AWS' managed OpenSearch service offers also _Cold_ storage.
It is meant for data accessed only occasionally or no longer in active use.
Cold indexes are normally detached from nodes and stored in S3, meaning one **can't** read from nor write to cold indexes by default.
Should one need to query them, one needs to selectively attach them to UltraWarm nodes. Use [Index State Management][index state management in amazon opensearch service] to automate indexes migration to lower storage states after they meet specific conditions. ### UltraWarm storage Refer [UltraWarm storage for Amazon OpenSearch Service]. Requirements: - OpenSearch/ElasticSearch >= v6.8. - Dedicated master nodes. - No `t2` nor `t3` instances types as data nodes. - When using a Multi-AZ architecture with _Standby_ domain, the number of warm nodes **must** be a multiple of the number of Availability Zones being used. - Others. Considerations: - When calculating UltraWarm storage requirements, consider only the size of the primary shards.
S3 removes the need for replicas and abstracts away any operating system or service considerations. - Dashboards and `_cat/indices` will still report UltraWarm index size as the _total_ of all primary and replica shards. - There are [limits](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/limits.html#limits-ultrawarm) to the amount of storage each instance type can address and the maximum number of warm nodes supported by Domains. - Amazon recommends a maximum shard size of 50 GiB. - Upon enablement, UltraWarm might not be available to use for several hours even if the domain state is _Active_. - The minimum amount of UltraWarm instances allowed by AWS is 2. > Before disabling UltraWarm, one **must** either delete **all** warm indexes or migrate them back to hot storage.
> After warm storage is empty, wait five minutes before attempting to disable UltraWarm. ### Cold storage Refer [Cold storage for Amazon OpenSearch Service]. Requirements: - OpenSearch/ElasticSearch >= v7.9. - [UltraWarm storage] enabled for the same domain. Considerations: - One **can't** read from nor write to cold indexes. ## Operations ### Migrate indexes to UltraWarm storage > Indexes' health **must** be green to perform migrations. Migrations are executed one index at a time, sequentially.
There can be up to 200 migrations in the queue.
Any request that exceeds the limit will be rejected. > Index migrations to UltraWarm storage require a force merge operation, which purges documents that were marked for > deletion.
> By default, UltraWarm merges indexes into one segment. One can set this value up to 1000. Migrations might fail during snapshots, shard relocations, or force merges.
Failures during snapshots or shard relocation are typically due to node failures or S3 connectivity issues.
Lack of disk space is usually the underlying cause of force merge failures. Start migration: ```plaintext POST _ultrawarm/migration/my-index/_warm ``` Check the migration's status: ```plaintext GET _ultrawarm/migration/my-index/_status ``` ```json { "migration_status": { "index": "my-index", "state": "RUNNING_SHARD_RELOCATION", "migration_type": "HOT_TO_WARM", "shard_level_status": { "running": 0, "total": 5, "pending": 3, "failed": 0, "succeeded": 2 } } } ``` If a migration is in the queue but has not yet started, it can be removed from the queue: ```plaintext POST _ultrawarm/migration/_cancel/my-index ``` ### Return warm indexes to hot storage Migrate them back to hot storage: ```plaintext POST _ultrawarm/migration/my-index/_hot ``` There can be up to 10 queued migrations from warm to hot storage at a time.
Migrations requests are processed one at a time in the order they were queued. Indexes return to hot storage with **one** replica. ### Migrate indexes to Cold storage As for [UltraWarm storage][migrate indexes to ultrawarm storage], just change the endpoints accordingly: ```plaintext POST _ultrawarm/migration/my-index/_cold GET _ultrawarm/migration/my-index/_status POST _ultrawarm/migration/_cancel/my-index GET _cold/indices/_search POST _cold/migration/_warm GET _cold/migration/my-index/_status POST _cold/migration/my-index/_cancel ``` ## Best practices Refer [Operational best practices for Amazon OpenSearch Service] and [Best practices for configuring your Amazon OpenSearch Service domain]. - Use [dedicated master nodes] in **production** clusters. - Use Multi-AZ deployments in **production** clusters. ### Dedicated master nodes Refer [Dedicated master nodes in Amazon OpenSearch Service]. They increase cluster stability by performing cluster management tasks.
They do **not** hold data nor respond to data upload requests. Only **one** of the dedicated master nodes is active, while the others wait as backup in case the active dedicated master node fails. All data upload requests are served by the data nodes, while all cluster management tasks are offloaded to the active dedicated master node. Cluster management tasks are: - Tracking all nodes in the cluster. - Maintaining routing information for nodes in the cluster. - Tracking the number of indexes in the cluster. - Tracking the number of shards belonging to each index. - Updating the cluster state after state changes.
I.e., creating an index and adding or removing nodes in the cluster. - Replicating changes to the cluster state across all nodes in the cluster. - Monitoring the health of all cluster nodes by sending heartbeat signals. Use Multi-AZ with Standby **adds** three dedicated master nodes to each OpenSearch Service domain it is enabled for. Even deploying in Single-AZ mode, **three** dedicated master nodes are recommended for stability.
In any case, **never** choose an even number of dedicated master nodes to avoid _split brain_ problems. If a cluster has an **even** number of master-eligible nodes, OpenSearch and Elasticsearch versions 7.x and later will ignore one node so that the voting configuration is always an odd number.
As such, an even number of dedicated master nodes are essentially equivalent to that number - 1. > If a cluster doesn't have the necessary quorum to elect a new master node, write and read requests to the cluster will > both fail.
> This behavior differs from the OpenSearch default. Master nodes size is highly correlated with the data instance size and the number of instances, indexes, and shards they can manage. ## Cost-saving measures - Choose appropriate [instance types and sizes][supported instance types in amazon opensearch service].
Leverage the ability to select them to tailor the service offering to one's needs. > [OR1 instances][or1 storage for amazon opensearch service] **cannot** (currently?) be selected as master nodes.
> They must also be selected **at domain creation**. - Consider using reserved instances for long-term savings. - Enable index-level compression to save storage space and reduce I/O costs. - Use Index Lifecycle Management policies to move old data in lower storage tiers. - Consider using [S3] as data store for infrequently accessed or archived data. - Consider adjusting the frequency and retention period of snapshots.
By default, AWS OpenSearch takes **daily** snapshots and retains them for **14 days**. - If using `gp2` EBS volumes, move to `gp3`. - Enable autoscaling (serverless only). - Optimize indexes' sharding and replication. - Optimize queries. - Optimize data ingestion. - Optimize indexes' mapping and settings. - Optimize the JVM heap size. - Summarize and compress historical data using [index rollups]. - Check out caches. - Reduce the number of requests using throttling and rate limiting. - Move to Single-AZ deployments. - Filter out and compress source data before sending it to OpenSearch to reduce the storage footprint and data transfer costs. - Share a single OpenSearch cluster with multiple accounts to reduce the overall number of instances and resources. ## Further readings - [OpenSearch] - [Hot-warm architecture] - [Supported instance types in Amazon OpenSearch Service] ### Sources - [Cost-saving strategies for AWS OpenSearch(FinOps): optimize performance without breaking the bank] - [OpenSearch cost optimization: 12 expert tips] - [How do I reduce the cost of using OpenSearch Service domains?] - [Right-size Amazon OpenSearch instances to cut costs by 50% or more] - [Reducing Amazon OpenSearch service costs: our journey to over 60% savings] - [UltraWarm storage for Amazon OpenSearch Service] - [Index State Management in Amazon OpenSearch Service] - [Cold storage for Amazon OpenSearch Service] - [Lower your Amazon OpenSearch Service storage cost with gp3 Amazon EBS volumes] - [Dedicated master nodes in Amazon OpenSearch Service] - [Best practices for configuring your Amazon OpenSearch Service domain] - [Operational best practices for Amazon OpenSearch Service] - [OR1 storage for Amazon OpenSearch Service] [migrate indexes to ultrawarm storage]: #migrate-indexes-to-ultrawarm-storage [ultrawarm storage]: #ultrawarm-storage [dedicated master nodes]: #dedicated-master-nodes [hot-warm architecture]: ../../opensearch.md#hot-warm-architecture [opensearch]: ../../opensearch.md [s3]: s3.md [best practices for configuring your amazon opensearch service domain]: https://aws.amazon.com/blogs/big-data/best-practices-for-configuring-your-amazon-opensearch-service-domain/ [cold storage for amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/cold-storage.html [dedicated master nodes in amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/managedomains-dedicatedmasternodes.html [how do i reduce the cost of using opensearch service domains?]: https://repost.aws/knowledge-center/opensearch-domain-pricing [index state management in amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ism.html [lower your amazon opensearch service storage cost with gp3 amazon ebs volumes]: https://aws.amazon.com/blogs/big-data/lower-your-amazon-opensearch-service-storage-cost-with-gp3-amazon-ebs-volumes/ [operational best practices for amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/bp.html [or1 storage for amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/or1.html [supported instance types in amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/supported-instance-types.html [ultrawarm storage for amazon opensearch service]: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ultrawarm.html [cost-saving strategies for aws opensearch(finops): optimize performance without breaking the bank]: https://ramchandra-vadranam.medium.com/cost-saving-strategies-for-aws-opensearch-finops-optimize-performance-without-breaking-the-bank-f87f0bb2ce37 [index rollups]: https://opensearch.org/docs/latest/im-plugin/index-rollups/index/ [opensearch cost optimization: 12 expert tips]: https://opster.com/guides/opensearch/opensearch-capacity-planning/how-to-reduce-opensearch-costs/ [reducing amazon opensearch service costs: our journey to over 60% savings]: https://medium.com/kreuzwerker-gmbh/how-we-accelerate-financial-and-operational-efficiency-with-amazon-opensearch-6b86b41d50a0 [right-size amazon opensearch instances to cut costs by 50% or more]: https://cloudfix.com/blog/right-size-amazon-opensearch-instances-cut-costs/