Elasticsearch Replication Fundamentals for Data Resilience

Elasticsearch replication is a crucial aspect of ensuring data resilience in your Elasticsearch cluster. It allows you to maintain multiple copies of your data, making it easier to recover in case of data loss or hardware failure.

Data replication in Elasticsearch involves creating a copy of your data on multiple nodes, which can be located in different data centers or even on different continents. This ensures that your data is always available, even if one of the nodes goes down.

A common replication strategy is to use a master-slave replication model, where one node is designated as the master and the others act as slaves. The master node is responsible for accepting incoming data and replicating it to the slave nodes.

With Elasticsearch replication, you can choose from a variety of replication factors, including 1, 2, and 3. The replication factor determines how many copies of your data are maintained in the cluster.

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Replication in Elasticsearch is configured at the index level, where you can select how many replicas of each shard you want, with one being the default value.

Replica shards are complete copies of shards that can serve search requests, similar to primary shards.

A shard that has been replicated one or more times is referred to as the primary shard.

Replication works by creating copies of each shard in an index, known as replicas or replica shards.

A primary shard and its replica shards are collectively known as a replication group.

Elasticsearch automatically coordinates where queries will be executed and parallelization.

Elasticsearch only adds replica shards for clusters with multiple nodes.

If your cluster has only one node, replication won’t be helpful if the node fails.

It’s necessary to have at least two nodes in a production setup to protect against data loss.

Snapshots provide a way to take backups so that you can restore data to a point in time.

Replication cannot help with data recovery from a point in time, only with ensuring you don’t lose your latest data.

For your interest: Elasticsearch _template

Replication is a way to prevent data loss in Elasticsearch, especially when a node experiences a failure like a disk failure.

Elasticsearch supports shard replication natively, which is enabled by default without any configuration.

Replication works by creating a copy of the data, so if one node fails, the data can be retrieved from the replica.

If two nodes break down at the same time, you can restore the data from another data source, such as a relational database.

Typically, one or two replicas are sufficient, but this depends on how critical your setup is.

For critical systems, it's recommended to replicate shards twice or more.

This also means that for a production setup, you will need at least two nodes to protect yourself against data loss.

Replication ensures that you won't lose the data that a given index stores at the current point in time.

Here's a summary of the replication purposes:

Replication only works with live data, so it's not a substitute for snapshots, which enable you to export the current state of the cluster or specific indices to a file.

Cross Cluster Replication is a powerful feature that allows you to replicate changes from one Elasticsearch cluster to another. This means you can have a primary cluster where data is actively being written, and a secondary cluster that mirrors that data in real-time.

To set up Cross Cluster Replication, you need to follow a few steps, including connecting a local cluster to a remote cluster, creating a leader index in the remote cluster, and creating a follower index that replicates the leader index. The follower index is passive and can serve read requests and searches, but can't accept direct writes.

You can define remote clusters through an API call or the Kibana UI. To define a remote cluster via API, you'll need to specify the alias, endpoint, and seeds. For example, you can use the API call `GET /_remote/info` to retrieve all configured remote cluster information.

Replication occurs using the Elasticsearch transport protocol, and the default port is 9300. However, the cluster is listening for the HTTP protocol on port 9200. You can also define remote clusters in the Kibana UI by navigating to Stack Management > Remote Clusters.

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To replicate an index, you'll need to create a follower index with the `create follower` API, referencing the remote cluster and leader index. For example, you can replicate an index called `syslog-copy` from the `DC-cluster` to the `DR-cluster`.

Cross Cluster Replication is a platinum-level feature that's available through a 30-day trial license. You can activate the trial license through the `start trial` API or directly from Kibana.

Here are the basic steps to set up Cross Cluster Replication:

Cluster health is a critical aspect of Elasticsearch replication, and it's essential to monitor it closely to ensure your cluster is running smoothly. A cluster's health is determined by the number of active shards, the number of shards that are not yet allocated, and the number of shards that are in the process of being relocated.

Elasticsearch provides a simple way to check the health of your cluster using the Cluster Health API. This API returns a simple health status, which can be either green, yellow, or red. A green status indicates that all shards are active and available, a yellow status indicates that some shards are not yet allocated, and a red status indicates that there are problems with the cluster.

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In a healthy cluster, all shards should be active and available. If a shard becomes unavailable, it can cause problems with the cluster's overall health. Elasticsearch replication helps to prevent this by automatically relocating shards to other nodes in the cluster.

Elasticsearch has a built-in mechanism for handling shard failures, which is called the "primary shard" strategy. This strategy ensures that a primary shard is always available, even if one of the replica shards fails. This helps to maintain the cluster's overall health and prevent data loss.

The number of replica shards can also impact cluster health. Having too few replica shards can leave the cluster vulnerable to data loss in the event of a node failure. On the other hand, having too many replica shards can increase the load on the cluster and slow down performance.

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To get started with Elasticsearch replication, you need to meet some prerequisites. Local and remote clusters must be version 6.7.x or higher, and they must be in compatible versions. Local and remote cluster must trust each other.

Additionally, ensure that security configurations are in place if your clusters use Elasticsearch’s security features. Clusters should be properly configured and operational, and the transport and HTTP settings on both clusters must allow for communication between them.

Here are the specific requirements to keep in mind:

Keep in mind that Elasticsearch replication has some limitations. It's designed to replicate user-generated indices only, and doesn't currently replicate system indices, machine learning jobs, index templates, or other specific types of data.

A unique perspective: Elasticsearch Indices

Before you start working with CCR, there are some essential prerequisites to consider.

First and foremost, your local and remote clusters must be version 6.7.x or higher. This ensures that they have the necessary features and capabilities to support CCR.

To ensure seamless communication between clusters, local and remote clusters must be in compatible versions. This prevents potential compatibility issues that can arise from mixing different versions.

For CCR to work, local and remote cluster must trust each other. This means that they need to have a secure connection established between them.

Additional reading: Elasticsearch Version History

Security is also a crucial aspect to consider. If your clusters use Elasticsearch's security features, ensure that security configurations are in place.

Before proceeding, make sure that your clusters are properly configured and operational. This includes checking that the transport and HTTP settings on both clusters allow for communication between them.

Here's a quick rundown of the prerequisites:

Limitations are an important consideration when it comes to cross-cluster replication. It's not designed to replicate everything, and some data will need to be manually replicated to a remote cluster.

System indices are not replicated, which means you'll need to find another way to keep them in sync across clusters.

Machine learning jobs are also not replicated, so you'll need to set up a separate process for these.

Index templates, index lifecycle management, and snapshot lifecycle management policies are not replicated either.

User permissions and role mappings, snapshot repository settings, cluster settings, and searchable snapshots are also not replicated.

For another approach, see: Elasticsearch Index Format

Here are some of the specific things that aren't replicated by cross-cluster replication:

You'll need to replicate these manually to a remote cluster if you want them to be in sync.

Elasticsearch throws a warning if new replicas are assigned to nodes with more than 85% disk usage.

This warning is a sign that your cluster is running low on disk space, and you should investigate ways to free up space or expand your storage.

If you've created too many replicas, you may run into problems if there aren't enough resources available in the cluster.

To avoid this issue, monitor your cluster's resources and adjust your replication settings accordingly.

Additional reading: Elastic Cross Cluster Search

Getting Started with Elasticsearch Replication is easier than you think. CCR, or Cross-Cluster Replication, is a platinum level feature that's available for a 30-day trial license. This means you can try it out without committing to a purchase.

To activate the trial license, you can use the start trial API or directly from Kibana.

Curious to learn more? Check out: Azure Replication