- Introducing Elasticsearch Service
- Adding data to Elasticsearch
- Migrating data
- Ingesting data from your application
- Ingest data with Node.js on Elasticsearch Service
- Ingest data with Python on Elasticsearch Service
- Ingest data from Beats to Elasticsearch Service with Logstash as a proxy
- Ingest data from a relational database into Elasticsearch Service
- Ingest logs from a Python application using Filebeat
- Ingest logs from a Node.js web application using Filebeat
- Configure Beats and Logstash with Cloud ID
- Best practices for managing your data
- Configure index management
- Enable cross-cluster search and cross-cluster replication
- Access other deployments of the same Elasticsearch Service organization
- Access deployments of another Elasticsearch Service organization
- Access deployments of an Elastic Cloud Enterprise environment
- Access clusters of a self-managed environment
- Enabling CCS/R between Elasticsearch Service and ECK
- Edit or remove a trusted environment
- Migrate the cross-cluster search deployment template
- Manage data from the command line
- Preparing a deployment for production
- Securing your deployment
- Monitoring your deployment
- Monitor with AutoOps
- Configure Stack monitoring alerts
- Access performance metrics
- Keep track of deployment activity
- Diagnose and resolve issues
- Diagnose unavailable nodes
- Why are my shards unavailable?
- Why is performance degrading over time?
- Is my cluster really highly available?
- How does high memory pressure affect performance?
- Why are my cluster response times suddenly so much worse?
- How do I resolve deployment health warnings?
- How do I resolve node bootlooping?
- Why did my node move to a different host?
- Snapshot and restore
- Managing your organization
- Your account and billing
- Billing Dimensions
- Billing models
- Using Elastic Consumption Units for billing
- Edit user account settings
- Monitor and analyze your account usage
- Check your subscription overview
- Add your billing details
- Choose a subscription level
- Check your billing history
- Update billing and operational contacts
- Stop charges for a deployment
- Billing FAQ
- Elasticsearch Service hardware
- Elasticsearch Service GCP instance configurations
- Elasticsearch Service GCP default provider instance configurations
- Elasticsearch Service AWS instance configurations
- Elasticsearch Service AWS default provider instance configurations
- Elasticsearch Service Azure instance configurations
- Elasticsearch Service Azure default provider instance configurations
- Change hardware for a specific resource
- Elasticsearch Service regions
- About Elasticsearch Service
- RESTful API
- Release notes
- Enhancements and bug fixes - December 2024
- Enhancements and bug fixes - November 2024
- Enhancements and bug fixes - Late October 2024
- Enhancements and bug fixes - Early October 2024
- Enhancements and bug fixes - September 2024
- Enhancements and bug fixes - Late August 2024
- Enhancements and bug fixes - Early August 2024
- Enhancements and bug fixes - July 2024
- Enhancements and bug fixes - Late June 2024
- Enhancements and bug fixes - Early June 2024
- Enhancements and bug fixes - Early May 2024
- Bring your own key, and more
- AWS region EU Central 2 (Zurich) now available
- GCP region Middle East West 1 (Tel Aviv) now available
- Enhancements and bug fixes - March 2024
- Enhancements and bug fixes - January 2024
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- AWS region EU North 1 (Stockholm) now available
- GCP regions Asia Southeast 2 (Indonesia) and Europe West 9 (Paris)
- Enhancements and bug fixes
- Enhancements and bug fixes
- Bug fixes
- Enhancements and bug fixes
- Role-based access control, and more
- Newly released deployment templates for Integrations Server, Master, and Coordinating
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Enhancements and bug fixes
- Cross environment search and replication, and more
- Enhancements and bug fixes
- Enhancements and bug fixes
- Azure region Canada Central (Toronto) now available
- Azure region Brazil South (São Paulo) now available
- Azure region South Africa North (Johannesburg) now available
- Azure region Central India (Pune) now available
- Enhancements and bug fixes
- Azure new virtual machine types available
- Billing Costs Analysis API, and more
- Organization and billing API updates, and more
- Integrations Server, and more
- Trust across organizations, and more
- Organizations, and more
- Elastic Consumption Units, and more
- AWS region Africa (Cape Town) available
- AWS region Europe (Milan) available
- AWS region Middle East (Bahrain) available
- Enhancements and bug fixes
- Enhancements and bug fixes
- GCP Private Link, and more
- Enhancements and bug fixes
- GCP region Asia Northeast 3 (Seoul) available
- Enhancements and bug fixes
- Enhancements and bug fixes
- Native Azure integration, and more
- Frozen data tier and more
- Enhancements and bug fixes
- Azure region Southcentral US (Texas) available
- Azure region East US (Virginia) available
- Custom endpoint aliases, and more
- Autoscaling, and more
- Cross-region and cross-provider support, warm and cold data tiers, and more
- Better feature usage tracking, new cost and usage analysis page, and more
- New features, enhancements, and bug fixes
- AWS region Asia Pacific (Hong Kong)
- Enterprise subscription self service, log in with Microsoft, bug fixes, and more
- SSO for Enterprise Search, support for more settings
- Azure region Australia East (New South Wales)
- New logging features, better GCP marketplace self service
- Azure region US Central (Iowa)
- AWS region Asia Pacific (Mumbai)
- Elastic solutions and Microsoft Azure Marketplace integration
- AWS region Pacific (Seoul)
- AWS region EU West 3 (Paris)
- Traffic management and improved network security
- AWS region Canada (Central)
- Enterprise Search
- New security setting, in-place configuration changes, new hardware support, and signup with Google
- Azure region France Central (Paris)
- Regions AWS US East 2 (Ohio) and Azure North Europe (Ireland)
- Our Elasticsearch Service API is generally available
- GCP regions Asia East 1 (Taiwan), Europe North 1 (Finland), and Europe West 4 (Netherlands)
- Azure region UK South (London)
- GCP region US East 1 (South Carolina)
- GCP regions Asia Southeast 1 (Singapore) and South America East 1 (Sao Paulo)
- Snapshot lifecycle management, index lifecycle management migration, and more
- Azure region Japan East (Tokyo)
- App Search
- GCP region Asia Pacific South 1 (Mumbai)
- GCP region North America Northeast 1 (Montreal)
- New Elastic Cloud home page and other improvements
- Azure regions US West 2 (Washington) and Southeast Asia (Singapore)
- GCP regions US East 4 (N. Virginia) and Europe West 2 (London)
- Better plugin and bundle support, improved pricing calculator, bug fixes, and more
- GCP region Asia Pacific Southeast 1 (Sydney)
- Elasticsearch Service on Microsoft Azure
- Cross-cluster search, OIDC and Kerberos authentication
- AWS region EU (London)
- GCP region Asia Pacific Northeast 1 (Tokyo)
- Usability improvements and Kibana bug fix
- GCS support and private subscription
- Elastic Stack 6.8 and 7.1
- ILM and hot-warm architecture
- Elasticsearch keystore and more
- Trial capacity and more
- APM Servers and more
- Snapshot retention period and more
- Improvements and snapshot intervals
- SAML and multi-factor authentication
- Next generation of Elasticsearch Service
- Branding update
- Minor Console updates
- New Cloud Console and bug fixes
- What’s new with the Elastic Stack
Billing Dimensions
editBilling Dimensions
editElasticsearch Service Billing is based on your actual usage across a number of dimensions, as follows:
Read on for detail about each of these billing dimensions.
Deployment capacity
editDeployment capacity refers to the cost of the nodes in your Elasticsearch deployment, plus additional node types such as Kibana, APM, and ML. Each node type is priced in terms of GB of RAM per hour (CPU and disk are scaled with RAM and included in this price). To calculate deployment capacity costs, we total up the cost of the nodes in your deployment(s) and multiply by GBs of RAM and how long they’ve been running.
Deployment capacity typically constitutes the majority of your bill, and is the easiest to understand and control.
How can I control the deployment capacity cost?
editDeployment capacity is purely a function of your current deployment configuration and time. To reduce this cost, you must configure your deployment to use fewer resources. To determine how much a particular deployment configuration will cost, try our Elasticsearch Service Pricing Calculator.
Data Transfer
editData Transfer accounts for the volume of data (payload) going into, out of, and between the nodes in a deployment, which is summed up to a cumulative amount within a billing cycle.
We meter and bill data transfer using three dimensions:
- 1. Data in (free)
- Data in accounts for all of the traffic going into the deployment. It includes index requests with data payload, as well as queries sent to the deployment (although the byte size of the latter is typically much smaller).
- 2. Data out
- Data out accounts for all of the traffic coming out of the deployment. This includes search results, as well as monitoring data sent from the deployment. The same rate applies regardless of the destination of the data, whether to the internet, to another region, or to a cloud provider account in the same region. Data coming out of the deployment through AWS PrivateLink, GCP Private Service Connect, or Azure Private Link, is also considered Data out.
- 3. Data inter-node
- Data inter-node accounts for all of the traffic sent between the components of the deployment. This includes the data sync between nodes of a cluster which is managed automatically by Elasticsearch cluster sharding. It also includes data related to search queries executed across multiple nodes of a cluster. Note that single-node Elasticsearch clusters typically have lower charges, but may still incur inter-node charges accounting for data exchanged with Kibana nodes or other nodes, such as machine learning or APM.
We provide a free allowance of 100GB per month, which includes the sum of data out and data inter-node, across all deployments in the account. Once this threshold is passed, a charge is applied for any data transfer used in excess of the 100GB monthly free allowance.
Data inter-node charges are currently waived for Azure deployments.
How can I control the Data Transfer cost?
editData transfer out of deployments and between nodes of the cluster is hard to control, as it is a function of the use case employed for the cluster and cannot always be tuned. Use cases such as batch queries executed at a frequent interval may be revisited to help lower transfer costs, if applicable. Watcher email alerts also count towards data transfer out of the deployment, so you may want to reduce their frequency and size.
The largest contributor to inter-node data transfer is usually shard movement between nodes in a cluster. The only way to prevent shard movement is by having a single node in a single availability zone. This solution is only possible for clusters up to 64GB RAM and is not recommended as it creates a risk of data loss. Oversharding can cause excessive shard movement. Avoiding oversharding can also help control costs and improve performance. Note that creating snapshots generates inter-node data transfer. The storage cost of snapshots is detailed later in this document.
The exact root cause of unusual data transfer is not always something we can identify as it can have many causes, some of which are out of our control and not associated with Cloud configuration changes. It may help to enable monitoring and examine index and shard activity on your cluster.
Storage
editStorage costs are tied to the cost of storing the backup snapshots in the underlying IaaS object store, such as AWS S3, Google Cloud GCS or Azure Storage. These storage costs are not for the disk storage that persists the Elasticsearch indices, as that is already included in the RAM Hours.
As is common with Cloud providers, we meter and bill snapshot storage using two dimensions:
- 1. Storage size (GB/month)
-
This is calculated by metering the storage space (GBs) occupied by all snapshots of all deployments tied to an account. The same unit price applies to all regions. To calculate the due charges, we meter the amount of storage on an hourly basis and produce an average size (in GB) for a given month. The average amount is then used to bill the account for the GB/month used within a billing cycle (a calendar month).
For example, if the storage used in April 2019 was 100GB for 10 days, and then 130GB for the remaining 20 days of the month, the average storage would be 120 GB/month, calculated as (100*10 + 130*20)/30.
We provide a free allowance of 100 GB/month to all accounts across all the account deployments. Any metered storage usage below that amount will not be billed. Whenever the 100 GB/month threshold is crossed, we bill for the storage used in excess of the 100GB/month free allowance.
- 2. Storage API requests (1K Requests/month)
-
These costs are calculated by counting the total number of calls to backup or restore snapshots made by all deployments associated with an account. Unlike storage size, this dimension is cumulative, summed up across the billing cycle, and is billed at a price of 1,000 requests.
We provide a free allowance of 100,000 API requests to all accounts each month across all the account deployments. Once this threshold is passed, we bill only for the use of API requests in excess of the free allowance.
A single snapshot operation does not equal a single API call. There could be thousands of API calls associated with a single snapshot operation, as different files are written, deleted, and modified. The price we list is per 1000 API calls, so a rate of $0.0018 for 1000 API calls would cost $1.80 for a million calls.
How can I control the storage cost?
editSnapshots in Elasticsearch Service save data incrementally at each snapshot event. This means that the effective snapshot size may be larger than the size of the current indices. The snapshot size increases as data is added or updated in the cluster, and deletions do not reduce the snapshot size until the snapshot containing that data is removed.
API requests are executed every time a snapshot is taken or restored, affecting usage costs. In the event that you have any automated processes that use the Elasticsearch API to create or restore snapshots, these should be set so as to avoid unexpected charges.
You can use Kibana to configure a snapshot lifecycle management (SLM) policy to automate when snapshots are created and deleted, along with other options. To learn more, refer to the Snapshot and Restore documentation.
Note that reducing either the snapshot frequency or retention period limits the availability and the recency of available data to restore from. Your snapshot policy should be configured with both costs and data availability in mind in order to minimize the potential for loss of data. Note also that reducing snapshot frequency and retention will not necessarily decrease your storage costs significantly. For example, if your dataset is only growing over time, then the total amount of data stored across all of your snapshots will be equal to your cluster size, whether that’s split across 10 snapshots or 100.
Synthetics
editSynthetic Monitoring browser tests are charged per test run (metered in 60 second increments). Lightweight tests are charged per location per month (per deployment) for up to 1k simultaneous test run capacity (~2.6 billion tests per month). Tests executed from private locations do not incur an execution charge. All test result data is stored in your deployment and billed for under existing dimensions.
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