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The dependable small-deployment design is three services on one Ubuntu VPS: CouchDB stores documents, Logstash consumes CouchDB’s continuous _changes feed, and Elasticsearch serves search queries. Keep CouchDB and Elasticsearch on localhost or a private interface, persist Logstash’s sequence state, and put a TLS-authenticated reverse proxy or private network in front of any endpoint that must be reached remotely.
This is an event-driven integration, not a built-in CouchDB connector. The procedure below installs each service, streams creates and updates into an Elasticsearch index, propagates deletes, and lets the pipeline resume after a restart.
What you are building
CouchDB remains the system of record. Every database change appears in its _changes feed. Logstash’s couchdb_changes input maintains a connection to that feed and turns each change into an event. The Elasticsearch output writes those events to a deterministic index while preserving the CouchDB document ID as Elasticsearch’s _id.
That ID mapping is essential: an update then replaces the existing search document instead of creating a second copy. A deletion event must be sent as an Elasticsearch delete operation. Because a changes feed can repeat events and is only partially ordered, the pipeline must be idempotent.
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Recommended service layout
- CouchDB: localhost or a private address, normally port 5984.
- Logstash: reads the continuous feed and stores its last sequence on persistent disk.
- Elasticsearch: localhost or a private address, normally port 9200, with authentication and TLS enabled.
- Reverse proxy or private network: the only remotely reachable path when applications or administrators are not on the VPS itself.
Single node or cluster?
| Choice | Use it when | Trade-offs |
|---|---|---|
| Single CouchDB and single-node Elasticsearch | A small application, development environment, or moderate workload fits on one VPS. | Lowest cost and simplest operations, but one host is a single failure domain. |
| CouchDB and Elasticsearch clusters | You need node-level availability, larger data sets, or independent scaling. | More memory, storage, networking, backups, monitoring, and configuration discipline. |
| Application writes directly to Elasticsearch | The application already owns indexing logic and can handle retries and replay. | Maximum control, but every client must implement consistency, delete handling, and recovery. |
| Logstash bridge | You want one replayable integration layer between CouchDB and Elasticsearch. | Introduces another service to operate, but centralizes credentials, transformations, and sequence tracking. |
No universal CPU, RAM, or disk size is correct for this combination. Requirements depend on document count, attachment volume, mapping complexity, indexing rate, retention, shard count, and how much search traffic the VPS serves. Measure those variables and leave room for operating-system and recovery overhead rather than choosing a fixed specification.
Prepare the Ubuntu VPS
1. Create a safe administrative workflow
- Provision a supported Ubuntu LTS release. The current Apache CouchDB package guidance lists Ubuntu 22.04 (jammy) and Ubuntu 24.04 (noble) convenience packages.
- Create a non-root administrator, install its SSH key, and use
sudofor administrative commands. Disable password SSH authentication after key login has been tested. - Update the host and install basic tools:
sudo apt update
sudo apt full-upgrade -y
sudo apt install -y curl gnupg ca-certificates lsb-release apt-transport-https
2. Plan persistent storage
Reserve persistent space for CouchDB’s data directory, Elasticsearch’s data and transaction logs, Logstash’s queue and sequence file, operating-system logs, and backups. Do not place the sequence file on ephemeral storage: losing it can force an unintended replay. Keep enough free space for Elasticsearch segment merges and CouchDB compaction, which temporarily require additional disk.
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sudo apt install -y ufw
sudo ufw default deny incoming
sudo ufw default allow outgoing
sudo ufw allow from TRUSTED_ADMIN_IP to any port 22 proto tcp
sudo ufw enable
sudo ufw status verbose
Replace TRUSTED_ADMIN_IP with the administrator’s actual address or management network. Do not open 5984, 9200, CouchDB cluster ports, or arbitrary Erlang ports to the public internet.
Install and configure CouchDB
1. Add the Apache package source
Use Apache CouchDB’s current Debian/Ubuntu installation instructions to install its signing key and add the repository entry matching your Ubuntu codename (jammy or noble). After adding the signed repository, refresh package metadata and install CouchDB:
sudo apt update
sudo apt install -y couchdbDuring the package dialog, select single-node for this deployment, choose the intended bind address, and set an administrator password. CouchDB 3.0 and later will not start without an administrator account.
2. Verify the bind address and administrator
For a same-host pipeline, bind CouchDB to 127.0.0.1. If another private host must access it, bind only to that private interface and restrict the firewall to that network. Never publish port 5984 directly as an unauthenticated internet service.
sudo systemctl enable --now couchdb
sudo systemctl status couchdb
curl --fail --user 'ADMIN_USER:ADMIN_PASSWORD' http://127.0.0.1:5984/
curl --fail --user 'ADMIN_USER:ADMIN_PASSWORD' http://127.0.0.1:5984/_up
The first request should return CouchDB’s version and welcome information; /_up should report a healthy node. Replace the sample credentials in your shell, and avoid placing real passwords in shell history.
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3. Create the application database and least-privilege reader
Create the database before starting the pipeline:
curl --user 'ADMIN_USER:ADMIN_PASSWORD' -X PUT
http://127.0.0.1:5984/appdbUse CouchDB’s security settings to create a dedicated account that can read this database. The Logstash account needs to read the database and its changes feed; it should not be a full server administrator.
4. Check the changes feed
curl --user 'COUCHDB_READER:COUCHDB_PASSWORD'
'http://127.0.0.1:5984/appdb/_changes?feed=normal'A normal feed is useful for an initial check. The Logstash input will use the continuous feed so it can remain connected and receive future changes. CouchDB guarantees only the most recent change for a given document, so consumers must not depend on receiving every intermediate revision.
Cluster-specific networking
A CouchDB cluster requires more than opening 5984. Nodes need port 4369 and private Erlang communication ports, consistent node identities, and matching cluster settings. Keep all of that traffic on a private interface; never expose cluster or random Erlang ports publicly. Use a cluster only after you have a documented membership, backup, and failure-recovery plan.
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1. Install the Debian package
Follow Elastic’s Debian-package procedure for your Ubuntu release, add its signed package repository, then install and enable Elasticsearch:
sudo apt update
sudo apt install -y elasticsearch
sudo systemctl daemon-reload
sudo systemctl enable --now elasticsearch
sudo systemctl status elasticsearchPackage defaults and security bootstrap behavior differ between Elasticsearch releases. On a new single-node installation, security is enabled by default. Set credentials, configure TLS as required by the installed release, and explicitly declare single-node discovery when the package expects it.
2. Set single-node discovery and a private bind
Edit /etc/elasticsearch/elasticsearch.yml and set values equivalent to:
cluster.name: couch-search
node.name: couch-search-1
discovery.type: single-node
network.host: 127.0.0.1
If Logstash runs on a different private host, use the private address instead of loopback and restrict port 9200 to that network. Do not bind Elasticsearch to all interfaces merely to make testing easier.
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3. Set and test credentials
Use the password-reset utility supplied with your installed package to set the built-in administrator password, or create a dedicated indexing user with only the privileges required for the target index. Store credentials in Logstash’s keystore or an environment mechanism protected by filesystem permissions, not in a world-readable pipeline file.
sudo /usr/share/elasticsearch/bin/elasticsearch-reset-password -u elastic
curl --fail --user 'elastic:ELASTIC_PASSWORD' http://127.0.0.1:9200/If HTTPS is enabled, use https:// and provide the CA certificate when testing. Certificate verification should remain enabled; disabling it only hides a configuration problem.
4. Create an index strategy before loading data
Choose a deterministic index name such as appdb-documents. Define field types or an index template before importing a large database. Automatic type inference can turn a value that is numeric in one document and textual in another into a mapping conflict. Decide how CouchDB attachments, arrays, dates, and analyzed text should be represented before production indexing.
Install Logstash and the CouchDB input
1. Install Logstash
Install the Logstash package from Elastic’s repository and enable the service:
sudo apt update
sudo apt install -y logstash
sudo systemctl enable logstashInstall the CouchDB input plugin into the same Logstash installation:
sudo /usr/share/logstash/bin/logstash-plugin install logstash-input-couchdb_changes
sudo /usr/share/logstash/bin/logstash-plugin list --verbose | grep couchdbPlugin option names can change between releases. Check the installed plugin’s help output and use its documented database-name option (db or dbname, depending on the release) rather than silently guessing if validation reports an unknown setting.
2. Store secrets and state outside the pipeline
Use Logstash’s keystore for usernames and passwords where possible:
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sudo -u logstash /usr/share/logstash/bin/logstash-keystore --path.settings /etc/logstash create
sudo -u logstash /usr/share/logstash/bin/logstash-keystore --path.settings /etc/logstash add COUCHDB_PASSWORD
sudo -u logstash /usr/share/logstash/bin/logstash-keystore --path.settings /etc/logstash add ELASTICSEARCH_PASSWORDProtect /var/lib/logstash and place the sequence file on persistent storage owned by the Logstash service account.
3. Create the pipeline
Save a pipeline such as /etc/logstash/conf.d/couchdb-to-elasticsearch.conf. The example uses the commonly documented db option; use dbname if that is the option exposed by your installed plugin version.
input {
couchdb_changes {
host => "127.0.0.1"
port => 5984
db => "appdb"
username => "COUCHDB_READER"
password => "${COUCHDB_PASSWORD}"
sequence_path => "/var/lib/logstash/couchdb-appdb.sequence"
heartbeat => 10000
reconnect_interval => 10
include_docs => true
secure => false
}
}
filter {
mutate {
add_field => { "[@metadata][couch_id]" => "%{[_id]}" }
}
}
output {
if [deleted] == true {
elasticsearch {
hosts => ["http://127.0.0.1:9200"]
user => "logstash_indexer"
password => "${ELASTICSEARCH_PASSWORD}"
index => "appdb-documents"
document_id => "%{[@metadata][couch_id]}"
action => "delete"
}
} else {
elasticsearch {
hosts => ["http://127.0.0.1:9200"]
user => "logstash_indexer"
password => "${ELASTICSEARCH_PASSWORD}"
index => "appdb-documents"
document_id => "%{[@metadata][couch_id]}"
action => "update"
doc_as_upsert => true
document_type => "_doc"
}
}
}Some plugin versions expose the document identifier as id rather than _id, or emit the document body under a nested field when include_docs is enabled. Inspect one test event and adjust the field reference before production. The non-delete branch must send the actual document body, not only change metadata; if your plugin nests it, use a mutate or ruby filter to promote that body to the field expected by the Elasticsearch output.
4. Configure HTTPS for remote services
If CouchDB or Elasticsearch is on another host, set the input’s secure option and its ca_file to the issuing CA certificate. Configure the Elasticsearch output with its CA certificate as well. Validate hostnames and certificate chains. Do not set verification to “none” to work around an expired, mismatched, or self-signed certificate.
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5. Validate and start the pipeline
sudo -u logstash /usr/share/logstash/bin/logstash
--path.settings /etc/logstash
-t
sudo systemctl restart logstash
sudo systemctl status logstash
sudo journalctl -u logstash -fThe configuration test must pass before Logstash is restarted. Watch for authentication failures, an incorrect database option, permission errors on sequence_path, TLS validation failures, and rejected Elasticsearch mappings.
How synchronization behaves
Creates and updates
The input follows the continuous _changes feed and records the last sequence it has processed. A non-delete event is treated as an upsert: the event’s CouchDB ID selects the Elasticsearch document, and the newest body replaces the prior indexed version.
Deletes
CouchDB emits a change marked as deleted. The pipeline must issue an Elasticsearch delete using the same document ID. If the index does not contain that ID, Elasticsearch may return a not-found result; treat that as harmless during replay, but investigate authorization or connectivity errors.
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Ordering and duplicates
The feed is not a globally ordered transaction log. Only the latest change for a document is guaranteed, and a client can see repeated events. Idempotent upserts and ID-based deletes make repeats safe. If your application requires every intermediate revision, store revisions separately rather than assuming the changes feed provides them.
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With a durable sequence_path, Logstash resumes from the saved sequence after a normal restart. A clean restart is not a guarantee that every event reached Elasticsearch: monitor output errors and feed lag, and reconcile after outages.
Initial loading and controlled reindexing
Decide whether the first run should process existing changes or only future ones. Letting the input start from its default position can index the database’s current backlog; an explicitly configured initial sequence can begin later. Record that decision in deployment documentation.
- Create the target index or template and verify mappings.
- Start Logstash with a persistent sequence path.
- Watch CouchDB, Logstash, and Elasticsearch logs while the backlog drains.
- Query the index and compare a sample of document IDs with CouchDB.
- Only after the mapping is stable, switch application traffic to search results from Elasticsearch.
To rebuild an index, stop Logstash, create a new index name or remove the old one, and deliberately reset or replace the sequence state. Restarting with an old sequence will replay changes; deleting the sequence can cause a full or partial re-ingestion depending on plugin behavior. Document the chosen replay boundary and watch for duplicate or stale records.
Verification checklist
Service and endpoint checks
systemctl status couchdb elasticsearch logstash
journalctl -u couchdb --since "15 minutes ago"
journalctl -u elasticsearch --since "15 minutes ago"
journalctl -u logstash --since "15 minutes ago"
Confirm that CouchDB and Elasticsearch listen only on the intended interface:
sudo ss -lntp | grep -E '(:5984|:9200)'
End-to-end document test
- Create a uniquely named test document in CouchDB.
- Watch the Logstash journal and confirm that the event is accepted.
- Query the Elasticsearch target index by the CouchDB document ID.
- Update the same CouchDB document and confirm that the same Elasticsearch
_idchanges rather than a second hit appearing. - Delete the CouchDB document and verify that the corresponding Elasticsearch document disappears.
- Restart Logstash, create another document, and confirm that processing resumes from the durable sequence.
- From an external host, test firewall rules and verify that only SSH from trusted addresses and intentionally published proxy endpoints are reachable.
Security, backups, and operations
- Credentials: use separate least-privilege CouchDB read and Elasticsearch indexing accounts; rotate them without embedding passwords in world-readable files.
- Transport: use HTTPS with CA validation whenever traffic crosses hosts or an untrusted network.
- Exposure: keep 5984 and 9200 private unless a deliberately configured reverse proxy supplies authentication, rate limits, and TLS. Never expose CouchDB cluster or Erlang ports.
- Backups: schedule and test CouchDB backups and Elasticsearch snapshots. A search index is rebuildable only if the source data and replay plan still exist.
- Capacity: monitor disk utilization, memory pressure, Elasticsearch indexing failures, CouchDB compaction, Logstash queue depth, and changes-feed lag.
- Mapping changes: incompatible Elasticsearch mappings require a new index and a controlled replay, not an in-place field-type edit.
Troubleshooting by symptom
Logstash cannot connect to CouchDB
- Check that CouchDB is running and listening on the address configured in the input.
- Run an authenticated
/_changes?feed=normalrequest from the Logstash host. - Verify the database name, reader permissions, password source, and firewall rules.
- For HTTPS, verify the CA file, hostname, and certificate expiry.
Elasticsearch rejects events
- Read the Logstash journal for the exact index, mapping, or authorization error.
- Test the indexing user against the target index with a direct authenticated request.
- Check that the event contains a non-empty document ID and a document body.
- Resolve mapping conflicts with a corrected template and a new index, then replay deliberately.
Documents are duplicated
Inspect the Elasticsearch results for differing _id values. The output must set document_id from the CouchDB ID and use update/upsert behavior for ordinary changes. If the input’s ID field differs from the example, map the field emitted by your installed plugin.
Events stop after a restart
- Confirm that the sequence file exists, is readable and writable by the Logstash account, and resides on persistent storage.
- Check whether the service uses the same pipeline and
path.settingsafter reboot. - Inspect logs for a corrupt sequence or an invalid saved position; stop the pipeline before replacing state.
- If state must be reset, record the replay plan and watch for the resulting backlog.
When to choose a different architecture
Keep the three-service design for a small, controllable deployment where one VPS can handle the measured workload and a short outage is acceptable. Move to separate hosts or managed infrastructure when CouchDB storage, Elasticsearch indexing, and search traffic compete for resources, when maintenance windows are unacceptable, or when independent scaling and failure isolation justify the added cost.
Direct application indexing can be appropriate when the application already has a durable job queue and precise domain-level transformations. Logstash is preferable when you want a standard bridge, centralized credentials, filtering, replay from a saved sequence, and one operational place to observe synchronization.
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