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migrate_indexes() now backfills dkim_results_combined and spf_results_combined on aggregate documents saved by older versions, so ES/OS users get historical data in the reworked alignment tables without running the documented _update_by_query by hand. The backfill is submitted as a non-blocking background task (wait_for_completion=false, conflicts=proceed) guarded by a cheap count query, making repeated startups a fast no-op once an index is backfilled; any cluster error is logged as a warning and retried at the next startup rather than raised. The manual command remains documented for users who upgrade dashboards without pointing the new parsedmarc at the cluster or who want to control write-load timing. The legacy published_policy.fo long-to-text reindex migration in the OpenSearch module is kept ahead of the new backfill, for clusters upgraded from very old data. Verified end-to-end against the live dev environment: a real CLI startup backfilled 9 stripped OpenSearch documents (logged with task ID) while the already-backfilled Elasticsearch side stayed silent, and a second startup was silent on both engines. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
308 lines
11 KiB
Markdown
308 lines
11 KiB
Markdown
# Elasticsearch and Kibana
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To set up visual dashboards of DMARC data, install Elasticsearch and Kibana.
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:::{note}
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Elasticsearch and Kibana 8 or later are required (parsedmarc's 8.x Python
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client also supports Elasticsearch 9). OpenSearch users must use the
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`[opensearch]` configuration section instead — the Elasticsearch 8.x client
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refuses to connect to non-Elasticsearch clusters.
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:::
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## Installation
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On Debian/Ubuntu based systems, run:
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```bash
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sudo apt-get install -y apt-transport-https
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wget -qO - https://artifacts.elastic.co/GPG-KEY-elasticsearch | sudo gpg --dearmor -o /usr/share/keyrings/elasticsearch-keyring.gpg
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echo "deb [signed-by=/usr/share/keyrings/elasticsearch-keyring.gpg] https://artifacts.elastic.co/packages/8.x/apt stable main" | sudo tee /etc/apt/sources.list.d/elastic-8.x.list
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sudo apt-get update
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sudo apt-get install -y elasticsearch kibana
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```
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For CentOS, RHEL, and other RPM systems, follow the Elastic RPM guides for
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[Elasticsearch] and [Kibana].
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:::{note}
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Previously, the default JVM heap size for Elasticsearch was very small (1g),
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which will cause it to crash under a heavy load. To fix this, increase the
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minimum and maximum JVM heap sizes in `/etc/elasticsearch/jvm.options` to
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more reasonable levels, depending on your server's resources.
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Make sure the system has at least 2 GB more RAM than the assigned JVM
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heap size.
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Always set the minimum and maximum JVM heap sizes to the same
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value.
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For example, to set a 4 GB heap size, set
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```bash
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-Xms4g
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-Xmx4g
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```
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See <https://www.elastic.co/guide/en/elasticsearch/reference/current/important-settings.html#heap-size-settings>
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for more information.
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:::
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```bash
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sudo systemctl daemon-reload
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sudo systemctl enable elasticsearch.service
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sudo systemctl enable kibana.service
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sudo systemctl start elasticsearch.service
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sudo systemctl start kibana.service
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```
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As of Elasticsearch 8.7, activate secure mode (xpack.security.*.ssl)
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```bash
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sudo vim /etc/elasticsearch/elasticsearch.yml
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```
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Add the following configuration
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```text
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# Enable security features
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xpack.security.enabled: true
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xpack.security.enrollment.enabled: true
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# Enable encryption for HTTP API client connections, such as Kibana, Logstash, and Agents
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xpack.security.http.ssl:
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enabled: true
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keystore.path: certs/http.p12
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# Enable encryption and mutual authentication between cluster nodes
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xpack.security.transport.ssl:
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enabled: true
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verification_mode: certificate
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keystore.path: certs/transport.p12
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truststore.path: certs/transport.p12
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```
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```bash
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sudo systemctl restart elasticsearch
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```
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To create a self-signed certificate, run:
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```bash
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openssl req -x509 -nodes -days 365 -newkey rsa:4096 -keyout kibana.key -out kibana.crt
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```
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Or, to create a Certificate Signing Request (CSR) for a CA, run:
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```bash
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openssl req -newkey rsa:4096-nodes -keyout kibana.key -out kibana.csr
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```
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Fill in the prompts. Watch out for Common Name (e.g. server FQDN or YOUR
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domain name), which is the IP address or domain name that you will use to access Kibana. it is the most important field.
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If you generated a CSR, remove the CSR after you have your certs
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```bash
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rm -f kibana.csr
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```
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Move the keys into place and secure them:
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```bash
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sudo mv kibana.* /etc/kibana
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sudo chmod 660 /etc/kibana/kibana.key
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```
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Activate the HTTPS server in Kibana
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```bash
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sudo vim /etc/kibana/kibana.yml
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```
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Add the following configuration
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```text
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server.host: "SERVER_IP"
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server.publicBaseUrl: "https://SERVER_IP"
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server.ssl.enabled: true
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server.ssl.certificate: /etc/kibana/kibana.crt
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server.ssl.key: /etc/kibana/kibana.key
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```
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:::{note}
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For more security, you can configure Kibana to use a local network connection
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to elasticsearch :
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```text
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elasticsearch.hosts: ['https://SERVER_IP:9200']
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```
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=>
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```text
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elasticsearch.hosts: ['https://127.0.0.1:9200']
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```
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:::
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```bash
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sudo systemctl restart kibana
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```
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Enroll Kibana in Elasticsearch
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```bash
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sudo /usr/share/elasticsearch/bin/elasticsearch-create-enrollment-token -s kibana
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```
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Then access to your web server at `https://SERVER_IP:5601`, accept the self-signed
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certificate and paste the token in the "Enrollment token" field.
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```bash
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sudo /usr/share/kibana/bin/kibana-verification-code
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```
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Then put the verification code to your web browser.
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End Kibana configuration
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```bash
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sudo /usr/share/elasticsearch/bin/elasticsearch-setup-passwords interactive
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sudo /usr/share/kibana/bin/kibana-encryption-keys generate
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sudo vim /etc/kibana/kibana.yml
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```
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Add previously generated encryption keys
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```text
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xpack.encryptedSavedObjects.encryptionKey: xxxx...xxxx
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xpack.reporting.encryptionKey: xxxx...xxxx
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xpack.security.encryptionKey: xxxx...xxxx
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```
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```bash
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sudo systemctl restart kibana
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sudo systemctl restart elasticsearch
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```
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Now that Elasticsearch is up and running, use `parsedmarc` to send data to
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it.
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Download (right-click the link and click save as) [export.ndjson].
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Connect to kibana using the "elastic" user and the password you previously provide
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on the console ("End Kibana configuration" part).
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Import `export.ndjson` the Saved Objects tab of the Stack management
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page of Kibana. (Hamburger menu -> "Management" -> "Stack Management" ->
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"Kibana" -> "Saved Objects")
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It will give you the option to overwrite existing saved dashboards or
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visualizations, which could be used to restore them if you or someone else
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breaks them, as there are no permissions/access controls in Kibana without
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the commercial [X-Pack].
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```{image} _static/screenshots/saved-objects.png
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:align: center
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:alt: A screenshot of setting the Saved Objects Stack management UI in Kibana
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:target: _static/screenshots/saved-objects.png
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```
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```{image} _static/screenshots/confirm-overwrite.png
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:align: center
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:alt: A screenshot of the overwrite conformation prompt
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:target: _static/screenshots/confirm-overwrite.png
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```
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## Upgrading Kibana index patterns
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`parsedmarc` 5.0.0 makes some changes to the way data is indexed in
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Elasticsearch. if you are upgrading from a previous release of
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`parsedmarc`, you need to complete the following steps to replace the
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Kibana index patterns with versions that match the upgraded indexes:
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1. Login in to Kibana, and click on Management
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2. Under Kibana, click on Saved Objects
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3. Check the checkboxes for the `dmarc_aggregate` and `dmarc_failure`
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index patterns
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4. Click Delete
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5. Click Delete on the conformation message
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6. Download (right-click the link and click save as)
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the latest version of [export.ndjson]
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7. Import `export.ndjson` by clicking Import from the Kibana
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Saved Objects page
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## Backfilling the combined DKIM/SPF result fields
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As of the version fixing [#169](https://github.com/domainaware/parsedmarc/issues/169),
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aggregate documents include `dkim_results_combined` and `spf_results_combined` —
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scalar string arrays that keep each auth result's selector/scope, domain, and
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result paired, which the dashboards' alignment-detail tables aggregate on.
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Reports saved by older versions lack these fields and will not appear in
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those tables.
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parsedmarc now backfills this automatically. On startup, it runs a cheap
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count query against each configured aggregate index pattern to check for
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documents that have DKIM or SPF results but are missing the corresponding
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combined field. If any are found, it submits the backfill as a background
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`_update_by_query` task (`wait_for_completion=false`), so startup is never
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blocked on it; progress is logged, including the task ID. The check itself
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is idempotent — once an index is fully backfilled, later startups see a
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count of 0 and log nothing further — and it works the same way on
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OpenSearch. Any error talking to the cluster (for example, no indexes yet
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on a fresh install) is logged as a warning and retried on the next startup,
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rather than aborting parsedmarc.
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If you upgrade the dashboards without pointing the new parsedmarc version
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at the cluster, or you'd rather control when the write load happens, you
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can still run the backfill manually. It is idempotent (documents that
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already have the fields are skipped), so it is safe to re-run. It works
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identically on OpenSearch; just adjust the URL and credentials. The query
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matches only documents that have at least one DKIM or SPF auth result and
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lack the corresponding combined field; documents with no auth results are
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skipped, because an `exists` query cannot see an empty array, and for
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search purposes an empty `dkim_results_combined` is identical to an
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absent one.
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```bash
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curl -X POST "http://localhost:9200/dmarc_aggregate*/_update_by_query?conflicts=proceed&wait_for_completion=false" \
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-H "Content-Type: application/json" -d '
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{
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"query": {
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"bool": {
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"minimum_should_match": 1,
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"should": [
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{
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"bool": {
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"must": [{"exists": {"field": "dkim_results.domain"}}],
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"must_not": [{"exists": {"field": "dkim_results_combined"}}]
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}
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},
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{
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"bool": {
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"must": [{"exists": {"field": "spf_results.domain"}}],
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"must_not": [{"exists": {"field": "spf_results_combined"}}]
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}
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}
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]
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}
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},
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"script": {
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"lang": "painless",
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"source": "List dk = new ArrayList(); def dr = ctx._source.dkim_results; if (dr != null) { if (!(dr instanceof List)) { dr = [dr]; } for (e in dr) { if (e == null) { continue; } def sel = e.selector != null ? e.selector : \"none\"; def dom = e.domain != null ? e.domain : \"none\"; def res = e.result != null ? e.result : \"none\"; dk.add(sel + \" / \" + dom + \" / \" + res); } } ctx._source.dkim_results_combined = dk; List sp = new ArrayList(); def sr = ctx._source.spf_results; if (sr != null) { if (!(sr instanceof List)) { sr = [sr]; } for (e in sr) { if (e == null) { continue; } def sc = e.scope != null ? e.scope : \"mfrom\"; def dom = e.domain != null ? e.domain : \"none\"; def res = e.result != null ? e.result : (e.results != null ? e.results : \"none\"); sp.add(sc + \" / \" + dom + \" / \" + res); } } ctx._source.spf_results_combined = sp;"
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}
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}'
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```
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`wait_for_completion=false` returns a task ID — check progress with
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`GET _tasks/<task id>`. Adjust the index pattern if you use a custom
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`index_prefix`/`index_suffix`. After backfilling, re-import the updated
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dashboards ndjson (the index pattern saved object changed too) per the
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import instructions above.
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## Records retention
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Starting in version 5.0.0, `parsedmarc` stores data in a separate
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index for each day to make it easy to comply with records
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retention regulations such as GDPR. For more information,
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check out the Elastic guide to [managing time-based indexes efficiently](https://www.elastic.co/blog/managing-time-based-indices-efficiently).
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[elasticsearch]: https://www.elastic.co/guide/en/elasticsearch/reference/current/rpm.html
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[export.ndjson]: https://raw.githubusercontent.com/domainaware/parsedmarc/master/dashboards/opensearch/opensearch_dashboards.ndjson
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[kibana]: https://www.elastic.co/guide/en/kibana/current/rpm.html
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[x-pack]: https://www.elastic.co/products/x-pack
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