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NGINX and Apache do not produce interchangeable records. Apache’s standard combined access format can usually be parsed with %{COMBINEDAPACHELOG}, while NGINX access fields depend on the active log_format. Error logs from either server need their own parser. The configuration below keeps the original message, tags failures, handles file state deliberately, and leaves enough metadata to troubleshoot production pipelines.
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Choose the collection design before writing filters
There are three practical ways to get web-server logs into Logstash. The right choice depends on where Logstash runs, how much buffering you need, and who owns parsing.
| Method | Use it when | Advantages | Important limitations |
|---|---|---|---|
Logstash file input |
Logstash runs on the web host or has dependable read access to its files. | Simple topology; Logstash reads the files directly and tracks its position. | Requires filesystem access, careful permissions, and correct rotation handling on every host. |
| Filebeat to Logstash | A lightweight shipper is already installed, or logs must leave the web host without running a full Logstash instance there. | Separates collection from parsing, provides local buffering, and is suited to many hosts. | You must coordinate Filebeat inputs, tags or fields, Logstash filters, and queue/back-pressure behavior. |
| Syslog input | An existing syslog forwarder already sends the web-server records. | Works with established TCP or UDP forwarding and centralizes network ingestion. | Transport metadata can obscure the original format; UDP can lose records, and custom messages need a timestamp-bearing Grok pattern. |
Whichever method you select, preserve the original line in message, attach source metadata, and keep access and error events distinguishable. This makes a malformed line diagnosable instead of silently discarded.
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Find the actual NGINX and Apache log files
Do not assume a copied example path is correct. Package layouts, operating systems, containers, virtual hosts, and custom configurations change locations.
NGINX
Inspect the running configuration and each included file for access_log, error_log, and log_format. The access_log directive determines the access destination and format; error_log determines the error destination and severity threshold. A host can have several access files for different virtual servers and more than one error file.
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Check the active virtual-host configuration for CustomLog and ErrorLog. Distribution packages commonly place files under a directory such as /var/log/apache2 or /var/log/httpd, but the directive in the running configuration is authoritative. Confirm that the Logstash service account can traverse the directory and read rotated files when required.
Build a path inventory
- Record every active access and error destination, including per-site files.
- Record the exact format name or literal format string for each access destination.
- Identify rotation behavior, compression, truncation, and retention rules.
- Choose narrow globs that include only intended logs. For example,
/var/log/nginx/*.logand/var/log/apache2/*_logare safer starting points than a recursive glob covering unrelated application files. - Copy one current access line and one current error line from every distinct format for testing.
Start with a local-file pipeline
The following skeleton demonstrates conditional routing. It uses valid field names, keeps a debugging output, and deliberately leaves NGINX parsing format-specific. Replace the Elasticsearch host with your own supported destination and add authentication according to that deployment.
input {
file {
path => ["/var/log/nginx/*.log", "/var/log/apache2/*_log"]
start_position => "beginning"
sincedb_path => "/var/lib/logstash/plugins/inputs/file/sincedb-web"
tags => ["web-file"]
}
}
filter {
if [path] =~ /apache/ and [path] =~ /access/ {
mutate {
add_field => {
"[service][name]" => "apache"
"[log][type]" => "access"
}
}
grok {
match => { "message" => "%{COMBINEDAPACHELOG}" }
tag_on_failure => ["_apache_access_grok_failure"]
}
date {
match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
tag_on_failure => ["_apache_access_date_failure"]
}
} else if [path] =~ /nginx/ and [path] =~ /access/ {
mutate {
add_field => {
"[service][name]" => "nginx"
"[log][type]" => "access"
}
}
# Add a Grok pattern matching this host's configured log_format.
} else {
mutate {
add_field => { "[log][type]" => "error" }
}
# Apply an Apache- or NGINX-specific error pattern here.
}
}
output {
elasticsearch {
hosts => ["https://your-cluster.example"]
}
stdout { codec => rubydebug }
}start_position => "beginning" controls the initial read of content that has no recorded position. The file input stores offsets in its sincedb registry; it does not replay content whose position is already registered merely because Logstash restarts. Treat the registry as state: back it up when appropriate, give it a stable path, and do not delete it casually in production.
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Parse Apache access logs with the combined pattern
A standard Apache combined access line contains the client address, identity and user fields, timestamp, request line, status, response byte count, referrer, and user agent. Elastic’s Grok examples use %{COMBINEDAPACHELOG} to split that line into fields. Apply the date filter after Grok has created timestamp.
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filter {
if [service][name] == "apache" and [log][type] == "access" {
grok {
match => { "message" => "%{COMBINEDAPACHELOG}" }
tag_on_failure => ["_grokparsefailure_apache_access"]
}
date {
match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
target => "@timestamp"
tag_on_failure => ["_dateparsefailure_apache_access"]
}
}
}Keep the raw message even after extraction. It is useful when a module adds a field, a proxy changes quoting, or a line must be reconstructed for an incident review. If a site uses a format other than combined access, use a pattern that reflects that format instead of forcing the composite pattern to match.
Parse NGINX access logs from the deployed log_format
NGINX does not have one universal access-line grammar. Operators often add upstream response time, forwarded addresses, request IDs, TLS details, or custom variables. A pattern copied from another server can therefore fail or, worse, assign values to the wrong fields.
Turn the format declaration into a contract
- Read the active
log_formatdeclaration, including inherited configuration and included files. - List each variable in order, noting literal separators and whether values are quoted.
- Write a Grok pattern for that exact order and save it with a version or configuration identifier.
- Test it against lines containing empty values, spaces in quoted fields, IPv6 addresses, and long request URLs.
- Tag failures and retain the original line instead of dropping it.
For example, a pattern for a format containing an address, timestamp, request, status, byte count, referrer, user agent, and upstream timing must capture those fields in precisely that sequence. The names should be stable across hosts so dashboards do not need one query per server. If two NGINX configurations differ, route them using path, host metadata, or an explicit format tag rather than one permissive pattern.
Normalize the NGINX timestamp
Once Grok captures the timestamp, use a date filter with the exact layout emitted by that format. Include the timezone when the line supplies one. If the format emits a local time without an offset, configure the date filter’s timezone deliberately and document the assumption; otherwise events can appear shifted when hosts use different zones.
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Handle NGINX and Apache error logs separately
Error lines are not access records. They describe severity and a diagnostic message rather than an HTTP request and response. Sending them through an access parser creates false failures and misleading fields.
NGINX error logs
NGINX error records commonly include a timestamp, severity, process or connection context, and message text. The configured error_log location and severity determine what is written. Build a pattern for the exact version and deployment style, capture severity into a consistent field such as log.level, and leave the remainder in a message field. Preserve request IDs or upstream details when present.
Apache error logs
Apache error formats vary by version, module, and logging configuration. Use a separate conditional and a pattern that matches the installed format. Capture the timestamp and level when available, then apply a date filter. Do not apply COMBINEDAPACHELOG to an error line; the grammar is fundamentally different.
Keep unmatched errors visible
Add a source-specific failure tag such as _grokparsefailure_nginx_error or _grokparsefailure_apache_error. Route tagged events to a review index or alert stream while still retaining the raw line. A parse failure should be an observable condition, not silent data loss.
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Choose ECS compatibility and field names deliberately
Grok composite patterns can emit different field names when ecs_compatibility is enabled. Decide this before creating index templates, dashboards, alerts, and saved queries. Changing modes later can leave old and new documents with incompatible mappings.
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- Use one documented ECS mode for the pipeline and its shared patterns.
- Keep service identity under consistent fields such as
[service][name]. - Use
[log][type]for the access/error distinction, or another documented namespace used consistently by your index templates. - Store source-specific values such as upstream timing under stable, clearly named fields.
- Keep
@timestampas the event time after parsing the web server’s timestamp.
Validate a representative Apache access event, NGINX access event, and each error format against the destination’s mappings before enabling broad ingestion.
File input, Filebeat, or syslog: a practical decision
Use the file input when Logstash is close to the files
This is appropriate for a small number of hosts or a colocated Logstash process. Verify read permissions, monitor the sincedb location, and test rotation. The input follows files by path and position; careless registry deletion can cause duplicates, while an incorrect path or inaccessible directory causes gaps.
Use Filebeat when collection and parsing should be separate
Elastic’s advanced web-log tutorial demonstrates Filebeat sending Apache logs to Logstash, where the events are parsed into named fields before indexing. In this design, Filebeat owns discovery, harvesting, and local buffering; Logstash owns conditional routing, Grok, date conversion, enrichment, and output. Attach fields or tags in Filebeat so Logstash can distinguish NGINX from Apache and access from error streams without relying only on filename conventions.
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Logstash’s syslog input can listen on TCP and UDP and accept a custom grok_pattern for non-standard messages. The pattern must expose a timestamp that Logstash can parse. Confirm whether the sender prepends priority, hostname, or program fields, and test both transport paths separately. Prefer TCP where delivery guarantees matter; if UDP is required, account for possible loss and size limits.
Rotation, truncation, and state: prevent gaps and duplicates
Test the lifecycle, not just a static sample.
- Rename-and-create rotation: verify that Logstash continues reading the old file to its end and begins the new file.
- Copy-truncate rotation: verify behavior when a file is truncated in place; offsets and inode tracking can produce duplicates or missed lines depending on timing.
- Compression: ensure the input does not attempt to parse compressed archives unless your chosen shipper explicitly supports that workflow.
- Restart recovery: stop and start Logstash, then confirm that the registry resumes from the expected offsets.
- Permissions: test after rotation, because a newly created file can have different ownership or mode bits.
- Multiline records: web access lines are normally single-line; if an error format can span lines, configure multiline handling at the collector rather than letting fragments reach Grok independently.
Measure event counts around a controlled rotation and compare the raw files with indexed documents. Do not “fix” duplicates by deleting state until you understand which offsets were recorded.
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Validate the pipeline before indexing everything
- Run Logstash with
stdout { codec => rubydebug }alongside the production output. - Feed one known Apache combined access line, one non-combined Apache line, one NGINX access line for every deployed format, and one error line from each server.
- Confirm that
@timestampreflects the log event time, not ingestion time. - Check that status, request, bytes, client address, severity, and source metadata have the expected values.
- Intentionally submit malformed lines and verify that they retain
messageand receive the intended failure tag. - Query the destination for failure tags and inspect them after deployment, especially following a web-server configuration change.
Troubleshoot common failures
No events arrive
Check the path against the running configuration, directory traversal permissions, SELinux or other mandatory access controls, and the sincedb position. A file already registered at its end will not be replayed by start_position => "beginning"; use a controlled test file or a separate registry for testing.
Apache fields are empty
Confirm that the line is actually combined format and that a proxy or module has not added fields. Inspect the raw message, then select a matching pattern or write a custom one.
NGINX parsing fails after a configuration change
Compare the active log_format with the Grok pattern. Added variables, changed quoting, and optional upstream values are common causes. Version the pattern with the deployment and add a test line to the pipeline’s validation set.
Timestamps are wrong
Inspect the captured timestamp, date pattern, and timezone. Apply the date filter only after Grok has populated the field, and ensure the format token matches the server’s month, offset, and sub-second precision.
Events are duplicated after rotation
Review the rotation method, inode behavior, and registry state. Avoid deleting sincedb as a first response; doing so can replay all retained content. Correct the rotation and state strategy, then test it under the same timing used in production.
Production checklist
- Confirm every NGINX and Apache path from the active configuration.
- Separate access and error inputs and parsers.
- Use
COMBINEDAPACHELOGonly for compatible Apache access lines. - Maintain custom, versioned Grok patterns for each NGINX
log_format. - Parse source timestamps and preserve the original
message. - Choose ECS compatibility before templates and dashboards.
- Tag and monitor parse failures instead of dropping unmatched events.
- Test rotation, truncation, compression, permissions, multiline behavior, and registry recovery.
- Keep rubydebug output during development, then remove or restrict it when production logging is established.
- Validate destination mappings with representative events from every deployed format.
The Bottom Line
Collect local files with Logstash’s file input when it has reliable access; otherwise ship with Filebeat or an existing syslog path. The durable solution is format-aware: separate access from error logs, parse Apache combined access lines with COMBINEDAPACHELOG, derive NGINX patterns from the active log_format, normalize timestamps, preserve raw messages, and test file state through rotation before trusting the indexed data.
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