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Collect NGINX and Apache logs with Logstash by first identifying the active access and error-log files, then routing each stream to its own parser. Use Logstash’s file input for files it can read locally, Filebeat when an agent already ships the files, or the syslog input when another system forwards them. Parse standard Apache combined access lines with %{COMBINEDAPACHELOG}, match NGINX against the deployed log_format, normalize the source timestamp, and test rotation and registry recovery before indexing the events.
What the pipeline should do
A reliable web-log pipeline has four distinct stages:
- Read: obtain events from local files, Filebeat, or syslog.
- Identify: attach metadata for the web server and stream, such as
apache/accessornginx/error. - Parse: apply a parser that matches that exact format. Access and error records must not share a generic parser.
- Normalize and deliver: convert the original timestamp, retain the raw message, and send validated events to Elasticsearch or another supported destination.
The most common failures happen when a pipeline assumes a default path, treats every web log as Apache combined format, or starts indexing before its fields and timestamp conventions are settled.
Find the real log files and formats
Inspect NGINX rather than trusting a copied path
NGINX access and error logging are configured independently. The access_log directive determines the access-file location and its log_format; error_log determines the error-file location and the minimum severity recorded. Package defaults differ between operating systems, containers, source builds, and custom virtual-host configurations.
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Inspect the running configuration and each enabled server block. Record every active access file, error file, and format name. A host may have several files, for example one access log per virtual host and a shared error log. Do not assume that a file named access.log uses the standard fields: operators often add upstream response time, forwarded addresses, request IDs, or other variables.
Locate Apache files from the running installation
Apache commonly writes files below an installation-specific log directory. Debian-derived layouts often resemble /var/log/apache2/, while other packages use a different directory and names. Treat these as examples, not universal paths. Confirm the active CustomLog and ErrorLog directives and note the format assigned to each CustomLog.
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| Stream | Typical content | Parsing implication |
|---|---|---|
| Access | One HTTP request per line, usually a configurable access format | Use the exact configured format. Standard combined access lines can use COMBINEDAPACHELOG. |
| Error | Severity, time, process or module context, and a diagnostic message | Use a separate, format-specific Grok pattern; access patterns are not appropriate. |
Use narrow globs
For a local pipeline, a starting path list might be /var/log/nginx/*.log and /var/log/apache2/*_log. Narrow the patterns if those directories contain rotated archives, audit records, or unrelated application files. A broad recursive glob can ingest files that have no matching parser and can create duplicate or misleading events.
Choose how Logstash receives the events
| Method | Use it when | Main considerations |
|---|---|---|
Logstash file input |
Logstash runs on the web host or has dependable filesystem access | Logstash tracks file positions in its registry. Permissions, rotation, truncation, and registry recovery are your responsibility. |
| Filebeat to Logstash | A lightweight agent already runs on each web host or Logstash should not read application disks | Filebeat handles local harvesting and forwards events over the Beats protocol. Parser ownership can remain in Logstash, or move to the agent if you standardize it there. |
Logstash syslog input |
Another service already forwards the logs through syslog | Choose TCP or UDP deliberately, expose only the required listener, and supply a Grok pattern that captures a parseable timestamp. |
File input is the shortest path for a single host. Filebeat is usually easier to scale across many hosts because collection stays close to the files and Logstash receives a consistent transport. Syslog avoids adding a file harvester when forwarding already exists, but its framing and transport behavior are controlled by the sender and can vary substantially.
Build a local-file pipeline
Prepare access and state
- Identify the user that runs Logstash and grant it read access to the selected files and traverse access to every parent directory.
- Choose a persistent
path.datalocation so the file-input registry survives a restart. Losing that registry can cause old content to be read again. - Start with one representative access line and one representative error line from every deployed format. Keep the original lines in a secure test file if production permissions prevent repeated reads.
- Validate the configuration before starting the service. The exact command depends on the installation, but Logstash supports a configuration-test mode such as
bin/logstash --config.test_and_exit -f /etc/logstash/conf.d/web.conf.
Use conditional routing
This example demonstrates the design. Adjust the path tests and parsers to your actual filenames; the path test is not a substitute for inspecting the web-server configuration.
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input {
file {
path => ["/var/log/nginx/*.log", "/var/log/apache2/*_log"]
start_position => "beginning"
}
}
filter {
if [path] =~ /apache/ and [path] =~ /access/ {
mutate {
add_field => {
"[service][name]" => "apache"
"[log][type]" => "access"
}
}
grok {
match => { "message" => "%{COMBINEDAPACHELOG}" }
}
date {
match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
}
} else if [path] =~ /nginx/ and [path] =~ /access/ {
mutate {
add_field => {
"[service][name]" => "nginx"
"[log][type]" => "access"
}
}
# Match the deployed NGINX log_format here.
} else if [path] =~ /apache/ and [path] =~ /error/ {
mutate {
add_field => {
"[service][name]" => "apache"
"[log][type]" => "error"
}
}
# Apply an Apache error-log pattern here.
} else if [path] =~ /nginx/ and [path] =~ /error/ {
mutate {
add_field => {
"[service][name]" => "nginx"
"[log][type]" => "error"
}
}
# Apply an NGINX error-log pattern here.
} else {
mutate { add_tag => ["unclassified_web_log"] }
}
}
output {
elasticsearch {
hosts => ["${ELASTICSEARCH_HOSTS}"]
}
stdout { codec => rubydebug }
}The metadata field is deliberately [log][type]. A malformed field name in a copied example can prevent the configuration from behaving as intended. Keep the stdout output during development so you can inspect fields before relying on index mappings and dashboards; remove or restrict it in production if it would expose sensitive request data.
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Parse Apache access logs
Use the built-in combined pattern when it truly matches
Apache’s standard combined access format contains the client address, identity and authenticated-user fields, timestamp, request line, response status, response size, referrer, and user agent. For that exact grammar, the Grok pattern %{COMBINEDAPACHELOG} separates the values into named fields. Follow it with a date filter:
grok {
match => { "message" => "%{COMBINEDAPACHELOG}" }
}
date {
match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
}The date filter should run after Grok has created timestamp. The Apache timestamp includes a numeric UTC offset, so the filter can convert it to Logstash’s event time without guessing the host’s local timezone.
Know when combined parsing is wrong
Apache formats are configurable. Added request IDs, forwarded-client fields, virtual-host names, or different quoting will cause a combined-pattern mismatch or misaligned fields. Compare a real line with the active LogFormat, then create a custom pattern that captures each field in its actual order. Keep the unmodified message even after successful parsing; it is valuable when a format changes or a field needs forensic review.
Parse NGINX access logs against the deployed format
Why a default pattern is unsafe
NGINX writes whatever variables the configured log_format contains. Two servers can both be called “default NGINX” while emitting different fields. A parser that expects only the common request, status, byte count, referrer, and user-agent fields will fail when upstream timing, forwarded addresses, or request IDs are inserted.
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Start with a format-specific Grok expression
For a conventional combined-style NGINX line, a custom expression can look like this:
grok {
match => {
"message" => "%{IPORHOST:clientip} - %{DATA:auth} [%{HTTPDATE:timestamp}] "%{WORD:verb} %{DATA:request}(?: HTTP/%{NUMBER:httpversion})?" %{NUMBER:response:int} %{NUMBER:bytes:int} "%{DATA:referrer}" "%{DATA:agent}""
}
}
date {
match => ["timestamp", "dd/MMM/yyyy:HH:mm:ss Z"]
}This is only a starting point. If the NGINX configuration emits a different timestamp, an upstream field, or a request containing characters this expression does not cover, revise the pattern and test it against representative lines. Version custom patterns with the deployment configuration so a later change to log_format does not silently corrupt fields.
Tag failures instead of discarding data
Configure Grok to add a failure tag, or rely on the standard _grokparsefailure tag, and monitor its rate. A failed parse should retain the raw message and source metadata. Dropping the event makes it impossible to distinguish a quiet server from a parser that stopped matching.
Handle NGINX and Apache error logs separately
NGINX error records
NGINX error lines generally contain a date and time, bracketed severity, process information, and a diagnostic message. Some lines add a connection identifier, client address, server name, request, or host. A deliberately broad first pass can capture the stable outer structure:
grok {
match => {
"message" => "(?<timestamp>d{4}/d{2}/d{2} d{2}:d{2}:d{2}) [%{LOGLEVEL:severity}] %{GREEDYDATA:error_detail}"
}
}
date {
match => ["timestamp", "yyyy/MM/dd HH:mm:ss"]
}Once the outer parse is reliable, add fields for process IDs, client address, request, and host only if your deployed lines contain them consistently. Preserve error_detail or the original message for lines that include a different shape.
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Apache error records
Apache error formats vary with the server version, module, and configured error-log format. They may include a human-readable date, module and severity labels, process or thread identifiers, and a message. Route these records to a separate Grok expression rather than trying to force them through COMBINEDAPACHELOG. Build the expression from actual samples and use a date pattern that matches the emitted date, including fractional seconds when present.
Keep severity useful
Store the source severity as a dedicated field and do not infer severity from the text of an access request. NGINX’s error_log directive controls the minimum severity written, so a missing debug message may reflect configuration rather than a collection failure.
Choose ECS field names before indexing
Grok composite patterns can emit different field names depending on the plugin’s ecs_compatibility setting. Decide whether your index templates, dashboards, alert rules, and queries expect ECS-compatible fields or the legacy names before changing that setting. Apply the same decision to every pipeline that writes the destination index.
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Send events through Filebeat instead of local file input
Use Filebeat when each web host should harvest its own files and forward events to a central Logstash tier. A minimal Filebeat input can resemble:
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filebeat.inputs:
- type: filestream
paths:
- /var/log/nginx/*.log
- /var/log/apache2/*_log
output.logstash:
hosts: ["${LOGSTASH_HOST}:5044"]Configure Logstash with a Beats listener on the chosen port, then perform the same source classification and parsing there. You can add fields at the agent, but keep the ownership of parser definitions clear. If Logstash is responsible for parsing, send the original line and enough host/path metadata to select the correct NGINX or Apache pattern.
Filebeat does not remove the need to test rotation, permissions, multiline behavior, and back-pressure. Confirm that the agent’s registry is persistent and that its harvester settings match the way your logrotate or container runtime renames and recreates files.
Accept forwarded logs with the syslog input
If a relay already sends web logs through syslog, Logstash can listen on TCP, UDP, or both. Use a dedicated port and network policy rather than exposing a listener broadly. A custom pattern must capture a timestamp that Logstash can parse:
input {
syslog {
port => 5514
grok_pattern => "<%{POSINT:priority}>%{SYSLOGTIMESTAMP:timestamp} %{HOSTNAME:sender} %{GREEDYDATA:message}"
}
}Adapt the expression to the sender’s actual framing and payload. If the sender wraps an entire NGINX or Apache line inside the syslog message, parse the syslog envelope first and then apply the web-server parser to the remaining message. UDP can lose events under congestion; TCP provides a connection and back-pressure but still requires queue and failure monitoring.
Understand file positions, rotation, and duplication
start_position is not a replay switch
start_position => "beginning" tells a new file-input registration where to begin reading. It does not force Logstash to reread content whose position is already stored in the file-input registry. To deliberately replay a file, you need a controlled test environment and a clear registry procedure; never delete production state casually.
Test the rotation patterns you actually use
- Rename the active file and create a new file with the original name.
- Truncate a file in place if your rotation tool uses copy-truncate.
- Compress or remove an older file and verify that the glob does not ingest the archive.
- Restart Logstash during rotation and confirm that the registry resumes from the expected byte offset.
- Check that the service account can read newly created files, not just the files present during installation.
Watch for duplicate events after a registry reset and missed events after an inode or rename-handling mismatch. Keep event identifiers or source offsets available in your operational logs so an apparent application spike can be compared with collector behavior.
Quick Recap
Validate a pipeline before production indexing
- Send one known Apache combined access line and verify every expected field and the converted event timestamp.
- Send one Apache error line and confirm that it bypasses the access parser.
- Repeat with one line from every NGINX
log_formatand one NGINX error line. - Intentionally send a malformed line and verify that the raw message remains and a parse-failure tag appears.
- Inspect the event with
stdout { codec => rubydebug }before enabling dashboards or index templates. - Stop and restart Logstash, then confirm that already-read content is not unexpectedly replayed.
- Exercise log rotation, permission changes, truncation, and temporary destination failure.
- Measure queue growth and parse-failure rates after deployment, not only successful event counts.
Troubleshoot by symptom
| Symptom | Likely cause | Action |
|---|---|---|
| No events arrive | Wrong path, insufficient permissions, inactive directive, or a registry position at end-of-file | Confirm the running configuration, read the file as the Logstash user, inspect the registry, and test with a newly appended line. |
| Apache fields are empty | The line is not standard combined format | Compare it with LogFormat and replace COMBINEDAPACHELOG with a custom pattern. |
| NGINX fields shift or parse fails | The deployed log_format has added or reordered fields |
Capture a real line, revise the pattern, and version it with the NGINX configuration. |
| Events have the wrong time | Date filter ran before Grok, used the wrong layout, or ignored an offset | Parse first, then apply the exact date layout and timezone information emitted by the source. |
| Error lines look like access requests | A single parser is being applied to both streams | Route by source metadata or path and give each error format its own parser. |
| Events duplicate after restart | File-input registry was lost or moved | Restore persistent state, identify the replay window, and avoid resetting the registry without a replay plan. |
| New rotated files are ignored | Glob, permissions, or harvester behavior does not match the rotation method | Test the exact rename/truncate sequence and inspect collector logs while rotating a test file. |
A production-ready decision checklist
- Have you confirmed every active NGINX
access_log,error_log, andlog_format? - Have you confirmed Apache’s active
CustomLogandErrorLogpaths and formats? - Are access and error streams tagged and parsed independently?
- Does each parser preserve the original
message? - Is the source timestamp converted only after successful parsing?
- Is the chosen ECS compatibility mode consistent with index mappings and dashboards?
- Is file-input state persistent, or is the Filebeat registry persistent on every host?
- Have rotation, truncation, permissions, multiline behavior, restart recovery, and destination back-pressure been tested?
- Are parse failures visible through tags and monitoring rather than silently discarded?
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