In Kubernetes, managing scattered container logs can be difficult, resulting in inefficient troubleshooting and high O&M costs. Deploying the Simple Log Service (SLS) LoongCollector in DaemonSet mode and configuring log collection in the SLS console allows for unified log collection and structured processing. This approach improves log retrieval, problem diagnosis, and observability analysis efficiency.
Usage notes
Runtime environment:
Supports Container Service for Kubernetes (ACK) (Managed and Dedicated editions) and self-managed Kubernetes clusters.
Kubernetes version 1.10.0 or later that supports
Mount propagation: HostToContainer.Container runtime (Docker and Containerd only)
Docker:
Requires access permissions for docker.sock.
Standard output collection supports only the JSON log driver.
Supports only the overlay and overlay2 storage drivers. For other storage driver types, you must manually mount the log directory.
Containerd: Requires access permissions for containerd.sock.
Resource requirements: LoongCollector (Logtail) runs with high priority as system-cluster-critical. Avoid deploying it if cluster resources are insufficient, as this may evict existing pods on the node.
CPU: Reserve at least 0.1 Core.
Memory: Reserve at least 150 MB for the collection component and at least 100 MB for the controller component.
Actual usage depends on the collection rate, the number of monitored directories and files, and the level of send congestion. Ensure that the actual usage is below 80% of the limit.
Permission requirements: The Alibaba Cloud account or RAM user used for deployment must have the
AliyunLogFullAccesspermission.To create custom policies, refer to the AliyunCSManagedLogRolePolicy system policy. Copy the permissions included in the policy and grant them to the target RAM user or role for fine-grained permission configuration.
Collection configuration workflow
Install LoongCollector: Deploy LoongCollector in DaemonSet mode. This ensures that a collection container runs on each node in the cluster to collect logs from all containers on that node.
For Sidecar mode, see Collect text logs from a cluster (Sidecar).
Create a logstore: A logstore is a storage unit for log data. Multiple logstores can be created in a project.
Create a collection configuration:
This topic describes only common configuration parameters and core options for typical use cases. For a complete list of configuration parameters and their descriptions, see More information.
Minimal configuration (Required): Establish a data collection tunnel from the cluster to the SLS project.
Common processing configurations (Optional): Configure common data processing plugins to parse raw logs into structured data. For example, use regular expressions or delimiters for parsing, or perform data masking and filtering.
This topic describes only native processing plugins that cover common log processing use cases. For more features, see Extended processing plugins.
Other advanced configurations (Optional): Collect multiline text logs and enrich log tags for more fine-grained collection.
Install LoongCollector (Logtail)
LoongCollector is a new-generation log collection agent from SLS and an upgraded version of Logtail. LoongCollector and Logtail cannot coexist. To install Logtail, see Install, run, upgrade, and uninstall Logtail.
This topic describes only the basic steps to install LoongCollector. For more information about the parameters, see Install LoongCollector (Kubernetes). If you have installed LoongCollector or Logtail, skip this step and create a logstore to store the collected logs.
ACK cluster
Install LoongCollector from the Container Service for Kubernetes console. By default, logs are sent to a Simple Log Service project under the current Alibaba Cloud account.
Log on to the ACK console. In the left navigation pane, click Clusters.
On the Clusters page, click the name of the target cluster.
In the navigation pane on the left, click Add-ons.
On the Logs and Monitoring tab, find loongcollector and click Install.
NoteFor a new cluster, on the Advanced Options section, select Enable Log Service. Then Create Project or Select Project.
After the installation is complete, SLS automatically creates related resources in the region where the ACK cluster resides. Log on to the Simple Log Service console to view them.
Resource type
Resource name
Function
Project
k8s-log-${cluster_id}A resource management unit that isolates logs of different services.
To create a project for more flexible log resource management, see Create a project.
Machine group
k8s-group-${cluster_id}A collection of log collection nodes.
Logstore
config-operation-logImportantDo not delete this logstore.
Stores logs of the loongcollector-operator component. Its billing method is the same as that of a regular logstore. For more information, see Billable items for the pay-by-ingested-data mode. We recommend that you do not create collection configurations in this logstore.
Self-managed cluster
Connect to the Kubernetes cluster. Select the command for your region to download LoongCollector and its dependent components:
Regions in China:
wget https://aliyun-observability-release-cn-shanghai.oss-cn-shanghai.aliyuncs.com/loongcollector/k8s-custom-pkg/3.0.12/loongcollector-custom-k8s-package.tgz; tar xvf loongcollector-custom-k8s-package.tgz; chmod 744 ./loongcollector-custom-k8s-package/k8s-custom-install.shRegions outside China:
wget https://aliyun-observability-release-ap-southeast-1.oss-ap-southeast-1.aliyuncs.com/loongcollector/k8s-custom-pkg/3.0.12/loongcollector-custom-k8s-package.tgz; tar xvf loongcollector-custom-k8s-package.tgz; chmod 744 ./loongcollector-custom-k8s-package/k8s-custom-install.shGo to the
loongcollector-custom-k8s-packagedirectory and modify the./loongcollector/values.yamlconfiguration file.# ===================== Required Information ===================== # The name of the project where logs from this cluster will be collected, for example, k8s-log-custom-sd89ehdq projectName: "" # The region of the project, for example, Shanghai: cn-shanghai region: "" # The UID of the Alibaba Cloud account that owns the project. Enclose it in quotation marks, for example, "123456789" aliUid: "" # The network to use. Optional parameters: Internet, Intranet. The default is Internet. net: Internet # The AccessKey ID and AccessKey secret of the Alibaba Cloud account or RAM user. The account must have the AliyunLogFullAccess system policy permission. accessKeyID: "" accessKeySecret: "" # A custom cluster ID. The name can contain only uppercase letters, lowercase letters, digits, and hyphens (-). clusterID: ""In the
loongcollector-custom-k8s-packagedirectory, run the following command to install LoongCollector and other dependent components:bash k8s-custom-install.sh installAfter the installation is complete, check the running status of the components.
If the pod fails to start, check whether the values.yaml configuration is correct and whether the relevant images were pulled successfully.
# Check the pod status kubectl get po -n kube-system | grep loongcollector-dsSLS also automatically creates the following resources. Log on to the Simple Log Service console to view them.
Resource type
Resource name
Function
Project
The value of
projectNamedefined in the values.yaml fileA resource management unit that isolates logs of different services.
To create a project for more flexible log resource management, see Create a project.
Machine group
k8s-group-${cluster_id}A collection of log collection nodes.
Logstore
config-operation-logImportantDo not delete this logstore.
Stores logs of the loongcollector-operator component. Its billing method is the same as that of a regular logstore. For more information, see Pay-by-data-written billable items. We recommend that you do not create collection configurations in this logstore.
Create a logstore
If you have already created a logstore, skip this step and proceed to create a collection configuration.
SLS supports two billing methods: pay-by-ingested-data and pay-by-feature. When you create a logstore, choose the appropriate billing method as needed.
Log on to the Simple Log Service console and click the name of the target project.
In the navigation pane on the left, choose
and click +.On the Create Logstore page, complete the following core configurations:
Logstore Name: Set a name that is unique within the project. This name cannot be changed after creation.
Logstore Type: Choose Standard or Query based on the specification comparison.
Billing Mode:
pay-by-feature: Billed independently for resources such as storage, indexing, and read/write operations. Suitable for small-scale use cases or when feature usage is uncertain.
pay-by-ingested-data: Billed only by the amount of raw data written. It provides a 30-day free storage period and free features such as data transformation and delivery. The cost model is simple and suitable for use cases where the storage period is close to 30 days or the data processing pipeline is complex.
Data Retention Period: Set the number of days to retain logs. The value ranges from 1 to 3650 days. 3650 days means permanent storage. The default is 30 days.
Keep the default settings for other configurations and click OK. For more information about other configurations, see Manage a logstore.
Minimal configuration
After you install LoongCollector and create a logstore, a collection configuration can be set up. This section describes two basic use cases: container standard output and cluster text logs. These use cases upload raw logs to the logstore without parsing or processing, making them suitable for quickly establishing a data channel.
On the Logstore
|
|
after Data Collection.
Collect container standard output (stdout)
| Raw log: |
Collected raw standard output (stdout): |
Collect cluster text logs
| Raw log: |
The entire raw log line is stored in the content field: |
Common processing configurations
After completing the minimal configuration, add processing plugins in the section to parse raw logs into structured data or perform data masking and filtering. To add processing plugins for an existing collection configuraiton, do as follows:
In the navigation pane on the left, choose
Logstores and find the target logstore.Click
before its name to expand the logstore.Click Logtail Configurations. In the configuration list, find the target Logtail configuration and click Manage Logtail Configuration in the Actions column.
On the Logtail configuration page, click Edit, scroll down to the section, and configure a parsing plugin.
This section describes only native plugins that cover common log processing use cases. For more information, see Extended plugins.
For Logtail 2.0 and later versions, and for the LoongCollector component, follow these plugin combination rules:
Prioritize using native plugins.
If native plugins cannot meet your needs, configure extended plugins after the native plugins.
Native plugins can only be used before extended plugins.
Structured configuration
Regular expression parsing
Use regular expressions to extract log fields and parse the log into key-value pairs.
| Raw log: |
Custom regular expression parsing: Regular expression |
Delimiter-based parsing
Use a delimiter to structure the log content and parse it into multiple key-value pairs. Both single-character and multi-character delimiters are supported.
Click Add Processor and choose :
| Raw log: |
Split fields by the specified character |
Standard JSON parsing
Structure an object-type JSON log and parse it into key-value pairs.
Click Add Processor and choose :
| Raw Log: |
Standard JSON key-value pairs are automatically extracted: |
Nested JSON parsing
Parse a nested JSON log into key-value pairs by specifying the expansion depth.
Click Add Processor and choose :
| Raw log: |
Expansion depth: 0, with the expansion depth used as a prefix. | |
Expansion depth: 1, with the expansion depth used as a prefix. |
JSON array parsing
Use the json_extract function to extract JSON objects from a JSON array.
Set Processing Method to SPL:
| Raw log: |
Extracted JSON array structure: |
NGINX log parsing
Structure the log content into multiple key-value pairs based on the definition in log_format. If the default content does not meet your needs, use a custom format.
Click Add Processor and choose :
| Raw log: |
Parsed into key-value pairs based on the |
Apache log parsing
Structure the log content into multiple key-value pairs based on the definition in the Apache log configuration file.
Click Add Processor and choose :
| Raw log: |
Apache Common Log Format |
Data masking
Mask sensitive data in logs.
In the Processor Configurations section, click Add Processor and choose :
| Raw log: |
Masking result: |
Content filtering
Match log field values based on regular expressions and collect only logs that meet the whitelist conditions.
In the Processor Configurations section, click Add Processor and choose :
| Raw log: |
Filtered log: Set Field Name to |
Time parsing
Parse the time field in the log and set the parsing result as the log's __time__ field.
In the Processor Configurations section, click Add Processor and choose :
| Raw log: |
Time parsing:
|
Other advanced configurations
After completing the minimal configuration or common processing configurations, perform the following operations to collect multiline logs, configure topic types, and more for fine-grained log collection.
To modify an existing collection configuration, do as follows:
In the navigation pane on the left, choose
Logstores and find the target logstore.Click
before its name to expand the logstore.Click Logtail Configurations. In the configuration list, find the target Logtail configuration and click Manage Logtail Configuration in the Actions column.
On the Logtail configuration page, click Edit.
Feature | Purpose |
Multiline log collection | Process cross-line logs such as Java stack traces. |
Log topic types | Set topics based on machine groups, file paths, or custom rules to categorize your log sources. |
Container filtering and blacklist |
|
Log tag enrichment | Add environment variables and container information as metadata fields. |
Compression for log transmission | Enable |
Multiline log collection
By default, SLS works in single-line mode, treating each line of text as a separate log. This can incorrectly split multiline logs containing content such as stack traces or JSON, leading to a loss of context.
To address this issue, enable Multi-line Mode and define a Regex to Match First Line. This allows SLS to accurately identify the starting line of a complete log, thereby merging multiple lines into a single log entry.
Processor Configurations:
| Raw log: |
Single-line mode: Each line is a separate log, and the stack information is broken up, losing context.
| |
Multi-line mode: A first-line regular expression identifies the complete log, preserving the full semantic structure. |
Configure topic types
: Select the topic generation method.
Machine Group Topic: SLS lets you apply one collection configuration to multiple machine groups. When LoongCollector reports data, it uses the machine group's topic as the log topic and uploads it to the logstore. Use topics to distinguish logs from different machine groups.
File Path Extraction: If different users or applications write logs to different top-level directories but with the same subdirectory paths and filenames, it becomes difficult to distinguish the log source from the filename. Configure File Path Extraction. Use a regular expression to match the full file path and use the matched result (username or application name) as the log topic to be uploaded to the logstore.
NoteIn the regular expression for the file path, you must escape the forward slash (/).
Extract using a file path regular expression
Use case: Different users record logs in different directories, but the log filenames are the same. The directory paths are as follows.
/data/logs ├── userA │ └── serviceA │ └── service.log ├── userB │ └── serviceA │ └── service.log └── userC └── serviceA └── service.logIf you only configure the file path as
/data/logsand the filename asservice.login the Logtail Configuration, LoongCollector (Logtail) will collect the content from all threeservice.logfiles into the same logstore. This makes it impossible to distinguish which user produced which log. Use a regular expression to extract values from the file path to generate different log topics.Regular expression
Extraction result
\/data\/logs\/(.*)\/serviceA\/.*__topic__: userA __topic__: userB __topic__: userCExtract using multiple capturing groups
Use case: If a single log topic is not enough to distinguish the source of the logs, configure multiple regular expression capturing groups in the log file path to extract key information. These capturing groups include named capturing groups (?P<name>) and unnamed capturing groups.
Named capturing group: The generated tag field is
__tag__:{name}.Unnamed capturing group: The generated tag field is
__tag__:__topic_{i}__, where{i}is the sequence number of the capturing group.
NoteWhen there are multiple capturing groups in the regular expression, the
__topic__field is not generated.For example, if the file path is
/data/logs/userA/serviceA/service.log, extract multiple values from the file path in the following ways:Example
Regular expression
Extraction result
Use an unnamed capturing group for regular expression extraction.
\/data\/logs\/(.*?)\/(.*?)\/service.log__tag__:__topic_1__: userA __tag__:__topic_2__: serviceAUse a named capturing group for regular expression extraction.
\/data\/logs\/(?P<user>.*?)\/(?P<service>.*?)\/service.log__tag__:user: userA __tag__:service: serviceAValidation: After configuration, query logs based on the log topic.
On the log query and analysis page, enter the corresponding generated log topic, such as
__topic__: userAor__tag__:__topic_1__: userA, to query logs for that topic.
Custom: Enter
customized:// + custom topic nameto use a custom static log topic.
Container filtering and blacklists
Container filtering
Input Configurations:
Enable Container Filtering, click Add, select a filtering method, and configure it. Multiple conditions are combined with an "AND" relationship.
Environment Variable Blacklist/Whitelist: Specify the environment variable conditions for the containers to be collected.
K8s Pod Label Blacklist/Whitelist: Specify the label conditions for the pod where the containers to be collected are located.
K8s Pod Name Regex Match: Specify the containers to be collected by pod name.
K8s Namespace Regex Match: Specify the containers to be collected by namespace name.
K8s Container Name Regex Match: Specify the containers to be collected by container name.
Container Label Blacklist/Whitelist: Collect containers whose labels meet the conditions. Used in Docker use cases. Not recommended for Kubernetes use cases.
All regular expression matching uses the Go language's RE2 engine, which has a limited feature set compared to engines such as PCRE. To write regular expressions, refer to Appendix: Regular expression limits (container filtering) for the correct syntax.
Blacklist
: Enable Collection Blacklist, click Add, and configure the blacklist.
Supports full matching and wildcard matching for directories and filenames. Wildcard characters only support the asterisk (*) and the question mark (?).
File Path Blacklist: The file path to be ignored. Example:
/home/admin/private*.log: During collection, ignore all files in the/home/admin/directory that start with "private" and end with ".log"./home/admin/private*/*_inner.log: During collection, ignore files ending with "_inner.log" within directories that start with "private" under the/home/admin/directory.
File Blacklist: Configure the filenames to be ignored during collection. Example:
app_inner.log: During collection, ignore all files namedapp_inner.log.
Directory Blacklist: The directory path cannot end with a forward slash (/). Example:
/home/admin/dir1/: The directory blacklist will not take effect./home/admin/dir*: During collection, ignore files in subdirectories that start with "dir" under the/home/admin/directory./home/admin/*/dir: During collection, ignore all files in subdirectories named "dir" at the second level under the/home/admin/directory. For example, files in the/home/admin/a/dirdirectory are ignored, while files in the/home/admin/a/b/dirdirectory are collected.
Log tag enrichment
:
Enable Log Tag Enrichment and click Add:
Environment Variables: Configure an environment variable name and a tag name. The environment variable value will be stored in the tag name.
Environment Variable Name: Specify the name of the environment variable to be extracted.
Tag Name: The name of the environment variable tag.
Pod Labels: Configure a pod label name and a tag name. The pod label value will be stored in the tag name.
Pod Label Name: The name of the Kubernetes pod label to be extracted.
Tag Name: The name of the tag.
Compression for log transmission
:
Only Logtail 1.3.4 and later versions support zstd compression.
lz4: Fast compression speed, lower compression ratio.
zstd: High compression ratio, slightly lower speed, high memory usage.
What to do next
Log query and analysis: Each collected container text log contains the following default field information:
Field
Description
__tag__:__hostname__
The name of the container's host.
__tag__:__path__
The path of the log file within the container.
__tag__:_container_ip_
The IP address of the container.
__tag__:_image_name_
The name of the image used by the container.
__tag__:_pod_name_
The name of the pod.
__tag__:_namespace_
The namespace to which the pod belongs.
__tag__:_pod_uid_
The unique identifier (UID) of the pod.
Data visualization: Use visualization dashboards to monitor key metric trends.
Automatic alerting for data anomalies: Set alert policies to detect system anomalies in real time.
Troubleshooting: No data collected from container logs
Check for new logs: After configuring LoongCollector (Logtail) for collection, if there are no new logs in the target log file, LoongCollector (Logtail) will not collect from that file.
Check the machine group heartbeat status: Go to the 
Resources > Machine Groups page, click the name of the target machine group. In the section, view the heartbeat status and record the number of nodes with an OK heartbeat status.
Check the number of worker nodes in the container cluster.
Obtain the cluster KubeConfig and connect to the cluster using kubectl.
View the number of worker nodes in the cluster.
kubectl get node | grep -v masterThe system will return a result similar to the following.
NAME STATUS ROLES AGE VERSION cn-hangzhou.i-bp17enxc2us3624wexh2 Ready <none> 238d v1.10.4 cn-hangzhou.i-bp1ad2b02jtqd1shi2ut Ready <none> 220d v1.10.4
Compare whether the number of nodes with an OK heartbeat status is consistent with the number of worker nodes in the container cluster. Choose a troubleshooting method based on the comparison result.
The heartbeat status of all nodes in the machine group is Failed:
If it is a self-managed cluster, check if the following parameters are configured correctly:
{regionId},{aliuid},{access-key-id}, and{access-key-secret}.If they are incorrect, run the
helm del --purge alibaba-log-controllercommand to delete the installation package, and then reinstall.
The number of nodes with an OK heartbeat status is less than the number of worker nodes in the cluster.
Determine if a DaemonSet has been manually deployed using a YAML file.
Run the following command. If there is a result, it means a DaemonSet was previously deployed manually using a YAML file.
kubectl get po -n kube-system -l k8s-app=logtailConfigure parameters such as ${your_region_name}, ${your_aliyun_user_id}, and ${your_machine_group_name} based on actual values.
Update the resource.
kubectl apply -f ./logtail-daemonset.yaml
FAQ
How do I send ACK cluster logs to a project in another Alibaba Cloud account?
Manually install LoongCollector (Logtail) in the ACK cluster and configure it with the target Alibaba Cloud account ID or AccessKey. This enables sending container logs to an SLS project in another Alibaba Cloud account.
Use case: Collect log data from an ACK cluster to an SLS project in a different Alibaba Cloud account for reasons such as organizational structure, permission isolation, or unified monitoring. Manually install LoongCollector (Logtail) for cross-account configuration.
Procedure: The following procedure uses the manual installation of LoongCollector as an example. To learn how to install Logtail, see Install and configure Logtail.
Connect to the Kubernetes cluster. Select the command for your region to download LoongCollector and its dependent components:
Regions in China:
wget https://aliyun-observability-release-cn-shanghai.oss-cn-shanghai.aliyuncs.com/loongcollector/k8s-custom-pkg/3.0.12/loongcollector-custom-k8s-package.tgz; tar xvf loongcollector-custom-k8s-package.tgz; chmod 744 ./loongcollector-custom-k8s-package/k8s-custom-install.shRegions outside China:
wget https://aliyun-observability-release-ap-southeast-1.oss-ap-southeast-1.aliyuncs.com/loongcollector/k8s-custom-pkg/3.0.12/loongcollector-custom-k8s-package.tgz; tar xvf loongcollector-custom-k8s-package.tgz; chmod 744 ./loongcollector-custom-k8s-package/k8s-custom-install.shGo to the
loongcollector-custom-k8s-packagedirectory and modify the./loongcollector/values.yamlconfiguration file.# ===================== Required Information ===================== # The name of the project where logs from this cluster will be collected, for example, k8s-log-custom-sd89ehdq projectName: "" # The region of the project, for example, Shanghai: cn-shanghai region: "" # The UID of the Alibaba Cloud account that owns the project. Enclose it in quotation marks, for example, "123456789" aliUid: "" # The network to use. Optional parameters: Internet, Intranet. The default is Internet. net: Internet # The AccessKey ID and AccessKey secret of the Alibaba Cloud account or RAM user. The account must have the AliyunLogFullAccess system policy permission. accessKeyID: "" accessKeySecret: "" # A custom cluster ID. The name can contain only uppercase letters, lowercase letters, digits, and hyphens (-). clusterID: ""In the
loongcollector-custom-k8s-packagedirectory, run the following command to install LoongCollector and other dependent components:bash k8s-custom-install.sh installAfter the installation is complete, check the running status of the components.
If the pod fails to start, check whether the values.yaml configuration is correct and whether the relevant images were pulled successfully.
# Check the pod status kubectl get po -n kube-system | grep loongcollector-dsSLS also automatically creates the following resources. Log on to the Simple Log Service console to view them.
Resource type
Resource name
Function
Project
The value of
projectNamedefined in the values.yaml fileA resource management unit that isolates logs of different services.
To create a project for more flexible log resource management, see Create a project.
Machine group
k8s-group-${cluster_id}A collection of log collection nodes.
Logstore
config-operation-logImportantDo not delete this logstore.
Stores logs of the loongcollector-operator component. Its billing method is the same as that of a regular logstore. For more information, see Pay-by-data-written billable items. We recommend that you do not create collection configurations in this logstore.
How can I collect logs from the same file or container standard output using multiple collection configurations?
By default, to prevent data duplication, SLS restricts each log source to be collected by only one collection configuration:
A text log file can only match one Logtail collection configuration.
A container's standard output (stdout) can also only be collected by one standard output collection configuration.
Log on to the Simple Log Service console and go to the target project.
In the navigation pane on the left, choose
Logstores and find the target logstore.Click
before its name to expand the logstore.Click Logtail Configurations. In the configuration list, find the target Logtail configuration and click Manage Logtail Configuration in the Actions column.
On the Logtail configuration page, click Edit and scroll down to the Input Configurations section:
To collect text file logs: Enable Allow File to Be Collected for Multiple Times.
To collect container standard output: Enable Allow Collection by Different Logtail Configurations.
Appendix: Regular expression limits (container filtering)
The regular expressions for container filtering are based on the Go RE2 engine. The RE2 engine has several syntax limitations compared to other engines, such as Perl Compatible Regular Expressions (PCRE). Note the following when you write regular expressions:
1. Named group syntax differences
Go uses the (?P<name>...) syntax to define named groups and does not support the (?<name>...) syntax from PCRE.
Correct:
(?P<year>\d{4})Incorrect:
(?<year>\d{4})
2. Unsupported regular expression features
The following common but complex regular expression features are not supported by RE2. Avoid using them:
Assertions:
(?=...),(?!...),(?<=...),(?<!...)Conditional expressions:
(?(condition)true|false)Recursive matching:
(?R),(?0)Subprogram references:
(?&name),(?P>name)Atomic groups:
(?>...)
3. Recommendations
Use a tool such as Regex101 to debug regular expressions. To validate compatibility, select the Golang (RE2) mode. The plugin cannot parse or match expressions that contain unsupported syntax.
More information
Global configuration parameters
Input configuration parameters
Processor configuration parameters
Parameter | Description |
Log Sample | A sample of the log to be collected. Use a log from your actual scenario. The log sample helps configure log processing parameters and reduces configuration difficulty. You can add multiple samples, with a total length not exceeding 1500 characters. |
Multi-line Mode |
|
Processing Method | Processors, which includes native and extended plugins. For more information, see Overview of Logtail plugins for data processing. Important For limitations on the use of processing plugins, refer to the prompts on the console page.
|
