OpenSearch
Send logs to Amazon OpenSearch Service
The OpenSearch output plugin lets you ingest your records into an OpenSearch database. The following instructions assume you have an operational OpenSearch service running in your environment.
Configuration parameters
This plugin supports the following parameters:
Host
IP address or hostname of the target OpenSearch instance.
127.0.0.1
Port
TCP port of the target OpenSearch instance.
9200
Path
OpenSearch accepts new data on HTTP query path /_bulk
. It's possible to serve OpenSearch behind a reverse proxy on a sub-path. This option defines such path on the Fluent Bit side. It adds a path prefix in the indexing HTTP POST URI.
Empty string
Buffer_Size
Specify the buffer size used to read the response from the OpenSearch HTTP service. Use for debugging purposes where it's required to read full responses. The response size grows depending of the number of records inserted. Set this value to False
to set an unlimited amount of memory. Otherwise set the value according to the Unit Size specification.
4KB
Pipeline
OpenSearch lets you set up filters called pipelines. This option defines which pipeline the database should use. For performance reasons is strongly suggested to do parsing and filtering on Fluent Bit side, avoid pipelines.
none
AWS_Auth
Enable AWS Sigv4 Authentication for Amazon OpenSearch Service.
Off
AWS_Region
Specify the AWS region for Amazon OpenSearch Service.
none
AWS_STS_Endpoint
Specify the custom STS endpoint to be used with STS API for Amazon OpenSearch Service.
none
AWS_Role_ARN
AWS IAM Role to assume to put records to your Amazon cluster.
none
AWS_External_ID
External ID for the AWS IAM Role specified with aws_role_arn
.
none
AWS_Service_Name
Service name to be used in AWS Sigv4 signature. For integration with Amazon OpenSearch Serverless, set to aoss
. See the FAQ section on Amazon OpenSearch Serverless for more information.
es
AWS_Profile
AWS profile name.
default
HTTP_User
Optional. Username credential for access.
none
HTTP_Passwd
Password for user defined in HTTP_User
.
none
Type
Type name. This option is ignored if Suppress_Type_Name
is enabled.
_doc
Logstash_Format
Enable Logstash format compatibility. This option takes a boolean value: True
/False
, On
/Off
Off
Logstash_Prefix
When Logstash_Format
is enabled, the Index name is composed using a prefix and the date. For example, if Logstash_Prefix
is equal to mydata
your index will become mydata-YYYY.MM.DD
. The last string appended belongs to the date when the data is being generated.
logstash
Logstash_Prefix_Key
When included, the value of the key in the record will be evaluated as key reference and overrides Logstash_Prefix
for index generation. If the key/value isn't found in the record then the Logstash_Prefix
option will act as a fallback. The parameter is expected to be a record accessor.
none
Logstash_Prefix_Separator
Set a separator between Logstash_Prefix
and Date
.
-
Logstash_DateFormat
Time format, based on strftime, to generate the second part of the Index
name.
%Y.%m.%d
Time_Key
When Logstash_Format
is enabled, each record will get a new timestamp field. The Time_Key
property defines the name of that field.
@timestamp
Time_Key_Format
When Logstash_Format
is enabled, this property defines the format of the timestamp.
%Y-%m-%dT%H:%M:%S
Time_Key_Nanos
When Logstash_Format
is enabled, enabling this property sends nanosecond precision timestamps.
Off
Include_Tag_Key
When enabled, append the Tag
name to the record.
Off
`Tag_Key
When Include_Tag_Key
is enabled, this property defines the key name for the tag.
_flb-key
Generate_ID
When enabled, generate _id
for outgoing records. This prevents duplicate records when retrying.
Off
Id_Key
If set, _id
will be the value of the key from incoming record and Generate_ID
option is ignored.
none
Write_Operation
Operation to use to write in bulk requests.
create
Replace_Dots
When enabled, replace field name dots (.
) with underscores (_
).
Off
Trace_Output
When enabled, print the OpenSearch API calls to stdout (for diagnostics only).
Off
Trace_Error
When enabled, print the OpenSearch API calls to stdout when OpenSearch returns an error (for diagnostics only).
Off
Current_Time_Index
Use current time for index generation instead of message record.
Off
Suppress_Type_Name
When enabled, mapping types is removed and the Type
option is ignored.
Off
Compress
Set payload compression mechanism. Allowed value: gzip
.
none (no compression)
The parameters index
and type
can be confusing if you are new to OpenSearch. If you have used a common relational database before, they can be compared to the database
and table
concepts. Also see the FAQ.
TLS / SSL
The OpenSearch output plugin supports TLS/SSL. For more details about the properties available and general configuration, see TLS/SSL.
write_operation
write_operation
The write_operation
can be any of:
create
(default)
Adds new data - if the data already exists (based on its id), the op is skipped.
index
New data is added while existing data (based on its id) is replaced (reindexed).
update
Updates existing data (based on its id). If no data is found, the op is skipped.
upsert
Known as merge
or insert
if the data doesn't exist. Updates if the data exists (based on its id).
Id_Key
or Generate_ID
is required for update
and upsert
.
Get started
To insert records into an OpenSearch service, you can run the plugin from the command line or through the configuration file.
Command line
The OpenSearch plugin can read the parameters from the command line in two ways, through the -p
argument (property) or by setting them directly through the service URI. The URI format is the following:
es://host:port/index/type
Using the format specified, start Fluent Bit through:
fluent-bit -i cpu -t cpu -o es://192.168.2.3:9200/my_index/my_type \
-o stdout -m '*'
which is similar to do:
fluent-bit -i cpu -t cpu -o opensearch -p Host=192.168.2.3 -p Port=9200 \
-p Index=my_index -p Type=my_type -o stdout -m '*'
Configuration file
In your main configuration file append the following:
pipeline:
inputs:
- name: cpu
tag: cpu
outputs:
- name: opensearch
match: '*'
host: 192.168.2.3
port: 9200
index: my_index
type: my_type
About OpenSearch field names
Some input plugins can generate messages where the field names contain dots (.
). The OpenSearch plugin replaces them with an underscore (_
):
{"cpu0.p_cpu"=>17.000000}
becomes
{"cpu0_p_cpu"=>17.000000}
FAQ
Logstash_Prefix_Key
Logstash_Prefix_Key
The following snippet demonstrates using the namespace name as extracted by the kubernetes
filter as logstash
prefix:
pipeline:
outputs:
- name: opensearch
match: '*'
# ...
logstash_prefix: logstash
logstash_prefix_key: $kubernetes['namespace_name']
For records that do nor have the field kubernetes.namespace_name
, the default prefix, logstash
will be used.
Fluent Bit and Amazon OpenSearch Service
The Amazon OpenSearch Service adds an extra security layer where HTTP requests must be signed with AWS Sigv4. This plugin supports Amazon OpenSearch Service with IAM Authentication.
For details about how AWS credentials are fetched, see AWS credentials.
Example configuration:
pipeline:
outputs:
- name: opensearch
match: '*'
host: vpc-test-domain-ke7thhzoo7jawsrhmm6mb7ite7y.us-west-2.es.amazonaws.com
port: 443
index: my_index
type: my_type
aws_auth: on
aws_region: us-west-2
tls: on
Notice that the Port
is set to 443
, tls
is enabled, and AWS_Region
is set.
Action/metadata contains an unknown parameter type
Similar to Elastic Cloud, OpenSearch in version 2.0 and later needs to have the type option removed by setting Suppress_Type_Name On
.
Without this you will see errors like:
{"error":{"root_cause":[{"type":"illegal_argument_exception","reason":"Action/metadata line [1] contains an unknown parameter [_type]"}],"type":"illegal_argument_exception","reason":"Action/metadata line [1] contains an unknown parameter [_type]"},"status":400}
Fluent-Bit and Amazon OpenSearch serverless
Amazon OpenSearch Serverless is an offering that eliminates your need to manage OpenSearch clusters. All existing Fluent Bit OpenSearch output plugin options work with OpenSearch Serverless. For Fluent Bit, you must specify the service name as aoss
(Amazon OpenSearch Serverless) when you enable AWS_Auth
:
pipeline:
outputs:
- name: opensearch
match: '*'
host: vpc-test-domain-ke7thhzoo7jawsrhmm6mb7ite7y.us-west-2.es.amazonaws.com
port: 443
index: my_index
type: my_type
aws_auth: on
aws_region: <aws-region>
aws_service_name: aoss
Data access permissions
When sending logs to OpenSearch Serverless, your AWS IAM entity needs OpenSearch Serverless Data Access permissions. Give your IAM entity the following data access permissions to your serverless collection:
aoss:CreateIndex
aoss:UpdateIndex
aoss:WriteDocument
With data access permissions, IAM policies aren't needed to access the collection.
Issues with the OpenSearch cluster
The Fluent Bit service might generate errors without any additional detail in the logs to explain the source of the issue, even with the service's log_level
attribute set to Debug.
For example, in this scenario the logs show that a connection was successfully established with the OpenSearch domain, and yet an error is still returned:
...
[2023/07/10 19:26:00] [debug] [http_client] not using http_proxy for header
[2023/07/10 19:26:00] [debug] [output:opensearch:opensearch.5] Signing request with AWS Sigv4
[2023/07/10 19:26:00] [debug] [aws_credentials] Requesting credentials from the EC2 provider..
[2023/07/10 19:26:00] [debug] [output:opensearch:opensearch.5] HTTP Status=200 URI=/_bulk
[2023/07/10 19:26:00] [debug] [upstream] KA connection #137 to [MY_OPENSEARCH_DOMAIN]:443 is now available
[2023/07/10 19:26:00] [debug] [out flush] cb_destroy coro_id=1746
[2023/07/10 19:26:00] [debug] [task] task_id=2 reached retry-attempts limit 5/5
[2023/07/10 19:26:00] [error] [engine] chunk '7578-1689017013.184552017.flb' cannot be retried: task_id=2, input=tail.6 > output=opensearch.5
[2023/07/10 19:26:00] [debug] [task] destroy task=0x7fd1cc4d5ad0 (task_id=2)
...
This behavior could be indicative of a hard-to-detect issue with index shard usage in the OpenSearch domain. Although OpenSearch index shards and disk space are related, they're not directly tied to one another. OpenSearch domains are limited to 1,000 index shards per data node, regardless of the size of the nodes. Shard usage isn't proportional to disk usage. An individual index shard can hold anywhere from a few kilobytes to dozens of gigabytes of data.
Depending index creation and shard allocation configuration in the OpenSearch domain, all the available index shards could be used before the data nodes run out of disk space. This can result in exhibition disk-related performance issues (nodes crashing, data corruption, or the dashboard going offline). The primary issue that arises when a domain is out of available index shards is that new indexes can no longer be created (although logs can still be added to existing indexes).
When that happens, the Fluent Bit OpenSearch output can show confusing behavior. For example:
Errors suddenly appear (outputs were previously working and there were no changes to the Fluent Bit configuration when the errors began)
Errors aren't consistently occurring (some logs are still reaching the OpenSearch domain)
The Fluent Bit service logs show errors, but without any detail as to the root cause
If any of those symptoms are present, consider using the OpenSearch domain's API endpoints to troubleshoot possible shard issues.
Running this command will show both the shard count and disk usage on all the nodes in the domain.
GET _cat/allocation?v
Index creation issues can appear if any hot data nodes have around 1,000 shards. Creation issues can also occur if the total number of shards spread across hot and ultra warm data nodes in the cluster is greater than 1,000 times the total number of nodes. For example, in a cluster with six nodes, the maximum shard count would be 6000
.
Alternately, running this command to manually create a new index will return an explicit error related to shard count if the maximum has been exceeded:
PUT <index-name>
There are multiple ways to resolve excessive shard usage in an OpenSearch domain. Deleting or combining indexes, adding more data nodes to the cluster, or updating the domain's index creation and sharding strategy can resolve this issue. Consult the OpenSearch documentation for more information about how to use these strategies.
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