WebLogic Analytics
Project description
$ wls-analytics
Advanced Log Analysis for WebLogic Server Clusters
In the landscape of clustered WebLogic servers, managing and analyzing logs can pose a significant challenge. wls-analytics is a command-line tool that enables you to analyze logs from multiple WebLogic servers and domains. It is designed to be used by administrators and engineers who need to quickly identify and resolve issues in clustered WebLogic environments.
wls-analytics offers a range of features tailored to the complexities of clustered WebLogic servers. It enables administrators and engineers to dissect logs within specific time intervals, construct efficient index files, and apply customizable patterns for data categorization.
Installation
You can install wls-analytics from PyPI as follows.
$ pip install wls-analytics
When you want to install from source, after you clone the repository, you can build the module as follows.
$ pip install --upgrade setuptools wheel
$ make build
The module package will be created under the dist
directory. You can then install it as follows.
pip install dist/wls_analytics-{version}-py3-none-any.whl
Please change the version of the module accordingly.
Run wlsanalytics --help
for details how to use the tool.
Features
There is a command to analyze SOA out logs. You can use it as follows.
Set the home directory of the tool in the WLSA_HOME
environment variable.
$ export WLSA_HOME=/path/to/wls-analytics
Create the configuration file in $WLSA_HOME/config/config.yaml
and define the sets of log files the tool should analyze. Please check config/config.yaml
for the sample configuration file.
In the same configuration file, define the patterns to be searched in logs. There is already a number of patterns defined in the file. You can add your own patterns as well.
Define the location of the configuration file in the WLSA_CONFIG
environment variable. Alternatively, you can provide the path to the configuration file as an argument to the command.
$ export WLSA_CONFIG=$WLSA_HOME/config/config.yaml
Run the command to analyze the set of log files called o2c
. The set must be defined in the configuration file.
$ wlsanalytics soa error o2c --from "2023-09-19 11:06:39" --to "2023-09-19 12:06:39"
There are various configuration options you can use. Run wlsanalytics soa error --help
for details.
As a result, you will get the following output:
-- Time range: 2023-09-19 11:06:39 - 2023-09-19 12:06:39
-- Searching files in the set 'o2c'
-- Reading entries from 2 files: 83.6MB [00:07, 12.4MB/s]
-- Completed in 9.43s
TIME SERVER FLOW_ID COMPOSITE ERROR DETAIL
2023-09-19 11:06:51.875000 soa_server1 1293508714 SyncCustomerPartyListBRMCommsProvA… ERR_VALIDATION_FAILED PCM_OP_UPDATE_CUSTOMER
2023-09-19 11:07:33.145000 soa_server1 1293447650 SyncCustomerPartyListBRMCommsProvA… ERR_VALIDATION_FAILED PCM_OP_UPDATE_CUSTOMER
2023-09-19 11:08:02.565000 soa_server1 1293525804 SyncCustomerPartyListBRMCommsProvA… ERR_VALIDATION_FAILED PCM_OP_UPDATE_CUSTOMER
...
When you use the index option --index
, there will be an index created for the output. You can then use to explore log entries that belong to specifc error by using the index value.
wlsanalytics soa index tevu
This will open the less
viewer on your local computer with the entries that belong to the error with the index value tevu
.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
File details
Details for the file wls_analytics-0.4.2-py3-none-any.whl
.
File metadata
- Download URL: wls_analytics-0.4.2-py3-none-any.whl
- Upload date:
- Size: 29.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.3
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a9cad641afce0f494dd35a9c883dbed7d4fd539a0330db7888ac442b70d593ee |
|
MD5 | 7325edf94ef2f01d3bd524180725d934 |
|
BLAKE2b-256 | 01205bf51ecd02e3181d867e122c62c31799ab010a18880b34187546f3a17607 |