zhongyu211/diagnose
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Overview Architecture The Diagnose project will use Django as the web framework, below is the Django architecture: 1. The URL dispatcher (urls.py) maps the requested URL to a view function and calls it. If catching is enabled, the view function can check to see if a cached version of the page exists and bypass all further steps, returning the cached version, instead, Note that this page-level caching is only one available caching option in Django. You can cache more granularly, as well. 2. The view function (usually in views.py) performs the requested action, which typically involves reading or writing to the database. It may include other tasks, as well. 3. The model (usually in models.py) defines the data in Python and interacts with it, although typically contained in a relational database (MySQL in diagnose project), other data storage mechanisms are possible as well (XMl, text files, LDAP, etc.). 4. After performing any requested tasks, the view returns an HTTP response object (usually after passing the data through a template) to the web browser. Optionally, the view can save a version of the HTTP response object in the caching system for a specified length of time. 5. Templates typically return HTML pages. The Django template language offers HTML authors a simple-to-learn syntax while providing all the power needed for presentation logic. Performance This module will show the system performance statics Critical resource display Data structure: Thanks to SDM measurement table SDM_MEAS_LOAD_STATION_HSS as original data, below info are stored in DB: Table: SDM_MEAS_LOAD_STATION_HSS FEName Day Time MsgClass Blade Duration STATION_ID ACTIVE_IN_AO_NUM ROLLBACK_ACTIVE_JOBNUM Note: FEName -> NodeName Remove MsgClass, Blade UI Time selection: duration or point Resource selection: single or multiple resource Blade selection: single or multiple blades Output: CPU usage per process Data structure: Thanks to mCAS measurement table MS_PROCESS_MEAS as original data, below info are stored in DB: Table: MS_PROCESS_MEAS Node Day Time Blade Process CPU UI Time selection: duration or point Blade selection: single or multiple blades Trouble shooting This module will provide a simple troubleshooting feature: Solution Search PRID/PUID in Description and return all lines containing this sub info Data structure: NodeName Day Time MsgClass Blade Title Description Log ID UI User input: sub info(PUID/PRID) Message type: MAR, SAR, UDR… Timeslot: duration Abnormal logs This module will show the histogram of log ID stored in DB, such as top 10 error types. Solution Fetch all record in a period and Sort by LogID, then display it using histogram. UI Timeslot: duration Timeslot: duration Number: digit Utils sdm_dmt_parser.py This script is used to generate table schema Input: /vob/sdm_mcas/src/utils/meas/SDM.dmt Output: models.py class SDM_MEAS_LOAD_STATION_HSS(models.Model): FEName = models.TextField(blank = True, null = True) Day = models.DateField() Time = models.TimeField() MsgClass = models.TextField(blank = True, null = True) Blade = models.TextField(blank = True, null = True) Duration = models.TextField(blank = True, null = True) STATION_ID = models.TextField(blank = True, null = True) PROCESS_NAME = models.TextField(blank = True, null = True) ACTIVE_IN_AO_NUM = models.TextField(blank = True, null = True) ACTIVE_IN_AO_NUM_MEAN = models.TextField(blank = True, null = True) omlog_parser.py This script is used to parse OMlog and IMSRTlog etc. Input: OMlog and IMSRTLog files Output: txt files meas_parser.py this script is used to parse meas logs. Input: measlog* files Output: txt files
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This is a project for do diagnose the Alcatel-Lucent SDM project
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