Viewing and Setting Up System Logs

To filter logs:

1. Click the Add Filter button.

2. Select filtering option in the drop-down list:

• State. Select one of the statuses: Executing, Successful, Error, Cancel, Information, Warning.

• Event. Select type of event from the list.

• Account Type. Select the account type: Administrator, API user.

• Authentication Type. Select type of authentication from the list.

• Login. Specify login.

• Device ID. Specify device identifier.

• IP Address/Host. Specify IP address or host.

• Start. Specify date ranges and event start time.

• End. Specify date ranges and event end time.

• Synchronization. Specify date ranges and event synchronization time.

• Environment. Specify environment name.

• Project. Specify project name.

• Data Source. Specify data source name.

• Resource. Specify resource name.

• Group. Specify group name.

• Users. Specify user name.

• Recipients List. Specify recipients list.

• Loading. Specify data transfer time.

• Saving. Specify time of event saving to database.

• Total Time. Specify total time of request processing.

• Reading. Specify time of reading from database.

After executing the operation logs are filtered according to the specified conditions.

NOTE. To monitor system errors, filter the log with records by the Error status. If required, specify date ranges and time of event start and end.

To export logs to a JSON file:

1. Filter logs if required.

2. Click the Export button.

After executing the operations the logs will be filtered according to the specified conditions and will be exported to the logs.json file.

It is used to work with the following data sources: PostgreSQL, Local Database, cache-db Database.

The example of request execution command:

psql --connect-timeout=4 -h <IP address or DNS name of server> -p 5432 -d database -U <user name> -W <user password> -c "SET search_path TO public; SELECT * FROM fruit_upsert(upsert_rows := ARRAY[]::::"public".fruit_struct[], delete_ids := ARRAY[]::::"public".fruit_id[]);"

The command should contain the user credentials used by mobile platform server to address data source.

The command can be executed using one of the methods:

• From the fmp_server_1 container on mobile platform server.

• From the fmp-dashboard pod in the cluster deployed on Kubernetes or Deckhouse.

• From any external system, which has access to the data source and where the postgresql-client utility is installed.

It is used for the SAP, 1C, SOAP, JSON, WEB data source.

The example of request execution command:

curl -i --user <user name>:<user password> --header "Content-Type: application/json" --header "Accept: application/json" --header "Connection: keep-alive" --data ''{"IM_ZHHT_BASET": []}'' 'http://<IP address or DNS name of server>:00/sap/client=b75&mandant=001/ZHHDEMO_1TABLE?lang=RU'

The command should contain the user credentials used by mobile platform server to address data source.

The command can be started from any external system, which has access to the data source and where the curl utility 7.81.0 or later is installed.

It is used for the Oracle data source.

The example of request execution command:

sqlplus <user name>/<user password>@<IP address or DNS name of server>:1521/orcl <<EOF
SELECT "R_ID", "R_NAME" FROM TABLE(PCKDEMOMERGE.fruits_get(ID1 => :ID1))
EXIT
EOF

The command should contain the user credentials used by mobile platform server to address data source.

THe command can be started from any external system, which has access to the data source and where sqlplus utility 12.1 or later is installed.

It is used for the SQL Server data source.

The example of request execution command:

sqlcmd -S <IP address DNS name of server> -d mobile_data -U  <user name> -P <user password> -Q "SET CONNECTION TIMEOUT 40; DECLARE @scalar_text varchar(max) = param_test;DECLARE @scalar_int int = None;DECLARE @scalar_bigint bigint = None;DECLARE @scalar_decimal decimal(18, 0) = None;DECLARE @scalar_numeric numeric(18, 0) = None;DECLARE @scalar_float float(53) = None;DECLARE @scalar_datetimeoffset datetimeoffset = CONVERT(datetimeoffset, None);DECLARE @scalar_varchar varchar(max) = None;DECLARE @scalar_nvarchar nvarchar(max) = None;DECLARE @scalar_ntext nvarchar(max) = None;DECLARE @scalar_varbinary varbinary(max) = None; EXEC [dbo].[hhdemo_basescalars] @scalar_text = @scalar_text, @scalar_int = @scalar_int, @scalar_bigint = @scalar_bigint, @scalar_decimal = @scalar_decimal, @scalar_numeric = @scalar_numeric, @scalar_float = @scalar_float, @scalar_datetimeoffset = @scalar_datetimeoffset, @scalar_varchar = @scalar_varchar, @scalar_nvarchar = @scalar_nvarchar, @scalar_ntext = @scalar_ntext, @scalar_varbinary = @scalar_varbinary;"

The command should contain the user credentials used by mobile platform server to address data source.

The command can be started from any external system, which has access to the data source and where the sqlcmd utility 17.6.1.1 or later is installed.

It is used for the Foresight data source.

The example of data source request execution using python script:

import http.client
import json
from typing import Optional
 
# Set user credentials
hashed_password = "<user password>"

username = "<user name>"

repository_id = "FUNCTION"
fap_type = "D"
fap_object = "195258"
params = json.loads("{"attributes": []}")
structures = json.loads("{}")
url_path = "/FPBI_App_v10.x/axis2/services/PP.SOM.Som"

method = "POST"
.........................................
.........................................
.........................................
 
# open DIM
payload = open_dim(metabase_moniker, combo_param_monikers)
conn.request(method, url_path, payload, headers)
res = conn.getresponse()
response_data = json.loads(res.read().decode("utf-8"))
meta = response_data["OpenDimResult"]["meta"]
data_ = meta["els"]["els"]["e"] if "e" in meta["els"]["els"] else []
keys = [elem["id"] for elem in meta["data"]["attrs"]["it"]]
a_rows = (elem["a"]["it"] for elem in data_)
ea_rows = (
    map(lambda x: x.get("@dv", None) if isinstance(x, dict) else None, elem["ea"]["it"])
    for elem in data_
)
result_data = {
    "a": (dict(zip(keys, row)) for row in a_rows),
    "ea": (dict(zip(keys, row)) for row in ea_rows),
}

The script should contain the user credentials used by mobile platform server to address the data source.

Save script text to a *.py file and execute the command:

python3 <file name>.py

The script can be executed from any external system, which has access to the data source and were Python is installed.

In some resources the latest cache version is stored in RAM, and mobile platform server addresses Redis to handle a user request. This request can also be reproduced.

The example of request execution command:

redis-cli -a {<Redis user password>} --no-auth-warning HGETALL name
redis-cli -a {<Redis user password>} --no-auth-warning HMGET storage param1 param2
redis-cli -a {<Redis user password>} --no-auth-warning HGET storage param

The command can be executed using one of the methods:

• From the fmp_server_1 container on mobile platform server.

• From the fmp-dashboard pod in the cluster deployed on Kubernetes or Deckhouse.