Sending emails from web applications like PHP may result in rejecting the emails from some servers. Fighting spam emails results in too strict filters and rules, which reject the mails even before the anti-spam service of the accepting server. Here is an error:
Apr 1 04:10:18 srv-mail postfix/pickup: AB13578FAB3: uid=1015 from=<www-data>
Apr 1 04:10:18 srv-mail postfix/cleanup: AB13578FAB3: message-id=<20200401041018.AB13578FAB3@www.mydomain.com>
Apr 1 04:10:18 srv-mail postfix/qmgr: AB13578FAB3: from=<email@example.com>, size=7923, nrcpt=1 (queue active)
Apr 1 04:10:19 srv-mail postfix/smtp: AB13578FAB3: to=<firstname.lastname@example.org>, relay=mx.example.com[188.8.131.52]:25, delay=11, delays=0.02/0.01/0.65/10, dsn=5.0.0, status=bounced (host mx.example.com[184.108.40.206] said: 550-Sender verification is required but failed. (ID:550:0:5 550 (smtp1.mx.example.com)): email@example.com (in reply to MAIL FROM command))
The receiving server has too strict rules!
It just expects the “From” and the “Return-Path” headers to contain the same string – the sender’s email box.
As you can see, from the example above, the application sends all emails (from let’s say web forms) from the firstname.lastname@example.org and probably the www-data is the username of the OS user, under which the application executes.
Or you want to overwrite the Return-Path because it uses the username of the application, which sent the email like “web”, “apache”, “www-data” and so on.
Here is how to overwrite the Return-Path with postfix mail system.
STEP 1) Edit postfix configuration
Add a line in /etc/postfix/main.cf (it is perfectly fine to be on the last line):
smtp_generic_maps = hash:/etc/postfix/generic
And create the file /etc/postfix/generic with mapping “email@example.com firstname.lastname@example.org”:
The domains of the emails may be different or the same. It doesn’t matter. If you do not know what is your “email@example.com” the mail logs in /var/log/messages or /varlog/mail maight help to find the emailbox or just send yourself an email and look for the Return-Path.
And a real-world example for /etc/postfix/generic
STEP 2) Generate the hash file, which postfix will use. Reload the postfix.
The postfix will use the hash file add in the configuration. Just execute:
The above command will create a binary file /etc/postfix/generic.db, which will be used by the postfix mail system. Do not edit the file directly. To add entry, just use a text editor and edit /etc/postfix/generic (without the “.db” suffix) and then reload/restart the postfix to enable the new configuration.
And reload (or restart) postfix with
1) active connections – active (executing PHP code on the CPU right now – “php running”), max active, idle; 2) requests; 3) performance – max children reached or slow requests (it depends on your version of netdata).
CHART 4) PHP-FPM – request information
1) reuqest duration – minimum, maximum, avarage – how much time do a request take time – very useful to see how fast is your backend application. 2) request CPU in procentages; 3) request memory – reuested memory by your php fpm processes.
CHART 5) MySQL – performance metrics
1) bandwidth – The amount of data sent to mysql clients (out) and received from mysql clients (in); 2) queries – The number of statements executed by the server. To see a slow queries the slow query log should be enabled.
CHART 6) MySQL – handlers and locks
1) handlers – netdata Quotation: “Usage of the internal handlers of mysql. This chart provides very good insights of what the mysql server is actually doing. – commit, the number of internal COMMIT statements; delete, the number of times that rows have been deleted from tables; prepare, a counter for the prepare phase of two-phase commit operations; read first, the number of times the first entry in an index was read. A high value suggests that the server is doing a lot of full index scans; e.g. SELECT col1 FROM foo, with col1 indexed; read key, the number of requests to read a row based on a key. If this value is high, it is a good indication that your tables are properly indexed for your queries; read next, the number of requests to read the next row in key order. This value is incremented if you are querying an index column with a range constraint or if you are doing an index scan; read prev, the number of requests to read the previous row in key order. This read method is mainly used to optimize ORDER BY … DESC; read rnd, the number of requests to read a row based on a fixed position. A high value indicates you are doing a lot of queries that require sorting of the result. You probably have a lot of queries that require MySQL to scan entire tables or you have joins that do not use keys properly; read rnd next, the number of requests to read the next row in the data file. This value is high if you are doing a lot of table scans. Generally this suggests that your tables are not properly indexed or that your queries are not written to take advantage of the indexes you have; rollback, the number of requests for a storage engine to perform a rollback operation; savepoint, the number of requests for a storage engine to place a savepoint; savepoint rollback, the number of requests for a storage engine to roll back to a savepoint; update, the number of requests to update a row in a table; write, the number of requests to insert a row in a table.” 2) MySQL table locks counters, netdata Quotation: ” immediate, the number of times that a request for a table lock could be granted immediately – waited, the number of times that a request for a table lock could not be granted immediately and a wait was needed. If this is high and you have performance problems, you should first optimize your queries, and then either split your table or tables or use replication.”
CHART 7) MySQL – sorts, selects and temporaries
1) mysql SELECT JOIN – full range, range, scan; 2) mysql sorts – range and scan; 3) temporaries – disk tables (writing to the disk is slow and should be avoided!!!) and tables.
CHART 8) MySQL – connections and binlog
1) connections in seconds – all and aborted – if you are using persistent connections to MySQL you can see a busy MySQL server could have 2-3 new connections in a minute, because all the application backend uses the pool of already opened connections to the server. 2) connection errors – accepted, internal, max, peer_addr, select, tcpwrap; 3) binlog transactions per second
1) Innodb I/O bandwidth – reads and writes; 2) Innodb I/O Operations – reads, writes and fsyncs; 3) Innodb Pending I/O Operations – reads and fsyncs; 4) Innodb Log Operations – write requests and writes.
CHART 11) MySQL – Innodb engine infromation 2
1) Innodb OS Log Operations – fsyncs; 2) Innodb OS Log bandwidth – write (megabytes/s); 3) Innodb current row locks – current_waits; 4) Innodb row operations – inserted, read, updated and deleted.
CHART 12) MySQL – Innodb engine infromation 3
1) Innodb buffer pool pages – data, dirty, free, flushed, misc, total; 2) Innodb buffer pool bytes – data and dirty; 3) Innodb buffer pool read ahaed – all, evicted, random; 4) Innodb buffer pool requests – reads and writes per second.
CHART 13) MySQL – Innodb engine infromation 4
1) Innodb buffer pool operations – disk reads – operations per second.
CHART 14) MySQL – query cache (qcache)
1) query cache operations – hits, low memory prunes, inserts, not cached; 2) queries in the cache; 3) query cache free memory; 4) query cache memory blocks – free and total.
CHART 15) MySQL – myisam engine information
This server does not uses MyISAM engine, so you can see almost everything is zero – 1) MyISAM key cache blocks – unused and used; 2) MyISAM key cache requests – reads and writes; 3) MyISAM key cache disk operation – reads and writes.
CHART 16) MySQL – files
1) open files – how many files are opened at the moment; 2) opened file rate – files per second.
1) cache size – available and used; 2) network – in and out megabytes per second.
CHART 18) Memcached – connections and items
1) connections – current and total. Persistent connections are used, so no new connections often; 2) items cached – current and total. 3) items – evicted (forced removed – be careful here, this means your cached items are forcedly removed by the server because of lack of memory?) and reclaims (expired items).
CHART 19) Memcached – get and set operations
1) get operation requests – hits and misses; 2) get operations rate – requests per second; 3) set operation requests – requests per second.
CHART 20) Memcached – check and set ops, delete ops, increment ops
1) check and set operation requests – hits, misses, bad value; 2) delete operation requests – hits and misses; increment operation requests – hits and misses
CHART 21) Memcached – decrement ops, touch ops
1) decrement operation request – hits and misses; 2) touch operation requests – hits and misses; 3) touch operation requests rate – requests per second.
CHART 22) Postfix – mail service
1) Postfix Queue Emails – the emails in the queue of the mail transfer agent, these mails are in transfer state; 2) Postfix Queue Emails size – size.
CHART 23) Redis – performance metrics for in-memory data structure store, used as a database, cache and message broker.
1) operations – commands and operations per second; 2) hit rate – persentage, the effectiveness of the cache.
CHART 24) Redis – memory, keys, network
1) Redis memory utilization – total and lua; 2) keys – how many keys does each database have – keys per database name; 3) network – Redis network bandwidth – in and out in megabytes per second.
CHART 25) Redis – connections and replication
1) Redis connections – received per second – it’s like new connections and if you use persistent connections no new connections are opened often; 2) Redis clients – connected processes to the redis server; 3) replication – connected slave servers.
CHART 26) Redis – persistence (save the databases to the disks)
1) Persistence changes since last save – changes – how many changed items have been there since last save of the databases to the disks. 2) Duration of the RDB Save operation – rdb save in time; 3) Status of the last RDB Save Operation – rdb status.
CHART 27) Web server access logs information
Live parsing of the access logs – be careful here, because this could take a good deal of CPU and I/O of your busy server. Here we included only the default nginx log, which does not save many records. netdata Quotation: “Information extracted from a server log file. web_log plugin incrementally parses the server log file to provide, in real-time, a break down of key server performance metrics. For web servers, an extended log file format may optionally be used (for nginx and apache) offering timing information and bandwidth for both requests and responses. web_log plugin may also be configured to provide a break down of requests per URL pattern (check /etc/netdata/python.d/web_log.conf).” – 1) responses – success and bad requests per second; 2) Response codes – 1xx and 4xx and more if any in the logs.
CHART 28) Web server access logs information – detailed response code, bandwidth, http methods
1) detailed response code – requests per second; 2) bandwidth of the requests and reponses; 3) Requests per HTTP Method – GET, POST, PUT, DELETE and so on if they present in the logs.
CHART 29) Web server access logs information – http versions, ip protocols, clients
1) Requests per HTTP Version – 1.0, 1.1 and 2.0 if any in the logs; 2) Requests per IP protocol – IPv4 and IPv6 (if used); 3) clients – unique client IPs per data collection.
CHART 30) Web server access logs information – unique client IPs