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Apache Log Viewer Serial 13: The Ultimate Guide to Web Analytics and Reporting



You can also use the CustomLog directive to change the location of the log file. In Linux, Apache commonly writes logs to the /var/log/apache2 or /var/log/httpd directories depending on your OS and Virtual Host overrides. You can also define a LogFormat string after the filename, which will only apply the format string to this file.


Apache supports a rotatelogs program capable of rotating logs based on time or file size. However, the standard Linux logrotate command is available on most systems and is a good mechanism for Apache log rotation. On most systems, Apache will have a default plain text logrotate configuration file at /etc/logrotate.d/apache2 or /etc/logrotate.d/httpd.




Apache Log Viewer Serial 13




On Debian-based distributions, the default vhost configuration for unencrypted sites (port 80) can be found at /etc/apache2/sites-available/000-default.conf. The default vhost configuration for sites encrypted with SSL/TLS (port 443) is at /etc/apache2/sites-available/default-ssl.conf.


In OpenSUSE, the default vhost config for unencrypted sites (port 80) is located at /etc/apache2/default-vhost.conf, and the default config for sites encrypted with SSL/TLS is located at /etc/apache2/default-vhost-ssl.conf.


The consadm command enables you to select a serial device as an auxiliary (or remote) console. Using the consadm command, a system administrator can configure one or more serial ports to display redirected console messages and to host sulogin sessions when the system transitions between run levels. This feature enables you to dial in to a serial port with a modem to monitor console messages and participate in init state transitions. (For more information, see sulogin(1M) and the step-by-step procedures that follow.)


If you are logged in to a system using a serial port, and an init or shutdown command is issued to transition to another run level, the login session is lost whether this device is the auxiliary console or not. This situation is identical to releases without auxiliary console capabilities.


If you want to run an interactive login session by logging into a system using a terminal that is connected to a serial port,and then using the consadm command to see the console messages fromthe terminal, note the following behavior:


As the system is coming up, you must provide information to rc scripts on the default console device. After the system comes back up, the login program runs on the serial ports and you can log back into another interactive session. If you've designated the device to be an auxiliary console, you will continue to get console messages on your terminal, but all input from the terminal goes to your interactive session.


The node's serial ports output, if the VM instance metadataserial-port-logging-enable is set to true. As of GKE1.16-13-gke.400,serial port outputfor nodes is collected by the Logging agent. To disableserial port output logging, set--metadata serial-port-logging-enable=false during cluster creation.Serial port output is useful for troubleshooting crashes, failed boots,startup issues, or shutdown issues with GKE nodes.Disabling these logs might limit Google's ability to troubleshoot suchissues.


As of GKE 1.16-13-gke.400, serial port outputfor nodes is retained in Cloud Logging. To disable serial port output loggingto Cloud Logging, set --metadata serial-port-logging-enable=false duringcluster creation.


By storing them in a separate log bucket with limited access, control plane logsin the log bucket will not automatically be accessible to anyone withroles/logging.viewer access to the project. Additionally, if you decide todelete certain control plane logs due to privacy or security concerns, storingthem in a separate log bucket with limited access makes it possible to deletethe logs easily without impacting logs from other components or services.


Some PostgreSQL data types and functions have special rules regarding transactional behavior. In particular, changes made to a sequence (and therefore the counter of a column declared using serial) are immediately visible to all other transactions and are not rolled back if the transaction that made the changes aborts. See Section 9.17 and Section 8.1.4.


The Repeatable Read isolation level only sees data committed before the transaction began; it never sees either uncommitted data or changes committed during transaction execution by concurrent transactions. (However, the query does see the effects of previous updates executed within its own transaction, even though they are not yet committed.) This is a stronger guarantee than is required by the SQL standard for this isolation level, and prevents all of the phenomena described in Table 13.1 except for serialization anomalies. As mentioned above, this is specifically allowed by the standard, which only describes the minimum protections each isolation level must provide.


The Repeatable Read mode provides a rigorous guarantee that each transaction sees a completely stable view of the database. However, this view will not necessarily always be consistent with some serial (one at a time) execution of concurrent transactions of the same level. For example, even a read-only transaction at this level may see a control record updated to show that a batch has been completed but not see one of the detail records which is logically part of the batch because it read an earlier revision of the control record. Attempts to enforce business rules by transactions running at this isolation level are not likely to work correctly without careful use of explicit locks to block conflicting transactions.


The Serializable isolation level provides the strictest transaction isolation. This level emulates serial transaction execution for all committed transactions; as if transactions had been executed one after another, serially, rather than concurrently. However, like the Repeatable Read level, applications using this level must be prepared to retry transactions due to serialization failures. In fact, this isolation level works exactly the same as Repeatable Read except that it also monitors for conditions which could make execution of a concurrent set of serializable transactions behave in a manner inconsistent with all possible serial (one at a time) executions of those transactions. This monitoring does not introduce any blocking beyond that present in repeatable read, but there is some overhead to the monitoring, and detection of the conditions which could cause a serialization anomaly will trigger a serialization failure.


and obtains the result 300, which it inserts in a new row with class = 1. Then both transactions try to commit. If either transaction were running at the Repeatable Read isolation level, both would be allowed to commit; but since there is no serial order of execution consistent with the result, using Serializable transactions will allow one transaction to commit and will roll the other back with this message:


To guarantee true serializability PostgreSQL uses predicate locking, which means that it keeps locks which allow it to determine when a write would have had an impact on the result of a previous read from a concurrent transaction, had it run first. In PostgreSQL these locks do not cause any blocking and therefore can not play any part in causing a deadlock. They are used to identify and flag dependencies among concurrent Serializable transactions which in certain combinations can lead to serialization anomalies. In contrast, a Read Committed or Repeatable Read transaction which wants to ensure data consistency may need to take out a lock on an entire table, which could block other users attempting to use that table, or it may use SELECT FOR UPDATE or SELECT FOR SHARE which not only can block other transactions but cause disk access.


Predicate locks in PostgreSQL, like in most other database systems, are based on data actually accessed by a transaction. These will show up in the pg_locks system view with a mode of SIReadLock. The particular locks acquired during execution of a query will depend on the plan used by the query, and multiple finer-grained locks (e.g., tuple locks) may be combined into fewer coarser-grained locks (e.g., page locks) during the course of the transaction to prevent exhaustion of the memory used to track the locks. A READ ONLY transaction may be able to release its SIRead locks before completion, if it detects that no conflicts can still occur which could lead to a serialization anomaly. In fact, READ ONLY transactions will often be able to establish that fact at startup and avoid taking any predicate locks. If you explicitly request a SERIALIZABLE READ ONLY DEFERRABLE transaction, it will block until it can establish this fact. (This is the only case where Serializable transactions block but Repeatable Read transactions don't.) On the other hand, SIRead locks often need to be kept past transaction commit, until overlapping read write transactions complete.


Consistent use of Serializable transactions can simplify development. The guarantee that any set of successfully committed concurrent Serializable transactions will have the same effect as if they were run one at a time means that if you can demonstrate that a single transaction, as written, will do the right thing when run by itself, you can have confidence that it will do the right thing in any mix of Serializable transactions, even without any information about what those other transactions might do, or it will not successfully commit. It is important that an environment which uses this technique have a generalized way of handling serialization failures (which always return with an SQLSTATE value of '40001'), because it will be very hard to predict exactly which transactions might contribute to the read/write dependencies and need to be rolled back to prevent serialization anomalies. The monitoring of read/write dependencies has a cost, as does the restart of transactions which are terminated with a serialization failure, but balanced against the cost and blocking involved in use of explicit locks and SELECT FOR UPDATE or SELECT FOR SHARE, Serializable transactions are the best performance choice for some environments. 2ff7e9595c


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