Displaying 1 to 10 from 22 results

Scribe - Real time log aggregation used in Facebook

Scribe is a server for aggregating log data that's streamed in real time from clients. It is designed to be scalable and reliable. It is developed and maintained by Facebook. It is designed to scale to a very large number of nodes and be robust to network and node failures. There is a scribe server running on every node in the system, configured to aggregate messages and send them to a central scribe server (or servers) in larger groups.

Logstash - Centralized log storage, indexing, and searching

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use. Logstash comes with a web interface for searching and drilling into all of your logs.

Octopussy - Perl/XML Logs Analyzer, Alerter & Reporter

Octopussy is a Log analyzer tool. It analyzes the log, generates reports and alerts the admin. It has LDAP support to maintain users list. It exports report by Email, FTP & SCP. Scheduled reports could be generated. RRD tool to generate graphs.

Awstats - Advanced web, streaming, ftp and mail server statistics

AWStats is a powerful tool that generates advanced web, streaming, ftp or mail server statistics graphically. It can analyze log files from all major server tools like Apache log files, WebStar, IIS and a lot of other web, proxy, wap, streaming servers, mail servers and some ftp servers. This log analyzer works as a CGI or from command line and shows you all possible information your log contains, in few graphical web pages.

nxlog - Multi platform Log management

nxlog is a modular, multi-threaded, high-performance log management solution with multi-platform support. In concept it is similar to syslog-ng or rsyslog but is not limited to unix/syslog only. It can collect logs from files in various formats, receive logs from the network remotely over UDP, TCP or TLS/SSL . It supports platform specific sources such as the Windows Eventlog, Linux kernel logs, Android logs, local syslog etc.

Graylog2 - Open Source Log Management

Graylog2 is an open source log management solution that stores your logs in ElasticSearch. It consists of a server written in Java that accepts your syslog messages via TCP, UDP or AMQP and stores it in the database. The second part is a web interface that allows you to manage the log messages from your web browser. Take a look at the screenshots or the latest release info page to get a feeling of what you can do with Graylog2.

Meniscus - The Python Event Logging Service

Meniscus is a Python based system for event collection, transit and processing in the large. It's primary use case is for large-scale Cloud logging, but can be used in many other scenarios including usage reporting and API tracing. Its components include Collection, Transport, Storage, Event Processing & Enhancement, Complex Event Processing, Analytics.

Flume - Log management using HDFS

Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.

Fluentd - Data collector, Log Everything in JSON

Fluentd is an event collector system. It is a generalized version of syslogd, which handles JSON objects for its log messages. It collects logs from various data sources and writes them to files, database or other types of storages.

Kafka - A high-throughput distributed messaging system

Kafka provides a publish-subscribe solution that can handle all activity stream data and processing on a consumer-scale web site. This kind of activity (page views, searches, and other user actions) are a key ingredient in many of the social feature on the modern web. This data is typically handled by "logging" and ad hoc log aggregation solutions due to the throughput requirements. This kind of ad hoc solution is a viable solution to providing logging data to Hadoop.