Results for next-machine

Next-generation machine learning infrastructure

Speed up your Vagrant workflow

To create seed data based on your development database? Run the dump tasks, commit the files, and on the next machine run the laod tasks.

This plugin helps you setup and debug `ssh-doctor` forwarding for Capistrano deployment. It peforms a number of checks on the local machine as well as on the servers. Report output with suggested next steps is provided in case there are any errors with the setup.

An enhanced state machine gem for ruby (doesn't require Rails). Provides more robust DSL state declaration syntax than other state machines. Multiple "actions" per event (i.e., next state, labmda, or a "decider".

State machines are awesome but sometimes you need a little more. Like who should do what in order for it to move on? How many steps are left? How can I restfully trigger the next event? Self Control adds route helpers, controller actions and a dsl to turn your existing state machines into full workflows. It is designed to use rails 3 with ActiveModel and should work with any state machine with just a few extra methods.

This plugin helps you setup and debug `ssh-agent` forwarding for Capistrano deployment. It peforms a number of checks on the local machine as well as on the servers. Report output with suggested next steps is provided in case there are any errors with the setup.

This Ruby gem leverages Machine Learning(ML) techniques to make predictions(forecasts) and classifications in various applications. It provides capabilities such as predicting next month's billing, forecasting upcoming sales orders, identifying patient's potential findings(like Diabetes), determining user approval status, classifying text, generating similarity scores, and making recommendations. It uses Python3 under the hood, powered by popular machine learning techniques including NLP(Natural Language Processing), Decision Tree, K-Nearest Neighbors and Logistic Regression, Random Forest and Linear Regression algorithms.

Often Redis is used for rate limiting purposes. Usually the rate limit packages available count how many times something happens on a certain second or a certain minute. When the clock ticks to the next minute, rate limit counter is reset back to the zero. This might be problematic if you are looking to limit rates where hits per integration time window is very low. If you are looking to limit to the five hits per minute, in one time window you get just one hit and six in another, even though the average over two minutes is 3.5. This package allows you to implement a correct rolling window of threshold that's backed by ATOMIC storage in Redis meaning you can use this implementation across multiple machines and processes.

OCRAN (One-Click Ruby Application Next) packages Ruby applications for distribution. It bundles your script, the Ruby interpreter, gems, and native libraries into a self-contained artifact that runs without requiring Ruby to be installed on the target machine. Three output formats are supported on all platforms: - Self-extracting executable (.exe on Windows, native binary on Linux/macOS) - Directory with a launch script (--output-dir) - Zip archive with a launch script (--output-zip) This is a fork of OCRA maintained for Ruby 3.2+ compatibility. Migration guide: replace OCRA_EXECUTABLE with OCRAN_EXECUTABLE in your code. Usage: ocran helloworld.rb # builds helloworld.exe / helloworld ocran --output-dir out/ app.rb ocran --output-zip app.zip app.rb See readme at https://github.com/largo/ocran Report problems at https://github.com/largo/ocran/issues

Log2json lets you read, filter and send logs as JSON objects via Unix pipes. It is inspired by Logstash, and is meant to be compatible with it at the JSON event/record level so that it can easily work with Kibana. Reading logs is done via a shell script(eg, `tail`) running in its own process. You then configure(see the `syslog2json` or the `nginxlog2json` script for examples) and run your filters in Ruby using the `Log2Json` module and its contained helper classes. `Log2Json` reads from stdin the logs(one log record per line), parses the log lines into JSON records, and then serializes and writes the records to stdout, which then can be piped to another process for processing or sending it to somewhere else. Currently, Log2json ships with a `tail-log` script that can be run as the input process. It's the same as using the Linux `tail` utility with the `-v -F` options except that it also tracks the positions(as the numbers of lines read from the beginning of the files) in a few files in the file system so that if the input process is interrupted, it can continue reading from where it left off next time if the files had been followed. This feature is similar to the sincedb feature in Logstash's file input. Note: If you don't need the tracking feature(ie, you are fine with always tailling from the end of file with `-v -F -n0`), then you can just use the `tail` utility that comes with your Linux distribution.(Or more specifically, the `tail` from the GNU coreutils). Other versions of the `tail` utility may also work, but are not tested. The input protocol expected by Log2json is very simple and documented in the source code. ** The `tail-log` script uses a patched version of `tail` from the GNU coreutils package. A binary of the `tail` utility compiled for Ubuntu 12.04 LTS is included with the Log2json gem. If the binary doesn't work for your distribution, then you'll need to get GNU coreutils-8.13, apply the patch(it can be found in the src/ directory of the installed gem), and then replace the bin/tail binary in the directory of the installed gem with your version of the binary. ** P.S. If you know of a way to configure and compile ONLY the tail program in coreutils, please let me know! The reason I'm not building tail post gem installation is that it takes too long to configure && make because that actually builds every utilties in coreutils. For shipping logs to Redis, there's the `lines2redis` script that can be used as the output process in the pipe. For shipping logs from Redis to ElasticSearch, Log2json provides a `redis2es` script. Finally here's an example of Log2json in action: From a client machine: tail-log /var/log/{sys,mail}log /var/log/{kern,auth}.log | syslog2json | queue=jsonlogs \ flush_size=20 \ flush_interval=30 \ lines2redis host.to.redis.server 6379 0 # use redis DB 0 On the Redis server: redis_queue=jsonlogs redis2es host.to.es.server Resources that help writing log2json filters: - look at log2json.rb source and example filters - http://grokdebug.herokuapp.com/ - http://www.ruby-doc.org/stdlib-1.9.3/libdoc/date/rdoc/DateTime.html#method-i-strftime

Log2json lets you read, filter and send logs as JSON objects via Unix pipes. It is inspired by Logstash, and is meant to be compatible with it at the JSON event/record level so that it can easily work with Kibana. Reading logs is done via a shell script(eg, `tail`) running in its own process. You then configure(see the `syslog2json` or the `nginxlog2json` script for examples) and run your filters in Ruby using the `Log2Json` module and its contained helper classes. `Log2Json` reads from stdin the logs(one log record per line), parses the log lines into JSON records, and then serializes and writes the records to stdout, which then can be piped to another process for processing or sending it to somewhere else. Currently, Log2json ships with a `tail-log` script that can be run as the input process. It's the same as using the Linux `tail` utility with the `-v -F` options except that it also tracks the positions(as the numbers of lines read from the beginning of the files) in a few files in the file system so that if the input process is interrupted, it can continue reading from where it left off next time if the files had been followed. This feature is similar to the sincedb feature in Logstash's file input. Note: If you don't need the tracking feature(ie, you are fine with always tailling from the end of file with `-v -F -n0`), then you can just use the `tail` utility that comes with your Linux distribution.(Or more specifically, the `tail` from the GNU coreutils). Other versions of the `tail` utility may also work, but are not tested. The input protocol expected by Log2json is very simple and documented in the source code. ** The `tail-log` script uses a patched version of `tail` from the GNU coreutils package. A binary of the `tail` utility compiled for Ubuntu 12.04 LTS is included with the Log2json gem. If the binary doesn't work for your distribution, then you'll need to get GNU coreutils-8.13, apply the patch(it can be found in the src/ directory of the installed gem), and then replace the bin/tail binary in the directory of the installed gem with your version of the binary. ** P.S. If you know of a way to configure and compile ONLY the tail program in coreutils, please let me know! The reason I'm not building tail post gem installation is that it takes too long to configure && make because that actually builds every utilties in coreutils. For shipping logs to Redis, there's the `lines2redis` script that can be used as the output process in the pipe. For shipping logs from Redis to ElasticSearch, Log2json provides a `redis2es` script. Finally here's an example of Log2json in action: From a client machine: tail-log /var/log/{sys,mail}log /var/log/{kern,auth}.log | syslog2json | queue=jsonlogs \ flush_size=20 \ flush_interval=30 \ lines2redis host.to.redis.server 6379 0 # use redis DB 0 On the Redis server: redis_queue=jsonlogs redis2es host.to.es.server Resources that help writing log2json filters: - look at log2json.rb source and example filters - http://grokdebug.herokuapp.com/ - http://www.ruby-doc.org/stdlib-1.9.3/libdoc/date/rdoc/DateTime.html#method-i-strftime

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