Fluentd meetup in Japan. I talked about "Dive into Fluent plugin".
Some contents are outdated. See this slide: http://www.slideshare.net/repeatedly/dive-into-fluentd-plugin-v012
This document summarizes the key features and changes between versions of Fluentd, an open source data collector.
The main points are:
1) Fluentd v1.0 will provide stable APIs and features while remaining compatible with v0.12 and v0.14. It will have no breaking API changes.
2) New features in v0.14 and v1.0 include nanosecond time resolution, multi-core processing, Windows support, improved buffering and plugins, and more.
3) The goals for v1.0 include migrating more plugins to the new APIs, addressing issues, and improving documentation. A release is planned for Q2 2017.
This document provides an overview of Fluentd, an open source data collector. It discusses the key features of Fluentd including structured logging, reliable forwarding, and a pluggable architecture. The document then summarizes the architectures and new features of different Fluentd versions, including v0.10, v0.12, and the upcoming v0.14 and v1 releases. It also discusses Fluentd's ecosystem and plugins as well as Treasure Data's use of Fluentd in its log data collection and analytics platform.
Fluentd Hacking Guide at RubyKaigi 2014Naotoshi Seo
This document summarizes a talk on hacking the Fluentd log streaming framework. It discusses Fluentd's bootstrap sequence and how it loads plugins. It explains how input plugins pass data to output plugins and how the BufferedOutput plugin works by buffering data to avoid blocking. It cautions that output plugins can block which BufferedOutput avoids, but it can also get stuck if the buffer exceeds capacity. It recommends tuning buffer size and thread counts to improve performance.
Fluentd v1 will focus on providing a stable and pluggable architecture for log forwarding and processing. Key features include a new configuration format that allows embedding Ruby code, improved filtering and labeling of events, and an error stream for handling errors. Other potential improvements include multi-processing support, zero downtime restarts, an actor framework, and JRuby/Windows compatibility. td-agent2 will upgrade the core libraries and use the new v1 configuration by default.
Fighting API Compatibility On Fluentd Using "Black Magic"SATOSHI TAGOMORI
The document discusses Fluentd's changes to its plugin API between versions 0.12 and 0.14. In 0.14, the API was overhauled to separate entry points from implementations and introduce a plugin base class to control data and control flow. A compatibility layer was added to allow most 0.12 plugins to work unmodified in 0.14 by handling calls to overridden methods. However, plugins that override certain methods like #emit may cause errors due to changes in how buffering works.
Fluentd is a data collector for unified logging that provides a robust core and plugins. It allows for reliable data transfer through error handling and retries. The core handles common concerns like parsing, buffering, and writing data, while plugins handle input, output, and other use cases. Fluentd has a pluggable architecture and processes data through a pipeline of input, parser, filter, buffer, formatter, and output plugins.
The document summarizes the new plugin API in Fluentd v0.14. Key points include:
- The v0.12 plugin API was fragmented and difficult to write tests for. The v0.14 API provides a unified architecture.
- The main plugin classes are Input, Filter, Output, Buffer, and plugins must subclass Fluent::Plugin::Base.
- The Output plugin supports both buffered and non-buffered processing. Buffering can be configured by tags, time, or custom fields.
- "Owned" plugins like Buffer are instantiated by primary plugins and can access owner resources. Storage is a new owned plugin for persistent storage.
- New test drivers emulate plugin
This document discusses using Docker and Fluentd together for logging container architectures. It describes different patterns for aggregating logs from containers using Fluentd, including 1-level and 2-level aggregation. A new Docker logging driver called "fluentd" is announced that will directly send container logs to Fluentd. The document also provides information on the official Fluentd Docker image.
Thrift is a software framework that allows for efficient cross-language communication. It provides features such as RPC, code generation, and serialization to make it easy to define and develop services that can be used across multiple languages. Supported languages include C++, Java, Python, PHP and more. Thrift handles low-level details like data serialization while providing an interface definition language to define services and data structures.
This document summarizes Fluentd v1.0 and provides details about its new features and release plan. It notes that Fluentd v1.0 will provide stable APIs and compatibility with previous versions while improving plugin APIs, adding Windows and multicore support, and increasing event time resolution to nanoseconds. The release is planned for Q3 2017 to allow feedback on v0.14 before finalizing v1.0 features.
Fluentd Unified Logging Layer At FossasiaN Masahiro
Masahiro Nakagawa is a senior software engineer at Treasure Data and the main maintainer of Fluentd. Fluentd is a data collector for unified logging that provides a streaming data transfer based on JSON. It has a simple core with plugins written in Ruby to provide functionality like input/output, buffering, parsing, filtering and formatting of data.
This document describes a presentation about introducing black magic programming patterns in Ruby and their pragmatic uses. It provides an overview of Fluentd, including what it is, its versions, and the changes between versions 0.12 and 0.14. Specifically, it discusses how the plugin API was updated in version 0.14 to address problems with the version 0.12 API. It also explains how a compatibility layer was implemented to allow most existing 0.12 plugins to work without modification in 0.14.
Fluentd v1 provides major improvements over v0.12 including nanosecond event time resolution, multi-core support, Windows support, and new plugin APIs. The new plugin APIs provide well-controlled lifecycles and integrate all output plugins. v1 also introduces a server engine based supervisor, dynamic buffering capabilities, and various plugin helpers. While maintaining compatibility with v0.12 plugins, v1 focuses on ease of use, stability, performance and flexibility.
Apache thrift-RPC service cross languagesJimmy Lai
This slides illustrate how to use Apache Thrift for building RPC service and provide demo example code in Python. The example scenario is: we have a prepared machine learning model, and we'd like to load the model in advance as a server for providing prediction service.
Fluentd is an open source data collector that allows users to collect, process, and store log data and events. It has a pluggable architecture that allows adding input plugins to collect data from various sources and output plugins to send data to different storage solutions. It provides reliable log forwarding and processing capabilities.
Facebook is a company that operates at massive scale. In this talk we’ll talk about how we use Python at Facebook.
Be it building back-end services, fast prototyping, automation, scaling operations, or simply gluing together various pieces of our infrastructure, Python is at the heart of it and allows our engineers to quickly deliver working solutions.
We’ll talk about our review process, unit testing, deployment workflow and various open-source framework we use.
Stackless Python is used extensively in EVE Online to provide cooperative multitasking. It allows tasks to be split across multiple tasklets that run concurrently without preemption. Channels are used to synchronize tasklets in a way similar to coroutines. This approach allows EVE's massive multiplayer server to handle over 120,000 concurrent users on a single database shard using Stackless Python's lightweight tasklets and channels for communication and synchronization.
This is the fourteenth (and last for now) set of slides from a Perl programming course that I held some years ago.
I want to share it with everyone looking for intransitive Perl-knowledge.
A table of content for all presentations can be found at i-can.eu.
The source code for the examples and the presentations in ODP format are on https://github.com/kberov/PerlProgrammingCourse
The document summarizes the key features and changes in Fluentd v0.14, including new plugin APIs, plugin storage and helpers, time with nanosecond resolution, a ServerEngine-based supervisor for Windows support, and plans for symmetric multi-core processing, a counter API, and TLS/authentication in future versions. It also benchmarks some performance improvements and outlines the roadmap for Treasure Agent 3.0 based on Fluentd v0.14.
The Parenscript Common Lisp to JavaScript compilerVladimir Sedach
The document discusses the Parenscript Common Lisp to JavaScript compiler. It describes what Parenscript is and is not, how it works, and its history and uses. Key points include that Parenscript compiles Common Lisp to readable JavaScript code without runtime dependencies or new types, and is used in web frameworks, libraries, and commercial projects.
This document discusses setting up an Apache web server with virtual domains and dynamic CGI pages. It provides instructions for installing and configuring Apache from source, including a sample httpd.conf configuration file. It also describes a simple shell script-based web server for testing purposes.
PHP may seem to be a very easy language but many of don't know how PHP works. We will discuss the less known facts about PHP and we will also cover some common type of software design patterns used with PHP
RESTLess Design with Apache Thrift: Experiences from Apache Airavatasmarru
Apache Airavata is software for providing services to manage scientific applications on a wide range of remote computing resources. Airavata can be used by both individual scientists to run scientific workflows as well as communities of scientists through Web browser interfaces. It is a challenge to bring all of Airavata’s capabilities together in the single API layer that is our prerequisite for a 1.0 release. To support our diverse use cases, we have developed a rich data model and messaging format that we need to expose to client developers using many programming languages. We do not believe this is a good match for REST style services. In this presentation, we present our use and evaluation of Apache Thrift as an interface and data model definition tool, its use internally in Airavata, and its use to deliver and distribute client development kits.
This document provides a tutorial on using ParenScript, a tool for embedding Lisp code into JavaScript and HTML documents. It demonstrates several examples of using ParenScript, including embedding a simple onclick handler, generating a JavaScript file from ParenScript code, and rewriting an existing slideshow script in ParenScript. The slideshow example shows how to integrate data from Common Lisp into the generated JavaScript code to customize the behavior. Overall, the tutorial provides a good introduction to basic ParenScript usage and concepts through examples.
The document provides an overview of snaps and snapd:
- Snaps are packages that provide application sandboxing and confinement using interfaces and security policies. They work across distributions and allow automatic updates.
- Snapcraft is used to build snaps by defining parts and plugins in a yaml file. Snaps are mounted at runtime rather than unpacked.
- Snapd is the daemon that installs, removes, and updates snaps. It manages security interfaces and confinement policies between snaps.
- The store publishes snaps to channels of different risk levels. Snapd installs the revisions specified by the store for each channel.
The document discusses configuring the Apache web server. It covers topics like:
- The Apache configuration file httpd.conf and options within it like DocumentRoot
- Using .htaccess files to override httpd.conf settings for specific directories
- Configuring password authentication for directories using htpasswd
- Setting up virtual hosts to serve different websites from the same server using different IP addresses
Firebird Security (in English): The Past and The FutureAlexey Kovyazin
This document discusses the history and development of security in Firebird databases. It describes how security was initially approached for early versions of InterBase, then improvements made over time in Firebird versions 1.0 through 3.0. Key points covered include adding user authentication, addressing buffer overflows, implementing Windows trusted authentication, and plans for Firebird 3 to allow custom authentication plugins and mapping of operating system users to database roles.
This document provides an overview of Fluentd, an open source data collector for structured logging. Fluentd uses a pluggable architecture and JSON format for log messages, allowing logs to be filtered, buffered, and reliably forwarded to storage. It provides client libraries for integrating with applications in languages like Ruby, Perl, PHP, Python and Java. Fluentd is positioned as an alternative to other log collection systems like Scribe and Flume, with advantages of being easier to install, configure, extend with plugins, and smaller footprint.
Update version of Fluentd plugin guide : http://www.slideshare.net/repeatedly/fluentd-meetup-dive-into-fluent-plugin
Thrift is a software framework that allows for efficient cross-language communication. It provides features such as RPC, code generation, and serialization to make it easy to define and develop services that can be used across multiple languages. Supported languages include C++, Java, Python, PHP and more. Thrift handles low-level details like data serialization while providing an interface definition language to define services and data structures.
This document summarizes Fluentd v1.0 and provides details about its new features and release plan. It notes that Fluentd v1.0 will provide stable APIs and compatibility with previous versions while improving plugin APIs, adding Windows and multicore support, and increasing event time resolution to nanoseconds. The release is planned for Q3 2017 to allow feedback on v0.14 before finalizing v1.0 features.
Fluentd Unified Logging Layer At FossasiaN Masahiro
Masahiro Nakagawa is a senior software engineer at Treasure Data and the main maintainer of Fluentd. Fluentd is a data collector for unified logging that provides a streaming data transfer based on JSON. It has a simple core with plugins written in Ruby to provide functionality like input/output, buffering, parsing, filtering and formatting of data.
This document describes a presentation about introducing black magic programming patterns in Ruby and their pragmatic uses. It provides an overview of Fluentd, including what it is, its versions, and the changes between versions 0.12 and 0.14. Specifically, it discusses how the plugin API was updated in version 0.14 to address problems with the version 0.12 API. It also explains how a compatibility layer was implemented to allow most existing 0.12 plugins to work without modification in 0.14.
Fluentd v1 provides major improvements over v0.12 including nanosecond event time resolution, multi-core support, Windows support, and new plugin APIs. The new plugin APIs provide well-controlled lifecycles and integrate all output plugins. v1 also introduces a server engine based supervisor, dynamic buffering capabilities, and various plugin helpers. While maintaining compatibility with v0.12 plugins, v1 focuses on ease of use, stability, performance and flexibility.
Apache thrift-RPC service cross languagesJimmy Lai
This slides illustrate how to use Apache Thrift for building RPC service and provide demo example code in Python. The example scenario is: we have a prepared machine learning model, and we'd like to load the model in advance as a server for providing prediction service.
Fluentd is an open source data collector that allows users to collect, process, and store log data and events. It has a pluggable architecture that allows adding input plugins to collect data from various sources and output plugins to send data to different storage solutions. It provides reliable log forwarding and processing capabilities.
Facebook is a company that operates at massive scale. In this talk we’ll talk about how we use Python at Facebook.
Be it building back-end services, fast prototyping, automation, scaling operations, or simply gluing together various pieces of our infrastructure, Python is at the heart of it and allows our engineers to quickly deliver working solutions.
We’ll talk about our review process, unit testing, deployment workflow and various open-source framework we use.
Stackless Python is used extensively in EVE Online to provide cooperative multitasking. It allows tasks to be split across multiple tasklets that run concurrently without preemption. Channels are used to synchronize tasklets in a way similar to coroutines. This approach allows EVE's massive multiplayer server to handle over 120,000 concurrent users on a single database shard using Stackless Python's lightweight tasklets and channels for communication and synchronization.
This is the fourteenth (and last for now) set of slides from a Perl programming course that I held some years ago.
I want to share it with everyone looking for intransitive Perl-knowledge.
A table of content for all presentations can be found at i-can.eu.
The source code for the examples and the presentations in ODP format are on https://github.com/kberov/PerlProgrammingCourse
The document summarizes the key features and changes in Fluentd v0.14, including new plugin APIs, plugin storage and helpers, time with nanosecond resolution, a ServerEngine-based supervisor for Windows support, and plans for symmetric multi-core processing, a counter API, and TLS/authentication in future versions. It also benchmarks some performance improvements and outlines the roadmap for Treasure Agent 3.0 based on Fluentd v0.14.
The Parenscript Common Lisp to JavaScript compilerVladimir Sedach
The document discusses the Parenscript Common Lisp to JavaScript compiler. It describes what Parenscript is and is not, how it works, and its history and uses. Key points include that Parenscript compiles Common Lisp to readable JavaScript code without runtime dependencies or new types, and is used in web frameworks, libraries, and commercial projects.
This document discusses setting up an Apache web server with virtual domains and dynamic CGI pages. It provides instructions for installing and configuring Apache from source, including a sample httpd.conf configuration file. It also describes a simple shell script-based web server for testing purposes.
PHP may seem to be a very easy language but many of don't know how PHP works. We will discuss the less known facts about PHP and we will also cover some common type of software design patterns used with PHP
RESTLess Design with Apache Thrift: Experiences from Apache Airavatasmarru
Apache Airavata is software for providing services to manage scientific applications on a wide range of remote computing resources. Airavata can be used by both individual scientists to run scientific workflows as well as communities of scientists through Web browser interfaces. It is a challenge to bring all of Airavata’s capabilities together in the single API layer that is our prerequisite for a 1.0 release. To support our diverse use cases, we have developed a rich data model and messaging format that we need to expose to client developers using many programming languages. We do not believe this is a good match for REST style services. In this presentation, we present our use and evaluation of Apache Thrift as an interface and data model definition tool, its use internally in Airavata, and its use to deliver and distribute client development kits.
This document provides a tutorial on using ParenScript, a tool for embedding Lisp code into JavaScript and HTML documents. It demonstrates several examples of using ParenScript, including embedding a simple onclick handler, generating a JavaScript file from ParenScript code, and rewriting an existing slideshow script in ParenScript. The slideshow example shows how to integrate data from Common Lisp into the generated JavaScript code to customize the behavior. Overall, the tutorial provides a good introduction to basic ParenScript usage and concepts through examples.
The document provides an overview of snaps and snapd:
- Snaps are packages that provide application sandboxing and confinement using interfaces and security policies. They work across distributions and allow automatic updates.
- Snapcraft is used to build snaps by defining parts and plugins in a yaml file. Snaps are mounted at runtime rather than unpacked.
- Snapd is the daemon that installs, removes, and updates snaps. It manages security interfaces and confinement policies between snaps.
- The store publishes snaps to channels of different risk levels. Snapd installs the revisions specified by the store for each channel.
The document discusses configuring the Apache web server. It covers topics like:
- The Apache configuration file httpd.conf and options within it like DocumentRoot
- Using .htaccess files to override httpd.conf settings for specific directories
- Configuring password authentication for directories using htpasswd
- Setting up virtual hosts to serve different websites from the same server using different IP addresses
Firebird Security (in English): The Past and The FutureAlexey Kovyazin
This document discusses the history and development of security in Firebird databases. It describes how security was initially approached for early versions of InterBase, then improvements made over time in Firebird versions 1.0 through 3.0. Key points covered include adding user authentication, addressing buffer overflows, implementing Windows trusted authentication, and plans for Firebird 3 to allow custom authentication plugins and mapping of operating system users to database roles.
This document provides an overview of Fluentd, an open source data collector for structured logging. Fluentd uses a pluggable architecture and JSON format for log messages, allowing logs to be filtered, buffered, and reliably forwarded to storage. It provides client libraries for integrating with applications in languages like Ruby, Perl, PHP, Python and Java. Fluentd is positioned as an alternative to other log collection systems like Scribe and Flume, with advantages of being easier to install, configure, extend with plugins, and smaller footprint.
Update version of Fluentd plugin guide : http://www.slideshare.net/repeatedly/fluentd-meetup-dive-into-fluent-plugin
Fluentd is an open source data collector designed for log aggregation and processing. It has a pluggable architecture that allows for flexible input, filtering, and output of log data. It is useful for log collection, processing, and forwarding to storage or analysis services in real-time.
Fluentd is an open source data collector that allows flexible data collection, processing, and storage. It collects log data from various sources using input plugins and sends the data to various outputs like files, databases or forward to other Fluentd servers. It uses a pluggable architecture so new input/output plugins can be added through Ruby gems. It provides features like buffering, retries and reliability.
Fluentd is a log collector that makes log collection easy. It allows users to collect, store, process, and visualize logs in JSON format. Fluentd works by using input plugins to collect logs, output plugins to export logs to different databases and storage systems, and buffer plugins to filter and route logs. Key features include its large number of plugins, support for JSON formatting, and ability to automatically handle failures and retries.
This document discusses how to collect big data into Hadoop using Apache Flume and Fluentd. It describes some problems with a poor man's approach to data collection and discusses the basic theories of divide and conquer and streaming to make data collection more efficient. It then provides an overview of how Apache Flume and Fluentd work, including their network topologies, configurations, and plugin systems. Examples are given of how Fluentd has been used at Treasure Data to collect and analyze REST API logs, backend logs, and Hadoop logs. The document concludes with a discussion of developing plugins for Fluentd.
Masahiro Nakagawa from Treasure Data gave a presentation on Fluentd, an open source log collector. Fluentd allows for reliable and structured logging, forwarding, and processing of data through its pluggable architecture. It can collect logs from various sources and output to different destinations using plugins. Common uses of Fluentd include log aggregation, monitoring, and analysis on large-scale architectures.
This document discusses Fluentd, an open source data collector. It provides an overview of Fluentd's architecture and components including input plugins, parser plugins, buffer plugins, output plugins, and formatter plugins. It also outlines Fluentd's roadmap, including plans to add filtering capabilities and improve the plugin API. Examples are given throughout to illustrate how Fluentd works and can be configured for use cases like log collection.
This document discusses Fluentd, an open source log collector. It provides a pluggable architecture that allows data to be collected, filtered, and forwarded to various outputs. Fluentd uses JSON format for log messages and MessagePack internally. It is reliable, scalable, and extensible through plugins. Common use cases include log aggregation, monitoring, and analytics across multiple servers and applications.
Fluentd is a log collector similar to syslog but uses JSON format for log messages. This provides benefits like machine-readability through use of field names and type information without rigid schemas. Fluentd collects logs from applications in real-time and routes them to storage. It supports plugins to filter, buffer, and route logs flexibly to different outputs like databases, file systems, or cloud services. Fluentd is useful for log analysis and helps address issues with traditional batch-oriented collection through rsync.
This document summarizes Masahiro Nakagawa's presentation on Fluentd and Embulk. Fluentd is a data collector for unified logging that allows for streaming data transfer based on JSON. It is written in Ruby and uses plugins to collect, process, and output data. Embulk is a bulk loading tool that allows high performance parallel processing of data to load it into various databases and storage systems. Both tools use a pluggable architecture to provide flexibility in handling different data sources and targets.
Yuta Iwama completed an internship where they added several new features and enhancements to Fluentd. Some of the key additions included implementing a counter API, adding data compression to buffers and forwards, creating a new simpler output plugin for secondary sections, developing a CLI tool to read dumped log data, and optimizing multiple filter calls. The internship provided valuable experience contributing to an open source middleware project and learning about aspects of design, development, and code quality.
Masahiro Nakagawa introduced Fluentd, an open source data collector. Fluentd provides a unified logging layer and collects data through a streaming data transfer based on JSON. It is written in Ruby and uses a plugin architecture to allow for various input and output functions. Fluentd is used in production environments for log aggregation, metrics collection, and data processing tasks.
Fluentd is an open source data collector that provides a unified logging layer between data sources and backend systems. It decouples these systems by collecting and processing logs and events in a flexible and scalable way. Fluentd uses plugins and buffers to make data collection reliable even in the case of errors or failures. It can forward data between Fluentd nodes for high availability and load balancing.
Collect distributed application logging using fluentd (EFK stack)Marco Pas
This document discusses using Fluentd to collect distributed application logging in a containerized environment. It provides an overview of Fluentd, including its pluggable architecture and configuration. It then demonstrates capturing logging from Docker containers and HTTP services and storing the logs in MongoDB and Elasticsearch as part of the ELK stack. It shows filtering and parsing logs from a Spring Boot application. Finally, it discusses setting up Fluentd for high availability.
This document summarizes the new features of Fluentd v11, including a reliable architecture based on ServerEngine for zero-downtime restarting. It introduces flexible record handling through filters and labels. The configuration format is improved to allow hashes, arrays, and embedded Ruby code. Plugins are enhanced with actors and a dedicated error stream. The developer seeks feedback on the alpha status features before a release date is set.
The document discusses the logging system Fluentd. It describes how Fluentd provides extensibility through plugins, uses a unified JSON log format, and offers simplicity. Major companies like NHN Japan and COOKPAD use Fluentd in production. The future of Fluentd includes new features like filters in sources, labels, faster MessagePack serialization, and a more efficient process model with live restart capabilities.
Fluentd is an open source data collector that allows flexible data collection, processing, and output. It supports streaming data from sources like logs and metrics to destinations like databases, search engines, and object stores. Fluentd's plugin-based architecture allows it to support a wide variety of use cases. Recent versions of Fluentd have added features like improved plugin APIs, nanosecond time resolution, and Windows support to make it more suitable for containerized environments and low-latency applications.
The document summarizes updates to Tagomoris' Fluentd cluster and new Fluentd plugins. It states that the cluster has grown from 89 processes on 12 nodes to 92,000 messages per second and 184Mbps, and the number of plugins has increased from 10 to 19, including new plugins for routing, monitoring, filtering, and outputting data. It promotes developing plugins to expand Fluentd's capabilities for real-time data processing.
Fluentd: Unified Logging Layer at CWT2014N Masahiro
The document summarizes Masahiro Nakagawa's presentation on Fluentd at the Cloudera World Tokyo conference. Fluentd is an open source log collector written in Ruby that uses a pluggable architecture and JSON format for log messages. It provides unified logging and data processing capabilities. The presentation covered Fluentd's core functionality, related products from Treasure Data, use cases, and the company's roadmap.
Fluentd Project Intro at Kubecon 2019 EUN Masahiro
Fluentd is a streaming data collector that can unify logging and metrics collection. It collects data from sources using input plugins, processes and filters the data, and outputs it to destinations using output plugins. It is commonly used for container logging, collecting logs from files or Docker and adding metadata before outputting to Elasticsearch or other targets. Fluentbit is a lightweight version of Fluentd that is better suited for edge collection and forwarding logs to a Fluentd instance for aggregation.
Fluentd and Distributed Logging at KubeconN Masahiro
This document discusses distributed logging with containers using Fluentd. It notes the challenges of logging in container environments where logs need to be collected from ephemeral containers and transferred to storage. It introduces Fluentd as a flexible data collection tool that can collect logs from containers using various plugins and methods like log drivers, shared volumes, and application libraries. The document discusses deployment patterns for Fluentd including using it for source-side aggregation to buffer and transfer logs more efficiently and for destination-side aggregation to scale log storage.
This document summarizes recent updates to Presto, including new data types, connectors, syntax, features, functions, and configuration options. Some key additions are support for DECIMAL, VARCHAR, and new data types; connectors for Redis, MongoDB, and other data sources; transaction support; and a variety of new SQL functions for strings, dates, aggregation, and more. Upcoming work includes prepared statements, a new optimizer, and other performance and usability improvements.
This document discusses using Fluentd to collect streaming data from Apache Kafka. It presents two approaches: 1) the fluent-plugin-kafka plugin which allows Fluentd to act as a producer and consumer of Kafka topics, and 2) the kafka-fluentd-consumer project which runs a standalone Kafka consumer that sends events to Fluentd. Configuration examples are provided for both approaches. The document concludes that Fluentd and Kafka can work together to build reliable and flexible data pipelines.
fluent-plugin-beats at Elasticsearch meetup #14N Masahiro
This document summarizes a presentation about integrating Fluentd with Elastic Beats data collection agents. It introduces Beats, their supported outputs including Elasticsearch, and various third party Beats. It then describes the fluent-plugin-beats plugin which allows Fluentd to receive events from Beats using the Lumberjack protocol. An example configuration is shown. Performance tests show Fluentd can handle over 100,000 events/sec while Filebeat is slower at 18,000 events/sec. The conclusion is that Beats are useful for collection but Fluentd may be better than Filebeat for high volume environments.
Technologies for Data Analytics PlatformN Masahiro
This document discusses building a data analytics platform and summarizes various technologies that can be used. It begins by outlining reasons for analyzing data like reporting, monitoring, and exploratory analysis. It then discusses using relational databases, parallel databases, Hadoop, and columnar storage to store and process large volumes of data. Streaming technologies like Storm, Kafka, and services like Redshift, BigQuery, and Treasure Data are also summarized as options for a complete analytics platform.
- The document discusses logging for containers using Fluentd, an open source data collector. It describes how Fluentd can provide a unified logging layer, reliably forwarding and aggregating logs from multiple containers and applications in a pluggable way.
- Key points covered include using Fluentd with the new Docker logging drivers to directly collect logs from containers, avoiding performance penalties from other approaches. A demo of Fluentd is also mentioned.
How to create Treasure Data #dotsbigdataN Masahiro
This document provides an overview of Treasure Data's big data analytics platform. It discusses how Treasure Data ingests and processes large amounts of schema-less data from various sources in real-time and at scale. It also describes how Treasure Data stores and indexes the data for fast querying using SQL interfaces while maintaining schema flexibility.
Treasure Data and AWS - Developers.io 2015N Masahiro
This document discusses Treasure Data's data architecture. It describes how Treasure Data collects and imports log data using Fluentd. The data is stored in columnar format in S3 and metadata is stored in PostgreSQL. Treasure Data uses Presto to enable fast analytics on the large datasets. The document provides details on the import process, storage, partitioning, and optimizations to improve query performance.
- Treasure Data is a cloud data service that provides data acquisition, storage, and analysis capabilities.
- It collects data from various sources using Fluentd and Embulk and stores it in its own columnar database called Plazma DB.
- It offers various computing frameworks like Hive, Pig, and Presto for analytics and visualization with tools like Tableau.
- Presto is an interactive SQL query engine that can query data in HDFS, Hive, Cassandra and other data stores.
This document summarizes Masahiro Nakagawa's presentation on Fluentd at the Data Transfer Middleware Meetup #1. It discusses Fluentd's history and architecture, including the core plugins in v0.10 and new features in v0.12 like filtering and labeling. The roadmap is outlined, with v0.14 adding new plugin APIs and v1 focusing on stability. Other projects like Treasure Agent and fluentd-forwarder that comprise the Fluentd ecosystem are also briefly mentioned.
The document discusses Presto, an open source distributed SQL query engine for interactive analysis of large datasets. It provides summaries of Presto's capabilities, architecture, and how it addresses issues with other SQL engines on Hadoop like Hive being too slow. Key points include that Presto allows direct querying of data in HDFS without needing to copy it elsewhere, uses a distributed query execution model rather than MapReduce, and supports many connectors and a PostgreSQL gateway.
This document provides a summary of a discussion comparing D and C++ programming languages. It includes several points about features of D such as its short name, lack of semicolons, struct syntax, delegate syntax, templates, compile-time function execution, classes, exceptions, contracts, and package management. It also references future potential features for D like the compiler as a library, thread-local garbage collection, and lightweight threads.
This presentation discusses Sedue, an open source search engine. It describes Sedue's architecture including its distributed file system, query server, indexer, document repository, and archive manager. It also covers Sedue's real-time indexing capabilities and use of technologies like MongoDB for indexing and data storage.
The document discusses RedBull and its benefits for driven development. It mentions using Emacs and VS Code for development and links to resources on kernel development with D programming language and an event on RedBull driven development. The document encourages enjoying RedBull.
1. The document discusses the programming language D, providing statistics on D developers from 2010.
2. It notes key contributors to D including tama, Rainer, John, Mihail, Andrei, and packages like Phobos, Visual D, and GDB support for D.
3. Finally, it shows statistics on D developers from the US, Japan, Germany, Norway, Poland and other countries.
Supercharge Your AI Development with Local LLMsFrancesco Corti
In today's AI development landscape, developers face significant challenges when building applications that leverage powerful large language models (LLMs) through SaaS platforms like ChatGPT, Gemini, and others. While these services offer impressive capabilities, they come with substantial costs that can quickly escalate especially during the development lifecycle. Additionally, the inherent latency of web-based APIs creates frustrating bottlenecks during the critical testing and iteration phases of development, slowing down innovation and frustrating developers.
This talk will introduce the transformative approach of integrating local LLMs directly into their development environments. By bringing these models closer to where the code lives, developers can dramatically accelerate development lifecycles while maintaining complete control over model selection and configuration. This methodology effectively reduces costs to zero by eliminating dependency on pay-per-use SaaS services, while opening new possibilities for comprehensive integration testing, rapid prototyping, and specialized use cases.
New Ways to Reduce Database Costs with ScyllaDBScyllaDB
How ScyllaDB’s latest capabilities can reduce your infrastructure costs
ScyllaDB has been obsessed with price-performance from day 1. Our core database is architected with low-level engineering optimizations that squeeze every ounce of power from the underlying infrastructure. And we just completed a multi-year effort to introduce a set of new capabilities for additional savings.
Join this webinar to learn about these new capabilities: the underlying challenges we wanted to address, the workloads that will benefit most from each, and how to get started. We’ll cover ways to:
- Avoid overprovisioning with “just-in-time” scaling
- Safely operate at up to ~90% storage utilization
- Cut network costs with new compression strategies and file-based streaming
We’ll also highlight a “hidden gem” capability that lets you safely balance multiple workloads in a single cluster. To conclude, we will share the efficiency-focused capabilities on our short-term and long-term roadmaps.
Adtran’s SDG 9000 Series brings high-performance, cloud-managed Wi-Fi 7 to homes, businesses and public spaces. Built on a unified SmartOS platform, the portfolio includes outdoor access points, ceiling-mount APs and a 10G PoE router. Intellifi and Mosaic One simplify deployment, deliver AI-driven insights and unlock powerful new revenue streams for service providers.
Protecting Your Sensitive Data with Microsoft Purview - IRMS 2025Nikki Chapple
Session | Protecting Your Sensitive Data with Microsoft Purview: Practical Information Protection and DLP Strategies
Presenter | Nikki Chapple (MVP| Principal Cloud Architect CloudWay) & Ryan John Murphy (Microsoft)
Event | IRMS Conference 2025
Format | Birmingham UK
Date | 18-20 May 2025
In this closing keynote session from the IRMS Conference 2025, Nikki Chapple and Ryan John Murphy deliver a compelling and practical guide to data protection, compliance, and information governance using Microsoft Purview. As organizations generate over 2 billion pieces of content daily in Microsoft 365, the need for robust data classification, sensitivity labeling, and Data Loss Prevention (DLP) has never been more urgent.
This session addresses the growing challenge of managing unstructured data, with 73% of sensitive content remaining undiscovered and unclassified. Using a mountaineering metaphor, the speakers introduce the “Secure by Default” blueprint—a four-phase maturity model designed to help organizations scale their data security journey with confidence, clarity, and control.
🔐 Key Topics and Microsoft 365 Security Features Covered:
Microsoft Purview Information Protection and DLP
Sensitivity labels, auto-labeling, and adaptive protection
Data discovery, classification, and content labeling
DLP for both labeled and unlabeled content
SharePoint Advanced Management for workspace governance
Microsoft 365 compliance center best practices
Real-world case study: reducing 42 sensitivity labels to 4 parent labels
Empowering users through training, change management, and adoption strategies
🧭 The Secure by Default Path – Microsoft Purview Maturity Model:
Foundational – Apply default sensitivity labels at content creation; train users to manage exceptions; implement DLP for labeled content.
Managed – Focus on crown jewel data; use client-side auto-labeling; apply DLP to unlabeled content; enable adaptive protection.
Optimized – Auto-label historical content; simulate and test policies; use advanced classifiers to identify sensitive data at scale.
Strategic – Conduct operational reviews; identify new labeling scenarios; implement workspace governance using SharePoint Advanced Management.
🎒 Top Takeaways for Information Management Professionals:
Start secure. Stay protected. Expand with purpose.
Simplify your sensitivity label taxonomy for better adoption.
Train your users—they are your first line of defense.
Don’t wait for perfection—start small and iterate fast.
Align your data protection strategy with business goals and regulatory requirements.
💡 Who Should Watch This Presentation?
This session is ideal for compliance officers, IT administrators, records managers, data protection officers (DPOs), security architects, and Microsoft 365 governance leads. Whether you're in the public sector, financial services, healthcare, or education.
🔗 Read the blog: https://nikkichapple.com/irms-conference-2025/
nnual (33 years) study of the Israeli Enterprise / public IT market. Covering sections on Israeli Economy, IT trends 2026-28, several surveys (AI, CDOs, OCIO, CTO, staffing cyber, operations and infra) plus rankings of 760 vendors on 160 markets (market sizes and trends) and comparison of products according to support and market penetration.
UiPath Community Berlin: Studio Tips & Tricks and UiPath InsightsUiPathCommunity
Join the UiPath Community Berlin (Virtual) meetup on May 27 to discover handy Studio Tips & Tricks and get introduced to UiPath Insights. Learn how to boost your development workflow, improve efficiency, and gain visibility into your automation performance.
📕 Agenda:
- Welcome & Introductions
- UiPath Studio Tips & Tricks for Efficient Development
- Best Practices for Workflow Design
- Introduction to UiPath Insights
- Creating Dashboards & Tracking KPIs (Demo)
- Q&A and Open Discussion
Perfect for developers, analysts, and automation enthusiasts!
This session streamed live on May 27, 18:00 CET.
Check out all our upcoming UiPath Community sessions at:
👉 https://community.uipath.com/events/
Join our UiPath Community Berlin chapter:
👉 https://community.uipath.com/berlin/
Nix(OS) for Python Developers - PyCon 25 (Bologna, Italia)Peter Bittner
How do you onboard new colleagues in 2025? How long does it take? Would you love a standardized setup under version control that everyone can customize for themselves? A stable desktop setup, reinstalled in just minutes. It can be done.
This talk was given in Italian, 29 May 2025, at PyCon 25, Bologna, Italy. All slides are provided in English.
Original slides at https://slides.com/bittner/pycon25-nixos-for-python-developers
Maxx nft market place new generation nft marketing placeusersalmanrazdelhi
PREFACE OF MAXXNFT
MaxxNFT: Powering the Future of Digital Ownership
MaxxNFT is a cutting-edge Web3 platform designed to revolutionize how
digital assets are owned, traded, and valued. Positioned at the forefront of the
NFT movement, MaxxNFT views NFTs not just as collectibles, but as the next
generation of internet equity—unique, verifiable digital assets that unlock new
possibilities for creators, investors, and everyday users alike.
Through strategic integrations with OKT Chain and OKX Web3, MaxxNFT
enables seamless cross-chain NFT trading, improved liquidity, and enhanced
user accessibility. These collaborations make it easier than ever to participate
in the NFT ecosystem while expanding the platform’s global reach.
With a focus on innovation, user rewards, and inclusive financial growth,
MaxxNFT offers multiple income streams—from referral bonuses to liquidity
incentives—creating a vibrant community-driven economy. Whether you
'
re
minting your first NFT or building a digital asset portfolio, MaxxNFT empowers
you to participate in the future of decentralized value exchange.
https://maxxnft.xyz/
Co-Constructing Explanations for AI Systems using ProvenancePaul Groth
Explanation is not a one off - it's a process where people and systems work together to gain understanding. This idea of co-constructing explanations or explanation by exploration is powerful way to frame the problem of explanation. In this talk, I discuss our first experiments with this approach for explaining complex AI systems by using provenance. Importantly, I discuss the difficulty of evaluation and discuss some of our first approaches to evaluating these systems at scale. Finally, I touch on the importance of explanation to the comprehensive evaluation of AI systems.
Multistream in SIP and NoSIP @ OpenSIPS Summit 2025Lorenzo Miniero
Slides for my "Multistream support in the Janus SIP and NoSIP plugins" presentation at the OpenSIPS Summit 2025 event.
They describe my efforts refactoring the Janus SIP and NoSIP plugins to allow for the gatewaying of an arbitrary number of audio/video streams per call (thus breaking the current 1-audio/1-video limitation), plus some additional considerations on what this could mean when dealing with application protocols negotiated via SIP as well.
UiPath Community Zurich: Release Management and Build PipelinesUiPathCommunity
Ensuring robust, reliable, and repeatable delivery processes is more critical than ever - it's a success factor for your automations and for automation programmes as a whole. In this session, we’ll dive into modern best practices for release management and explore how tools like the UiPathCLI can streamline your CI/CD pipelines. Whether you’re just starting with automation or scaling enterprise-grade deployments, our event promises to deliver helpful insights to you. This topic is relevant for both on-premise and cloud users - as well as for automation developers and software testers alike.
📕 Agenda:
- Best Practices for Release Management
- What it is and why it matters
- UiPath Build Pipelines Deep Dive
- Exploring CI/CD workflows, the UiPathCLI and showcasing scenarios for both on-premise and cloud
- Discussion, Q&A
👨🏫 Speakers
Roman Tobler, CEO@ Routinuum
Johans Brink, CTO@ MvR Digital Workforce
We look forward to bringing best practices and showcasing build pipelines to you - and to having interesting discussions on this important topic!
If you have any questions or inputs prior to the event, don't hesitate to reach out to us.
This event streamed live on May 27, 16:00 pm CET.
Check out all our upcoming UiPath Community sessions at:
👉 https://community.uipath.com/events/
Join UiPath Community Zurich chapter:
👉 https://community.uipath.com/zurich/
Securiport is a border security systems provider with a progressive team approach to its task. The company acknowledges the importance of specialized skills in creating the latest in innovative security tech. The company has offices throughout the world to serve clients, and its employees speak more than twenty languages at the Washington D.C. headquarters alone.
European Accessibility Act & Integrated Accessibility TestingJulia Undeutsch
Emma Dawson will guide you through two important topics in this session.
Firstly, she will prepare you for the European Accessibility Act (EAA), which comes into effect on 28 June 2025, and show you how development teams can prepare for it.
In the second part of the webinar, Emma Dawson will explore with you various integrated testing methods and tools that will help you improve accessibility during the development cycle, such as Linters, Storybook, Playwright, just to name a few.
Focus: European Accessibility Act, Integrated Testing tools and methods (e.g. Linters, Storybook, Playwright)
Target audience: Everyone, Developers, Testers
Dev Dives: System-to-system integration with UiPath API WorkflowsUiPathCommunity
Join the next Dev Dives webinar on May 29 for a first contact with UiPath API Workflows, a powerful tool purpose-fit for API integration and data manipulation!
This session will guide you through the technical aspects of automating communication between applications, systems and data sources using API workflows.
📕 We'll delve into:
- How this feature delivers API integration as a first-party concept of the UiPath Platform.
- How to design, implement, and debug API workflows to integrate with your existing systems seamlessly and securely.
- How to optimize your API integrations with runtime built for speed and scalability.
This session is ideal for developers looking to solve API integration use cases with the power of the UiPath Platform.
👨🏫 Speakers:
Gunter De Souter, Sr. Director, Product Manager @UiPath
Ramsay Grove, Product Manager @UiPath
This session streamed live on May 29, 2025, 16:00 CET.
Check out all our upcoming UiPath Dev Dives sessions:
👉 https://community.uipath.com/dev-dives-automation-developer-2025/
8. Agenda
Yes, I talk about
- an example of Fluentd plugins
- Fluentd and libraries
- how to develop a Fluentd plugins
No, I don’t talk about
- the details of each plugin
- the experience of production
2012 2 4
9. Example
based on bit.ly/fluentd-with-mongo
2012 2 4
10. Install
Plugin name is fluent-plugin-xxx ,
and fluent-gem is included in Fluentd gem.
2012 2 4
24. Serialization:
JSON like fast and compact format.
RPC:
Async and parallelism for high performance.
IDL:
Easy to integrate and maintain the service.
2012 2 4
25. Binary format,
Header + Body,
and
Variable length.
2012 2 4
26. Note that
Ruby version can’t handle a Time object.
2012 2 4
27. So,
we use an Integer object instead of a Time.
2012 2 4
37. We can load the plugin configuration using
config_param and configure method.
config_param set config value to
@<config name> automatically.
2012 2 4
38. <source>
type tail
path /path/to/log
...
</source> fluentd.conf
class TailInput < Input
Plugin.register_input(’tail’, self)
config_param :path, :string
...
end in_tail.rb
2012 2 4
39. One trick is here:
Fluentd’s configuration module does not
verify a default value. So,
we can use the nil like Tribool :)
config_param :tag, :string, :default => nil
Fluentd does not check the type
2012 2 4
41. SetTagKeyMixin:
Provide ‘tag_key’ and ‘include_tag_key’.
SetTimeKeyMixin:
Provide ‘time_key’ and ‘include_time_key’.
DetachMultiProcessMixin:
Provide ‘detach_process’ and
execute an action in the multi-process.
2012 2 4
42. Mixin usage
Code Flow
super
class MongoOutput <
BufferedOutput BufferedOutput
... super
include SetTagKeyMixin
config_set_default SetTagKeyMixin
:include_tag_key, false
super
...
end MongoOutput
2012 2 4
45. class NewInput < Input
...
def configure(conf)
# parse a configuration manually
end
def start
# invoke action
end
def shutdown
# cleanup resources
end
end
2012 2 4
46. In action method,
we use Engine.emit to input data.
tag = "app.tag"
time = Engine.now
Sample:
record = {"key" => "value", ...}
Engine.emit(tag, time, record)
2012 2 4
47. How to read an input in an efficient way?
We use a thread and an event loop.
2012 2 4
48. Thread
class ForwardInput < Fluent::Input
...
def start
...
@thread = Thread.new(&method(:run))
end
def run
...
end
end
2012 2 4
49. Event loop
class ForwardInput < Fluent::Input
...
def start
@loop = Coolio::Loop.new
@lsock = listen
@loop.attach(@lsock)
...
end
...
end
2012 2 4
50. Note that
We must use Engine.now instead of Time.now
2012 2 4
58. class NewOutput < BufferedOutput
# configure, start and shutdown
# are same as input plugin
def format(tag, time, record)
# convert event to raw string
end
def write(chunk)
# write chunk to target
# chunk has multiple formatted data
end
end
2012 2 4
59. Output has 3 buffering modes.
None
Buffered
Time sliced
2012 2 4
60. Buffering type
Buffered Time sliced
from in
Buffer has an internal
chunk map to manage a chunk.
A key is tag in Buffered,
chunk queue but a key is time slice in
limit chunk limit TimeSliced buffer.
go out def write(chunk)
chunk # chunk.key is time slice
end
2012 2 4
61. How to write an output in an efficient way?
We can use multi-process (input too).
See: DetachMultiProcessMixin
with detach_multi_process
2012 2 4
64. class MongoOutputTest < Test::Unit::TestCase
def setup
Fluent::Test.setup
require 'fluent/plugin/out_mongo'
end
def create_driver(conf = CONFIG)
Fluent::Test::BufferedOutputTestDriver.new
(Fluent::MongoOutput) {
def start # prevent external access
super
end
...
}.configure(conf)
end
2012 2 4
65. ...
def test_format
# test format using emit and expect_format
end
def test_write
d = create_driver
t = emit_documents(d)
# return a result of write method
collection_name, documents = d.run
assert_equal([{...}, {...}, ...], documents)
assert_equal('test', collection_name)
end
...
end
2012 2 4
66. It’s a weak point in Fluentd... right?
2012 2 4