InfluxQL is a powerful query language for InfluxDB, and TICKScript is a domain specific language used by Kapacitor to define tasks involving the extraction, transformation and loading of data and also involving the tracking of arbitrary changes and detection of events within data. The combination of these two can make your monitoring apps powerful. During this session, InfluxData Engineer Michael DeSa will share best practices for using these powerful tools. Prerequisite: Intro To Kapacitor.
Slides of my talk about the DashProfiler perl module, which enables lightweight always-on performance monitoring for critical sections of code. See
http://search.cpan.org/perldoc?DashProfiler
This document is a presentation from OpenStack Summit Sydney. It describes how to easily install OpenStack on Kubernetes. It explains Kubernetes and OpenStack-Helm.
DBD::Gofer is the scalable stateless proxy driver for Perl DBI.
These are the slides for my lightning talk on DBD::Gofer given at the Italian Perl Workshop in 2008 (with a few extra slides added).
You use InfluxData to monitor the performance of your infrastructure and apps—so it is equally important to keep your InfluxEnterprise instance up and running. Tim Hall, InfluxData VP of Products, will outline why and how you can monitor InfluxEnterprise with InfluxDB.
InfluxQL is a powerful query language for InfluxDB, and TICKScript is a domain specific language used by Kapacitor to define tasks involving the extraction, transformation and loading of data and also involving the tracking of arbitrary changes and detection of events within data. The combination of these two can make your monitoring apps powerful. During this session, InfluxData Engineer Michael DeSa will share best practices for using these powerful tools. Prerequisite: Intro To Kapacitor.
Slides of my talk about the DashProfiler perl module, which enables lightweight always-on performance monitoring for critical sections of code. See
http://search.cpan.org/perldoc?DashProfiler
This document is a presentation from OpenStack Summit Sydney. It describes how to easily install OpenStack on Kubernetes. It explains Kubernetes and OpenStack-Helm.
DBD::Gofer is the scalable stateless proxy driver for Perl DBI.
These are the slides for my lightning talk on DBD::Gofer given at the Italian Perl Workshop in 2008 (with a few extra slides added).
You use InfluxData to monitor the performance of your infrastructure and apps—so it is equally important to keep your InfluxEnterprise instance up and running. Tim Hall, InfluxData VP of Products, will outline why and how you can monitor InfluxEnterprise with InfluxDB.
How I Learned to Stop Worrying and Love the Cloud - Wesley Beary, Engine YardSV Ruby on Rails Meetup
Wesley Beary: Cloud computing scared the crap out of me - the quirks and nightmares
of provisioning computing and storage on AWS, Terremark, Rackspace,
etc - until I took the bull by the horns. Let me now show you how I
tamed that bull.
Learn how to easily get started cloud computing with fog. It gives you
the reins within any Ruby application or script. If you can control
your infrastructure choices, you can make better choices in
development and get what you need in production.
You'll get an overview of fog and concrete examples to give you a head
start on your own provisioning workflow.
Video Transcoding at the ABC with Microservices at GOTO ChicagoDaphne Chong
ABC iview is a video on demand service from the Australian Broadcasting Corporation. In 2015, we built a new service in-house to handle transcoding for all of iview's content.
Metro is built on AWS, and uses FFmpeg, node.js and go components to transcode content quickly and cost-efficiently.
Presented at GOTO Chicago on 2nd May 2017
Slides for my talk at SkyCon'12 in Limerick.
Here I've squeezed four talks into one, covering a lot of ground quickly, so I've included links to more detailed presentations and other resources.
Paul will outline his vision around the platform and give the latest updates on IFQL ( a new query language), the decoupling of query and storage, the impact of hybrid cloud environments on architecture, cardinality, and discuss the technical directions of the platform. This talk will walk through the vision and architecture with demonstrations of working prototypes of the projects.
Video Transcoding at Scale for ABC iview (NDC Sydney)Daphne Chong
ABC iview is a video on demand service from the Australian Broadcasting Corporation. In 2015, we built a new service in-house to handle transcoding for all of iview's content.
Metro is built on AWS, and uses FFmpeg, node.js and go components to transcode content quickly and cost-efficiently.
This talk was presented on August 4th 2016 at NDC Sydney.
Slides of my talk on Devel::NYTProf and optimizing perl code at YAPC::NA in June 2014. It covers use of NYTProf and outlines a multi-phase approach to optimizing your perl code.
A video of the talk and questions is available at https://www.youtube.com/watch?v=T7EK6RZAnEA&list=UU7y4qaRSb5w2O8cCHOsKZDw
Inside the ABC's new Media Transcoding system, MetroDaphne Chong
The ABC recently launched a new video transcoding system to process all the video content for ABC iview, our catch-up TV service.
Metro is a cost-efficient, scalable, cloud-based system that was built using Golang, Node, FFmpeg, and heavily utilises a variety of AWS technology including queues, varied capacity autoscaling, hosted database servers, and notifications. The system has been live since December 2015, and has successfully processed thousands of pieces of content.
Streams are often underestimated and skipped as possible solutions. In many cases, we created much more complex solutions than their streams counterpart. Why?
It's hard to answer, but in this presentation, I would like to tell you a story about how we started to use FS2, without sacrificing purity and code readability. (https://github.com/functional-streams-for-scala/fs2)
Slides for my Perl Memory Use talk at YAPC::Asia in Tokyo, September 2012.
(This uploaded version includes quite a few slides from the OSCON version that I skipped at YAPC::Asia in order to have more time for a demo.)
Slides for my talk at the London Perl Workshop in Nov 2013, featuring the Devel::SizeMe perl module.
See also the screencast at https://archive.org/details/Perl-Memory-Profiling-LPW2013
Exploiting Multicore CPUs Now: Scalability and Reliability for Off-the-shelf ...Emery Berger
Multiple core CPUs are here. Conventional wisdom holds that, to take best advantage of these processors, we now need to rewrite sequential applications to make them multithreaded. Because of the difficulty of programming correct and efficient multithreaded applications (e.g., race conditions, deadlocks, and scalability bottlenecks), this is a major challenge.
This talk presents two alternative approaches that bring the power of multiple cores to today's software. The first approach focuses on building highly-concurrent client-server applications from legacy code. I present a system called Flux that allows users to take unmodified off-the-shelf *sequential* C and C++ code and build concurrent applications. The Flux compiler combines the Flux program and the sequential code to generate a deadlock-free, high-concurrency server. Flux also generates discrete event simulators that accurately predict actual server performance under load. While the Flux language was initially targeted at servers, we have found it to be a useful abstraction for sensor networks, and I will briefly talk about our use of an energy-aware variant of Flux in a deployment on the backs of endangered turtles. The second approach uses the extra processing power of multicore CPUs to make legacy C/C++ applications more reliable. I present a system called DieHard that uses randomization and replication to transparently harden programs against a wide range of errors, including buffer overflows and dangling pointers. Instead of crashing or running amok, DieHard lets programs continue to run correctly in the face of memory errors with high probability. This is joint work with Brendan Burns, Kevin Grimaldi, Alex Kostadinov, Jacob Sorber, and Mark Corner (University of Massachusetts Amherst), and Ben Zorn (Microsoft Research).
Node has revolutionized modern runtimes. Their async by default strategy boasts 3x the throughput of Java. And yet, the language runs 5x slower than C++ (when JS is interpreted).
This talk is an advanced intro into the world of Node where we take a closer look under the hood. What's the event loop? Why are there multiple compilers for JS in Node/V8? How many threads are actually used in Node and for what purpose? We'll answer these questions and more as we go over libuv, v8, the node core library, npm, and more.
If you're developing with Node, want to start, or are just curious about how it works, please check it out!
How I Learned to Stop Worrying and Love the Cloud - Wesley Beary, Engine YardSV Ruby on Rails Meetup
Wesley Beary: Cloud computing scared the crap out of me - the quirks and nightmares
of provisioning computing and storage on AWS, Terremark, Rackspace,
etc - until I took the bull by the horns. Let me now show you how I
tamed that bull.
Learn how to easily get started cloud computing with fog. It gives you
the reins within any Ruby application or script. If you can control
your infrastructure choices, you can make better choices in
development and get what you need in production.
You'll get an overview of fog and concrete examples to give you a head
start on your own provisioning workflow.
Video Transcoding at the ABC with Microservices at GOTO ChicagoDaphne Chong
ABC iview is a video on demand service from the Australian Broadcasting Corporation. In 2015, we built a new service in-house to handle transcoding for all of iview's content.
Metro is built on AWS, and uses FFmpeg, node.js and go components to transcode content quickly and cost-efficiently.
Presented at GOTO Chicago on 2nd May 2017
Slides for my talk at SkyCon'12 in Limerick.
Here I've squeezed four talks into one, covering a lot of ground quickly, so I've included links to more detailed presentations and other resources.
Paul will outline his vision around the platform and give the latest updates on IFQL ( a new query language), the decoupling of query and storage, the impact of hybrid cloud environments on architecture, cardinality, and discuss the technical directions of the platform. This talk will walk through the vision and architecture with demonstrations of working prototypes of the projects.
Video Transcoding at Scale for ABC iview (NDC Sydney)Daphne Chong
ABC iview is a video on demand service from the Australian Broadcasting Corporation. In 2015, we built a new service in-house to handle transcoding for all of iview's content.
Metro is built on AWS, and uses FFmpeg, node.js and go components to transcode content quickly and cost-efficiently.
This talk was presented on August 4th 2016 at NDC Sydney.
Slides of my talk on Devel::NYTProf and optimizing perl code at YAPC::NA in June 2014. It covers use of NYTProf and outlines a multi-phase approach to optimizing your perl code.
A video of the talk and questions is available at https://www.youtube.com/watch?v=T7EK6RZAnEA&list=UU7y4qaRSb5w2O8cCHOsKZDw
Inside the ABC's new Media Transcoding system, MetroDaphne Chong
The ABC recently launched a new video transcoding system to process all the video content for ABC iview, our catch-up TV service.
Metro is a cost-efficient, scalable, cloud-based system that was built using Golang, Node, FFmpeg, and heavily utilises a variety of AWS technology including queues, varied capacity autoscaling, hosted database servers, and notifications. The system has been live since December 2015, and has successfully processed thousands of pieces of content.
Streams are often underestimated and skipped as possible solutions. In many cases, we created much more complex solutions than their streams counterpart. Why?
It's hard to answer, but in this presentation, I would like to tell you a story about how we started to use FS2, without sacrificing purity and code readability. (https://github.com/functional-streams-for-scala/fs2)
Slides for my Perl Memory Use talk at YAPC::Asia in Tokyo, September 2012.
(This uploaded version includes quite a few slides from the OSCON version that I skipped at YAPC::Asia in order to have more time for a demo.)
Slides for my talk at the London Perl Workshop in Nov 2013, featuring the Devel::SizeMe perl module.
See also the screencast at https://archive.org/details/Perl-Memory-Profiling-LPW2013
Exploiting Multicore CPUs Now: Scalability and Reliability for Off-the-shelf ...Emery Berger
Multiple core CPUs are here. Conventional wisdom holds that, to take best advantage of these processors, we now need to rewrite sequential applications to make them multithreaded. Because of the difficulty of programming correct and efficient multithreaded applications (e.g., race conditions, deadlocks, and scalability bottlenecks), this is a major challenge.
This talk presents two alternative approaches that bring the power of multiple cores to today's software. The first approach focuses on building highly-concurrent client-server applications from legacy code. I present a system called Flux that allows users to take unmodified off-the-shelf *sequential* C and C++ code and build concurrent applications. The Flux compiler combines the Flux program and the sequential code to generate a deadlock-free, high-concurrency server. Flux also generates discrete event simulators that accurately predict actual server performance under load. While the Flux language was initially targeted at servers, we have found it to be a useful abstraction for sensor networks, and I will briefly talk about our use of an energy-aware variant of Flux in a deployment on the backs of endangered turtles. The second approach uses the extra processing power of multicore CPUs to make legacy C/C++ applications more reliable. I present a system called DieHard that uses randomization and replication to transparently harden programs against a wide range of errors, including buffer overflows and dangling pointers. Instead of crashing or running amok, DieHard lets programs continue to run correctly in the face of memory errors with high probability. This is joint work with Brendan Burns, Kevin Grimaldi, Alex Kostadinov, Jacob Sorber, and Mark Corner (University of Massachusetts Amherst), and Ben Zorn (Microsoft Research).
Node has revolutionized modern runtimes. Their async by default strategy boasts 3x the throughput of Java. And yet, the language runs 5x slower than C++ (when JS is interpreted).
This talk is an advanced intro into the world of Node where we take a closer look under the hood. What's the event loop? Why are there multiple compilers for JS in Node/V8? How many threads are actually used in Node and for what purpose? We'll answer these questions and more as we go over libuv, v8, the node core library, npm, and more.
If you're developing with Node, want to start, or are just curious about how it works, please check it out!
Timelapse: interactive record/replay for the webbrrian
These are the slides for a series of work-in-progress talks given about Timelapse in June 2012. Please send comments and questions to @brrian on twitter, or find my email on the Timelapse project page:
http://cs.washington.edu/homes/burg/timelapse/
Exactly-Once Made Easy: Transactional Messaging in Apache Pulsar - Pulsar Sum...StreamNative
The highest message delivery guarantee that Apache Pulsar provides is 'exactly-once', producing at a single partition via Idempotent Producer. Users are guaranteed that every message produced to a single partition via an Idempotent Producer will be persisted exactly once, without data loss. However, there is no 'atomicity' when a producer attempts to produce messages to multiple partitions. From the consumer side, acknowledgment is a best-effort operation, which results in message redelivery, hence consumer will receive duplicate messages. Pulsar only guarantees 'at-least-once' consumption for consumers. It creates inconvenience and brings in complexity when you use Pulsar to build mission-critical services (such as billing services).
We introduce Transaction support in Pulsar 2.8.0 release, to simplify the process of building reliable and fault resilient services using Apache Pulsar and Pulsar Functions. It provides the capability to achieve end-to-end exactly-once for streaming jobs in other stream processing engines.
This presentation deep dives into the details of Pulsar transaction and how Pulsar transaction is applied to Pulsar Functions and other processing engines to achieve transactional event streaming. We will cover how Pulsar transaction works and how Pulsar Functions offers transaction support using Pulsar transaction.
Tapad's data pipeline is an elastic combination of technologies (Kafka, Hadoop, Avro, Scalding) that forms a reliable system for analytics, realtime and batch graph-building, and logging. In this talk, I will speak about the creation and evolution of the pipeline, and a concrete example – a day in the life of an event tracking pixel. We'll also talk about common challenges that we've overcome such as integrating different pieces of the system, schema evolution, queuing, and data retention policies.
A presentation for the Reactive Programming Enthusiasts Denver meet-up.
http://www.meetup.com/Reactive-Programming-Enthusiasts-Denver/
How Reactive Mongo helps utilize your hardware better and achieve a non-blocking application from the bottom up.
The Nuts and Bolts of Kafka Streams---An Architectural Deep DiveHostedbyConfluent
"Writing a Kafka Streams application is only the first step for your event driven applications. Eventually, you will deploy and tune your applications with different goals in mind (throughput, latency, robustness, high availability, you name it). To run and configure your applications efficiently, it is paramount to understand the internal architecture, and the dependencies and interactions of the different internal components. Otherwise, you end up with a trial-and-error approach that is cumbersome, potentially frustrating, and for sure not fun.
In this talk, we will explore the internal architecture of Kafka Streams to set you up for successfully running and tuning your applications. -- What does the internal threading model look like? How are partitions assigned and mapped to tasks? Why are there multiple internal consumers? What are the most important/interesting configurations and how do they interact with each other? -- Those are just a few questions we will answer in this session, enabling you to run and tune your applications in record time!"
Building a Versatile Analytics Pipeline on Top of Apache Spark with Mikhail C...Databricks
It is common for consumer Internet companies to start off with popular third-party tools for analytics needs. Then, when the user base and the company grows, they end up building their own analytics data pipeline and query engine to cope with their data scale, satisfy custom data enrichment and reporting needs and achieve high quality of their data. That’s exactly the path that was taken at Grammarly, the popular online proofreading service.
In this session, Grammarly will share how they improved business and marketing analytics, previously done with Mixpanel, by building their own in-house analytics engine and application on top of Apache Spark. Chernetsov wil touch upon several Spark tweaks and gotchas that they experienced along the way:
– Outputting data to several storages in a single Spark job
– Dealing with Spark memory model, building a custom spillable data-structure for your data traversal
– Implementing a custom query language with parser combinators on top of Spark sql parser
– Custom query optimizer and analyzer when you want not exactly sql
– Flexible-schema storage and query against multi-schema data with schema conflicts
– Custom aggregation functions in Spark SQL
Similar to Fluency - Yet another fluent logger (20)
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
5. What’s Fluency?
• Yet another fluent-logger-java
(https://github.com/komamitsu/fluency)
• 3x 4x faster than fluent-logger using
PackedForward format
• Easy to extend
• Many features
(Async flush, HB, Failover, Ack response)
• Used in LINE, Treasure Data, kafka-fluentd-consumer
7. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
8. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
9. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
10. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
11. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
12. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
13. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
14. Async flushing
Application Fluency Buffer FluentdFlusher
emit(event:A) append(event:A)
emit(event:B) append(event:B)
store events as
MessagePack
flush
send(event:[A, B])
emit(event:C) append(event:C)
flush
invoked
repeatedly
PackedForward
format
close close
force flush
emit(event:D) append(event:D)
send(event:[C,D])
event:C isn’t
ready for flush
event:A,B are
ready for flush
terminate
thread
25. 4x faster than
fluent-logger-java
fluency / fluent-logger-java: m3.large
fluentd: m3.large
See details: https://gist.github.com/komamitsu/c1e4045fe2ddb108cfbf12d5f014b683
But the actual
bottleneck
of this benchmark
might be Fluentd…
26. Java profiling (1/2)
fluency fluent-logger-java
fluency uses off heap
for buffer pool
Due to synchronization
28. Finding a bottleneck
fluency
emit (MessagePack
serialization & appending to
buffer) accounts for most of
the duration
String.getBytes in
MessagePack serialization
takes total 18%
ObjectMapper.writeValue
itself takes 40%