The document discusses the benefits of Erlang, including its functional nature, powerful pattern matching, built-in concurrency and fault tolerance through let it crash philosophy, ability to perform distributed computation, and capability for hot code upgrades without downtime. It covers Erlang's actor model approach to concurrency, use of processes and message passing, supervision trees for fault tolerance, and tools for debugging, profiling, and detecting bottlenecks.
UKOUG version of a presentation trying to establish the sensible limits of parallelism on a couple of hardware configurations. Detailed white paper is at http://oracledoug.com/px_slaves.pdf
Where the wild things are - Benchmarking and Micro-OptimisationsMatt Warren
You don’t want to prematurely optimise, but sometimes you want to optimise, the question is - where to start? Profiling and Benchmarking can help you figure out what your application is doing and where performance problems could arise - allowing you to find (and fix!) them before your customers do.
If you aren’t already benchmarking your code this talk will offer some starting points. We’ll look at how to accurately benchmark in .NET and things to avoid. Along the way we’ll also discover some surprising code optimisations!
Performance and how to measure it - ProgSCon London 2016Matt Warren
Starting with the premise that "Performance is a Feature", this session will look at how to measure, what to measure and how get the best performance from your .NET code.
We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed!
UKOUG version of a presentation trying to establish the sensible limits of parallelism on a couple of hardware configurations. Detailed white paper is at http://oracledoug.com/px_slaves.pdf
Where the wild things are - Benchmarking and Micro-OptimisationsMatt Warren
You don’t want to prematurely optimise, but sometimes you want to optimise, the question is - where to start? Profiling and Benchmarking can help you figure out what your application is doing and where performance problems could arise - allowing you to find (and fix!) them before your customers do.
If you aren’t already benchmarking your code this talk will offer some starting points. We’ll look at how to accurately benchmark in .NET and things to avoid. Along the way we’ll also discover some surprising code optimisations!
Performance and how to measure it - ProgSCon London 2016Matt Warren
Starting with the premise that "Performance is a Feature", this session will look at how to measure, what to measure and how get the best performance from your .NET code.
We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed!
Paradigma FP y OOP usando técnicas avanzadas de Programación | Programacion A...Víctor Bolinches
Charla Universidad de Valencia - http://www.uv.es/
Cátedra de Capgemini 2016/17 - http://www.uv.es/capgeminiuv/sobre_nosotros.html
Asignatura : Programación avanzada y Lenguajes de programación
Título : Paradigma FP y OOP usando técnicas avanzadas de Programación
Starting with the premise that "Performance is a Feature", this session will look at how to measure, what to measure and how get the best performance from your .NET code.
We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed!
Effective testing for spark programs Strata NY 2015Holden Karau
This session explores best practices of creating both unit and integration tests for Spark programs as well as acceptance tests for the data produced by our Spark jobs. We will explore the difficulties with testing streaming programs, options for setting up integration testing with Spark, and also examine best practices for acceptance tests.
Unit testing of Spark programs is deceptively simple. The talk will look at how unit testing of Spark itself is accomplished, as well as factor out a number of best practices into traits we can use. This includes dealing with local mode cluster creation and teardown during test suites, factoring our functions to increase testability, mock data for RDDs, and mock data for Spark SQL.
Testing Spark Streaming programs has a number of interesting problems. These include handling of starting and stopping the Streaming context, and providing mock data and collecting results. As with the unit testing of Spark programs, we will factor out the common components of the tests that are useful into a trait that people can use.
While acceptance tests are not always part of testing, they share a number of similarities. We will look at which counters Spark programs generate that we can use for creating acceptance tests, best practices for storing historic values, and some common counters we can easily use to track the success of our job.
Relevant Spark Packages & Code:
https://github.com/holdenk/spark-testing-base / http://spark-packages.org/package/holdenk/spark-testing-base
https://github.com/holdenk/spark-validator
Brief introduction to DTrace technologies within OpenSolaris/Solaris 10 and DTrace probes within Apache, PHP and MySQL can provide end to end dynamic tracing of your Drupal based web site..
Monitoring Complex Systems: Keeping Your Head on Straight in a Hard WorldBrian Troutwine
This talk will provide motivation for the extensive instrumentation of complex computer systems and make the argument that such systems. This talk will provide practical starting points in Erlang projects and maintain a perspective on the human organization around the computer system. Brian will focus on getting started with instrumentation in a systematic way and follow up with the challenge of interpreting and acting on metrics emitted from a production system in a way which does not overwhelm operators’ ability to effectively control or prioritize faults in the system. He’ll use historical examples and case studies from my work to keep the talk anchored in the practical.
Talk objectives:
Brian hopes to convince the audience of two things:
* that monitoring and instrumentation is an essential component of any long-lived system and
* that it's not so hard to get started, after all.
He’ll keep a clear-eyed view of what works and is difficult in practice so that the audience can make a reasoned decision after the talk.
Target audience:
This talk would appeal to engineers with long-running production employments, operations folks and Erlangers in general.
Paradigma FP y OOP usando técnicas avanzadas de Programación | Programacion A...Víctor Bolinches
Charla Universidad de Valencia - http://www.uv.es/
Cátedra de Capgemini 2016/17 - http://www.uv.es/capgeminiuv/sobre_nosotros.html
Asignatura : Programación avanzada y Lenguajes de programación
Título : Paradigma FP y OOP usando técnicas avanzadas de Programación
Starting with the premise that "Performance is a Feature", this session will look at how to measure, what to measure and how get the best performance from your .NET code.
We will look at real-world examples from the Roslyn code-base and StackOverflow (the product), including how the .NET Garbage Collector needs to be tamed!
Effective testing for spark programs Strata NY 2015Holden Karau
This session explores best practices of creating both unit and integration tests for Spark programs as well as acceptance tests for the data produced by our Spark jobs. We will explore the difficulties with testing streaming programs, options for setting up integration testing with Spark, and also examine best practices for acceptance tests.
Unit testing of Spark programs is deceptively simple. The talk will look at how unit testing of Spark itself is accomplished, as well as factor out a number of best practices into traits we can use. This includes dealing with local mode cluster creation and teardown during test suites, factoring our functions to increase testability, mock data for RDDs, and mock data for Spark SQL.
Testing Spark Streaming programs has a number of interesting problems. These include handling of starting and stopping the Streaming context, and providing mock data and collecting results. As with the unit testing of Spark programs, we will factor out the common components of the tests that are useful into a trait that people can use.
While acceptance tests are not always part of testing, they share a number of similarities. We will look at which counters Spark programs generate that we can use for creating acceptance tests, best practices for storing historic values, and some common counters we can easily use to track the success of our job.
Relevant Spark Packages & Code:
https://github.com/holdenk/spark-testing-base / http://spark-packages.org/package/holdenk/spark-testing-base
https://github.com/holdenk/spark-validator
Brief introduction to DTrace technologies within OpenSolaris/Solaris 10 and DTrace probes within Apache, PHP and MySQL can provide end to end dynamic tracing of your Drupal based web site..
Monitoring Complex Systems: Keeping Your Head on Straight in a Hard WorldBrian Troutwine
This talk will provide motivation for the extensive instrumentation of complex computer systems and make the argument that such systems. This talk will provide practical starting points in Erlang projects and maintain a perspective on the human organization around the computer system. Brian will focus on getting started with instrumentation in a systematic way and follow up with the challenge of interpreting and acting on metrics emitted from a production system in a way which does not overwhelm operators’ ability to effectively control or prioritize faults in the system. He’ll use historical examples and case studies from my work to keep the talk anchored in the practical.
Talk objectives:
Brian hopes to convince the audience of two things:
* that monitoring and instrumentation is an essential component of any long-lived system and
* that it's not so hard to get started, after all.
He’ll keep a clear-eyed view of what works and is difficult in practice so that the audience can make a reasoned decision after the talk.
Target audience:
This talk would appeal to engineers with long-running production employments, operations folks and Erlangers in general.
Building an ML Platform with Ray and MLflowDatabricks
A successful machine learning platform allows ML practitioners to focus solely on their experiments and models and minimizes the time it takes to develop ML applications and take them to production. However, building an ML Platform is typically not an easy task due to the many different components involved in the process. In this talk, we will show how two open source projects, Ray (https://ray.io/) and MLflow (https://mlflow.org/), work together to make it easy for ML platform developers to add scaling and experiment management to their platform.
We will first provide an overview of Ray and its native libraries: Ray Tune (https://tune.io) for distributed hyperparameter tuning and Ray Serve (https://docs.ray.io/en/master/serve/index.html) for scalable model serving. Then we will showcase how MLflow provides a perfect solution for managing experiments through integrations with Ray for tracking and model deployment. Finally, we will finish with a demo of an ML platform built on Ray, MLflow, and other open source tools.
Workshop "Can my .NET application use less CPU / RAM?", Yevhen TatarynovFwdays
In most cases it’s very hard to predict the number of resources needed for your .NET application. But If you spot some abnormal CPU or RAM usage, how to answer the question “Can my application use less?”.
Let’s see samples from real projects, where optimal resource usage by the application became one of the values for the product owner and see how less resource consumption can be.
The workshop will be actual for .NET developers who are interested in optimization of .NET applications, QA engineers who involved performance testing of .NET applications. It also will be interesting to everyone who "suspected" their .NET applications of non-optimal use of resources, but for some reason did not start an investigation.
Introduces important facts and tools to help you get starting with performance improvement.
Learn to monitor and analyze important metrics, then you can start digging and improving.
Includes useful munin probes, predefined SQL queries to investigate your database's performance, and a top 5 of the most common performance problems in custom Apps.
By Olivier Dony - Lead Developer & Community Manager, OpenERP
Big Data Day LA 2016/ Hadoop/ Spark/ Kafka track - Data Provenance Support in...Data Con LA
Debugging data processing logic in Data-Intensive Scalable Computing (DISC) systems is a difficult and time consuming effort. To aid this effort, we built Titian, a library that enables data provenance tracking data through transformations in Apache Spark.
Postgres Vision 2018: Making Postgres Even FasterEDB
Andres Freund, a Senior Database Architect at EnterpriseDB, is one of the leading developers of PostgreSQL and his work has been influential in advancing the replication, performance, and scalability capabilities of Postgres. In this presentation he delivered at Postgres Vision 2018, Freund discusses JIT and general performance enhancements to Postgres and explains why PostgreSQL 11 will be the best option for application developers.
Beyond Breakpoints: A Tour of Dynamic AnalysisFastly
Despite advances in software design and static analysis techniques, software remains incredibly complicated and difficult to reason about. Understanding highly-concurrent, kernel-level, and intentionally-obfuscated programs are among the problem domains that spawned the field of dynamic program analysis. More than mere debuggers, the challenge of dynamic analysis tools is to be able record, analyze, and replay execution without sacrificing performance. This talk will provide an introduction to the dynamic analysis research space and hopefully inspire you to consider integrating these techniques into your own internal tools.
Clojure is a modern dynamically typed lisp. Dynamical typing is ofter associated with poor performance and runtime failures. In this talk, I'll present some of the lessons learned on building Clojure/Script systems that are both ridiculously fast and will fail fast on errors. Will compare the performance of mutable, persistent & zero-copy data structures and show how we can use interpreters and compilers to build beautiful and performant abstractions. A quick demo on how to build a simple non-blocking web server that runs idiomatic Clojure to serve millions of requests per sec.
Clojure is awesome, and it can be fast too.
Video: https://www.youtube.com/watch?v=3SSHjKT3ZmA
High Availability can be a curiously nebulous term, and most people probably don't care about it until they can't access their online banking service, or their plane crashes.
This presentation examines some of the considerations necessary when building highly available computer systems, then focuses on the HA infrastructure software currently available from the Corosync/OpenAIS, Linux-HA and Pacemaker projects.
Originally presented at Linux Users Victoria in April 2010 (http://luv.asn.au/2010/04/06)
Similar to Valerii Vasylkov Erlang. measurements and benefits. (20)
Vladimir Lozanov How to deliver high quality apps to the app storeАліна Шепшелей
How to plan and organize QA processes in product development team. Balance between manual and automation testing in iOS products. Importance of collaboration with other teams and how to engage all the team into product quality advocacy.
Apache Spark is an open-source parallel processing framework that supports in-memory processing to boost the performance of big-data analytic applications. We will cover approaches of processing Big Data on Spark cluster for real time analytic, machine learning and iterative BI and also discuss the pros and cons of using Spark in Azure cloud.
Valerii Iakovenko Drones as the part of the presentАліна Шепшелей
Drones, these are the tools that have densely entered to our life now. These are sources of geospatial information which form the basis and supplements many systems of monitoring and control. In detail, the speech will be about agribusiness.
Dmitriy Kouperman Working with legacy systems. stabilization, monitoring, man...Аліна Шепшелей
About half of the developers, one way or another, faced with the legacy-projects. Not everyone can (and want) work with them. But with the right approach, such projects can be carried out with pleasure and even enthusiasm. We suggest that such a legacy of understanding, what are these project management techniques, practices, and explore the developers consider useful decisions: • Examples of optimization - it's worth a try; • Monitoring applications - JavaMelody; • Monitoring applications - logs and ELK (ELasticSearch + Logstash + Kibana); • Monitoring applications - Java Mission Control and Heap Dump Memory Analyzer Tool.
Anton Ivinskyi Application level metrics and performance testsАліна Шепшелей
It is important to understand how your code behaves in production, not just guess how it should behave. Know what takes time and what goes wrong. Measure it all. Be ready for the load with performance tests.
Kononenko Alina Designing for Apple Watch and Apple TVАліна Шепшелей
Apple Watch and Apple TV apps are inherently different from other apps, in both form and function. You will learn watchOS and tvOS user experience foundations and design principles, get the quick overview of the best existing solutions and possible ways of extending your projects to this platforms.
Mihail Patalaha Aso: how to start and how to finish?Аліна Шепшелей
How to collect the semantic core;
Which keywords to choose;
How to enter the keywords in the title and description;
How to understand the algorithm of Google Play;
How much traffic can be obtained by optimizing the ASO;
Tips to improve search results.
Gregory Shehet Undefined' on prod, or how to test a react appАліна Шепшелей
During the lecture we'll discuss the unit-testing of the interface. The stack of technologies: React (Redux, MobX), Mocha/Chai, React Tests Utils, Enzyme, Tape/Ava. Also, I will mention how we in Grammarly rewrite selenium to the unit tests, and how it works.
Alexey Osipenko Basics of functional reactive programmingАліна Шепшелей
During the report, we will develop incrementally construct primitives and algebra (in the worst case, just come up with a library interface) for the organization of interaction of the application with the mess in the real world. This approach will keep the application logic in the pure functions and declaratively associate external events with the necessary output.
And no React JS.
Step by step guide on building the multipurpose parser for scalable web data extraction.
Designing and usage of universal format for stripped web articles.
Format comparison with AMP(Google), Facebook Instant Articles and Apple News.
Alex Theedom Java ee revisits design patternsАліна Шепшелей
Enter "Django Channels": new way of desinging and thinking about your application. It separates transport and processing concerns in typical Django project using combination of ASGI (Asynchronous Server Gateway Interface) and worker processes, enabling your application to be "event-oriented" and implement new workflows for processing your data. How does it work? What do you need to start? Is it even useful? Learn for yourself with this introductory talk.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
11. • Behavior
• State
• Parallel
• Asynchronous Messages Mailboxes
• No Shared State
The Actor
Model
Carl Hewitt
1973
12. • Data + Code + Process
• Self-Contained Machines
• Stronger Encapsulation
• Less Inheritance
• Type Inference
• Hot Code Upgrades
Actor
structure
Behavior way
• Inheritance of Behavior only.
• Usually only one level deep.
• Usually one of the standard OTP behaviors:
• Generic Server
• Event
• State Machine
• Supervisor.
13. Actor vs. OO workflow
Synchronous Calls
Asynchronous Messages
14.
15. Actor Model: Benefits
• More true to the real world
• Better suited for parallel hardware
• Better suited for distributed architectures
• Scaling garbage collection (gc/actor)
• Less Magic
17. Erlang benefits
Functional nature
Pattern matching on steroids
Concurrency
Fault Tolerance
Let it crash
Distributed Computation
Debugging and profiling
Hot upgrades
21. Erlang benefits
Functional nature
Pattern matching on steroids
Concurrency
Fault Tolerance
Let it crash
Distributed Computation
Debugging and profiling
Hot upgrades
28. Remote shells
(salad@ferdmbp)1>
User switch command
--> h
c [nn] - connect to job
i [nn] - interrupt job
k [nn] - kill job
j - list all jobs
s [shell] - start local shell
r [node [shell]] - start remote shell
q - quit erlang
? | h - this message
--> r mustard@ferdmbp
--> j
1 {shell,start,[init]}
2* {mustard@ferdmbp,shell,start,[]}
--> c
Eshell V5.8.4 (abort with ^G)
(mustard@ferdmbp)1> node().
mustard@ferdmbp
29. Debugger and profilers
Tool Results
Size of
Result
Effects on Program
Execution Time
Records
Number of
Calls
Records
Execution
Time
Records
Called by
Records
Garbage
Collection
fprof
Per process to
screen/file
Large Significant slowdown Yes
Total and
own
Yes Yes
eprof
Per process/function
to screen/file
Medium Small slowdown Yes Only total No No
cover
Per module to
screen/file
Small Moderate slowdown Yes, per line No No No
cprof Per module to caller Small Small slowdown Yes No No No
dbg Text based tracer Large Small slowdonw No No Yes No
Communit
y
• recon
• redbug
• lager
• xprof
More
introspection
• etop
• pman
• os_mon
• debugger
34. Measurements
Activity
• millions active users
• fast processes for handling
Stability
• developers and operations sleeps fine
• no emergencies for a couple of years
Performance
• compatible to C,
• VM memory management
• lightweight concurrency
• scalability from a box
Issues
• concurrent bottlenecks
• Net splits
• Networks security
• Hot upgrades
35. Top 5 lines of code
46292
11703
7328
2784
1479
