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.
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
This document summarizes Gavin M. Roy's presentation on concurrency with multiprocessing in Python. It discusses using threads via the threading module, issues with the Global Interpreter Lock (GIL) in Python, and how to use the multiprocessing module to achieve true parallelism across multiple processes. It provides examples of creating threads and processes that run concurrently and examples of how to share objects between processes using connections, queues, pipes, managers and reduction tools.
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!
This document discusses using PostgreSQL statistics to optimize performance. It describes various statistics sources like pg_stat_database, pg_stat_bgwriter, and pg_stat_replication that provide information on operations, caching, and replication lag. It also provides examples of using these sources to identify issues like long transactions, temporary file growth, and replication delays.
The document discusses smoke testing, which are simple preliminary tests done after a software deployment to check for failures. It recommends conducting smoke tests that are fast, test key URLs and parameters, and validate status codes, response times, and that a response body is returned. The document then provides details on implementing concurrent smoke tests in PHP using a library that runs tests concurrently and collects results. It also outlines the server architecture used to route requests and deploy code, with smoke tests running before new code is switched to live.
- Replica sets in MongoDB allow for replication across multiple servers, with one server acting as the primary and able to accept writes, and other secondary servers replicating the primary.
- If the primary fails, the replica set will automatically elect a new primary from the secondary servers and continue operating without interruption.
- The replica set configuration specifies the members, their roles, and settings like heartbeat frequency to monitor member health and elect a primary if needed.
Mercurial is a decentralized version control system with a simple design and high performance. It uses a graph model to represent the history of commits, with each commit having a unique identifier and references to its parent commits. Basic operations in Mercurial include checking out revisions, making commits on branches, and pulling/pushing changes between repositories to share work. Mercurial avoids problems like multiple branch heads through its branching model and by disallowing amendments to existing commits.
The document provides an introduction to DTrace, a dynamic tracing framework available on Solaris, FreeBSD, Mac OS X and other operating systems. It discusses what DTrace is, how it works, examples of using DTrace to trace Oracle databases, potential issues with DTrace and conclusions.
Gevent is a Python library that uses greenlets to provide a synchronous-looking API for asynchronous applications. It uses a single OS thread and event loop to handle many connections concurrently by switching between greenlets frequently. This allows applications to achieve high concurrency with low memory usage compared to multithreading. Gevent patches common libraries like sockets to be non-blocking and cooperative. When data is available on a socket, the socket's greenlet is resumed to process it rather than blocking the entire program.
This document provides an overview of concurrency in Python using multiprocessing and threading. It begins by introducing the speaker and defining key terms like concurrency, threads, and processes. It then discusses the benefits and use cases of threads versus processes. The document also covers the Global Interpreter Lock (GIL) in Python and how multiprocessing can help avoid it. It provides an example benchmark showing multiprocessing can significantly outperform threading for CPU-bound tasks. Finally, it discusses key aspects of Python's multiprocessing module like Process, Queue, Pool, and Manager classes.
Do more than one thing at the same time, the Python wayJaime Buelta
The document discusses doing more than one thing at a time in Python using threads and processes. It describes how to create threads using the threading module and processes using the multiprocessing module. While threads are easier to use, the Global Interpreter Lock (GIL) in Python prevents true parallelism. Processes can better utilize multiple CPUs but require more work for communication. Asynchronous programming is recommended for I/O-bound tasks while processes are better for CPU-bound work. The talk cautions that threading should be used carefully in Python due to the GIL.
The document discusses concurrency in C++ and the use of std::async and std::future. It recommends preferring task-based programming over thread-based due to easier management. It notes that the default launch policy for std::async allows asynchronous or synchronous execution, creating uncertainty. It advises specifying std::launch::async if asynchronicity is essential to ensure concurrent execution and avoid issues with thread-local variables and timeout-based waits.
The document discusses protocol handlers in Gecko. It explains that protocol handlers allow Gecko to interact with different URI schemes like http, ftp, file etc. It provides an overview of how the awesome bar, browser UI, DocShell and Necko components work together to handle protocol requests from inputting a URL in the awesome bar to creating a channel and loading content. It also briefly introduces channels and stream listeners in Necko which are used for asynchronous loading of content.
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
The document discusses the os and sys modules in Python. It provides examples of how to use common os functions like rename, remove, mkdir, and listdir to work with files and directories. It also demonstrates how to use the sys module to access command line arguments and exit a program. Key functions covered include getcwd(), chdir(), split(), splitext(), join(), argv, and exit.
This document compares different methods for measuring performance and timing logic in Java, including System.currentTimeMillis(), System.nanoTime(), the StopWatch class from Apache Commons Lang, and the StopWatch utility from Spring Core. Code examples are provided for each method to demonstrate how to use it and sample output is shown. The Spring and Commons StopWatch implementations are then compared in terms of functionality.
Testing multi outputformat based mapreduceAshok Agarwal
The document describes using a MultiOutputFormat in MapReduce to generate separate output files for each stock price based on input that contains stock price data. It includes code for a mapper that extracts the stock name and price from each input record and a reducer that writes these values to individual files for each stock name. Unit tests are also described to test the reducer by mocking the MultipleOutputs class and validating that the output files contain the expected stock price values.
This document discusses profiling Go programs. It begins by stating the golden rule of premature optimization and emphasizes the importance of measuring before optimizing. Several Go profiling tools are described, including tools for timing, CPU profiling, and memory profiling. An example of a badly implemented LRU cache is provided and profiled to identify inefficiencies. Various improvements are then made to the LRU cache and tested, including using a linked list, random eviction, and eliminating slice operations. The document concludes with a discussion of memory recycling in Go programs.
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
This document summarizes a talk on building an ML platform with Ray and MLflow. Ray is an open-source framework for distributed computing and machine learning. It provides libraries like Ray Tune for hyperparameter tuning and Ray Serve for model serving. MLflow is a tool for managing the machine learning lifecycle including tracking experiments, managing models, and deploying models. The talk demonstrates how to build an end-to-end ML platform by integrating Ray and MLflow for distributed training, hyperparameter tuning, model tracking, and low-latency serving.
This document contains a presentation on MongoDB replication and replica sets. It discusses:
- The benefits of replication for avoiding downtime, data loss and handling failures.
- The lifecycle of a replica set including creation, initialization, failure and recovery of nodes.
- Different roles nodes can have like primary, secondary or arbiter.
- Configuration options for replica sets including priority, hidden nodes and tags.
- Considerations for developing applications using replica sets including write concerns, read preferences and consistency levels.
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.
PostgreSQL 8.4 introduced several new features including common table expressions, window functions, parallel restore, and performance improvements. Version 9.0 will focus on improving replication support through streaming replication and read-only hot standby servers. Overall, PostgreSQL continues to expand its feature set to better support modern SQL standards.
Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes ranging from gigabytes to petabytes. It is written in Java and uses a pluggable backend. Presto is fast due to code generation and runtime compilation techniques. It provides a library and framework for building distributed services and fast Java collections. Plugins allow Presto to connect to different data sources like Hive, Cassandra, MongoDB and more.
Worst-Case Scheduling of Software TasksLionel Briand
The document describes using a constrained optimization model to identify worst-case performance scenarios for real-time embedded systems (RTES) to support performance testing. It presents the model used to represent the static and dynamic properties of tasks in an RTES as well as the performance requirements as objective functions. The goal is to search for variable values, like task arrival times, that maximize objectives like deadline misses to generate worst-case test cases.
Profiling your Applications using the Linux Perf ToolsemBO_Conference
This document provides an overview of using the Linux perf tools to profile applications. It discusses setting up perf, benchmarking applications, profiling both CPU usage and sleep times, and analyzing profiling data. The document covers perf commands like perf record to collect profiling data, perf report to analyze the data, and perf script to convert it to other formats. It also discusses profiling options like call graphs and collecting kernel vs. user mode events.
This document summarizes two PHP monitoring tools: APM (Alternative PHP Monitor) and Pinba.
APM is a tool dedicated to error handling in PHP applications. It provides functions to retrieve error events and slow requests from a database. Pinba is focused on real-time performance monitoring. It allows setting timers and retrieving performance metrics like request time and memory usage. Both tools have low overhead and are open source alternatives to commercial monitoring solutions.
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.
Scaling python webapps from 0 to 50 million users - A top-down approachJinal Jhaveri
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This document provides an overview of scaling a Python web application from 0 to 50 million users. It discusses key bottlenecks and solutions at different levels including the load balancer, web server, web application and browser. It emphasizes the importance of profiling, measuring and improving performance iteratively. Specific techniques mentioned include using Memcached to avoid database trips, asynchronous programming, compression, caching, and a performance strategy of measure, profile and improve.
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.
The document discusses Bluespec, a hardware description language that combines features of Haskell and SystemVerilog assertions (SVA). Bluespec models all state explicitly using guarded atomic actions on state. Behavior is expressed as rules with guards and actions. Assertions in Bluespec are compiled into finite state machines and checked concurrently as rules. The document provides an example of using Bluespec to write functional and performance assertions for a cache controller design.
Presto generates Java bytecode at runtime to optimize query execution. Key query operations like filtering, projections, joins and aggregations are compiled into efficient Java methods using libraries like ASM and Fastutil. This bytecode generation improves performance by 30% through techniques like compiling row hashing for join lookups directly into machine instructions.
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
Mobile QA teams are responsible for thoroughly testing apps before release to ensure high quality. They use a variety of manual and automated testing methods at different stages of development. QA works closely with development and customer support to catch bugs, validate fixes, and improve the product based on user feedback. The goal is to deliver stable, bug-free apps through collaboration across teams.
Oleksandr Yefremov Continuously delivering mobile projectАліна Шепшелей
This document discusses best practices for continuously delivering mobile projects. It outlines a CI/CD workflow that includes running tests and manual QA on pull requests, notifying stakeholders, automatically generating changelogs and version bumps, preparing release artifacts, and publishing them to stores or S3. Key steps are running tests on pull requests, using strict PR naming conventions, notifying teams in Slack, automating versioning and publishing with scripts and Fastlane, and deploying beta builds to Fabric/Crashlytics. The full workflow aims to streamline mobile releases by automating repetitive tasks and integrating all steps.
Alexander Voronov Test driven development in real worldАліна Шепшелей
This document discusses test-driven development (TDD) practices. It covers topics like the benefits of cleaner interfaces and unbiased design when tests are written first. It also addresses challenges like introducing TDD to an existing codebase or team. Key points emphasized are starting simple with critical features, finding the lowest testable point, and making incremental changes to introduce tests and refactoring step-by-step. Continuous integration practices are also highlighted.
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.
This document provides an overview and agenda for an Apache HBase workshop. It introduces HBase as an open-source NoSQL database built on Hadoop that uses a column-family data model. The agenda covers what HBase is, its data model including rows, columns, cells and versions, CRUD operations, architecture including regions and masters, schema design best practices, and the Java API. Performance tips are given for client reads and writes such as using batches, caching, and tuning durability.
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.
Anton Parkhomenko Boost your design workflow or git rebase for designersАліна Шепшелей
The document provides 4 tips to boost a designer's workflow: 1) Use Git to version and collaborate on design files, 2) Automate repetitive processes, 3) Be prepared for changes by using flexible components and responsive design, 4) Create prototypes to gather feedback early in the design process.
Andrew Veles Product design is about the processАліна Шепшелей
This document discusses product design and the product design process. It emphasizes that product design is about focus, thinking through every step of the process from initial ideas to implementation. This includes activities like creating portraits, user stories, specifications, site maps, flows, wireframes, prototypes, and UI design. It also notes that the goal is stable growth for the product over time, but that the solution designed may need to change as problems change. Examples are provided of redesigns for a mobile app, desktop app, and logo. The conclusion emphasizes that building the right features for the right users is more challenging than just building features.
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
Mikhail Patalakha is a mobile ASO manager with experience managing over 50 successful projects. He provides tips for optimizing mobile app keywords and rankings, including opening the application, researching competitors' keywords, removing duplicates, getting new keywords from Google Keyword Planner, defining competition and traffic from services like SensorTower and ASOdesk, choosing keywords based on difficulty, and calculating approximate visitor numbers using a provided formula. His contact information is provided for further questions.
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.
Roman Ugolnikov Migrationа and sourcecontrol for your dbАліна Шепшелей
The document discusses database migration and source control. It describes how database structure, data, and logic can change across versions. It recommends using tools like Liquibase and Flyway to manage database schema changes and keep the database schema in sync with code. These tools allow defining changes in migration files and rolling back changes if needed. The document also covers how the tools work, supported databases, file formats, preconditions, and provides a demo of using the tools for a sample database migration.
JHipster is a Yeoman generator used to create a Spring Boot and AngularJS project. It saves development time by including accepted practices and scaffolding for both design and runtime. The generator supports technologies like Spring Boot, AngularJS, Bootstrap, and MySQL. Developers can add additional functionality through JHipster modules and sub-generators. The generated projects include tools for testing, deployment to Docker, and integration with services like Elasticsearch.
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.
Top 12 AI Technology Trends For 2024.pdfMarrie Morris
Technology has become an irreplaceable component of our daily lives. The role of AI in technology revolutionizes our lives for the betterment of the future. In this article, we will learn about the top 12 AI technology trends for 2024.
Welcome to Cyberbiosecurity. Because regular cybersecurity wasn't complicated...Snarky Security
How wonderful it is that in our modern age, every bit of our biological data can be digitized, stored, and potentially pilfered by cyber thieves! Isn't it just splendid to think that while scientists are busy pushing the boundaries of biotechnology, hackers could be plotting the next big bio-data heist? This delightful scenario is brought to you by the ever-expanding digital landscape of biology and biotechnology, where the integration of computer science, engineering, and data science transforms our understanding and manipulation of biological systems.
While the fusion of technology and biology offers immense benefits, it also necessitates a careful consideration of the ethical, security, and associated social implications. But let's be honest, in the grand scheme of things, what's a little risk compared to potential scientific achievements? After all, progress in biotechnology waits for no one, and we're just along for the ride in this thrilling, slightly terrifying, adventure.
So, as we continue to navigate this complex landscape, let's not forget the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. After all, what could possibly go wrong?
-------------------------
This document provides a comprehensive analysis of the security implications biological data use. The analysis explores various aspects of biological data security, including the vulnerabilities associated with data access, the potential for misuse by state and non-state actors, and the implications for national and transnational security. Key aspects considered include the impact of technological advancements on data security, the role of international policies in data governance, and the strategies for mitigating risks associated with unauthorized data access.
This view offers valuable insights for security professionals, policymakers, and industry leaders across various sectors, highlighting the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. The analysis serves as a crucial resource for understanding the complex dynamics at the intersection of biotechnology and security, providing actionable recommendations to enhance biosecurity in an digital and interconnected world.
The evolving landscape of biology and biotechnology, significantly influenced by advancements in computer science, engineering, and data science, is reshaping our understanding and manipulation of biological systems. The integration of these disciplines has led to the development of fields such as computational biology and synthetic biology, which utilize computational power and engineering principles to solve complex biological problems and innovate new biotechnological applications. This interdisciplinary approach has not only accelerated research and development but also introduced new capabilities such as gene editing and biomanufact
Choosing the Best Outlook OST to PST Converter: Key Features and Considerationswebbyacad software
When looking for a good software utility to convert Outlook OST files to PST format, it is important to find one that is easy to use and has useful features. WebbyAcad OST to PST Converter Tool is a great choice because it is simple to use for anyone, whether you are tech-savvy or not. It can smoothly change your files to PST while keeping all your data safe and secure. Plus, it can handle large amounts of data and convert multiple files at once, which can save you a lot of time. It even comes with 24*7 technical support assistance and a free trial, so you can try it out before making a decision. Whether you need to recover, move, or back up your data, Webbyacad OST to PST Converter is a reliable option that gives you all the support you need to manage your Outlook data effectively.
Generative AI technology is a fascinating field that focuses on creating comp...Nohoax Kanont
Generative AI technology is a fascinating field that focuses on creating computer models capable of generating new, original content. It leverages the power of large language models, neural networks, and machine learning to produce content that can mimic human creativity. This technology has seen a surge in innovation and adoption since the introduction of ChatGPT in 2022, leading to significant productivity benefits across various industries. With its ability to generate text, images, video, and audio, generative AI is transforming how we interact with technology and the types of tasks that can be automated.
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
What difficulties our team faced: life hacks with Blazor app routing, whether it is necessary to write JavaScript, which technology stack and architectural patterns we chose
What conclusions we made and what mistakes we committed
The Challenge of Interpretability in Generative AI Models.pdfSara Kroft
Navigating the intricacies of generative AI models reveals a pressing challenge: interpretability. Our blog delves into the complexities of understanding how these advanced models make decisions, shedding light on the mechanisms behind their outputs. Explore the latest research, practical implications, and ethical considerations, as we unravel the opaque processes that drive generative AI. Join us in this insightful journey to demystify the black box of artificial intelligence.
Dive into the complexities of generative AI with our blog on interpretability. Find out why making AI models understandable is key to trust and ethical use and discover current efforts to tackle this big challenge.
Demystifying Neural Networks And Building Cybersecurity ApplicationsPriyanka Aash
In today's rapidly evolving technological landscape, Artificial Neural Networks (ANNs) have emerged as a cornerstone of artificial intelligence, revolutionizing various fields including cybersecurity. Inspired by the intricacies of the human brain, ANNs have a rich history and a complex structure that enables them to learn and make decisions. This blog aims to unravel the mysteries of neural networks, explore their mathematical foundations, and demonstrate their practical applications, particularly in building robust malware detection systems using Convolutional Neural Networks (CNNs).
Redefining Cybersecurity with AI CapabilitiesPriyanka Aash
In this comprehensive overview of Cisco's latest innovations in cybersecurity, the focus is squarely on resilience and adaptation in the face of evolving threats. The discussion covers the imperative of tackling Mal information, the increasing sophistication of insider attacks, and the expanding attack surfaces in a hybrid work environment. Emphasizing a shift towards integrated platforms over fragmented tools, Cisco introduces its Security Cloud, designed to provide end-to-end visibility and robust protection across user interactions, cloud environments, and breaches. AI emerges as a pivotal tool, from enhancing user experiences to predicting and defending against cyber threats. The blog underscores Cisco's commitment to simplifying security stacks while ensuring efficacy and economic feasibility, making a compelling case for their platform approach in safeguarding digital landscapes.
How UiPath Discovery Suite supports identification of Agentic Process Automat...DianaGray10
📚 Understand the basics of the newly persona-based LLM-powered Agentic Process Automation and discover how existing UiPath Discovery Suite products like Communication Mining, Process Mining, and Task Mining can be leveraged to identify APA candidates.
Topics Covered:
💡 Idea Behind APA: Explore the innovative concept of Agentic Process Automation and its significance in modern workflows.
🔄 How APA is Different from RPA: Learn the key differences between Agentic Process Automation and Robotic Process Automation.
🚀 Discover the Advantages of APA: Uncover the unique benefits of implementing APA in your organization.
🔍 Identifying APA Candidates with UiPath Discovery Products: See how UiPath's Communication Mining, Process Mining, and Task Mining tools can help pinpoint potential APA candidates.
🔮 Discussion on Expected Future Impacts: Engage in a discussion on the potential future impacts of APA on various industries and business processes.
Enhance your knowledge on the forefront of automation technology and stay ahead with Agentic Process Automation. 🧠💼✨
Speakers:
Arun Kumar Asokan, Delivery Director (US) @ qBotica and UiPath MVP
Naveen Chatlapalli, Solution Architect @ Ashling Partners and UiPath MVP
Keynote : Presentation on SASE TechnologyPriyanka Aash
Secure Access Service Edge (SASE) solutions are revolutionizing enterprise networks by integrating SD-WAN with comprehensive security services. Traditionally, enterprises managed multiple point solutions for network and security needs, leading to complexity and resource-intensive operations. SASE, as defined by Gartner, consolidates these functions into a unified cloud-based service, offering SD-WAN capabilities alongside advanced security features like secure web gateways, CASB, and remote browser isolation. This convergence not only simplifies management but also enhances security posture and application performance across global networks and cloud environments. Discover how adopting SASE can streamline operations and fortify your enterprise's digital transformation strategy.
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
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