Java, Turbocharged
•
0 likes•136 views
Over the last twenty years, there has been a paradigm shift in software development: from meticulously planned release cycles to an experimental way of working in which lead times are becoming shorter and shorter. How can Java ever keep up with this trend when we have Docker containers that are several hundred megabytes in size, with warm-up times of ten minutes or longer? In this talk, I'll demonstrate how we can use Quarkus so that we can create super small, super fast Java containers! This will give us better possibilities for scaling up and down - which can be a game-changer, especially in a serverless environment. It will also provide the shortest possible lead times, as well as a much better use of cloud performance with the added bonus of lower costs.
Report
Share
Report
Share
Download to read offline
Recommended
Massively scalable ETL in real world applications: the hard way
Big Data examples always give the correct answers. However, in the real world, Big Data might be corrupt, contradictory or consist of so many small files it becomes extremely hard to keep track - let alone scale. A solid architecture will help to overcome many of the difficulties.
Floris will talk about a real-world implementation of a massively scalable ETL architecture. Two years ago, at the time of the implementation, Airflow just became part of Apache and still left many features to be desired for. However, requirements from the start were thousands of ETL tasks per day on average, but on occasion, this could become hundreds of thousands. The script-based method that was in place was already not capable to meet the requirements on a day to day basis and needed to be replaced as soon as possible. So this custom framework was rolled out in just 8 weeks of development time.
Big Data On Data You Don’t Have
Traditional Big Data is done on Data you have. You load the data into a repository and perform map reduce or other style calculations on the data. However, certain industries need to perform complex operations on data you might not have. Data you can acquire, Data that can be shared with you, and Data that you can model are all types of data you may not have but may need to integrate instantly into a complex data analysis. Problem is: you may not even know you need this data until deep into the execution stack at runtime. This talk discusses a new functional language paradigm for dealing naturally with data you don’t have and about how to make all data first-class citizens, regardless of whether you have it or you don’t, and we will give a demo of a project written in Scala to deal exactly with this issue.
Acoustic Time Series in Industry 4.0: Improved Reliability and Cyber-Security...
Industry 4.0, aka the "Fourth Industrial Revolution," refers to the computerization of manufacturing. One important aspect of Industry 4.0 is the ability to monitor the health and reliability of a physical manufacturing plant using low-cost IoT sensors. For example, machine learning models can be trained to predict the physical degradation of a manufacturing system as a function of acoustic measurements obtained from strategically placed microphones; however, the same acoustic measurements can be used to reverse engineer proprietary information about the manufacturing process and/or precisely what is being manufactured at the time of recording. Thus, improved reliability and fault tolerance is achieved at the cost of what appears to be an unprecedented new class of security vulnerabilities related to the acoustic side channel.
As a case study, we report a novel acoustic side channel attack against a commercial DNA synthesizer, a commonly used instrument in fields such as synthetic biology. Using a smart phone-quality microphone placed on or in the near vicinity of a DNA synthesizer, we were able to determine with 88.07% accuracy the sequence of DNA being produced; using a database of biologically relevant known-sequences, we increased the accuracy of our model to 100%. An academic or industrial research project may use the synthetic DNA to engineer an organism with desired traits or functions; however, while the organism is still under development, prior to publication, patent, and/or copyright, the research remains vulnerable to academic intellectual property theft and/or industrial espionage. On the other hand, this attack could also be used for benevolent purposes, for example, to determine whether a suspected criminal or terrorist is engineering a harmful pathogen. Thus, it is essential to recognize both the benefits and risks inherent to the cyber-physical systems that will inevitably control Industry 4.0 manufacturing processes and to take steps to mitigate them whenever possible.
Pushing it to the edge in IoT
Where is the edge in IoT and how much can you do there? Data collection? Analytics? I’ll show you how to build and deploy an embedded IoT edge platform that can do data collection, analytics, dashboarding and much more. All using Open Source.
As IoT deployments move forward, the need to collect, analyze, and respond to data further out on the edge becomes a critical factor in the success – or failure – of any IoT project. Network bandwidth costs may be dropping, and storage is cheaper than ever, but at IoT scale, these costs can still quickly overrun a project’s budget and ultimately doom it to failure.
The more you centralize your data collection and storage, the higher these costs become. Edge data collection and analysis can dramatically lower these costs, plus decrease the time to react to critical sensor data. With most data platforms, it simply isn’t practical, or even possible, to push collection AND analytics to the edge. In this talk I’ll show how I’ve done exactly this with a combination of open source hardware – Pine64 – and open source software – InfluxDB – to build a practical, efficient and scalable data collection and analysis gateway device for IoT deployments. The edge is where the data is, so the edge is where the data collection and analytics needs to be.
Drinking from the firehose, with virtual streams and virtual actors
Event Stream Processing is a popular paradigm for building robust and performant systems in many different domains, from IoT to fraud detection to high-frequency trading. Because of the wide range of scenarios and requirements, it is difficult to conceptualize a unified programming model that would be equally applicable to all of them. Another tough challenge is how to build streaming systems with cardinalities of topics ranging from hundreds to billions while delivering good performance and scalability.
In this session, Sergey Bykov will talk about the journey of building Orleans Streams that originated in gaming and monitoring scenarios, and quickly expanded beyond them. He will cover the programming model of virtual streams that emerged as a natural extension of the virtual actor model of Orleans, the architecture of the underlying runtime system, the compromises and hard choices made in the process. Sergey will share the lessons learned from the experience of running the system in production, and future ideas and opportunities that remain to be explored.
How do we deploy? From Punched cards to Immutable server pattern
A short retrospective of deployment approaches evolution and the key features of the most up-to-date concepts.
When Cloud Native meets the Financial Sector
We live in our own bubble of microservices and endlessly horizontal scaling infrastructure, but there is still critical infrastructure that runs the world of financial systems depending on Windows boxes, FTP servers, and single-threaded protocols. This talk is about how to glue these two worlds together, what works for us and what doesn't.
The big data Universe. Literally.
The advancement of technology in the last decade or so has allowed astronomy to see exponential growth in data volumes. ESA's space telescope Euclid will gather high-resolution images of a third of the sky, ~850GB of data downloaded daily for 6 years, by 2032 ground-based telescope LSST will have generated 500PB of data and the radio telescope SKA will be producing more data per second than the entire internet worldwide. This talk will address the questions of what current techniques exist to address big data volumes, how the astronomical community will prepare for this big data wave, and what other challenges lie ahead?
Recommended
Massively scalable ETL in real world applications: the hard way
Big Data examples always give the correct answers. However, in the real world, Big Data might be corrupt, contradictory or consist of so many small files it becomes extremely hard to keep track - let alone scale. A solid architecture will help to overcome many of the difficulties.
Floris will talk about a real-world implementation of a massively scalable ETL architecture. Two years ago, at the time of the implementation, Airflow just became part of Apache and still left many features to be desired for. However, requirements from the start were thousands of ETL tasks per day on average, but on occasion, this could become hundreds of thousands. The script-based method that was in place was already not capable to meet the requirements on a day to day basis and needed to be replaced as soon as possible. So this custom framework was rolled out in just 8 weeks of development time.
Big Data On Data You Don’t Have
Traditional Big Data is done on Data you have. You load the data into a repository and perform map reduce or other style calculations on the data. However, certain industries need to perform complex operations on data you might not have. Data you can acquire, Data that can be shared with you, and Data that you can model are all types of data you may not have but may need to integrate instantly into a complex data analysis. Problem is: you may not even know you need this data until deep into the execution stack at runtime. This talk discusses a new functional language paradigm for dealing naturally with data you don’t have and about how to make all data first-class citizens, regardless of whether you have it or you don’t, and we will give a demo of a project written in Scala to deal exactly with this issue.
Acoustic Time Series in Industry 4.0: Improved Reliability and Cyber-Security...
Industry 4.0, aka the "Fourth Industrial Revolution," refers to the computerization of manufacturing. One important aspect of Industry 4.0 is the ability to monitor the health and reliability of a physical manufacturing plant using low-cost IoT sensors. For example, machine learning models can be trained to predict the physical degradation of a manufacturing system as a function of acoustic measurements obtained from strategically placed microphones; however, the same acoustic measurements can be used to reverse engineer proprietary information about the manufacturing process and/or precisely what is being manufactured at the time of recording. Thus, improved reliability and fault tolerance is achieved at the cost of what appears to be an unprecedented new class of security vulnerabilities related to the acoustic side channel.
As a case study, we report a novel acoustic side channel attack against a commercial DNA synthesizer, a commonly used instrument in fields such as synthetic biology. Using a smart phone-quality microphone placed on or in the near vicinity of a DNA synthesizer, we were able to determine with 88.07% accuracy the sequence of DNA being produced; using a database of biologically relevant known-sequences, we increased the accuracy of our model to 100%. An academic or industrial research project may use the synthetic DNA to engineer an organism with desired traits or functions; however, while the organism is still under development, prior to publication, patent, and/or copyright, the research remains vulnerable to academic intellectual property theft and/or industrial espionage. On the other hand, this attack could also be used for benevolent purposes, for example, to determine whether a suspected criminal or terrorist is engineering a harmful pathogen. Thus, it is essential to recognize both the benefits and risks inherent to the cyber-physical systems that will inevitably control Industry 4.0 manufacturing processes and to take steps to mitigate them whenever possible.
Pushing it to the edge in IoT
Where is the edge in IoT and how much can you do there? Data collection? Analytics? I’ll show you how to build and deploy an embedded IoT edge platform that can do data collection, analytics, dashboarding and much more. All using Open Source.
As IoT deployments move forward, the need to collect, analyze, and respond to data further out on the edge becomes a critical factor in the success – or failure – of any IoT project. Network bandwidth costs may be dropping, and storage is cheaper than ever, but at IoT scale, these costs can still quickly overrun a project’s budget and ultimately doom it to failure.
The more you centralize your data collection and storage, the higher these costs become. Edge data collection and analysis can dramatically lower these costs, plus decrease the time to react to critical sensor data. With most data platforms, it simply isn’t practical, or even possible, to push collection AND analytics to the edge. In this talk I’ll show how I’ve done exactly this with a combination of open source hardware – Pine64 – and open source software – InfluxDB – to build a practical, efficient and scalable data collection and analysis gateway device for IoT deployments. The edge is where the data is, so the edge is where the data collection and analytics needs to be.
Drinking from the firehose, with virtual streams and virtual actors
Event Stream Processing is a popular paradigm for building robust and performant systems in many different domains, from IoT to fraud detection to high-frequency trading. Because of the wide range of scenarios and requirements, it is difficult to conceptualize a unified programming model that would be equally applicable to all of them. Another tough challenge is how to build streaming systems with cardinalities of topics ranging from hundreds to billions while delivering good performance and scalability.
In this session, Sergey Bykov will talk about the journey of building Orleans Streams that originated in gaming and monitoring scenarios, and quickly expanded beyond them. He will cover the programming model of virtual streams that emerged as a natural extension of the virtual actor model of Orleans, the architecture of the underlying runtime system, the compromises and hard choices made in the process. Sergey will share the lessons learned from the experience of running the system in production, and future ideas and opportunities that remain to be explored.
How do we deploy? From Punched cards to Immutable server pattern
A short retrospective of deployment approaches evolution and the key features of the most up-to-date concepts.
When Cloud Native meets the Financial Sector
We live in our own bubble of microservices and endlessly horizontal scaling infrastructure, but there is still critical infrastructure that runs the world of financial systems depending on Windows boxes, FTP servers, and single-threaded protocols. This talk is about how to glue these two worlds together, what works for us and what doesn't.
The big data Universe. Literally.
The advancement of technology in the last decade or so has allowed astronomy to see exponential growth in data volumes. ESA's space telescope Euclid will gather high-resolution images of a third of the sky, ~850GB of data downloaded daily for 6 years, by 2032 ground-based telescope LSST will have generated 500PB of data and the radio telescope SKA will be producing more data per second than the entire internet worldwide. This talk will address the questions of what current techniques exist to address big data volumes, how the astronomical community will prepare for this big data wave, and what other challenges lie ahead?
Streaming to a New Jakarta EE
The world is moving from a model where data sits at rest, waiting for people to make requests of it, to where data is constantly moving and streams of data flow to and from devices with or without human interaction. Decisions need to be made based on these streams of data in real-time, models need to be updated, and intelligence needs to be gathered. In this context, our old-fashioned approach of CRUD REST APIs serving CRUD database calls just doesn't cut it. It's time we moved to a stream-centric view of the world.
The TIPPSS Imperative for IoT - Ensuring Trust, Identity, Privacy, Protection...
Our increasingly connected world leveraging the Internet of Things (IoT) creates great value, in connected healthcare, smart cities, and more. The increasing use of IoT also creates great risk. We will discuss the challenges and risks we need to address as developers in TIPPSS - Trust, Identity, Privacy, Protection, Safety, and Security - for devices, systems and solutions we deliver and use. Florence leads IEEE workstreams on clinical IoT and data interoperability with blockchain addressing TIPPSS issues. She is an author of IEEE articles on "Enabling Trust and Security - TIPPSS for IoT" and "Wearables and Medical Interoperability - the Evolving Frontier", "TIPPSS for Smart Cities" in the 2017 book "Creating, Analysing and Sustaining Smarter Cities: A Systems Perspective" , and Editor in Chief for an upcoming book on "Women Securing the Future with TIPPSS for IoT."
Pushing AI to the Client with WebAssembly and Blazor
Want to run your AI algorithms directly in the browser on the client-side? Now you can with WebAssembly and Blazor. Join us as we write code directly in WebAssembly. Then, we’ll look at Blazor and how you can use it, along with WebAssembly to run your tooling client side in the browser.
Want to run your AI algorithms directly in the browser on the client-side without the need for transpilers or browser plug-ins? Well, now you can with WebAssembly and Blazor. WebAssembly (WASM) is the W3C specification that will be used to provide the next generation of development tools for the web and beyond. Blazor is Microsoft’s experiment that allows ASP.Net developers to create web pages that do much of the scripting work in C# using WASM. Come join us as we learn to write code directly in WebAssembly’s human-readable format. Then, we’ll look at the current state of Blazor and how you can use it, along with WebAssembly to run your tooling client side in the browser.
Axon Server went RAFTing
RAFT protocol is a well-known protocol for consensus in Distributed Systems. Want to learn how consensus is achieved in a system with a large amount of data such as Axon Server’s Event Store? Join this talk to hear about all specifics regarding data replication in highly available Event Store!
Axon is a free and open source Java framework for writing Java applications following DDD, event sourcing, and CQRS principles. While especially useful in a microservices context, Axon provides great value in building structured monoliths that can be broken down into microservices when needed.
Axon Server is a messaging platform specifically built to support distributed Axon applications. One of its key benefits is storing events published by Axon applications. In not so rare cases, the number of these events is over millions, even billions. Availability of Axon Server plays a significant role in the product portfolio. To keep event replication reliable we chose RAFT protocol for consensus implementation of our clustering features.
In short, consensus involves multiple servers agreeing on values. Once they reach a decision on a value, that decision is final. Typical consensus algorithms make progress when any majority of their servers is available; for example, a cluster of 5 servers can continue to operate even if 2 servers fail. If more servers fail, they stop making progress (but will never return an incorrect result).
Join this talk to learn why we chose RAFT; what were our findings during the design, the implementation, and testing phase; and what does it mean to replicate an event store holding billions of events!
The Six Pitfalls of building a Microservices Architecture (and how to avoid t...
Thinking of moving to Microservices? Watch out! That quest is full of traps, social traps. If you are not able to handle it, you may be blocked by meetings, frustration, endless challenges that will make you miss the monolith. In this talk, I share my experience and mistakes, so you can avoid them.
Creating or migrating to a Microservices architecture might easily become a big mess, not only due to technical challenges but mostly because of human factors: it’s a major change in the software culture of a company. In this talk, I’ll share my past experience as the technical lead of an ambitious Microservices-based product, I’ll go through the parts we struggled with, and give you some advice on how to deal with what I call the Six Pitfalls:
The Common Patterns Phobia
The Book Club Cult
The Never-Decoupled Story
The Buzz Words Syndrome
The Agile Trap
The Conway’s Law Hackers
Madaari : Ordering For The Monkeys
Instead of randomly injecting faults ( i.e. Chaos Monkey), what if we could order our experiments to perform min number of experiments for maximum yield? We present a solution(& results) to the problem of experiment selection using Lineage Driven Fault Injection to reduce the search space of faults.
Lineage Driven Fault Injection (LDFI) is a state of the art technique in chaos engineering experiment selection. LDFI since its inception has used an SAT solver under the hood which presents solutions to the decision problem (which faults to inject) in no particular order. As SRE’s we would like to perform experiments that reveal the bugs that the customers are most likely to hit first. In this talk, we present new improvements to LDFI that orders the experiment suggestions.
In the first the half of the talk we will show LDFI is a technique that can be widely used within an enterprise. We present the motivation for ordering the chaos experiments along with some prioritization we utilized while conducting the experiments. We also highlight how ordering is a general purpose technique that we can use to encode the peculiarities of a heterogeneous microservices architecture. LDFI can work in an enterprise by harnessing the observability infrastructure to model the redundancy of the system.
Next, we present experiments conducted within our organization using ordered LDFI and some preliminary results. We show examples of services where we discovered bugs, and how carefully controlling the order of experiments allowed LDFI to avoid running unnecessary experiments. We also present an example of an application where we declared the service shippable under crash stop model. We also present a comparison with Chaos Monkey and show how LDFI found the known bugs in a given application using orders of magnitude fewer experiments than a random fault injection tool like Chaos Monkey.
Finally, we discuss how we plan to take LDFI forward. We discuss open problems and possible solutions for scalarizing probabilities of failure, latency injection, integration with service mesh technologies like envoy for fine-grained fault injection, fault injection for stateful systems.
Key takeaways: 1) Understand how LDFI can be integrated in the enterprise by harnessing the observability infrastructure. 2) Limitations of LDFI w.r.t unordered solutions and why ordering matters for chaos engineering experiments. 3) Preliminary results of prioritized LDFI and a future direction for the community.
Servers are doomed to fail
Complexity in systems should be defeated if it is possible to do. But the default nature of our computer systems are complex and servers are doomed to fail. In this talk, we will go through new approaches in modern architectures to design and evaluate new computer systems.
Interaction Protocols: It's all about good manners
Distributed systems collaborate to achieve collective goals via a system of rules. Rules that affords good hygiene, fault tolerance, effective communication and trusted feedback. These rules form protocols which enable the system to achieve its goals.
Distributed and concurrent systems can be considered a social group that collaborates to achieve collective goals. In order to collaborate a system of rules must be applied, that affords good hygiene, fault tolerance, and effective communication to coordinate, share knowledge, and provide feedback in a polite trusted manner. These rules form a number of protocols which enable the group to act as a system which is greater than the sum of the individual components.
In this talk, we will explore the history of protocols and their application when building distributed systems.
A race of two compilers: GraalVM JIT versus HotSpot JIT C2. Which one offers ...
Do you want to check the efficiency of the new, state of the art, GraalVM JIT Compiler in comparison to the old but mostly used JIT C2? Let’s have a side by side comparison from a performance standpoint on the same source code.
The talk reveals how traditional Just In Time Compiler (e.g. JIT C2) from HotSpot/OpenJDK internally manages runtime optimizations for hot methods in comparison to the new, state of the art, GraalVM JIT Compiler on the same source code, emphasizing all of the internals and strategies used by each Compiler to achieve better performance in most common situations (or code patterns). For each optimization, there is Java source code and corresponding generated assembly code in order to prove what really happens under the hood.
Each test is covered by a dedicated benchmark (JMH), timings and conclusions. Main topics of the agenda: - Scalar replacement - Null Checks - Virtual calls - Lock coarsening - Lock elision - Virtual calls - Scalar replacement - Lambdas - Vectorization (few cases)
The tools used during my research study are JITWatch, Java Measurement Harness, and perf. All test scenarios will be launched against the latest official Java release (e.g. version 11).
Leadership at every level
Leadership is easy when you're a manager, or an expert in a field, or a conference speaker! In a Kanban organisation, though, we "encourage acts of leadership at every level". In this talk, we look at what it means to be a leader in the uncertain, changing and high-learning environment of software development. We learn about the importance of safety in encouraging others to lead and follow, and how to get that safety using both technical and human practices; the necessity of a clear, compelling vision and provision of information on how we're achieving it; and the need to be able to ask awkward and difficult questions... especially the ones without easy answers.
Machine Learning: The Bare Math Behind Libraries
During this presentation, we will answer how much you’ll need to invest in a superhero costume to be as popular as Superman. We will generate a unique logo which will stand against the ever popular Batman and create new superhero teams. We shall achieve it using linear regression and neural networks.
Machine learning is one of the hottest buzzwords in technology today as well as one of the most innovative fields in computer science – yet people use libraries as black boxes without basic knowledge of the field. In this session, we will strip them to bare math, so next time you use a machine learning library, you’ll have a deeper understanding of what lies underneath.
During this session, we will first provide a short history of machine learning and an overview of two basic teaching techniques: supervised and unsupervised learning.
We will start by defining what machine learning is and equip you with an intuition of how it works. We will then explain the gradient descent algorithm with the use of simple linear regression to give you an even deeper understanding of this learning method. Then we will project it to supervised neural networks training.
Within unsupervised learning, you will become familiar with Hebb’s learning and learning with concurrency (winner takes all and winner takes most algorithms). We will use Octave for examples in this session; however, you can use your favourite technology to implement presented ideas.
Our aim is to show the mathematical basics of neural networks for those who want to start using machine learning in their day-to-day work or use it already but find it difficult to understand the underlying processes. After viewing our presentation, you should find it easier to select parameters for your networks and feel more confident in your selection of network type, as well as be encouraged to dive into more complex and powerful deep learning methods.
Getting started with Deep Reinforcement Learning
Reinforcement Learning is a hot topic in Artificial Intelligence (AI) at the moment with the most prominent example of AlphaGo Zero. It shifted the boundaries of what was believed to be possible with AI. In this talk, we will have a look into Reinforcement Learning and its implementation.
Reinforcement Learning is a class of algorithms which trains an agent to act optimally in an environment. The most prominent example is AlphaGo Zero, where the agent is trained to place tokens on the board of Go in order to win the game. AlphaGo Zero has won against the world champion which was thought to be impossible at that time. This was enabled by combining Reinforcement Learning with Deep Neural Networks and is today known as Deep Reinforcement Learning. This has shifted the frontier of Artificial Intelligence and enabled multiple complex use cases, among them controlling the cooling devices in the server rooms by google. Applying Deep Reinforcement Learning saved them several million in power costs. In this talk, we will understand the basics of Deep Reinforcement Learning and implement a simple example. We will have a look at OpenAIs gym which is the defacto standard for Reinforcement Learning environments. This will enable the audience to implement both an environment and Reinforcement Learning agent on their own.
Toward Predictability and Stability At The Edge Of Chaos
As we edge towards larger, more complex and decoupled systems, combined with the continual growth of the global information graph, our frontiers of unsolved challenges grow equally as fast. Central challenges for distributed systems include persistence strategies across DCs, zones or regions, network partitions, data optimization, system stability in all phases.
How does leveraging CRDTs and Event Sourcing address several core distributed systems challenges? What are useful strategies and patterns involved in the design, deployment, and running of stateful and stateless applications for the cloud, for example with Kubernetes. Combined with code samples, we will see how Akka Cluster, Multi-DC Persistence, Split Brain, Sharding and Distributed Data can help solve these problems.
Numeric programming with spire
Spire is a Scala library for fast, generic, and precise numerics. It allows us to write generic numeric algorithms, provides the ‘number tower’ and offers a lot of utilities you didn’t know you needed.
Numeric programming is a notoriously difficult topic. For number crunching, e.g. solving systems of linear equations, we need raw performance. However, using floating-point numbers may lead to inaccurate results. On top of that, in functional programming, we’d really like to abstract over concrete number types, which is where abstract algebra comes into play. This interplay between abstract and concrete and the fact that everything needs to run on finite hardware is what makes good library support necessary for writing fast & correct programs. Spire is such a library in the Typelevel Scala ecosystem. This talk will be an introduction to Spire, showcasing the ‘number tower’, real-ish numbers and how to obey the law.
Istio Service Mesh & pragmatic microservices architecture
We have been celebrating 2018 as the Year of the Service Mesh, where an open source effort known as Istio has taken and changed how we design and release our applications.
As we start to go toward cloud-native infrastructure and build our applications out of microservices, we must fully face the drawbacks and challenges to doing so. Some of these challenges include how to consistently monitor and collect statistics, tracing, and another telemetry, how to add resiliency in the face of unexpected failure, how to do powerful feature routing and much more.
Istio and service mesh in general help developers solve this in a non-invasive way.
In this session, we’ll show how you can take advantage of these capabilities in an incremental way. We expect most developers haven’t adequately solved for these issues, so we’ll take it to step by step and build up a strong understanding of Istio, how to get quick wins, and harness its power in your production services architecture.
GraalVM: Run Programs Faster Everywhere
GraalVM is a high-performance runtime for dynamic, static, and native languages. GraalVM supports Java, Scala, Kotlin, Groovy, and other JVM-based languages. At the same time, it can run the dynamic scripting languages JavaScript including node.js, Ruby, R, and Python. In this session we'll talk about the performance boost you can get from running your code on GraalVM, look at the examples of running typical web-applications with it, enhancing them with code in other languages, creating native images for incredibly fast startup and low memory overhead for your services. GraalVM offers you the opportunity to write the code in the language you want, and run the resulting program really fast.
Continuous delivery in the real world
More and more IT organizations are taking the step to Continuous Delivery instead of thinking in sprints or releases. It’s an important investment, and it opens a world of tangible opportunities. In this talk, we’ll see how the ability to deploy individual features influences the way we work, design applications, and perform as an organisation.
Free the Functions with Fn project!
“Serverless” is the hottest ticket in town right now.
But many serverless platforms restrict your choice of language and / or dictate where your code runs.
In this talk, I’ll describe how we can go to the serverless ball with open source and the Fn project in particular.
“Serverless” aims to improve developer productivity by abstracting, underlying infrastructure layers. The servers are still there, but you just can’t see them.
This abstraction allows the developer to focus solely on the functions that deliver value to the business and not on the plumbing.
The economics of serverless are also interesting since you only consume resources when your functions run, rather than having applications running continually waiting to server requests.
Sadly some leading serverless platforms are not open and restrict choice in terms of: - language - deployment
In this talk, I want to show how you can do serverless development with your choice of language, and deployment location.
Presentation Summary
The evolution of “serverless”
Functions as a Service (FaaS)
open source serverless frameworks
The Fn project (see http://fnproject.io)
Fn functions
building
managing state
logging
FDKs (Function Development Kits)
How we can link individual functions together to create serverless applications
Building an example serverless application with Fn.
Leveraging AI for facilitating refugee integration
Today's world counts more than 20 million refugees, including over 1 million refugees resettled in Europe as a result of the ongoing Syrian civil war. When fleeing conflicts, refugees risk their lives with the hope of building a better future for themselves. However, upon resettling in a new country, refugees struggle to easily find the opportunities available to them and to filter the ones that are the most relevant to their profile and current context.
In this talk, we explain how AI can be leveraged to connect refugees in real-time and in a customized way to the opportunities that will accelerate the most their integration, bringing them a step forward towards the better future they strive to build for themselves.
An intro to Kubernetes operators
An Operator is an application that encodes the domain knowledge of the application and extends the Kubernetes API through custom resources. They enable users to create, configure, and manage their applications. Operators have been around for a while now, and that has allowed for patterns and best practices to be developed.
In this talk, Lili will explain what operators are in the context of Kubernetes and present the different tools out there to create and maintain operators over time. She will end by demoing the building of an operator from scratch, and also using the helper tools available out there.
Cyaniclab : Software Development Agency Portfolio.pdf
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Designing for Privacy in Amazon Web Services
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
More Related Content
More from J On The Beach
Streaming to a New Jakarta EE
The world is moving from a model where data sits at rest, waiting for people to make requests of it, to where data is constantly moving and streams of data flow to and from devices with or without human interaction. Decisions need to be made based on these streams of data in real-time, models need to be updated, and intelligence needs to be gathered. In this context, our old-fashioned approach of CRUD REST APIs serving CRUD database calls just doesn't cut it. It's time we moved to a stream-centric view of the world.
The TIPPSS Imperative for IoT - Ensuring Trust, Identity, Privacy, Protection...
Our increasingly connected world leveraging the Internet of Things (IoT) creates great value, in connected healthcare, smart cities, and more. The increasing use of IoT also creates great risk. We will discuss the challenges and risks we need to address as developers in TIPPSS - Trust, Identity, Privacy, Protection, Safety, and Security - for devices, systems and solutions we deliver and use. Florence leads IEEE workstreams on clinical IoT and data interoperability with blockchain addressing TIPPSS issues. She is an author of IEEE articles on "Enabling Trust and Security - TIPPSS for IoT" and "Wearables and Medical Interoperability - the Evolving Frontier", "TIPPSS for Smart Cities" in the 2017 book "Creating, Analysing and Sustaining Smarter Cities: A Systems Perspective" , and Editor in Chief for an upcoming book on "Women Securing the Future with TIPPSS for IoT."
Pushing AI to the Client with WebAssembly and Blazor
Want to run your AI algorithms directly in the browser on the client-side? Now you can with WebAssembly and Blazor. Join us as we write code directly in WebAssembly. Then, we’ll look at Blazor and how you can use it, along with WebAssembly to run your tooling client side in the browser.
Want to run your AI algorithms directly in the browser on the client-side without the need for transpilers or browser plug-ins? Well, now you can with WebAssembly and Blazor. WebAssembly (WASM) is the W3C specification that will be used to provide the next generation of development tools for the web and beyond. Blazor is Microsoft’s experiment that allows ASP.Net developers to create web pages that do much of the scripting work in C# using WASM. Come join us as we learn to write code directly in WebAssembly’s human-readable format. Then, we’ll look at the current state of Blazor and how you can use it, along with WebAssembly to run your tooling client side in the browser.
Axon Server went RAFTing
RAFT protocol is a well-known protocol for consensus in Distributed Systems. Want to learn how consensus is achieved in a system with a large amount of data such as Axon Server’s Event Store? Join this talk to hear about all specifics regarding data replication in highly available Event Store!
Axon is a free and open source Java framework for writing Java applications following DDD, event sourcing, and CQRS principles. While especially useful in a microservices context, Axon provides great value in building structured monoliths that can be broken down into microservices when needed.
Axon Server is a messaging platform specifically built to support distributed Axon applications. One of its key benefits is storing events published by Axon applications. In not so rare cases, the number of these events is over millions, even billions. Availability of Axon Server plays a significant role in the product portfolio. To keep event replication reliable we chose RAFT protocol for consensus implementation of our clustering features.
In short, consensus involves multiple servers agreeing on values. Once they reach a decision on a value, that decision is final. Typical consensus algorithms make progress when any majority of their servers is available; for example, a cluster of 5 servers can continue to operate even if 2 servers fail. If more servers fail, they stop making progress (but will never return an incorrect result).
Join this talk to learn why we chose RAFT; what were our findings during the design, the implementation, and testing phase; and what does it mean to replicate an event store holding billions of events!
The Six Pitfalls of building a Microservices Architecture (and how to avoid t...
Thinking of moving to Microservices? Watch out! That quest is full of traps, social traps. If you are not able to handle it, you may be blocked by meetings, frustration, endless challenges that will make you miss the monolith. In this talk, I share my experience and mistakes, so you can avoid them.
Creating or migrating to a Microservices architecture might easily become a big mess, not only due to technical challenges but mostly because of human factors: it’s a major change in the software culture of a company. In this talk, I’ll share my past experience as the technical lead of an ambitious Microservices-based product, I’ll go through the parts we struggled with, and give you some advice on how to deal with what I call the Six Pitfalls:
The Common Patterns Phobia
The Book Club Cult
The Never-Decoupled Story
The Buzz Words Syndrome
The Agile Trap
The Conway’s Law Hackers
Madaari : Ordering For The Monkeys
Instead of randomly injecting faults ( i.e. Chaos Monkey), what if we could order our experiments to perform min number of experiments for maximum yield? We present a solution(& results) to the problem of experiment selection using Lineage Driven Fault Injection to reduce the search space of faults.
Lineage Driven Fault Injection (LDFI) is a state of the art technique in chaos engineering experiment selection. LDFI since its inception has used an SAT solver under the hood which presents solutions to the decision problem (which faults to inject) in no particular order. As SRE’s we would like to perform experiments that reveal the bugs that the customers are most likely to hit first. In this talk, we present new improvements to LDFI that orders the experiment suggestions.
In the first the half of the talk we will show LDFI is a technique that can be widely used within an enterprise. We present the motivation for ordering the chaos experiments along with some prioritization we utilized while conducting the experiments. We also highlight how ordering is a general purpose technique that we can use to encode the peculiarities of a heterogeneous microservices architecture. LDFI can work in an enterprise by harnessing the observability infrastructure to model the redundancy of the system.
Next, we present experiments conducted within our organization using ordered LDFI and some preliminary results. We show examples of services where we discovered bugs, and how carefully controlling the order of experiments allowed LDFI to avoid running unnecessary experiments. We also present an example of an application where we declared the service shippable under crash stop model. We also present a comparison with Chaos Monkey and show how LDFI found the known bugs in a given application using orders of magnitude fewer experiments than a random fault injection tool like Chaos Monkey.
Finally, we discuss how we plan to take LDFI forward. We discuss open problems and possible solutions for scalarizing probabilities of failure, latency injection, integration with service mesh technologies like envoy for fine-grained fault injection, fault injection for stateful systems.
Key takeaways: 1) Understand how LDFI can be integrated in the enterprise by harnessing the observability infrastructure. 2) Limitations of LDFI w.r.t unordered solutions and why ordering matters for chaos engineering experiments. 3) Preliminary results of prioritized LDFI and a future direction for the community.
Servers are doomed to fail
Complexity in systems should be defeated if it is possible to do. But the default nature of our computer systems are complex and servers are doomed to fail. In this talk, we will go through new approaches in modern architectures to design and evaluate new computer systems.
Interaction Protocols: It's all about good manners
Distributed systems collaborate to achieve collective goals via a system of rules. Rules that affords good hygiene, fault tolerance, effective communication and trusted feedback. These rules form protocols which enable the system to achieve its goals.
Distributed and concurrent systems can be considered a social group that collaborates to achieve collective goals. In order to collaborate a system of rules must be applied, that affords good hygiene, fault tolerance, and effective communication to coordinate, share knowledge, and provide feedback in a polite trusted manner. These rules form a number of protocols which enable the group to act as a system which is greater than the sum of the individual components.
In this talk, we will explore the history of protocols and their application when building distributed systems.
A race of two compilers: GraalVM JIT versus HotSpot JIT C2. Which one offers ...
Do you want to check the efficiency of the new, state of the art, GraalVM JIT Compiler in comparison to the old but mostly used JIT C2? Let’s have a side by side comparison from a performance standpoint on the same source code.
The talk reveals how traditional Just In Time Compiler (e.g. JIT C2) from HotSpot/OpenJDK internally manages runtime optimizations for hot methods in comparison to the new, state of the art, GraalVM JIT Compiler on the same source code, emphasizing all of the internals and strategies used by each Compiler to achieve better performance in most common situations (or code patterns). For each optimization, there is Java source code and corresponding generated assembly code in order to prove what really happens under the hood.
Each test is covered by a dedicated benchmark (JMH), timings and conclusions. Main topics of the agenda: - Scalar replacement - Null Checks - Virtual calls - Lock coarsening - Lock elision - Virtual calls - Scalar replacement - Lambdas - Vectorization (few cases)
The tools used during my research study are JITWatch, Java Measurement Harness, and perf. All test scenarios will be launched against the latest official Java release (e.g. version 11).
Leadership at every level
Leadership is easy when you're a manager, or an expert in a field, or a conference speaker! In a Kanban organisation, though, we "encourage acts of leadership at every level". In this talk, we look at what it means to be a leader in the uncertain, changing and high-learning environment of software development. We learn about the importance of safety in encouraging others to lead and follow, and how to get that safety using both technical and human practices; the necessity of a clear, compelling vision and provision of information on how we're achieving it; and the need to be able to ask awkward and difficult questions... especially the ones without easy answers.
Machine Learning: The Bare Math Behind Libraries
During this presentation, we will answer how much you’ll need to invest in a superhero costume to be as popular as Superman. We will generate a unique logo which will stand against the ever popular Batman and create new superhero teams. We shall achieve it using linear regression and neural networks.
Machine learning is one of the hottest buzzwords in technology today as well as one of the most innovative fields in computer science – yet people use libraries as black boxes without basic knowledge of the field. In this session, we will strip them to bare math, so next time you use a machine learning library, you’ll have a deeper understanding of what lies underneath.
During this session, we will first provide a short history of machine learning and an overview of two basic teaching techniques: supervised and unsupervised learning.
We will start by defining what machine learning is and equip you with an intuition of how it works. We will then explain the gradient descent algorithm with the use of simple linear regression to give you an even deeper understanding of this learning method. Then we will project it to supervised neural networks training.
Within unsupervised learning, you will become familiar with Hebb’s learning and learning with concurrency (winner takes all and winner takes most algorithms). We will use Octave for examples in this session; however, you can use your favourite technology to implement presented ideas.
Our aim is to show the mathematical basics of neural networks for those who want to start using machine learning in their day-to-day work or use it already but find it difficult to understand the underlying processes. After viewing our presentation, you should find it easier to select parameters for your networks and feel more confident in your selection of network type, as well as be encouraged to dive into more complex and powerful deep learning methods.
Getting started with Deep Reinforcement Learning
Reinforcement Learning is a hot topic in Artificial Intelligence (AI) at the moment with the most prominent example of AlphaGo Zero. It shifted the boundaries of what was believed to be possible with AI. In this talk, we will have a look into Reinforcement Learning and its implementation.
Reinforcement Learning is a class of algorithms which trains an agent to act optimally in an environment. The most prominent example is AlphaGo Zero, where the agent is trained to place tokens on the board of Go in order to win the game. AlphaGo Zero has won against the world champion which was thought to be impossible at that time. This was enabled by combining Reinforcement Learning with Deep Neural Networks and is today known as Deep Reinforcement Learning. This has shifted the frontier of Artificial Intelligence and enabled multiple complex use cases, among them controlling the cooling devices in the server rooms by google. Applying Deep Reinforcement Learning saved them several million in power costs. In this talk, we will understand the basics of Deep Reinforcement Learning and implement a simple example. We will have a look at OpenAIs gym which is the defacto standard for Reinforcement Learning environments. This will enable the audience to implement both an environment and Reinforcement Learning agent on their own.
Toward Predictability and Stability At The Edge Of Chaos
As we edge towards larger, more complex and decoupled systems, combined with the continual growth of the global information graph, our frontiers of unsolved challenges grow equally as fast. Central challenges for distributed systems include persistence strategies across DCs, zones or regions, network partitions, data optimization, system stability in all phases.
How does leveraging CRDTs and Event Sourcing address several core distributed systems challenges? What are useful strategies and patterns involved in the design, deployment, and running of stateful and stateless applications for the cloud, for example with Kubernetes. Combined with code samples, we will see how Akka Cluster, Multi-DC Persistence, Split Brain, Sharding and Distributed Data can help solve these problems.
Numeric programming with spire
Spire is a Scala library for fast, generic, and precise numerics. It allows us to write generic numeric algorithms, provides the ‘number tower’ and offers a lot of utilities you didn’t know you needed.
Numeric programming is a notoriously difficult topic. For number crunching, e.g. solving systems of linear equations, we need raw performance. However, using floating-point numbers may lead to inaccurate results. On top of that, in functional programming, we’d really like to abstract over concrete number types, which is where abstract algebra comes into play. This interplay between abstract and concrete and the fact that everything needs to run on finite hardware is what makes good library support necessary for writing fast & correct programs. Spire is such a library in the Typelevel Scala ecosystem. This talk will be an introduction to Spire, showcasing the ‘number tower’, real-ish numbers and how to obey the law.
Istio Service Mesh & pragmatic microservices architecture
We have been celebrating 2018 as the Year of the Service Mesh, where an open source effort known as Istio has taken and changed how we design and release our applications.
As we start to go toward cloud-native infrastructure and build our applications out of microservices, we must fully face the drawbacks and challenges to doing so. Some of these challenges include how to consistently monitor and collect statistics, tracing, and another telemetry, how to add resiliency in the face of unexpected failure, how to do powerful feature routing and much more.
Istio and service mesh in general help developers solve this in a non-invasive way.
In this session, we’ll show how you can take advantage of these capabilities in an incremental way. We expect most developers haven’t adequately solved for these issues, so we’ll take it to step by step and build up a strong understanding of Istio, how to get quick wins, and harness its power in your production services architecture.
GraalVM: Run Programs Faster Everywhere
GraalVM is a high-performance runtime for dynamic, static, and native languages. GraalVM supports Java, Scala, Kotlin, Groovy, and other JVM-based languages. At the same time, it can run the dynamic scripting languages JavaScript including node.js, Ruby, R, and Python. In this session we'll talk about the performance boost you can get from running your code on GraalVM, look at the examples of running typical web-applications with it, enhancing them with code in other languages, creating native images for incredibly fast startup and low memory overhead for your services. GraalVM offers you the opportunity to write the code in the language you want, and run the resulting program really fast.
Continuous delivery in the real world
More and more IT organizations are taking the step to Continuous Delivery instead of thinking in sprints or releases. It’s an important investment, and it opens a world of tangible opportunities. In this talk, we’ll see how the ability to deploy individual features influences the way we work, design applications, and perform as an organisation.
Free the Functions with Fn project!
“Serverless” is the hottest ticket in town right now.
But many serverless platforms restrict your choice of language and / or dictate where your code runs.
In this talk, I’ll describe how we can go to the serverless ball with open source and the Fn project in particular.
“Serverless” aims to improve developer productivity by abstracting, underlying infrastructure layers. The servers are still there, but you just can’t see them.
This abstraction allows the developer to focus solely on the functions that deliver value to the business and not on the plumbing.
The economics of serverless are also interesting since you only consume resources when your functions run, rather than having applications running continually waiting to server requests.
Sadly some leading serverless platforms are not open and restrict choice in terms of: - language - deployment
In this talk, I want to show how you can do serverless development with your choice of language, and deployment location.
Presentation Summary
The evolution of “serverless”
Functions as a Service (FaaS)
open source serverless frameworks
The Fn project (see http://fnproject.io)
Fn functions
building
managing state
logging
FDKs (Function Development Kits)
How we can link individual functions together to create serverless applications
Building an example serverless application with Fn.
Leveraging AI for facilitating refugee integration
Today's world counts more than 20 million refugees, including over 1 million refugees resettled in Europe as a result of the ongoing Syrian civil war. When fleeing conflicts, refugees risk their lives with the hope of building a better future for themselves. However, upon resettling in a new country, refugees struggle to easily find the opportunities available to them and to filter the ones that are the most relevant to their profile and current context.
In this talk, we explain how AI can be leveraged to connect refugees in real-time and in a customized way to the opportunities that will accelerate the most their integration, bringing them a step forward towards the better future they strive to build for themselves.
An intro to Kubernetes operators
An Operator is an application that encodes the domain knowledge of the application and extends the Kubernetes API through custom resources. They enable users to create, configure, and manage their applications. Operators have been around for a while now, and that has allowed for patterns and best practices to be developed.
In this talk, Lili will explain what operators are in the context of Kubernetes and present the different tools out there to create and maintain operators over time. She will end by demoing the building of an operator from scratch, and also using the helper tools available out there.
More from J On The Beach (20)
The TIPPSS Imperative for IoT - Ensuring Trust, Identity, Privacy, Protection...
The TIPPSS Imperative for IoT - Ensuring Trust, Identity, Privacy, Protection...
Pushing AI to the Client with WebAssembly and Blazor
Pushing AI to the Client with WebAssembly and Blazor
The Six Pitfalls of building a Microservices Architecture (and how to avoid t...
The Six Pitfalls of building a Microservices Architecture (and how to avoid t...
Interaction Protocols: It's all about good manners
Interaction Protocols: It's all about good manners
A race of two compilers: GraalVM JIT versus HotSpot JIT C2. Which one offers ...
A race of two compilers: GraalVM JIT versus HotSpot JIT C2. Which one offers ...
Toward Predictability and Stability At The Edge Of Chaos
Toward Predictability and Stability At The Edge Of Chaos
Istio Service Mesh & pragmatic microservices architecture
Istio Service Mesh & pragmatic microservices architecture
Leveraging AI for facilitating refugee integration
Leveraging AI for facilitating refugee integration
Recently uploaded
Cyaniclab : Software Development Agency Portfolio.pdf
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Designing for Privacy in Amazon Web Services
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
How to Position Your Globus Data Portal for Success Ten Good Practices
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.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...
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).
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...
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/How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?
Worried about document security while sharing them in Salesforce? Fret no more! Here are the top-notch security standards XfilesPro upholds to ensure strong security for your Salesforce documents while sharing with internal or external people.
To learn more, read the blog: https://www.xfilespro.com/how-does-xfilespro-make-document-sharing-secure-and-seamless-in-salesforce/
BoxLang: Review our Visionary Licenses of 2024
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
2024 RoOUG Security model for the cloud.pptx
How we've evolved the MySQL server security model from a single DBA to the cloud.
Corporate Management | Session 3 of 3 | Tendenci AMS
Corporate Management | Session 3 of 3 | Tendenci AMSTendenci - The Open Source AMS (Association Management Software)
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/eventsLarge Language Models and the End of Programming
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
How Recreation Management Software Can Streamline Your Operations.pptx
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Understanding Globus Data Transfers with NetSage
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Lecture 1 Introduction to games development
Software engineering
Game Development
unity Game Development
Globus Compute Introduction - GlobusWorld 2024
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.
Strategies for Successful Data Migration Tools.pptx
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
De mooiste recreatieve routes ontdekken met RouteYou en FME
FME Innovation Day - presented by Nordend.
"De mooiste recreatieve routes ontdekken met RouteYou en FME." door Kevin Baker
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
SOCRadar Research Team: Latest Activities of IntelBroker
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
Recently uploaded (20)
Cyaniclab : Software Development Agency Portfolio.pdf
Cyaniclab : Software Development Agency Portfolio.pdf
How to Position Your Globus Data Portal for Success Ten Good Practices
How to Position Your Globus Data Portal for Success Ten Good Practices
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...
How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?
How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?
Corporate Management | Session 3 of 3 | Tendenci AMS
Corporate Management | Session 3 of 3 | Tendenci AMS
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...
How Recreation Management Software Can Streamline Your Operations.pptx
How Recreation Management Software Can Streamline Your Operations.pptx
Strategies for Successful Data Migration Tools.pptx
Strategies for Successful Data Migration Tools.pptx
De mooiste recreatieve routes ontdekken met RouteYou en FME
De mooiste recreatieve routes ontdekken met RouteYou en FME
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...
SOCRadar Research Team: Latest Activities of IntelBroker
SOCRadar Research Team: Latest Activities of IntelBroker