Anton Boyko "The future of serverless computing"
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Are you still planning your servers capacity in CPU and RAM? Do you enjoy answering questions like “what amount of servers we need to buy to serve 10K and 10M users”? Do you enjoy paying for those servers while they are sitting idle? In my session I will talk about the current state and the future of serverless computing. I will show several demos that show how to start using serverless computing, what are the application scenarios for it, how it can scale, what it will cost, etc. This session will be useful for developers and architects who are seeking a way to create an app utilizing all your previous skills, but make it scalable, reliable, fast and cost efficient.
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This talk wants to sum up the experience of designing, deploying and maintaining an Erlang application targeting the cloud and precisely AWS as hosting infrastructure.
As the application now serves a significantly large user base with a sustained throughput of thousands of games actions per second we're able to analyse retrospectively our engineering and architectural choices and see how Erlang fits in the cloud environment also comparing it to previous experiences of clouds deployments of other platforms.
We'll discuss properties of Erlang as a language and OTP as a framework and how we used them to design a system that is a good cloud citizen. We'll also discuss topics that are still open for a solution.
Erlang and the Cloud: A Fractal Approach to Throughput
This document summarizes a talk about building scalable systems for the cloud using Erlang. The speaker discusses how Erlang processes with local state (gen_servers) can act as units of throughput that can be composed across cloud computing instances to scale applications. By treating each gen_server as an independent unit of throughput, systems can leverage the elastic computing resources of the cloud in a loosely coupled way to easily scale up as more instances are added. In contrast to traditional monolithic architectures, this approach allows for fractal-like scaling where the overall structure remains similar at different scales.
Getting Started with Serverless Architectures
Serverless architectures let you build and deploy applications and services with infrastructure resources that require zero administration. In the past, you had to provision and scale servers to run your application code, install and operate distributed databases, and build and run custom software to handle API requests. Now, AWS provides a stack of scalable, fully-managed services that eliminates these operational complexities.
In this session, you will learn about the benefits of serverless architectures and the basics of the serverless stack AWS provides. We will also walk through how you can use serverless architectures for everything from data processing to mobile and web backends.
AWS DevDay San Francisco, June 21, 2016.
Presenter: Jeremy Edberg, Co-Founder, CloudNative, & AWS Community Hero
Deep Dive on Delivering Amazon EC2 Instance Performance
Amazon EC2 provides a broad selection of instance types to deliver high performance for a diverse mix of applications. In this session, we overview the drivers of system performance and discuss in depth how Amazon EC2 instances deliver system performance while also providing elasticity and complete control over your infrastructure. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Scaling habits of ASP.NET
The document discusses the scaling habits of ASP.NET applications over multiple versions from initial launch to large-scale business success. As an application grows from version 1 with a few users to version N with thousands of users, the key scaling challenges change from fixing logical problems to addressing performance bottlenecks and high availability requirements. The solutions also evolve from simple code optimizations to sophisticated architectures with load balancing, caching, and separate servers for web and database tiers.
AWS Summit London 2014 | Introduction to Amazon EC2 (100)
This document is an introduction to Amazon EC2 presented by Ian Massingham on April 30, 2014. It provides an overview of EC2's key functionality and growth over the past 7 years. EC2 allows users to provision compute capacity in the cloud and pay only for what they use. It offers choices for instance types, operating systems, storage options, and pricing models to meet different use cases. EC2 provides scalability, reliability, security, and cost savings compared to on-premises infrastructure.
Cloud Connected Devices on a Global Scale (CPN303) | AWS re:Invent 2013
Increasingly, mobile and other connected devices are leveraging the scalability and capabilities of the cloud to deliver services to end users. However, connecting these devices to the cloud presents unique challenges. Resource constraints make it impossible to use many common frameworks and transport restrictions make it difficult to use dynamic cloud resources. In this session, learn how you can develop and deploy highly-scalable global solutions using Amazon Web Services (Amazon Virtual Private Cloud, Elastic IP addresses, Amazon Route 53, Auto Scaling) and tools like Puppet. Hear how Panasonic and Banjo architect their cloud infrastructure from both a start-up and enterprise perspective.
How to Reduce your Spend on AWS
This document discusses how to reduce spending on AWS through various techniques:
1. Paying for cloud resources only when they are used through the pay-as-you-go model avoids upfront costs and allows turning off unused capacity.
2. Using reserved instances when capacity needs are predictable provides significant discounts compared to on-demand pricing.
3. Architecting applications in a "cost aware" manner, such as leveraging caching, auto-scaling, managed services, and right-sizing instances can optimize costs.
4. Taking advantage of AWS's economies of scale through consolidated billing and free services helps lower overall spend. Planning workload usage of spot instances can achieve up to 85% savings.
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Serverless Computing with Azure Functions Best Practices
Serverless Computing with Azure Functions Best Practices
Sql Start! 2020 - SQL Server Lift & Shift su Azure
Sql Start! 2020 - SQL Server Lift & Shift su Azure
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Erlang as a cloud citizen, a fractal approach to throughput
Erlang as a cloud citizen, a fractal approach to throughput
Erlang and the Cloud: A Fractal Approach to Throughput
Erlang and the Cloud: A Fractal Approach to Throughput
Deep Dive on Delivering Amazon EC2 Instance Performance
Deep Dive on Delivering Amazon EC2 Instance Performance
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AWS Summit London 2014 | Introduction to Amazon EC2 (100)
Cloud Connected Devices on a Global Scale (CPN303) | AWS re:Invent 2013
Cloud Connected Devices on a Global Scale (CPN303) | AWS re:Invent 2013
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"What I learned through reverse engineering", Yuri Artiukh
In recent years, I have gained most of my knowledge through reverse engineering, how I did it and what I learned during this period, I decided to share. All this concerns graphic programming, performance, best practices in the frontend.
"Impact of front-end architecture on development cost", Viktor Turskyi
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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A common task in modern JS is parsing, validating and then comparing JSON objects. In this talk I will quickly go through most common ways to parse/validate and compare objects we use today and then focus more on how runtime types (based on io-ts) can help make such tasks easier and quicker to implement.
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Python engineers are introduced to the transformative potential of Large Language Models (LLMs) in the realm of advanced data analysis and the application of Semantic Kernel techniques. We will talk about how LLMs like ChatGPT can be integrated into Python environments to automate data processing, enhance predictive modeling, and unlock deeper insights from complex datasets. The session will delve into practical strategies for embedding Semantic Kernel methods within Python projects, illustrating how these advanced techniques can refine the accuracy of machine learning models by embedding domain-specific knowledge directly into the analysis process. Attendees will leave with a clear roadmap for leveraging the combined power of LLMs and Semantic Kernels, equipped with actionable knowledge to drive innovation in their data analysis projects and beyond, marking a significant leap forward in the evolution of Python engineering practices.
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Today, large language models are becoming an integral part of almost every IT solution. However, their use is often accompanied by certain limitations, such as the relevance of information or its depth and specificity. One of the ways to overcome these limitations is the method of working with LLMs - RAG (Retrieval Augmented Generation).
"Debugging python applications inside k8s environment", Andrii Soldatenko
In an ideal world, you would write Python code and then it would work perfectly. But unfortunately, it doesn't work in this manner. In my talk, I'll cover how to efficiently debug your programs, especially in cloud environments or inside Kubernetes.
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MLOps (Machine Learning Operations) is a recent buzzword, that trends a lot. Let's figure out together how maintaining applications with machine learning components is significantly different from maintaining applications without them.
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Ever seen a code base where understanding a simple method meant jumping through tangled class hierarchies? We all have! And while "Favor composition over inheritance!" is almost as old as object-oriented programming, strictly avoiding all types of subclassing leads to verbose, un-Pythonic code. So, what to do?
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The current architecture of Prom.ua is built on microservices and GraphQL API, but it was not always like that. In this talk, I'll tell you how far we've come and how we've made using graphs in a microservice architecture convenient and simple. I will talk about the problems we faced and how we overcame them, made our development process more accessible, deployments faster, and the remains of the monolith less loaded.
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ETL stands for extract, transform, load. It's a process that combines data from different sources into a single repository for further processing, analysis, and utilization.
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"How Ukrainian IT specialist can go on vacation abroad without crossing the T...
I’m confident that many IT professionals are currently facing the same situation I was in a few months ago. Mobilization, uncertainty. How can I be maximally beneficial to the country with my experience and continue professional development in such circumstances? Since the onset of the full-scale invasion, I've been actively volunteering and assisting the army. Mobilization became the next logical step.
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I aim to dispel myths about the mobilization process and projects of the Armed Forces. Address your questions
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The leader must be strong all the time. The leader cannot afford to make mistakes, let alone fail in front of their team. Is that really true? Nick Gicinto, a cybersecurity leader with over 25 years of experience, who has worked for the CIA and has built security systems from scratch at Tesla and Uber, fully hiring teams for these projects, will talk about the importance of being vulnerable to build trust within a team.
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Sharing open feedback can be difficult because it equals much work on yourself. However, feedback needs attention and a special place in the corporate culture. It helps to grow dynamically, build a team of like-minded people and achieve powerful results.
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A list of difficulties that prevent quality work with feedback.
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“Who do I aspire to become?”
Summarizing key points with a reference to a practical form you can download to use.
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This talk will reveal four destructive communication patterns that can undermine team spirit, reduce productivity and cause conflict, and offer effective strategies for neutralizing them.
Let's start with exciting storytelling about a fictional team of developers working on Scrum. You will learn about situations that their team member noticed during team meetings.
Next, we will analyze "The Gottman Four Horsemen" model, which describes the four "horsemen of the apocalypse" of work relationships: criticism, defensiveness, contempt, and stonewalling. For each of these patterns, specific "antidotes" will be offered that allow you to build healthier and more productive relationships in the team.
Finally, we'll look at why this topic is critical to team productivity, drawing on Google's "Project Aristotle" research. Special attention will be paid to the concept of psychological safety, which is a key factor in the success of high-performance teams.
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DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
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Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
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5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
OpenID AuthZEN Interop Read Out - Authorization
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Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
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Anton Boyko "The future of serverless computing"
- 1. The future of serverless computing Anton Boyko Microsoft Azure MVP
- 2. Serverless? Population of homeless servers is growing
- 3. They asked me for NoSQL, so I dropped the database. No database, NoSQL!
- 5. Benefits of serverless Manage less Micro-pricing Ease of scale (up & down)
- 6. Reserved Agent Job 1 Job 2 Job 3 Serverless Job 1 Job 2 Job 3 Agent 1 Agent 2 • Fixed CPU • Fixed RAM • On-demand CPU • On-demand RAM
- 7. Serverless offerings Microsoft Azure • Azure Functions • Azure Logic Apps • Azure Container Instances AWS • AWS Fargate • AWS Lambda Google cloud • Cloud Functions • Cloud Run
- 8. Azure Logic Apps Declarative integration between services.
- 9. Azure Container Instances Containers billed by amount of seconds they run.
- 10. Azure Functions Event-driven on-demand custom code execution.
- 12. Impediments Why aren’t we there yet?
- 13. Capacity What will it cost to run a serverless app for 10K users?
- 14. Capacity planning • Q: What will it cost to run a serverless app for 10K users? • A: How will you calculate what it will cost to run a non-serverless app? • A: What will it cost to wash all the windows in Seattle?
- 15. Capacity calculation example Facts • Each user spent 5 minutes on average on your website daily. • Each user reads 10 articles daily. • Each user generates 15 requests daily (10 articles + 5 utility requests). • Each request takes 1 second on average. Conclusions • Each user consumes 1 sec per request. • Each user consumes 15 secs per day. • Each user consumes 450 secs per month. • 10K users consumes 4.5M secs per month.
- 16. DurabilityHow to orchestrate workflows? Sagas?
- 17. Durability – fan out / fan in
- 19. Consumption example – fan out / fan in 1 sec 3 sec 3 sec 3 sec 2 sec 6 sec Orchestrate Fan out Fan in Response
- 20. Durability – long running async HTTP API
- 23. Durability – human interaction
- 25. Performance How to get predictable and consistent performance level?
- 26. Performance Consumption • 1 CPU core • Up to 1.5 Gb RAM • Cold start • Scale down to 0 instances Premium • Up to 4 CPU cores • Up to 14 Gb RAM • Pre-warmed instance • Scale down to 1 instance Azure Function Plan switcher https://aka.ms/premium-plan-sample Understanding serverless cold start https://azure.microsoft.com/en-us/blog/understanding-serverless-cold-start/
- 28. Performance – cold start
- 29. Performance – cold start
- 30. Conclusion
- 32. Questioning the question mark Anton Boyko Microsoft Azure MVP me@boykoant.pro