Convince your boss to go Serverless at serverless week Brazil

Arvind Sharma Global Head - Retail & CPG Vertical Ciklum AG Arvind has over 20 years of industry experience in leading the delivery of business transformation programs in a digital ecosystem. With strong business engagement and consulting credentials, he creates a climate of collaboration and knowledge sharing, ensuring talent, irrespective of the location, is aligned with business goals and demonstrating exceptional user experience, from conception through to the delivery. He is versatile and proficient at building trust and developing relationships, from field personnel to the C-suite.

Explainability for machine learning (ML) algorithms is essential when moving to production, but it’s notoriously difficult to achieve transparency and navigate changing regulations, like the EU’s new AI legislation. In this session, Seldon CEO Alex Housley dives into what recent legislation means for organisations deploying ML, how they can protect their deployments with powerful monitoring capabilities and what to consider when building a robust ML deployment pipeline. With the support of real-world use cases, Alex also gives a practical guide to approaching deployment responsibly, and how to bake monitoring into ML pipelines to minimise risk and future-proof organisations.

This document discusses monitoring Citrix environments with eG Enterprise. It describes how eG Enterprise integrates with Citrix NetScaler/ADC to monitor every layer from code to bare metal across public, private and hybrid clouds. The presentation demonstrates how eG Enterprise provides visibility into Citrix environments, NetScaler appliances, user sessions, and geo-specific troubleshooting. It highlights the importance of NetScaler monitoring and common NetScaler problems. Dashboards, alerts, and mobile apps are shown to provide actionable insights for improved digital experiences.

The Briefing Room with Dr. Robin Bloor and Actian Live Webcast July 14, 2015 Watch the Archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=bbd4395ea2f8c60a03cfefc68c7aa823 Innovation often implies risk, which is why businesses have many issues to weigh when considering change. Yet the remarkable growth of data is driving many traditional systems into the ground, forcing information workers to take a critical look at their existing tools. Technologies like Hadoop offer economical solutions to big data management, but to truly take advantage of its capabilities, organizations must modernize their infrastructure. Register for this episode of The Briefing Room to learn from veteran Analyst Dr. Robin Bloor as he explains how and why organizations should improve legacy systems. He’ll be briefed by Todd Untrecht of Actian, who will tout his company’s Actian Vortex, a SQL-in-Hadoop solution. He will show how integrating a SQL engine directly in the Hadoop cluster can lead to faster analytics and greater control, while still maintaining existing investments. Visit InsideAnalysis.com for more information.

Maintaining a relevant and meaningful roadmap while adopting a state of the art Agile methodology is challenging and somewhat antonymous. This presentation proposes a framework for designing and maintaining an Agile Roadmap.

This document summarizes the benefits of PlanGrid, a construction project management app. It highlights how PlanGrid allows teams to access the latest plans and documents in real-time, reducing time wasted searching for information. It claims PlanGrid saves time and money by avoiding rework through better coordination and issue tracking. Customer testimonials praise how PlanGrid streamlines processes and keeps teams connected in the field and office.

Amit Kumar and Amit Anand discuss digital transformation at an enterprise using a 2 speed IT approach. They describe challenges faced including resistance to change and outdated architectures. Their solution was to create an elite development team using agile practices, innovation-ready architecture, and DevOps. This allowed for weekly releases and one-click deployments. It improved conversion rates, reduced time to market, and increased productivity.

The goal of Serverless is to focus on writing the code that delivers business value and offload everything else to your trusted partners (like Cloud providers or SaaS vendors). You want to iterate quickly and today’s code quickly becomes tomorrow’s technical debt. In this talk we will show why Serverless adoption increases the developer productivity and how to measure it. We will also go through AWS Serverless architectures where you only glue together different Serverless managed services relying solely on configuration, minimizing the amount of the code written.

The goal of Serverless is to focus on writing the code that delivers business value and offload everything else to your trusted partners (like Cloud providers or SaaS vendors). You want to iterate quickly and today’s code quickly becomes tomorrow’s technical debt. In this talk we will show why Serverless adoption increases the developer productivity and how to measure it. We will also go through AWS Serverless architectures where you only glue together different Serverless managed services relying solely on configuration, minimizing the amount of the code written.

This document discusses increasing developer productivity through serverless computing. It begins by outlining various types of cognitive load on developers and how serverless can help minimize extraneous load. It then discusses how technical debt and inability to evolve can reduce productivity. Serverless is presented as helping reduce technical debt through writing less code and fewer dependencies. The total cost of ownership advantages of serverless are covered, including no infrastructure maintenance, built-in auto-scaling, ability to do more with fewer resources, lower technical debt, and faster time to market. Best practices like evolutionary architecture, DevOps, and chaos engineering are discussed for effectively leveraging serverless. Recent improvements to serverless offerings from AWS are summarized.

The goal of Serverless is to focus on writing the code that delivers business value and offload everything else to your trusted partners (like Cloud providers or SaaS vendors). You want to iterate quickly and today’s code quickly becomes tomorrow’s technical debt. In this talk we will show why Serverless adoption increases the developer productivity and how to measure it. We will also go through AWS Serverless architectures where you only glue together different Serverless managed services relying solely on configuration, minimizing the amount of the code written.

The goal of Serverless is to focus on writing the code that delivers business value and offload everything else to your trusted partners (like Cloud providers or SaaS vendors). You want to iterate quickly and today’s code quickly becomes tomorrow’s technical debt. In this talk we will show why Serverless adoption increases the developer productivity and how to measure it. We will also go through AWS Serverless architectures where you only glue together different Serverless managed services relying solely on configuration, minimizing the amount of the code written.

The purpose of Serverless is to focus on writing the code that delivers business value and offload undifferentiated heavy lifting to the Cloud providers or SaaS vendors of your choice. Today’s code quickly becomes tomorrow’s technical debt even if you meet the perfect decision. The less you own, the better it is from the maintainability point of view. In this talk I will go through examples of the various Serverless architectures on AWS where you glue together different Serverless managed services relying mostly on configuration, significantly reducing the amount of the code written to perform the task. Own less, build more!

The purpose of Serverless is to focus on writing the code that delivers business value and offload undifferentiated heavy lifting to the Cloud providers or SaaS vendors of your choice. Today’s code quickly becomes tomorrow’s technical debt even if you meet the perfect decision. The less you own, the better it is from the maintainability point of view. In this talk I will go through examples of the various Serverless architectures on AWS where you glue together different Serverless managed services relying mostly on configuration, significantly reducing the amount of the code written to perform the task. Own less, build more!

The purpose of Serverless is to focus on writing the code that delivers business value and offload undifferentiated heavy lifting to the Cloud providers or SaaS vendors of your choice. Today’s code quickly becomes tomorrow’s technical debt even if you meet the perfect decision. The less you own, the better it is from the maintainability point of view. In this talk I will go through examples of the various Serverless architectures on AWS where you glue together different Serverless managed services relying mostly on configuration, significantly reducing the amount of the code written to perform the task. Own less, build more!

TCO of Serverless application. How Serverless helps us to be productive, write less code and implement evolutionary architectures. How to measure productivity to see you're on track with Serverless

The purpose of Serverless is to focus on writing the code that delivers business value and offload undifferentiated heavy lifting to the Cloud providers or SaaS vendors of your choice. Today’s code quickly becomes tomorrow’s technical debt even if you meet the perfect decision. The less you own, the better it is from the maintainability point of view. In this talk I will go through examples of the various Serverless architectures on AWS where you glue together different Serverless managed services relying mostly on configuration, significantly reducing the amount of the code written to perform the task. Own less, build more!

When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.

Slides from my talk at ConFoo Montreal, February 2016. A presentation on how to apply configuration management (CM) principles for your various environments, to control changes made to them. You apply CM on your code, why not on your environments content? This presentation will present the infrastructure as code principles using Chef and/or Ansible. Topics discussed include Continuous Integration, Continuous Delivery/Deployment principles, Infrastructure As Code and DevOps.

SaaS architectures can be deployed onto AWS in a number of ways, and each optimizes for different factors from security to cost optimization. Come learn more about common deployment models used on AWS for SaaS architectures and how each of those models are tuned for customer specific needs. We will also review options and tradeoffs for common SaaS architectures, including cost optimization, resource optimization, performance optimization, and security and data isolation.

Migrations of existing enterprise applications to the cloud can be complex. There are no migration methodologies or magic bullets that enable a simple lift and shift or automated migration. Typical migration projects take a great deal of discovery work, re-architecture, and refactoring. In this session, we will share known challenges and considerations that must be accounted for when designing, planning, and executing a migration. Topics will include: scale-out and distributed architectures, geographic dispersion, leveraging existing cloud services, and logging & monitoring. In addition, this session will address how in-depth discovery efforts can be paired with configuration management, automation, and source control to minimize the risk of future technical debt. Finally, we’ll cover the business and technical factors the affect the complexity of application refactoring.

Migrations of existing enterprise applications to the cloud can be complex. There are no migration methodologies or magic bullets that enable a simple lift and shift or automated migration. Typical migration projects take a great deal of discovery work, re-architecture, and refactoring. In this session, we will share known challenges and considerations that must be accounted for when designing, planning, and executing a migration. Topics will include: scale-out and distributed architectures, geographic dispersion, leveraging existing cloud services, and logging & monitoring. In addition, this session will address how in-depth discovery efforts can be paired with configuration management, automation, and source control to minimize the risk of future technical debt. Finally, we’ll cover the business and technical factors the affect the complexity of application refactoring.

The document discusses how DevOps practices can help organizations operate at hyper scale with AWS. It notes that software delivery has changed and disruption is faster than ever. It outlines some key DevOps tools needed like CI/CD pipelines for managing releases, testing, and deploying applications. The document discusses how Amazon transformed its development practices using microservices and pipelines to allow for faster delivery. It provides examples of how other companies have benefited from DevOps. Finally, it highlights some key AWS services that can help with DevOps practices like monitoring, infrastructure as code, and continuous integration/delivery pipelines.

Modelos de Cloud Computing - IAAS - PAAS . SAAS - Arquitecturas Serverless- Nubes Privadas y Públicas - Estrategias Híbridas

hen we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.

When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.

Presentazione dello speech tenuto da Carmine Spagnuolo (Postdoctoral Research Fellow - Università degli Studi di Salerno/ ACT OR) dal titolo "Technology insights: Decision Science Platform", durante il Decision Science Forum 2019, il più importante evento italiano sulla Scienza delle Decisioni.

ip.labs is the world's leading white label e-commerce software imaging company and processes millions of images every day. The workflows of our users consist of designing, saving, loading, ordering and delivering to the printing facilities the photo products like prints, photobooks, calendars, gift products among others. In this talk we'll explore the challenges of our previous solution based on ALB, EC2, EBS and EFS, our motivation and architecture behind the reimplementation of our image storage solution based on AWS Serverless services like API Gateway, Lambda, DynamoDB, SQS, SNS, EventBridge and others, benefits that we've got with this new solution but also challenges we needed to overcome and trade-offs we had to make.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.

In this talk, we’ll use a standard serverless application that uses API Gateway, Lambda, DynamoDB, SQS, Step Functions (and other AWS-managed services). We'll explore how Amazon DevOps Guru recognizes operational issues and anomalies like increased latency and error rates (timeouts, throttling, and resource limits) and integrate DevOps Guru with PagerDuty to provide even better incident management. Amazon DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. The service uses pre-trained ML models that are able to identify spikes in application requests, so it knows when to alert and when not to.

There is a misunderstanding that everything is possible with the Serverless Services in AWS. For example, the misunderstanding that your Lambda function may scale without limitations. But each AWS service (not only Serverless) has a big list of quotas that everybody needs to be aware of, understand, and take into account during the development. In this talk, I'll explain the most important quotas (in terms of scaling, but not only that) of Serverless services like API Gateway, Lambda, DynamoDB, SQS, and Aurora Serverless and how to architect your solution with these quotas in mind.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times which may heavily impact the latencies of your application. But the times change: Community and AWS as a cloud providers improve things steadily for Java developers. In this talk we look at the best practices, features and possibilities AWS offers for the Java developers to reduce the cold start times like GraalVM Native Image and AWS Lambda SnapStart based on CRaC (Coordinated Restore at Checkpoint) project.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times which may heavily impact the latencies of your application. But the times change: Community and AWS as a cloud providers improve things steadily for Java developers. In this talk we look at the best practices, features and possibilities AWS offers for the Java developers to reduce the cold start times like GraalVM Native Image and AWS Lambda SnapStart based on on FirecrackerVM snapshot and CRaC (Coordinated Restore at Checkpoint) project.

This document summarizes Amazon CodeCatalyst and DevOps Guru, which help revolutionize the DevOps lifecycle. Amazon CodeCatalyst allows developers to create serverless projects that include code, development environments, CI/CD pipelines, and issue/report tracking. DevOps Guru uses machine learning to detect operational issues in services like DynamoDB, API Gateway, and Lambda by analyzing metrics to find anomalies and reduce human intervention. It provides both reactive insights for existing issues and proactive insights to predict future problems.

In this talk we’ll use a standard Serverless application which uses of API Gateway, Lambda, DynamoDB, SQS, Step Functions (and other AWS managed services) and explore how Amazon DevOps Guru recognizes operational issues like increased latency and error rates (timeouts, throttling and resource limits) and integrate DevOps Guru with PagerDuty for providing even better incident management. Amazon DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. The service uses pre-trained ML models that are able to identify spikes in application requests, so it knows when to alert and when not to.

There is a misunderstanding, that everything is possible with the Serverless Services in AWS, for example that your Lambda function may scale without limitations . But each AWS service (not only Serverless) has a big list of quotas that everybody needs to be aware of, understand and take into account during the development. In this talk I'll explain the most important quotas of the Serverless Services like API Gateway, Lambda, DynamoDB, SQS and Aurora Serverless and how to architect your solution with these quotas in mind.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times which may heavily impact the latencies of your application. But the times change: Community and AWS as a cloud providers improve things steadily for Java developers. In this talk we look at the best practices, features and possibilities AWS offers for the Java developers to reduce the cold start times like GraalVM Native Image and AWS Lambda SnapStart based on CRaC (Coordinated Restore at Checkpoint) project.

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times and high memory footprint. For both you have to pay to the cloud providers of your choice. That's why  most developers tried to avoid using Java for such use cases. But the times change: Community and cloud providers improve things steadily for Java developers. In this talk we look at the features and possibilities AWS cloud provider offers for the Java developers and look the most popular Java frameworks, like Micronaut, Quarkus and Spring (Boot) and look how (AOT compiler and GraalVM Native Image play a huge role) they address Serverless challenges and enable Java for broad usage in the Serverless world. We'll also look into AWS Lambda SnapStart feature based on CRaC (Coordinated Restore at Checkpoint) project which also reduces the cold start time of Java Serverless application on AWS. We also look into the tools which help us figure out the optimal balance between Lambda memory footprint, invocation time and execution cost.

The document compares GitHub Copilot, Amazon CodeWhisperer, and ChatGPT for Java developers. It provides an overview of each tool, compares their programming language support, IDE support, and pricing. It demonstrates their abilities for general tasks, simple functions, more complex algorithms, JUnit testing, and Spring Boot web development. It concludes that while the tools provide helpful suggestions, developers are still needed to ensure correctness and efficiency. GitHub Copilot and ChatGPT benefit from OpenAI, while Amazon CodeWhisperer needs quality improvements for Java but may leverage AWS services.

Vadym Kazulkin presented on AWS Lambda SnapStart, which aims to reduce cold start times for Java functions on AWS Lambda. SnapStart works by saving snapshots of the JVM state during a "priming" invocation and restoring it on subsequent cold starts. This can reduce cold start times from seconds to milliseconds. However, SnapStart currently only supports Java 11/17 runtimes and some limitations remain around deployment time and full cold start measurement. Priming the application before taking snapshots can further reduce cold starts but with tradeoffs around additional Lambda costs and optimization time.

I will introduce two AWS services: CodeGuru and DevOps Guru. CodeGuru Reviewer uses ML and automated reasoning to automatically identify critical issues, security vulnerabilities, and hard-to-find bugs during application development. DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. It does this by having the ability to correlate and group metrics together to understand the relationships between those metrics, so it knows when to alert.

In this talk we’ll build a standard Serverless application which uses of API Gateway, Lambda and DynamoDB and explore how Amazon DevOps Guru recognizes operational issues like increased latency and error rates (timeouts and throttles) and integrate DevOps Guru with PagerDuty for providing even better incident management Amazon DevOps Guru analyzes data like application metrics, logs, events, and traces to establish baseline operational behavior and then uses ML to detect anomalies. The service uses pre-trained ML models that are able to identify spikes in application requests, so it knows when to alert and when not to.

In this talk I will compare 2 services which aim at automatically identifing critical issues, security vulnerabilities, and hard-to-find bugs during application development: Amazon CodeGuru and SonarQube from the perspective of the Java developer on AWS. Amazon CodeGuru Reviewer uses ML and automated reasoning to provide recommendations to developers on how to fix issues to improve code quality and dramatically reduce the time it takes to fix bugs before they reach customer-facing applications and result in a bad experience. SonarQube is an open-source platform for continuous inspection of code quality to perform automatic reviews with static analysis of code to detect bugs, code smells, and security vulnerabilities on 20+ programming languages. SonarQube offers reports on duplicated code, coding standards, unit tests, code coverage, code complexity, comments, bugs, and security vulnerabilities

Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless Community. Java is known for its high cold start times and high memory footprint. For both you have to pay to the cloud providers of your choice. That's why most developers tried to avoid using Java for such use cases. But the times change: Community and cloud providers improve things steadily for Java developers. In this talk we look at the features and possibilities AWS cloud provider offers for the Java developers and look the most popular Java frameworks, like Micronaut, Quarkus and Spring (Boot) and look how (AOT compiler and GraalVM native images play a huge role) they address Serverless challenges and enable Java for broad usage in the Serverless world.

This document discusses Projects Valhalla and Loom in Java. Project Valhalla aims to introduce value types to improve memory usage and performance. It plans to unify the Java type system by introducing value classes, primitive classes, and reference projections. Project Loom introduces virtual threads and continuations to enable simple and scalable concurrent programming using structured concurrency. Both projects are currently in preview stages in JDK 19.

Cybersecurity is a major concern in today's connected digital world. Threats to organizations are constantly evolving and have the potential to compromise sensitive information, disrupt operations, and lead to significant financial losses. Traditional cybersecurity techniques often fall short against modern attackers. Therefore, advanced techniques for cyber security analysis and anomaly detection are essential for protecting digital assets. This blog explores these cutting-edge methods, providing a comprehensive overview of their application and importance.

Today’s digitally connected world presents a wide range of security challenges for enterprises. Insider security threats are particularly noteworthy because they have the potential to cause significant harm. Unlike external threats, insider risks originate from within the company, making them more subtle and challenging to identify. This blog aims to provide a comprehensive understanding of insider security threats, including their types, examples, effects, and mitigation techniques.

Quantum Communications Q&A with Gemini LLM. These are based on Shannon's Noisy channel Theorem and offers how the classical theory applies to the quantum world.

We are honored to launch and host this event for our UiPath Polish Community, with the help of our partners - Proservartner! We certainly hope we have managed to spike your interest in the subjects to be presented and the incredible networking opportunities at hand, too! Check out our proposed agenda below 👇👇 08:30 ☕ Welcome coffee (30') 09:00 Opening note/ Intro to UiPath Community (10') Cristina Vidu, Global Manager, Marketing Community @UiPath Dawid Kot, Digital Transformation Lead @Proservartner 09:10 Cloud migration - Proservartner & DOVISTA case study (30') Marcin Drozdowski, Automation CoE Manager @DOVISTA Pawel Kamiński, RPA developer @DOVISTA Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner 09:40 From bottlenecks to breakthroughs: Citizen Development in action (25') Pawel Poplawski, Director, Improvement and Automation @McCormick & Company Michał Cieślak, Senior Manager, Automation Programs @McCormick & Company 10:05 Next-level bots: API integration in UiPath Studio (30') Mikolaj Zielinski, UiPath MVP, Senior Solutions Engineer @Proservartner 10:35 ☕ Coffee Break (15') 10:50 Document Understanding with my RPA Companion (45') Ewa Gruszka, Enterprise Sales Specialist, AI & ML @UiPath 11:35 Power up your Robots: GenAI and GPT in REFramework (45') Krzysztof Karaszewski, Global RPA Product Manager 12:20 🍕 Lunch Break (1hr) 13:20 From Concept to Quality: UiPath Test Suite for AI-powered Knowledge Bots (30') Kamil Miśko, UiPath MVP, Senior RPA Developer @Zurich Insurance 13:50 Communications Mining - focus on AI capabilities (30') Thomasz Wierzbicki, Business Analyst @Office Samurai 14:20 Polish MVP panel: Insights on MVP award achievements and career profiling

accommodate the strengths, weaknesses, threats and opportunities of autonomous vehicles

This presentation explores the practical application of image description techniques. Familiar guidelines will be demonstrated in practice, and descriptions will be developed “live”! If you have learned a lot about the theory of image description techniques but want to feel more confident putting them into practice, this is the presentation for you. There will be useful, actionable information for everyone, whether you are working with authors, colleagues, alone, or leveraging AI as a collaborator. Link to presentation recording and slides: https://bnctechforum.ca/sessions/details-of-description-part-ii-describing-images-in-practice/ Presented by BookNet Canada on June 25, 2024, with support from the Department of Canadian Heritage.

Invited Remote Lecture to SC21 The International Conference for High Performance Computing, Networking, Storage, and Analysis St. Louis, Missouri November 18, 2021

This is a slide deck that showcases the updates in Microsoft Copilot for May 2024

The integration of programming into civil engineering is transforming the industry. We can design complex infrastructure projects and analyse large datasets. Imagine revolutionizing the way we build our cities and infrastructure, all by the power of coding. Programming skills are no longer just a bonus—they’re a game changer in this era. Technology is revolutionizing civil engineering by integrating advanced tools and techniques. Programming allows for the automation of repetitive tasks, enhancing the accuracy of designs, simulations, and analyses. With the advent of artificial intelligence and machine learning, engineers can now predict structural behaviors under various conditions, optimize material usage, and improve project planning.

Are you interested in dipping your toes in the cloud native observability waters, but as an engineer you are not sure where to get started with tracing problems through your microservices and application landscapes on Kubernetes? Then this is the session for you, where we take you on your first steps in an active open-source project that offers a buffet of languages, challenges, and opportunities for getting started with telemetry data. The project is called openTelemetry, but before diving into the specifics, we’ll start with de-mystifying key concepts and terms such as observability, telemetry, instrumentation, cardinality, percentile to lay a foundation. After understanding the nuts and bolts of observability and distributed traces, we’ll explore the openTelemetry community; its Special Interest Groups (SIGs), repositories, and how to become not only an end-user, but possibly a contributor.We will wrap up with an overview of the components in this project, such as the Collector, the OpenTelemetry protocol (OTLP), its APIs, and its SDKs. Attendees will leave with an understanding of key observability concepts, become grounded in distributed tracing terminology, be aware of the components of openTelemetry, and know how to take their first steps to an open-source contribution! Key Takeaways: Open source, vendor neutral instrumentation is an exciting new reality as the industry standardizes on openTelemetry for observability. OpenTelemetry is on a mission to enable effective observability by making high-quality, portable telemetry ubiquitous. The world of observability and monitoring today has a steep learning curve and in order to achieve ubiquity, the project would benefit from growing our contributor community.

Your comprehensive guide to RPA in healthcare for 2024. Explore the benefits, use cases, and emerging trends of robotic process automation. Understand the challenges and prepare for the future of healthcare automation

Widya Salim and Victor Ma will outline the causal impact analysis, framework, and key learnings used to quantify the impact of reducing Twitter's network latency.

Solar Storms (Geo Magnetic Storms) are the motion of accelerated charged particles in the solar environment with high velocities due to the coronal mass ejection (CME).

Slide of the tutorial entitled "Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Emerging Trends" held at UMAP'24: 32nd ACM Conference on User Modeling, Adaptation and Personalization (July 1, 2024 | Cagliari, Italy)

Java Servlet programs

MuleSoft Meetup on APM and IDP

Blockchain technology is transforming industries and reshaping the way we conduct business, manage data, and secure transactions. Whether you're new to blockchain or looking to deepen your knowledge, our guidebook, "Blockchain for Dummies", is your ultimate resource.

Stream processing is a crucial component of modern data infrastructure, but constructing an efficient and scalable stream processing system can be challenging. Decoupling compute and storage architecture has emerged as an effective solution to these challenges, but it can introduce high latency issues, especially when dealing with complex continuous queries that necessitate managing extra-large internal states. In this talk, we focus on addressing the high latency issues associated with S3 storage in stream processing systems that employ a decoupled compute and storage architecture. We delve into the root causes of latency in this context and explore various techniques to minimize the impact of S3 latency on stream processing performance. Our proposed approach is to implement a tiered storage mechanism that leverages a blend of high-performance and low-cost storage tiers to reduce data movement between the compute and storage layers while maintaining efficient processing. Throughout the talk, we will present experimental results that demonstrate the effectiveness of our approach in mitigating the impact of S3 latency on stream processing. By the end of the talk, attendees will have gained insights into how to optimize their stream processing systems for reduced latency and improved cost-efficiency.

How do we build an IoT product, and make it profitable? Talk from the IoT meetup in March 2024. https://www.meetup.com/iot-sweden/events/299487375/