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.
ChatGPT (Chat Generative pre-defined transformer) is OpenAI's application that performs human like interactions. GitHub Copilot uses the OpenAI Codex to suggest code and entire functions in real-time, right from your editor. Deck contains more details about ChatGPT, AI, AGI, CoPilot, OpenAI API, and use case scenarios.
Presented at All Things Open RTP Meetup
Presented by Brent Laster
Title: Introduction to GitHub Copilot
Abstract: Learn about the future of coding with this presentation, "Introduction to GitHub Copilot." Join author, speaker, and DevOps director Brent Laster as we discuss the GitHub coding assistant that leverages the power of artificial intelligence to augment your development activities. In this session, we'll delve into the core features of GitHub Copilot, explaining what it is, and learning about its ability to generate code snippets, autocompletions, and even entire functions across a variety of programming languages.
Learn how Copilot enhances your coding efficiency by contextualizing suggestions based on your codebase and offering a seamless integration into popular code editors. We'll explore some example applications and look at how developers can harness Copilot to streamline their workflows and boost productivity. Whether you're a seasoned developer or just embarking on your coding journey, this presentation offers a quick introduction to GitHub Copilot's capabilities, as a starting point for you to embrace cutting-edge AI assistance in your coding endeavors.
For many decades now, the software industry has attempted to bridge the productivity gap, develop higher quality code and manage the ever growing complexity of software-intensive systems. The results have been mixed, and as a result, a great majority of today's software is still written manually by human developers. This is about to change rapidly as recent developments in the field of Artificial Intelligence show promising results. While artists and designers have been taken by surprise by OpenAI’s DALL-E 2’s capabilities in designing unique art, ChatGPT has astonished the rest of the world with its capability of understanding human interaction. AI-assisted coding solutions such as Github’s Copilot and Replit’s Ghostwriter, among many others, are rapidly developing in a direction where AI generates new code that runs fast with high quality. Little is known about the true capabilities of AI programmers and their impact on the software development industry, education, and research. This talk sheds light on the current state of ChatGPT, large language models including GPT-4, AI-assisted coding, highlights the research gaps, and proposes a way forward.
ChatGPT (Chat Generative pre-defined transformer) is OpenAI's application that performs human like interactions. GitHub Copilot uses the OpenAI Codex to suggest code and entire functions in real-time, right from your editor. Deck contains more details about ChatGPT, AI, AGI, CoPilot, OpenAI API, and use case scenarios.
Presented at All Things Open RTP Meetup
Presented by Brent Laster
Title: Introduction to GitHub Copilot
Abstract: Learn about the future of coding with this presentation, "Introduction to GitHub Copilot." Join author, speaker, and DevOps director Brent Laster as we discuss the GitHub coding assistant that leverages the power of artificial intelligence to augment your development activities. In this session, we'll delve into the core features of GitHub Copilot, explaining what it is, and learning about its ability to generate code snippets, autocompletions, and even entire functions across a variety of programming languages.
Learn how Copilot enhances your coding efficiency by contextualizing suggestions based on your codebase and offering a seamless integration into popular code editors. We'll explore some example applications and look at how developers can harness Copilot to streamline their workflows and boost productivity. Whether you're a seasoned developer or just embarking on your coding journey, this presentation offers a quick introduction to GitHub Copilot's capabilities, as a starting point for you to embrace cutting-edge AI assistance in your coding endeavors.
For many decades now, the software industry has attempted to bridge the productivity gap, develop higher quality code and manage the ever growing complexity of software-intensive systems. The results have been mixed, and as a result, a great majority of today's software is still written manually by human developers. This is about to change rapidly as recent developments in the field of Artificial Intelligence show promising results. While artists and designers have been taken by surprise by OpenAI’s DALL-E 2’s capabilities in designing unique art, ChatGPT has astonished the rest of the world with its capability of understanding human interaction. AI-assisted coding solutions such as Github’s Copilot and Replit’s Ghostwriter, among many others, are rapidly developing in a direction where AI generates new code that runs fast with high quality. Little is known about the true capabilities of AI programmers and their impact on the software development industry, education, and research. This talk sheds light on the current state of ChatGPT, large language models including GPT-4, AI-assisted coding, highlights the research gaps, and proposes a way forward.
Azure OpenAI Service provides REST API access to OpenAI's powerful language models, including the GPT-3, GPT-4, DALL-E, Codex, and Embeddings model series. These models can be easily adapted to any specific task, including but not limited to content generation, summarization, semantic search, translation, transformation, and code generation. Microsoft offers the accessibility of the service through REST APIs, Python or C# SDK, or the Azure OpenAI Studio.
Making Testing Easy w GitHub Copilot.pdfApplitools
Learn how to boost productivity with real-time code suggestions for a broad set of frameworks and languages with GitHub Copilot in this webinar with Rizel Scarlett.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
Platform Engineering is the practice of building and operating a common platform as a product for technology teams.
In this session, we will talk about why and when we need a platform. How to build Platform Engineering and demo.
Jirayut Nimsaeng
Founder & CEO
Opsta (Thailand) Co., Ltd.
Youtube Record: https://youtu.be/brBZYbNbnAo
Dev Mountain Tech Festival 2022 @ Khaoyai
March 19, 2022
What does it take to get an application into production? Many processes, tools and automation surround that application to deliver it to the customer. As it becomes more common for development teams to autonomously deliver and run their software, the focus of the traditional operational teams shifts towards an as-a-service mindset. But how is such a team positioned within the company? And is Platform Engineering any different from Software Engineering?
In this talk I’ll share my experiences as a platform engineer and explain why I believe that every company should be conscious about why and how to setup this responsibility. I’ll also discuss the biggest challenges surrounding it - and how to tackle them.
CI:CD in Lightspeed with kubernetes and argo cdBilly Yuen
Enterprises have benefited greatly from the elastic scalability and multi-region availability by moving to AWS, but the fundamental deployment model remains the same.
At Intuit, we have adopted k8s as our new saas platform and re-invented our CI/CD pipeline to take full advantage of k8s. In this presentation, we will discuss our journey from Spinnaker to Argo CD.
1. Reduce CI/CD time from 60 minutes to 10 minutes.
2. Reduce production release (or rollback) from 10 minutes to 2 minutes.
3. Enable concurrent deployment using spinnaker and argo cd as HA/DR to safely adopt the new platform with no downtime.
4. Be compatible with the existing application monitoring toolset.
At AWS re:Invent, we have launched support for blue/green deployments for services hosted using AWS Fargate and Amazon Elastic Container Service (Amazon ECS). Blue/green deployments help you minimize downtime during application updates. They allow you to launch a new version of your application alongside the old version and test the new version before you reroute traffic to it. You can also monitor the deployment process and, if there is an issue, quickly roll back.
In this workshop, you will create a new service in AWS Fargate that uses AWS CodeDeploy to manage the deployments, testing, and traffic cutover for you.
An Introduction to Generative AI - May 18, 2023CoriFaklaris1
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Vertex AI - Unified ML Platform for the entire AI workflow on Google CloudMárton Kodok
Vertex AI is a managed ML platform for practitioners to accelerate experiments and deploy AI models.
Enhanced developer experience
- Build with the groundbreaking ML tools that power Google
- Approachable from the non-ML developer perspective (AutoML, managed models, training)
- Ease the life of a data scientist/ML (has feature store, managed datasets, endpoints, notebooks)
- Infrastructure management overhead have been almost completely eliminated
- Unified UI for the entire ML workflow
- End-to-end integration for data and AI with build pipelines that outperform and solve complex ML tasks
- Explainable AI and TensorBoard to visualize and track ML experiments
GitOps è un nuovo metodo di CD che utilizza Git come unica fonte di verità per le applicazioni e per l'infrastruttura (declarative infrastructure/infrastructure as code), fornendo sia il controllo delle revisioni che il controllo delle modifiche. In questo talk vedremo come implementare workflow di CI/CD Gitops basati su Kubernetes, dalla teoria alla pratica passando in rassegna i principali strumenti oggi a disposizione come ArgoCD, Flux (aka Gitops engine) e JenkinsX
Unlocking the Power of ChatGPT and AI in Testing - NextSteps, presented by Ap...Applitools
Gain insights into the practical applications of ChatGPT, Bard, and other AI-based technological advancements, including GitHub CoPilot and Applitools Self-Healing Cloud, in this session with Anand Bagmar. Through specific use cases, Anand demonstrates how to enhance test automation processes—making them faster, more stable, and easier to implement.
Session recording and more info at applitools.com
Uncover how these tools can revolutionize your testing strategies and stay ahead of the curve in the ever-evolving world of test automation.
Increase the Velocity of Your Software Releases Using GitHub and DeployHubDevOps.com
Increase the velocity of your software releases by using continuous deployment driven by continuous delivery pipeline. After all, the goal of agile is to get code updates into the hands of your users fast and on a high frequency basis. This means installing all the way to production, not just staged for productio.
This webinar will show you an approach to achieving full continuous deployment using GitHub and DeployHub. You will learn how to declare your Application Package from your GitHub repository, manage approvals and deliver updates to environments across the CD pipeline from development through production.
GitHub and DeployHub work together to provide a complete DevOps process that results in a repeatable, consistent software releases process with a full continuous feedback loop.
Azure OpenAI Service provides REST API access to OpenAI's powerful language models, including the GPT-3, GPT-4, DALL-E, Codex, and Embeddings model series. These models can be easily adapted to any specific task, including but not limited to content generation, summarization, semantic search, translation, transformation, and code generation. Microsoft offers the accessibility of the service through REST APIs, Python or C# SDK, or the Azure OpenAI Studio.
Making Testing Easy w GitHub Copilot.pdfApplitools
Learn how to boost productivity with real-time code suggestions for a broad set of frameworks and languages with GitHub Copilot in this webinar with Rizel Scarlett.
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Unlocking the Power of Generative AI An Executive's Guide.pdfPremNaraindas1
Generative AI is here, and it can revolutionize your business. With its powerful capabilities, this technology can help companies create more efficient processes, unlock new insights from data, and drive innovation. But how do you make the most of these opportunities?
This guide will provide you with the information and resources needed to understand the ins and outs of Generative AI, so you can make informed decisions and capitalize on the potential. It covers important topics such as strategies for leveraging large language models, optimizing MLOps processes, and best practices for building with Generative AI.
Platform Engineering is the practice of building and operating a common platform as a product for technology teams.
In this session, we will talk about why and when we need a platform. How to build Platform Engineering and demo.
Jirayut Nimsaeng
Founder & CEO
Opsta (Thailand) Co., Ltd.
Youtube Record: https://youtu.be/brBZYbNbnAo
Dev Mountain Tech Festival 2022 @ Khaoyai
March 19, 2022
What does it take to get an application into production? Many processes, tools and automation surround that application to deliver it to the customer. As it becomes more common for development teams to autonomously deliver and run their software, the focus of the traditional operational teams shifts towards an as-a-service mindset. But how is such a team positioned within the company? And is Platform Engineering any different from Software Engineering?
In this talk I’ll share my experiences as a platform engineer and explain why I believe that every company should be conscious about why and how to setup this responsibility. I’ll also discuss the biggest challenges surrounding it - and how to tackle them.
CI:CD in Lightspeed with kubernetes and argo cdBilly Yuen
Enterprises have benefited greatly from the elastic scalability and multi-region availability by moving to AWS, but the fundamental deployment model remains the same.
At Intuit, we have adopted k8s as our new saas platform and re-invented our CI/CD pipeline to take full advantage of k8s. In this presentation, we will discuss our journey from Spinnaker to Argo CD.
1. Reduce CI/CD time from 60 minutes to 10 minutes.
2. Reduce production release (or rollback) from 10 minutes to 2 minutes.
3. Enable concurrent deployment using spinnaker and argo cd as HA/DR to safely adopt the new platform with no downtime.
4. Be compatible with the existing application monitoring toolset.
At AWS re:Invent, we have launched support for blue/green deployments for services hosted using AWS Fargate and Amazon Elastic Container Service (Amazon ECS). Blue/green deployments help you minimize downtime during application updates. They allow you to launch a new version of your application alongside the old version and test the new version before you reroute traffic to it. You can also monitor the deployment process and, if there is an issue, quickly roll back.
In this workshop, you will create a new service in AWS Fargate that uses AWS CodeDeploy to manage the deployments, testing, and traffic cutover for you.
An Introduction to Generative AI - May 18, 2023CoriFaklaris1
For this plenary talk at the Charlotte AI Institute for Smarter Learning, Dr. Cori Faklaris introduces her fellow college educators to the exciting world of generative AI tools. She gives a high-level overview of the generative AI landscape and how these tools use machine learning algorithms to generate creative content such as music, art, and text. She then shares some examples of generative AI tools and demonstrate how she has used some of these tools to enhance teaching and learning in the classroom and to boost her productivity in other areas of academic life.
Vertex AI - Unified ML Platform for the entire AI workflow on Google CloudMárton Kodok
Vertex AI is a managed ML platform for practitioners to accelerate experiments and deploy AI models.
Enhanced developer experience
- Build with the groundbreaking ML tools that power Google
- Approachable from the non-ML developer perspective (AutoML, managed models, training)
- Ease the life of a data scientist/ML (has feature store, managed datasets, endpoints, notebooks)
- Infrastructure management overhead have been almost completely eliminated
- Unified UI for the entire ML workflow
- End-to-end integration for data and AI with build pipelines that outperform and solve complex ML tasks
- Explainable AI and TensorBoard to visualize and track ML experiments
GitOps è un nuovo metodo di CD che utilizza Git come unica fonte di verità per le applicazioni e per l'infrastruttura (declarative infrastructure/infrastructure as code), fornendo sia il controllo delle revisioni che il controllo delle modifiche. In questo talk vedremo come implementare workflow di CI/CD Gitops basati su Kubernetes, dalla teoria alla pratica passando in rassegna i principali strumenti oggi a disposizione come ArgoCD, Flux (aka Gitops engine) e JenkinsX
Unlocking the Power of ChatGPT and AI in Testing - NextSteps, presented by Ap...Applitools
Gain insights into the practical applications of ChatGPT, Bard, and other AI-based technological advancements, including GitHub CoPilot and Applitools Self-Healing Cloud, in this session with Anand Bagmar. Through specific use cases, Anand demonstrates how to enhance test automation processes—making them faster, more stable, and easier to implement.
Session recording and more info at applitools.com
Uncover how these tools can revolutionize your testing strategies and stay ahead of the curve in the ever-evolving world of test automation.
Increase the Velocity of Your Software Releases Using GitHub and DeployHubDevOps.com
Increase the velocity of your software releases by using continuous deployment driven by continuous delivery pipeline. After all, the goal of agile is to get code updates into the hands of your users fast and on a high frequency basis. This means installing all the way to production, not just staged for productio.
This webinar will show you an approach to achieving full continuous deployment using GitHub and DeployHub. You will learn how to declare your Application Package from your GitHub repository, manage approvals and deliver updates to environments across the CD pipeline from development through production.
GitHub and DeployHub work together to provide a complete DevOps process that results in a repeatable, consistent software releases process with a full continuous feedback loop.
Revolutionize DevOps with ML capabilities. Deep dive into Amazon CodeGuru and...Vadym Kazulkin
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.
A presentation form Integration Stockholm where we shared our collected thoughts on how to implement Continuous Delivery in mainly Enterprise organisations. What has worked for us and what did not work and how to approach CI/CD and succeed...
Sitecore development approach evolution – destination helixPeter Nazarov
Sitecore Development Approach Evolution – Destination Helix
Sitecore officially recommended Helix as a set of overall design principles and conventions for Sitecore development around 18 month ago at SUGCON 2016 alongside with an official implementation example - Habitat. Why was it necessary? What are the benefits? Has it worked in practice? Peter Nazarov will share the outlook on why and how a combination of Sitecore Helix and Habitat benefits the business and development users of Sitecore in practice.
Security issues, dependency vulnerabilities, misconfigurations... All of those can make or break your Open Source projects. Also, you want to make sure you adhere to the best practices, especially when you use more complex tools like Kubernetes.
Let's see how we can use the tools that GitHub and Datree provide (most are Open Source too!) to secure your project and make sure that no misconfiguration ever reaches the deployment targets!
Revolutionize DevOps with ML capabilities. Introduction to Amazon CodeGuru an...Vadym Kazulkin
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.
Software release cycles are now measured in days instead of months. Cutting edge companies are continuously delivering high quality software at a fast pace. In this session, we cover how you can begin your DevOps journey by sharing best practices and tools used by engineering teams at Amazon. We showcase how you can accelerate developer productivity by implementing continuous integration and delivery workflows. In addition, we introduce AWS CodeStar, AWS CodeCommit, AWS CodeBuild, AWS CodePipeline, AWS CodeDeploy, and AWS X-Ray, the services inspired by Amazon's internal developer tools and DevOps practices.
Continues Integration and Continuous Delivery with Azure DevOps - Deploy Anyt...Janusz Nowak
Continues Integration and Continuous Delivery with Azure DevOps - Deploy Anything to Anywhere with Azure DevOps
Janusz Nowak
@jnowwwak
https://www.linkedin.com/in/janono
https://github.com/janusznowak
https://blog.janono.pl
A Tale of Two Pizzas: Accelerating Software Delivery with AWS Developer ToolsAmazon Web Services
Software release cycles are now measured in days instead of months. Cutting-edge companies are continuously delivering high-quality software at a fast pace. In this session, we will cover how you begin your DevOps journey by sharing best practices and tools by the "two pizza" engineering teams at Amazon. We will showcase how you can accelerate developer productivity by implementing continuous integration and delivery workflows. Here to share their story is FamilySearch, a large nonprofit customer, deploys 1700 code implementations a day using native AWS tools. This allows them to improve feature sets, provide better member experience, and improve their ability to deliver improved functionality quickly. FamilySearch has been doing DevOps in the cloud longer than any of our PS customers and their expertise in this field is unmatched. In this session, they'll provide deep insight into managing the challenges of migrating to a DevOps model, using cloud services to differentiate a business, and improving an organization's ability to do more with less.
Are you tired of the ever-increasing complexity in the world of DevOps? Do Docker and Kubernetes scripts, Ansible configurations, and networking woes make your head spin? It's time for a breath of fresh air.
Join us on a transformative journey where we shatter the myth that DevOps has to be overly complicated. Say goodbye to the days of struggling with incomplete scripts and tangled configurations. In this enlightening talk, we'll guide you through the process of rapidly onboarding your new standard microservice into the DevOps and Cloud universe.
We'll unveil the power of GitHub Actions, AWS, OpenAI API, and MS Teams Incoming Web hooks in a way that's both enlightening and entertaining. Additionally, we'll explore how Language Model APIs (LLMs) can be leveraged to enhance and streamline your DevOps workflows. You'll discover that DevOps doesn't have to be a labyrinth of complexity; it can be a streamlined and enjoyable experience.
So, if you're ready to simplify your DevOps journey and embrace a world where AWS, the OpenAI API, and GitHub Actions collaborate seamlessly while harnessing the potential of LLMs, join us and let's make DevOps a breeze!
Revolutionize DevOps with ML capabilities. Introduction to Amazon CodeGuru an...Vadym Kazulkin
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.
Software release cycles are now measured in days instead of months. Cutting edge companies are continuously delivering high-quality software at a fast pace. In this session, we will cover how you can begin your DevOps journey by sharing best practices and tools used by the engineering teams at Amazon. We will showcase how you can accelerate developer productivity by implementing continuous Integration and delivery workflows. We will also cover an introduction to AWS CodeStar, AWS CodeCommit, AWS CodeBuild, AWS CodePipeline, AWS CodeDeploy, AWS Cloud9, and AWS X-Ray the services inspired by Amazon's internal developer tools and DevOps practice.
High performance Serverless Java on AWS at GeeCon 2024 KrakowVadym Kazulkin
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.
Amazon DevOps Guru for Serverless Applications at DevOpsCon 2024 LondonVadym Kazulkin
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.
Making sense of service quotas of AWS Serverless services and how to deal wit...Vadym Kazulkin
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.
How to reduce cold starts for Java Serverless applications in AWS at JCON Wor...Vadym Kazulkin
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.
How to reduce cold starts for Java Serverless applications in AWS at Serverle...Vadym Kazulkin
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.
Revolutionize DevOps lifecycle with Amazon CodeCatalyst and DevOps Guru at De...Vadym Kazulkin
AWS is on a journey to revolutionize DevOps using the latest technologies. In this talk I'll introduce 2 Amazon services which cover different stages of the DevOps lifecycle: CodeCatalyst and DevOps Guru.
Amazon CodeCatalyst is an integrated service for software development teams adopting continuous integration and deployment practices into their software development process. CodeCatalyst puts the tools you need all in one place. You can plan work, collaborate on code, and build, test, and deploy applications with continuous integration/continuous delivery (CI/CD) tools. You can also integrate AWS resources with your projects by connecting your AWS accounts to your CodeCatalyst space. By managing all of the stages and aspects of your application lifecycle in one tool, you can deliver software quickly and confidently.
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.
Amazon DevOps Guru for the Serverless Applications at AWS Community Day NL 2023Vadym Kazulkin
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.
Making sense of service quotas of AWS Serverless services and how to deal wit...Vadym Kazulkin
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.
How to reduce cold starts for Java Serverless applications in AWS at InfoShar...Vadym Kazulkin
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.
Adopting Java for the Serverless World at Voxxed Days Bruxelles 2023Vadym Kazulkin
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.
AWS Lambda SnapStart: Why, How and What AWS Serverless Meetup New York Boston...Vadym Kazulkin
- Challenges of AWS Serverless applications written in Java
- Challenges and limitations of existing solutions like Graal VM Native Image
- What is AWS SnapStart and how it addresses those challenges
- Benchmarking AWS Lambda SnapStart using plain Java and also frameworks like Quarkus, Micronaut and SpringBoot
- Optimization techniques like Priming
- Current challenges and limitations of AWS Lambda SnapStart
Amazon DevOps Guru for the Serverless Applications at AWS Community Day Bene...Vadym Kazulkin
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.
Amazon CodeGuru vs SonarQube for Java Developers at JCon 2022Vadym Kazulkin
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
Adopting Java for the Serverless World at JUG Saxony Day 2022Vadym Kazulkin
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.
Adopting Java for the Serverless World at VoxxedDays LuxemburgVadym Kazulkin
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.
Adopting Java for the Serverless World at JUG Bonn 2022Vadym Kazulkin
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.
Adopting Java for the Serverless World at JUG Darmstadt 2022Vadym Kazulkin
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.
Adopting Java for the Serverless World at JAX 2022Vadym Kazulkin
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.
Adopting Java for the Serverless World at JUG Hessen 2022Vadym Kazulkin
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.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
5. Agenda
• Introduction to GitHub Copilot, AWS CodeWhisperer and
ChatGPT
• Comparison
• IDE Support and Pricing
• General tasks
• Simple functions
• More complex algorithms
• JUnit Testing
• Web Development (with Spring Boot)
• AWS Development (optional)
66. GitHub Copilot X Overview
GPT-4 Powered Chat
https://github.com/features/preview/copilot-x
67. GitHub Copilot X Overview
AI generated PR-Requests %
Automate automated testing
https://github.com/features/preview/copilot-x
68. Conclusions GitHub
• GitHub Copilot provides lots of meaningful suggestions
• Low number of compilation and algorithmic errors (most are easy
to correct)
• Only small steps required to complete the task or correct the errors
• Access to OpenAI technologies make it very promising
• Bringing GPT-4 capabilities like Chat as Copilot X is a huge step
forward
• GPT-4 has only knowledge as of September 2021
https://twitter.com/karpathy/status/1608895189078380544
70. Conclusions AWS CodeWhisperer
• AWS CodeWhisperer UX and suggestion quality needs to be
improved drastically (currently in Preview)
• Many Alt+C on several levels required to get some result
• Especially during the import suggestions
• Many imports statements required in advance in order to get
more or less correct suggestions
• Some compilation and algorithmic errors (most are easy to
correct)
• Drastically improved the quality of the suggestions between
preview and GA
71. Conclusions AWS CodeWhisperer
• Working with AWS Services should become the USP
• Glue together AWS Serverless Services (API Gateway, Lambda,
DynamoDB, SQS, EventBridge)
• Generate Infrastructure-as-a-Code (SAM, CDK) for it
• Integration with Amazon CodeGuru should become out of the
box feature
• My expectation: no CodeWhisperer code completion suggestion
shouldn’t violate best practices highlighted by CodeGuru
• Code Security Scans as an add-on feature
72. Conclusions ChatGPT
• Many suggestions are right or can be fixed quickly
• Sometimes missing pieces that need to be additionally requested
• Sometimes ChatGPT forgets the previous context
• Not all the suggestions are correct though
• Not existing classes or methods are suggested esp. with GPT-3.5
• Each new try with the same “command” may suggest totally different
(correct and sometimes wrong) solution
• ChatGPT-4 is a huge improvement over 3.5 for developers
• GPT-4 has only knowledge as of September 2021
73. Additional benefits of ChatGPT and
CodePilot X GPT-4 powered Chat
• Can explain the existing code
• Can provide suggestions for improving the existing code
• Can search for bugs in the existing code and try to fix it
• Can document the existing code
• Can more easily generate automated tests
• Capable of generating the whole application (Code, Maven/Gradle
dependency file, Deployment (IaaC))
74. Conclusions
• Lot of room the general improvements for the code completion tools
• Suggestion quality, UI/UX
• Developers who effectively use the AI tools will increase their
development speed and productivity
• Your profound expertise is still required to supervise the tool (correctness,
efficiency)
• Main target group -> senior developers
• GitHub Copilot and ChatGPT both powered by OpenAI APIs, so the
improvements and synergies are expected in both
• Already happened with the preview release of the Copilot X based on GPT-4
• Quality of Amazon CodeWhisperer should be improved (at least for Java)
75. Final Thoughts
• Code completion alone are not enough
• need full cycle support: dependency management, code, configuration,
deployment (cloud -> IaaC), testing, observability (logging, monitoring, alerting),
debugging applications.
• Context and environment understanding are crucial (and currently constrained)
• Microsoft will bring products for the conversational programming into the
Azure Cloud
• Copilot Suite (base on GPT-4) is everywhere in the Microsoft world: MS Office,
Bing, Azure Cloud
• Azure OpenAI service (currently limited) is already there.
76. Final Thoughts
• Put Amazon/AWS and Google as a Cloud Provider on pressure to answer
• Amazon partner and Hugging Face partner to make AI more accessible
• Amazon announced Bedrock
• Google answered with Bard
77. Announcing New Tools for Building with
Generative AI on AWS
https://aws.amazon.com/blogs/machine-learning/announcing-new-tools-for-building-with-generative-ai-on-aws/
