Microservices Tracing With Spring Cloud and Zipkin @Szczecin JUGMarcin Grzejszczak
The hype related to microservices continues. It’s already common knowledge that creating distributed systems is not easy. It’s high time to show how that complexity can be contained.
Service Discovery and Registry (Zookeeper / Consul / Eureka), easy request sending with client side load balancing (Feign + Ribbon), request proxying with Zuul. Everything is easy with Spring Cloud. Just add a dependency, a couple of lines of configuration and you’re ready to go.
That’s fixing difficulties related to writing code - what about solving the complexity of debugging distributed systems? Log correlation and visualizing latency of parts of the system? Spring Cloud Sleuth with Zipkin to the rescue!
The presentation will consist of some theory but there’ll also be live coding and demos.
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudNoritaka Sekiyama
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud (Hadoop / Spark Conference Japan 2019)
# English version #
http://hadoop.apache.jp/hcj2019-program/
Apache kafka 모니터링을 위한 Metrics 이해 및 최적화 방안SANG WON PARK
Apache Kafak의 빅데이터 아키텍처에서 역할이 점차 커지고, 중요한 비중을 차지하게 되면서, 성능에 대한 고민도 늘어나고 있다.
다양한 프로젝트를 진행하면서 Apache Kafka를 모니터링 하기 위해 필요한 Metrics들을 이해하고, 이를 최적화 하기 위한 Configruation 설정을 정리해 보았다.
[Apache kafka 모니터링을 위한 Metrics 이해 및 최적화 방안]
Apache Kafka 성능 모니터링에 필요한 metrics에 대해 이해하고, 4가지 관점(처리량, 지연, Durability, 가용성)에서 성능을 최적화 하는 방안을 정리함. Kafka를 구성하는 3개 모듈(Producer, Broker, Consumer)별로 성능 최적화를 위한 …
[Apache Kafka 모니터링을 위한 Metrics 이해]
Apache Kafka의 상태를 모니터링 하기 위해서는 4개(System(OS), Producer, Broker, Consumer)에서 발생하는 metrics들을 살펴봐야 한다.
이번 글에서는 JVM에서 제공하는 JMX metrics를 중심으로 producer/broker/consumer의 지표를 정리하였다.
모든 지표를 정리하진 않았고, 내 관점에서 유의미한 지표들을 중심으로 이해한 내용임
[Apache Kafka 성능 Configuration 최적화]
성능목표를 4개로 구분(Throughtput, Latency, Durability, Avalibility)하고, 각 목표에 따라 어떤 Kafka configuration의 조정을 어떻게 해야하는지 정리하였다.
튜닝한 파라미터를 적용한 후, 성능테스트를 수행하면서 추출된 Metrics를 모니터링하여 현재 업무에 최적화 되도록 최적화를 수행하는 것이 필요하다.
Microservices Tracing With Spring Cloud and Zipkin @Szczecin JUGMarcin Grzejszczak
The hype related to microservices continues. It’s already common knowledge that creating distributed systems is not easy. It’s high time to show how that complexity can be contained.
Service Discovery and Registry (Zookeeper / Consul / Eureka), easy request sending with client side load balancing (Feign + Ribbon), request proxying with Zuul. Everything is easy with Spring Cloud. Just add a dependency, a couple of lines of configuration and you’re ready to go.
That’s fixing difficulties related to writing code - what about solving the complexity of debugging distributed systems? Log correlation and visualizing latency of parts of the system? Spring Cloud Sleuth with Zipkin to the rescue!
The presentation will consist of some theory but there’ll also be live coding and demos.
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the CloudNoritaka Sekiyama
Amazon S3 Best Practice and Tuning for Hadoop/Spark in the Cloud (Hadoop / Spark Conference Japan 2019)
# English version #
http://hadoop.apache.jp/hcj2019-program/
Apache kafka 모니터링을 위한 Metrics 이해 및 최적화 방안SANG WON PARK
Apache Kafak의 빅데이터 아키텍처에서 역할이 점차 커지고, 중요한 비중을 차지하게 되면서, 성능에 대한 고민도 늘어나고 있다.
다양한 프로젝트를 진행하면서 Apache Kafka를 모니터링 하기 위해 필요한 Metrics들을 이해하고, 이를 최적화 하기 위한 Configruation 설정을 정리해 보았다.
[Apache kafka 모니터링을 위한 Metrics 이해 및 최적화 방안]
Apache Kafka 성능 모니터링에 필요한 metrics에 대해 이해하고, 4가지 관점(처리량, 지연, Durability, 가용성)에서 성능을 최적화 하는 방안을 정리함. Kafka를 구성하는 3개 모듈(Producer, Broker, Consumer)별로 성능 최적화를 위한 …
[Apache Kafka 모니터링을 위한 Metrics 이해]
Apache Kafka의 상태를 모니터링 하기 위해서는 4개(System(OS), Producer, Broker, Consumer)에서 발생하는 metrics들을 살펴봐야 한다.
이번 글에서는 JVM에서 제공하는 JMX metrics를 중심으로 producer/broker/consumer의 지표를 정리하였다.
모든 지표를 정리하진 않았고, 내 관점에서 유의미한 지표들을 중심으로 이해한 내용임
[Apache Kafka 성능 Configuration 최적화]
성능목표를 4개로 구분(Throughtput, Latency, Durability, Avalibility)하고, 각 목표에 따라 어떤 Kafka configuration의 조정을 어떻게 해야하는지 정리하였다.
튜닝한 파라미터를 적용한 후, 성능테스트를 수행하면서 추출된 Metrics를 모니터링하여 현재 업무에 최적화 되도록 최적화를 수행하는 것이 필요하다.
고승범(peter.ko) / kakao corp.(인프라2팀)
---
카카오에서는 빅데이터 분석, 처리부터 모든 개발 플랫폼을 이어주는 솔루션으로 급부상한 카프카(kafka)를 전사 공용 서비스로 운영하고 있습니다. 전사 공용 카프카를 직접 운영하면서 경험한 트러블슈팅과 운영 노하우 등을 공유하고자 합니다. 특히 카프카를 처음 접하시는 분들이나 이미 사용 중이신 분들이 많이 궁금해하는 프로듀서와 컨슈머 사용 시의 주의점 등에 대해서도 설명합니다.
LinkedIn started its Trino journey back in 2015 and has been an active contributor in the community. We have been witnessing massive growth YoY and our workload has been exponentially growing with more than 5k unique users, processing 100s of PB, millions of queries and quadrillions of rows every week. Trino at LinkedIn is used for a diverse variety of use cases like detecting fraud and abuse, data scientists measure impact of COVID on economic and jobs landscape, engineers run ad hoc analysis to debug production issues, business analysts build robust data driven offering to help salespeople make smarter decisions, site-reliability engineers analyze internal system performances and more. In this talk, we will go through Trino's growth at LinkedIn, how it fits into our data ecosystem, some of our operating challenges and dive into a few of our use cases. We'll also talk about our learnings, contributions, and philosophy on open source and what has worked well for us.
Dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
When it comes to data security, Uber’s business has unique needs related to scale, use-case, and technical stacks. This talk will discuss how our data platform team addressed specific challenges in deploying Uber's security requirements for Apache Hadoop, including how we leveraged open source building blocks. We'll share insights on how we augmented our Kerberized Hadoop integration with additional authentications mechanisms as well as our approach to supporting custom authentication in Apache Knox. In particular, we will elaborate Uber’s contributions to Apache Knox, specifically a novel pluggable platform for custom validation of any user request. This talk will also cover how we address table, column, and partition-level access control while ensuring improved developer productivity. In particular, we will explain how we translate RBAC policy into HDFS ACL to control data access, our internal audit platform built to detect and analyze the common security infringements, and real-world examples from our experiences in production.
Speakers
Mohammad Islam, Staff Software Engineer, Uber
Wei Han, Manager, Uber
Apache kafka performance(latency)_benchmark_v0.3SANG WON PARK
Apache Kafka를 이용하여 이미지 데이터를 얼마나 빠르게(with low latency) 전달 가능한지 성능 테스트.
최종 목적은 AI(ML/DL) 모델의 입력으로 대량의 실시간 영상/이미지 데이터를 전달하는 메세지 큐로 사용하기 위하여, Drone/제조공정 등의 장비에서 전송된 이미지를 얼마나 빨리 AI Model로 전달 할 수 있는지 확인하기 위함.
그래서 Kafka에서 이미지를 전송하는 간단한 테스트를 진행하였고,
이 과정에서 latency를 얼마나 줄여주는지를 확인해 보았다.(HTTP 프로토콜/Socket과 비교하여)
[현재 까지 결론]
- Apache Kafka는 대량의 요청 처리를 위한 throughtput에 최적화 된 솔루션임.
- 현재는 producer의 몇가지 옵션만 조정하여 테스트한 결과이므로,
- 잠정적인 결과이지만, kafka의 latency를 향상을 위해서는 많은 시도가 필요할 것 같음.
- 즉, 단일 요청의 latency는 확실히 느리지만,
- 대량의 처리를 기준으로 평균 latency를 비교하면 평균적인 latency는 많이 낮아짐.
Test Code : https://github.com/freepsw/kafka-latency-test
Consumer Driven Contracts and Your Microservice ArchitectureMarcin Grzejszczak
My talk from SpringOnePlatform about Spring Cloud Contract
Links:
* http://martinfowler.com/articles/consumerDrivenContracts.html - article about Consumer Driven Contracts by Ian Robinson
* https://github.com/marcingrzejszczak/springone-cdc-client - code for the client side of the presented example
* https://github.com/marcingrzejszczak/springone-cdc-server - code for the server side of the presented example
* https://cloud.spring.io/spring-cloud-contract/spring-cloud-contract.html - documentation of the Spring Cloud Contract project
During this brief walkthrough of the setup, configuration and use of the toolset we will show you how to find the trees from the forest in today's modern cloud environments and beyond.
고승범(peter.ko) / kakao corp.(인프라2팀)
---
카카오에서는 빅데이터 분석, 처리부터 모든 개발 플랫폼을 이어주는 솔루션으로 급부상한 카프카(kafka)를 전사 공용 서비스로 운영하고 있습니다. 전사 공용 카프카를 직접 운영하면서 경험한 트러블슈팅과 운영 노하우 등을 공유하고자 합니다. 특히 카프카를 처음 접하시는 분들이나 이미 사용 중이신 분들이 많이 궁금해하는 프로듀서와 컨슈머 사용 시의 주의점 등에 대해서도 설명합니다.
LinkedIn started its Trino journey back in 2015 and has been an active contributor in the community. We have been witnessing massive growth YoY and our workload has been exponentially growing with more than 5k unique users, processing 100s of PB, millions of queries and quadrillions of rows every week. Trino at LinkedIn is used for a diverse variety of use cases like detecting fraud and abuse, data scientists measure impact of COVID on economic and jobs landscape, engineers run ad hoc analysis to debug production issues, business analysts build robust data driven offering to help salespeople make smarter decisions, site-reliability engineers analyze internal system performances and more. In this talk, we will go through Trino's growth at LinkedIn, how it fits into our data ecosystem, some of our operating challenges and dive into a few of our use cases. We'll also talk about our learnings, contributions, and philosophy on open source and what has worked well for us.
Dive deep into some of the key innovations behind Amazon Aurora, discuss best practices and configurations, and share early customer experience from the field.
When it comes to data security, Uber’s business has unique needs related to scale, use-case, and technical stacks. This talk will discuss how our data platform team addressed specific challenges in deploying Uber's security requirements for Apache Hadoop, including how we leveraged open source building blocks. We'll share insights on how we augmented our Kerberized Hadoop integration with additional authentications mechanisms as well as our approach to supporting custom authentication in Apache Knox. In particular, we will elaborate Uber’s contributions to Apache Knox, specifically a novel pluggable platform for custom validation of any user request. This talk will also cover how we address table, column, and partition-level access control while ensuring improved developer productivity. In particular, we will explain how we translate RBAC policy into HDFS ACL to control data access, our internal audit platform built to detect and analyze the common security infringements, and real-world examples from our experiences in production.
Speakers
Mohammad Islam, Staff Software Engineer, Uber
Wei Han, Manager, Uber
Apache kafka performance(latency)_benchmark_v0.3SANG WON PARK
Apache Kafka를 이용하여 이미지 데이터를 얼마나 빠르게(with low latency) 전달 가능한지 성능 테스트.
최종 목적은 AI(ML/DL) 모델의 입력으로 대량의 실시간 영상/이미지 데이터를 전달하는 메세지 큐로 사용하기 위하여, Drone/제조공정 등의 장비에서 전송된 이미지를 얼마나 빨리 AI Model로 전달 할 수 있는지 확인하기 위함.
그래서 Kafka에서 이미지를 전송하는 간단한 테스트를 진행하였고,
이 과정에서 latency를 얼마나 줄여주는지를 확인해 보았다.(HTTP 프로토콜/Socket과 비교하여)
[현재 까지 결론]
- Apache Kafka는 대량의 요청 처리를 위한 throughtput에 최적화 된 솔루션임.
- 현재는 producer의 몇가지 옵션만 조정하여 테스트한 결과이므로,
- 잠정적인 결과이지만, kafka의 latency를 향상을 위해서는 많은 시도가 필요할 것 같음.
- 즉, 단일 요청의 latency는 확실히 느리지만,
- 대량의 처리를 기준으로 평균 latency를 비교하면 평균적인 latency는 많이 낮아짐.
Test Code : https://github.com/freepsw/kafka-latency-test
Consumer Driven Contracts and Your Microservice ArchitectureMarcin Grzejszczak
My talk from SpringOnePlatform about Spring Cloud Contract
Links:
* http://martinfowler.com/articles/consumerDrivenContracts.html - article about Consumer Driven Contracts by Ian Robinson
* https://github.com/marcingrzejszczak/springone-cdc-client - code for the client side of the presented example
* https://github.com/marcingrzejszczak/springone-cdc-server - code for the server side of the presented example
* https://cloud.spring.io/spring-cloud-contract/spring-cloud-contract.html - documentation of the Spring Cloud Contract project
During this brief walkthrough of the setup, configuration and use of the toolset we will show you how to find the trees from the forest in today's modern cloud environments and beyond.
The Windows Logging Cheat Sheet is the definitive guide on learning where to start with Windows Logging. How to Enable, Configure, Gather and Harvest events so you can catch a hacker in the act.
Continuous Delivery for Microservice Architectures with Concourse & Cloud Fou...VMware Tanzu
SpringOne Platform 2016
Speaker: Alex Ley; Product Manager, Pivotal
Building a continuous delivery pipeline for your micro-service based architecture can be a real challenge when using more conventional CI systems like Jenkins and GoCD. How do you get a clear picture of the CI workflow and status? What artifact was deployed and when? How is this all configured?
Introducing Concourse (https://concourse.ci), an open source pipeline based CI system that focuses on simplicity, usability and reproducibility. It offers isolated builds, a range of integrations and is built upon a proven technology stack from Cloud Foundry.
This talk will demonstrate creating a continuous delivery pipeline for a Spring microservice-based application that uses Spring Cloud. You will see how the pipeline tests services, integrates and then blue / green deploys to Cloud Foundry.
Expect to rush to your laptop to try out Concourse after this session!
SpringOne Platform 2017
Mark Michael, Pivotal; Glenn Oppegard, Pivotal
"Ever wonder what it takes to move a popular, high traffic web application from a traditional hosting environment to Cloud Foundry running on Amazon Web Services, and then moving it to Google Cloud Platform, without customers noticing?
In this talk, we’ll share our experience from beginning to end, starting with making the Pivotal Tracker code base cloud friendly, configuring app deployment and data services on Amazon Web Services, properly scaling the foundation and data services prior to going live and doing a seamless cutover in less than 3 hours. Then how and why we did it all again by moving to Google Cloud Platform...in a fraction of the time thanks to Cloud Foundry.
We’ll also share the benefits we’ve experienced by being on Cloud Foundry, including how it’s allowed us to fully automate our build, acceptance and Concourse deployment process inching ever closer to continuous delivery. Most importantly, we’ll reveal how it’s changed the way we do DevOps and in the process freed up countless developer hours to focus on improving our product instead of operations."
An edge gateway is an essential piece of infrastructure for large scale cloud based services. This presentation details the purpose, benefits and use cases for an edge gateway to provide security, traffic management and cloud cross region resiliency. How a gateway can be used to enhance continuous deployment, and help testing of new service versions and get service insights and more are discussed. Philosophical and architectural approaches to what belongs in a gateway vs what should be in services will be discussed. Real examples of how gateway services, built on top of Netflix's Open source project, Zuul, are used in front of nearly all of Netflix's consumer facing traffic will show how gateway infrastructure is used in real highly available, massive scale services.
Cloud Native Java with Spring Cloud ServicesVMware Tanzu
SpringOne Platform 2016
Speakers: Craig Walls; Spring Social Lead, Pivotal. Roy Clarkson; Spring Mobile Lead, Pivotal.
Developing cloud native applications presents several challenges. How do microservices discover each other? How do you configure them? How can you make them resilient to failure? How can you monitor the health of each microservice?
Spring Cloud addresses all of these concerns. Even so, you still must explicitly develop your own discovery server, configuration server, and circuit breaker dashboard for monitoring the circuit breakers in each microservice.
Spring Cloud Services for Pivotal Cloud Foundry picks up where Spring Cloud leaves off, offering a discovery server, configuration server, and Hystrix dashboard as services that can be bound to applications deployed in Pivotal Cloud Foundry, leaving you to focus on developing the services that drive your application. In this talk, we will introduce the capabilities provided by Spring Cloud Services and demonstrate how it makes simple work of deploying cloud native applications to Cloud Foundry.
SpringOne Platform 2016
Speaker: Justin Smith; Director, Pivotal
Credential hygiene is a perennial concern in all distributed computing systems. It’s certainly of utmost importance in cloud-native platforms. It’s common practice to encrypt credentials for storage and distribution, but they ultimately need to be made available as cleartext to the application that requires them. In this talk, we will discuss the options available and best practices for these sensitive operations. Topics include: key encrypting keys, hardware security modules, and relatively new and promising advances in muti-party computation.
Pivotal Cloud Foundry, Google Machine Learning, and SpringVMware Tanzu
SpringOne Platform 2017
Brian Gregory, Google; Brian Jimerson, Pivotal
Learn how Pivotal Cloud Foundry and Spring can accelerate development of applications that leverage Google Cloud's Machine Learning API. You will learn how Google's fully trained Machine Learning models can be easily consumed by Spring applications through the GCP Service Broker on Pivotal Cloud Foundry. This session will introduce the GCP Service Broker on Pivotal Cloud Foundry and the Google Cloud Machine Learning APIs. We will also demonstrate a working example of Spring applications using the Machine Learning APIs.
Latency analysis for your microservices using Spring Cloud & ZipkinVMware Tanzu
SpringOne Platform 2017
Marcin Grzejszczak, Pivotal; Reshmi Krishna, Pivotal
"Microservices are becoming increasingly popular. When a request spreads across several services, it quickly becomes challenging to analyse latency especially in real time. In this talk we will present an overview of the new features introduced in the latest Spring Cloud Sleuth release trains that helps you with latency analysis. We will cover recent additions and improvements including annotation based span creation and continuation, span adjusting.
We will then describe how to incorporate these features into an existing Spring Boot application so as to enable latency analysis of your microservices architecture.
Additionally we will deploy the application to Pivotal Cloud Foundry and will demonstrate how to do latency analysis out of the box with the help of PCF metrics and Spring Cloud Sleuth. By the end, you should feel empowered to add latency analysis into your microservices architecture."
The many benefits of a RESTful architecture has made it the standard way in which to design web based APIs. For example, the principles of REST state that we should leverage standard HTTP verbs which helps to keep our APIs simple. Server components that are considered RESTFul should be stateless which help to ensure that they can easily scale. We can leverage caching to gain further performance and scalability benefits.
However, the best practices of REST and security often seem to clash. How should a user be authenticated in a stateless application? How can a secured resource also support caching? Securing RESTful endpoints is further complicated by the the fact that security best practices evolve so rapidly.
In this talk Rob will discuss how to properly secure your RESTful endpoints. Along the way we will explore some common pitfalls when applying security to RESTful APIs. Finally, we will see how the new features in Spring Security can greatly simplify securing your RESTful APIs.
In the workshop with GCP, Home Depot & Cloud FoundryChristopher Grant
Christopher Grant and Eric Johnson talk about Home Depot's experience in piloting Spring apps running in Pivotal Cloud Foundry on top of Google Cloud Platform. They discuss Home Depot's journey using this cutting edge technology stack, including some...
SpringFramework 5에서 선보이는 Reactive와 같은 핵심기능이 2017 2017년 12월 샌프란시스코에서 열린 Spring One Platform행사에서 소개된 내용중 Spring Data, Spring Security, Spring WebFlux프로젝트에 녹아져 있는지 살펴봅니다. 또한 이러한 기능들이 어떻게 여러분의 시스템의 반응성을 높이고 효율적으로 동작하게 하는지 알아봅니다.
Lattice: A Cloud-Native Platform for Your Spring ApplicationsMatt Stine
As presented at SpringOne2GX 2015 in Washington, DC.
Lattice is a cloud-native application platform that enables you to run your applications in containers like Docker, on your local machine via Vagrant. Lattice includes features like:
Cluster scheduling
HTTP load balancing
Log aggregation
Health management
Lattice does this by packaging a subset of the components found in the Cloud Foundry elastic runtime. The result is an open, single-tenant environment suitable for rapid application development, similar to Kubernetes and Mesos Applications developed using Lattice should migrate unchanged to full Cloud Foundry deployments.
Lattice can be used by Spring developers to spin up powerful micro-cloud environments on their desktops, and can be useful for developing and testing cloud-native application architectures. Lattice already has deep integration with Spring Cloud and Spring XD, and you’ll have the opportunity to see deep dives into both at this year’s SpringOne 2GX. This session will introduce the basics:
Installing Lattice
Lattice’s Architecture
How Lattice Differs from Cloud Foundry
How to Package and Run Your Spring Apps on Lattice
Fast 5 Things You Can Do Now to Get Ready for the CloudVMware Tanzu
SpringOne Platform 2019
Fast 5 Things You Can Do Now to Get Ready for the Cloud
Speaker: Robert Sirchia, Practice Lead, Magenic Technologies
YouTube: https://youtu.be/WLw82cV0Lwk
SpringOne Platform 2016
Speaker: Kenny Bastani; Developer Advocate, Pivotal.
Cloud Foundry is a powerful structured platform. For many organizations their first experience with Cloud Foundry feels like jumping in a time machine and emerging in a world where the automations are done and--even more surprising--they work! But that’s just the beginning.
Cloud Foundry is a trustworthy, capable foundation you can build upon. It’s power lies in the flexibility provided through a structured, clear framework for extension. That’s what I want to show you in this talk.
There are several supported mechanisms for extending the platform. In this talk we’ll consider each method and which problem areas they address well. We’ll cover everything from user-provided services to first class services managed by BOSH.
You may be extending the platform to provide unique, new services to your users; or to bridge cloud-native applications running on Cloud Foundry with existing data centers and tools. No matter your use case you’ll gain a valuable understanding of the extensibility of the platform itself to truly make it your own.
Cloud Foundry gives platform operators and platform engineers an incredible framework for delivering transformative value to application developers. Learn how in this talk.
Extending the Platform with Spring Boot and Cloud FoundryKenny Bastani
When developing cloud native applications that are deployed and operated using a cloud platform, such as Cloud Foundry, there becomes a need to provision middleware services using the platform. The result of building platform services are that developers using the platform are able to take advantage of service offerings as bindings for their application deployments.
How to build Spring services for Cloud Native platforms using the Open Servic...VMware Tanzu
SpringOne Platform 2017
Matthew McNeeney, Pivotal; Sam Gunaratne, Pivotal
"The Open Service Broker API, a collaboration between Google, Red Hat, IBM, Pivotal and more, allows developers to deliver their services to applications running on multiple platforms across multiple clouds.
After providing an introduction to cloud-native applications and the need for stateful services, we will explain how the Open Service Broker API project can help Spring developers build a variety of services that can be deployed once and consumed anywhere.
We will then run a live demo where we build and deploy a service broker in Spring and consume it in via the Cloud Foundry marketplace."
SpringOne Platform 2017
Xiaokai He, Microsoft; Chris Anderson, Microsoft
Are you struggling with diagnosing your serverless functions? In this live coding session, we will quickly develop and deploy a serverless application to cloud, and then show you how we can go inside the black box and debugging functions locally and remotely.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
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
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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.