A quick comparison between Tomcat, Undertow, Jetty, Nginx Unit regarding features, performance, scalability, security, maintainability and extensibility
Java Performance Analysis on Linux with Flame GraphsBrendan Gregg
This document discusses using Linux perf_events (perf) profiling tools to analyze Java performance on Linux. It describes how perf can provide complete visibility into Java, JVM, GC and system code but that Java profilers have limitations. It presents the solution of using perf to collect mixed-mode flame graphs that include Java method names and symbols. It also discusses fixing issues with broken Java stacks and missing symbols on x86 architectures in perf profiles.
From cache to in-memory data grid. Introduction to Hazelcast.Taras Matyashovsky
This presentation:
* covers basics of caching and popular cache types
* explains evolution from simple cache to distributed, and from distributed to IMDG
* not describes usage of NoSQL solutions for caching
* is not intended for products comparison or for promotion of Hazelcast as the best solution
By Tom Wilkie, delivered at London Microservices User Group on 2/12/15
The rise of microservice-based applications has had many knock-on effects, not least on the complexity of monitoring your application. Order-of-magnitude increase in the number of moving parts and rate of change of the application require us to reassess traditional monitoring techniques.
In this talk we will discuss some different approaches to monitoring, visualising and tracing containerised, microservices-based applications. We’ll present different techniques to some of the emergent problems, and try not to rant too much.
Secrets of Performance Tuning Java on KubernetesBruno Borges
Java on Kubernetes may seem complicated, but after a bit of YAML and Dockerfiles, you will wonder what all that fuss was. But then the performance of your app in 1 CPU/1 GB of RAM makes you wonder. Learn how JVM ergonomics, CPU throttling, and GCs can help increase performance while reducing costs.
Kvm performance optimization for ubuntuSim Janghoon
This document discusses various techniques for optimizing KVM performance on Linux systems. It covers CPU and memory optimization through techniques like vCPU pinning, NUMA affinity, transparent huge pages, KSM, and virtio_balloon. For networking, it discusses vhost-net, interrupt handling using MSI/MSI-X, and NAPI. It also covers block device optimization through I/O scheduling, cache mode, and asynchronous I/O. The goal is to provide guidance on configuring these techniques for workloads running in KVM virtual machines.
Windows IOCP vs Linux EPOLL Performance ComparisonSeungmo Koo
1. The document compares the performance of IOCP and EPOLL for network I/O handling on Windows and Linux servers.
2. Testing showed that throughput was similar between IOCP and EPOLL, but IOCP had lower overall CPU usage without RSS/multi-queue enabled.
3. With RSS/multi-queue enabled on the NIC, CPU usage was nearly identical between IOCP and EPOLL.
Using eBPF for High-Performance Networking in CiliumScyllaDB
The Cilium project is a popular networking solution for Kubernetes, based on eBPF. This talk uses eBPF code and demos to explore the basics of how Cilium makes network connections, and manipulates packets so that they can avoid traversing the kernel's built-in networking stack. You'll see how eBPF enables high-performance networking as well as deep network observability and security.
HotSpot Synchronization, A Peek Under the Hood [JavaOne 2015 CON7570]David Buck
While there are many excellent resources about how to correctly use synchronization in your own code, what happens at the JVM level is still often a mystery for most users. In this session, I will pull back the curtain on HotSpot's locking implementation. We will look at the various types of locks that exist within HotSpot (thin, inflated, biased, etc.), how they are implemented, and the impact they have on your code's performance. We will also look at the various types of profiling information you can collect with tools like the Java Flight Recorder to better understand how locks are used by your application. Finally, we will look at the most common JVM tuning options for HotSpot and give some general tuning guidelines.
Tutorial: Using GoBGP as an IXP connecting routerShu Sugimoto
- Show you how GoBGP can be used as a software router in conjunction with quagga
- (Tutorial) Walk through the setup of IXP connecting router using GoBGP
Talk for AWS re:Invent 2014. Video: https://www.youtube.com/watch?v=7Cyd22kOqWc . Netflix tunes Amazon EC2 instances for maximum performance. In this session, you learn how Netflix configures the fastest possible EC2 instances, while reducing latency outliers. This session explores the various Xen modes (e.g., HVM, PV, etc.) and how they are optimized for different workloads. Hear how Netflix chooses Linux kernel versions based on desired performance characteristics and receive a firsthand look at how they set kernel tunables, including hugepages. You also hear about Netflix’s use of SR-IOV to enable enhanced networking and their approach to observability, which can exonerate EC2 issues and direct attention back to application performance.
Apache Knox setup and hive and hdfs Access using KNOXAbhishek Mallick
There are two ways to set up Apache Knox on a server: using Ambari or manually. The document then provides steps for configuring Knox using Ambari, including entering a master secret password and restarting services. It also provides commands for testing HDFS and Hive access through Knox by curling endpoints or using Beeline.
When does InnoDB lock a row? Multiple rows? Why would it lock a gap? How do transactions affect these scenarios? Locking is one of the more opaque features of MySQL, but it’s very important for both developers and DBA’s to understand if they want their applications to work with high performance and concurrency. This is a creative presentation to illustrate the scenarios for locking in InnoDB and make these scenarios easier to visualize. I'll cover: key locks, table locks, gap locks, shared locks, exclusive locks, intention locks, insert locks, auto-inc locks, and also conditions for deadlocks.
A Java Microservices Spring Boot and Docker case study.Subramanyam Vemala
This document provides steps to create a Java microservices project using Spring Boot and deploy it on Docker. It involves creating a Spring Boot project, adding dependencies, generating a JAR file, creating a Dockerfile, building a Docker image, and running the Docker container. The key steps are:
1. Create a Spring Boot project and add dependencies
2. Generate a JAR file
3. Create a Dockerfile
4. Build a Docker image and run the Docker container
5. Verify the application runs correctly by checking the browser output
Storm is a distributed and fault-tolerant realtime computation system. It was created at BackType/Twitter to analyze tweets, links, and users on Twitter in realtime. Storm provides scalability, reliability, and ease of programming. It uses components like Zookeeper, ØMQ, and Thrift. A Storm topology defines the flow of data between spouts that read data and bolts that process data. Storm guarantees processing of all data through its reliability APIs and guarantees no data loss even during failures.
This document provides an overview of Kubernetes including:
1) Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides container-centric infrastructure and allows for quickly deploying and scaling applications.
2) The main components of Kubernetes include Pods (groups of containers), Services (abstract access to pods), ReplicationControllers (maintain pod replicas), and a master node running key components like etcd, API server, scheduler, and controller manager.
3) The document demonstrates getting started with Kubernetes by enabling the master on one node and a worker on another node, then deploying and exposing a sample nginx application across the cluster.
The document discusses setting up and configuring an Apache Tomcat server. It includes steps to install Java, download and extract the Tomcat source package, set environment paths, start and stop the Tomcat server, and test functionality using HTML, JSP and Servlet files. The server runs on port 8080 by default and can host Java web applications built with Servlets and JSP.
This document provides an overview of patterns for scalability, availability, and stability in distributed systems. It discusses general recommendations like immutability and referential transparency. It covers scalability trade-offs around performance vs scalability, latency vs throughput, and availability vs consistency. It then describes various patterns for scalability including managing state through partitioning, caching, sharding databases, and using distributed caching. It also covers patterns for managing behavior through event-driven architecture, compute grids, load balancing, and parallel computing. Availability patterns like fail-over, replication, and fault tolerance are discussed. The document provides examples of popular technologies that implement many of these patterns.
Twitter - Architecture and Scalability lessonsAditya Rao
Twitter faced scaling issues as its user base grew to over 350,000 users. It addressed this through caching, partitioning its database, abuse prevention techniques, and an asynchronous, event-driven architecture. Lessons included planning for scaling from the start, optimizing databases and caching, and creating an open API to power growth.
Integrating microservices with apache camel on kubernetesClaus Ibsen
Apache Camel has fundamentally changed the way Java developers build system-to-system integrations by using enterprise integration patterns (EIP) with modern microservice architectures. In this session, we’ll show you best practices with Camel and EIPs, in the world of Spring Boot microservices running on Kubernetes. We'll also discuss practices how to build truly cloud-native distributed and fault-tolerant microservices and we’ll introduce the upcoming Camel 3.0 release, which includes serverless capabilities via Camel K. This talk is a mix with slides and live demos.
Empowering Your Java Applications with Quarkus. A New Era of Fast, Efficient,...Ivelin Yanev
In this informative presentation, we delve into the exciting world of Quarkus, a cutting-edge Java framework that has been revolutionizing the way we build and deploy Java applications. Quarkus is much more than just another framework; it represents a new era in Java development, characterized by speed, efficiency, and a cloud-native approach
This document discusses intrinsic methods in the HotSpot JVM. It provides background on what intrinsic methods are and how they are implemented and optimized in JVMs and native compilers. It gives examples of intrinsic methods in HotSpot VM like System.currentTimeMillis(), Unsafe.compareAndSwapInt(), and Math.log(). It also discusses intrinsic methods added in TaobaoJDK like TCrc32 and how to experiment implementing your own intrinsic methods in the C1 and C2 compilers.
High Concurrency Architecture and Laravel Performance TuningAlbert Chen
This document summarizes techniques for improving performance and concurrency in Laravel applications. It discusses caching routes and configuration files, using caching beyond just the database, implementing asynchronous event handling with message queues, separating database reads and writes, enabling OPcache and preloading in PHP 7.4, and analyzing use cases like a news site, ticketing system, and chat service. The document provides benchmarks showing performance improvements from these techniques.
오픈소스 검색엔진인 Elasticsearch 어떻게 저장하고 조회하는지 검색엔진의 개념에 대해서 간단히 살펴보고, Node.js 로 구현된 아주 간단한 예제를 소개합니다.
- 검색엔진과 Elasticsearch 소개
- Elasticsearch에서의 색인
- Elasticsearch에서의 조회
- Node.js 로 구현된 예제 소개
* 자바카페
자바카페 페이스북 : https://www.facebook.com/groups/javacafe/
자바카페 기술 블로그 : http://tech.javacafe.io/
Understanding MicroSERVICE Architecture with Java & Spring BootKashif Ali Siddiqui
This is a deep journey into the realm of "microservice architecture", and in that I will try to cover each inch of it, but with a fixed tech stack of Java with Spring Cloud. Hence in the end, you will be get know each and every aspect of this distributed design, and will develop an understanding of each and every concern regarding distributed system construct.
Scylla Summit 2022: Scylla 5.0 New Features, Part 1ScyllaDB
Discover the new features and capabilities of Scylla Open Source 5.0 directly from the engineers who developed it. This second block of lightning talks will cover the following topics:
- New IO Scheduler and Disk Parallelism
- Per-Service-Level Timeouts
- Better Workload Estimation for Backpressure and Out-of-Memory Conditions
- Large Partition Handling Improvements
- Optimizing Reverse Queries
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
This document provides a comparative analysis of the Jetty and Tomcat web servers. It discusses their technical differences, such as architecture (Jetty uses a modular component approach while Tomcat is monolithic) and performance (Jetty scales better with many idle connections). It also covers non-technical comparisons like market share (Jetty is gaining on Tomcat), development community (Jetty's is more stable and collaborative), and how Jetty more closely follows web standards. The document concludes that while Tomcat is widely used, Jetty's flexibility and responsiveness to changes make it a preferable option.
HotSpot Synchronization, A Peek Under the Hood [JavaOne 2015 CON7570]David Buck
While there are many excellent resources about how to correctly use synchronization in your own code, what happens at the JVM level is still often a mystery for most users. In this session, I will pull back the curtain on HotSpot's locking implementation. We will look at the various types of locks that exist within HotSpot (thin, inflated, biased, etc.), how they are implemented, and the impact they have on your code's performance. We will also look at the various types of profiling information you can collect with tools like the Java Flight Recorder to better understand how locks are used by your application. Finally, we will look at the most common JVM tuning options for HotSpot and give some general tuning guidelines.
Tutorial: Using GoBGP as an IXP connecting routerShu Sugimoto
- Show you how GoBGP can be used as a software router in conjunction with quagga
- (Tutorial) Walk through the setup of IXP connecting router using GoBGP
Talk for AWS re:Invent 2014. Video: https://www.youtube.com/watch?v=7Cyd22kOqWc . Netflix tunes Amazon EC2 instances for maximum performance. In this session, you learn how Netflix configures the fastest possible EC2 instances, while reducing latency outliers. This session explores the various Xen modes (e.g., HVM, PV, etc.) and how they are optimized for different workloads. Hear how Netflix chooses Linux kernel versions based on desired performance characteristics and receive a firsthand look at how they set kernel tunables, including hugepages. You also hear about Netflix’s use of SR-IOV to enable enhanced networking and their approach to observability, which can exonerate EC2 issues and direct attention back to application performance.
Apache Knox setup and hive and hdfs Access using KNOXAbhishek Mallick
There are two ways to set up Apache Knox on a server: using Ambari or manually. The document then provides steps for configuring Knox using Ambari, including entering a master secret password and restarting services. It also provides commands for testing HDFS and Hive access through Knox by curling endpoints or using Beeline.
When does InnoDB lock a row? Multiple rows? Why would it lock a gap? How do transactions affect these scenarios? Locking is one of the more opaque features of MySQL, but it’s very important for both developers and DBA’s to understand if they want their applications to work with high performance and concurrency. This is a creative presentation to illustrate the scenarios for locking in InnoDB and make these scenarios easier to visualize. I'll cover: key locks, table locks, gap locks, shared locks, exclusive locks, intention locks, insert locks, auto-inc locks, and also conditions for deadlocks.
A Java Microservices Spring Boot and Docker case study.Subramanyam Vemala
This document provides steps to create a Java microservices project using Spring Boot and deploy it on Docker. It involves creating a Spring Boot project, adding dependencies, generating a JAR file, creating a Dockerfile, building a Docker image, and running the Docker container. The key steps are:
1. Create a Spring Boot project and add dependencies
2. Generate a JAR file
3. Create a Dockerfile
4. Build a Docker image and run the Docker container
5. Verify the application runs correctly by checking the browser output
Storm is a distributed and fault-tolerant realtime computation system. It was created at BackType/Twitter to analyze tweets, links, and users on Twitter in realtime. Storm provides scalability, reliability, and ease of programming. It uses components like Zookeeper, ØMQ, and Thrift. A Storm topology defines the flow of data between spouts that read data and bolts that process data. Storm guarantees processing of all data through its reliability APIs and guarantees no data loss even during failures.
This document provides an overview of Kubernetes including:
1) Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides container-centric infrastructure and allows for quickly deploying and scaling applications.
2) The main components of Kubernetes include Pods (groups of containers), Services (abstract access to pods), ReplicationControllers (maintain pod replicas), and a master node running key components like etcd, API server, scheduler, and controller manager.
3) The document demonstrates getting started with Kubernetes by enabling the master on one node and a worker on another node, then deploying and exposing a sample nginx application across the cluster.
The document discusses setting up and configuring an Apache Tomcat server. It includes steps to install Java, download and extract the Tomcat source package, set environment paths, start and stop the Tomcat server, and test functionality using HTML, JSP and Servlet files. The server runs on port 8080 by default and can host Java web applications built with Servlets and JSP.
This document provides an overview of patterns for scalability, availability, and stability in distributed systems. It discusses general recommendations like immutability and referential transparency. It covers scalability trade-offs around performance vs scalability, latency vs throughput, and availability vs consistency. It then describes various patterns for scalability including managing state through partitioning, caching, sharding databases, and using distributed caching. It also covers patterns for managing behavior through event-driven architecture, compute grids, load balancing, and parallel computing. Availability patterns like fail-over, replication, and fault tolerance are discussed. The document provides examples of popular technologies that implement many of these patterns.
Twitter - Architecture and Scalability lessonsAditya Rao
Twitter faced scaling issues as its user base grew to over 350,000 users. It addressed this through caching, partitioning its database, abuse prevention techniques, and an asynchronous, event-driven architecture. Lessons included planning for scaling from the start, optimizing databases and caching, and creating an open API to power growth.
Integrating microservices with apache camel on kubernetesClaus Ibsen
Apache Camel has fundamentally changed the way Java developers build system-to-system integrations by using enterprise integration patterns (EIP) with modern microservice architectures. In this session, we’ll show you best practices with Camel and EIPs, in the world of Spring Boot microservices running on Kubernetes. We'll also discuss practices how to build truly cloud-native distributed and fault-tolerant microservices and we’ll introduce the upcoming Camel 3.0 release, which includes serverless capabilities via Camel K. This talk is a mix with slides and live demos.
Empowering Your Java Applications with Quarkus. A New Era of Fast, Efficient,...Ivelin Yanev
In this informative presentation, we delve into the exciting world of Quarkus, a cutting-edge Java framework that has been revolutionizing the way we build and deploy Java applications. Quarkus is much more than just another framework; it represents a new era in Java development, characterized by speed, efficiency, and a cloud-native approach
This document discusses intrinsic methods in the HotSpot JVM. It provides background on what intrinsic methods are and how they are implemented and optimized in JVMs and native compilers. It gives examples of intrinsic methods in HotSpot VM like System.currentTimeMillis(), Unsafe.compareAndSwapInt(), and Math.log(). It also discusses intrinsic methods added in TaobaoJDK like TCrc32 and how to experiment implementing your own intrinsic methods in the C1 and C2 compilers.
High Concurrency Architecture and Laravel Performance TuningAlbert Chen
This document summarizes techniques for improving performance and concurrency in Laravel applications. It discusses caching routes and configuration files, using caching beyond just the database, implementing asynchronous event handling with message queues, separating database reads and writes, enabling OPcache and preloading in PHP 7.4, and analyzing use cases like a news site, ticketing system, and chat service. The document provides benchmarks showing performance improvements from these techniques.
오픈소스 검색엔진인 Elasticsearch 어떻게 저장하고 조회하는지 검색엔진의 개념에 대해서 간단히 살펴보고, Node.js 로 구현된 아주 간단한 예제를 소개합니다.
- 검색엔진과 Elasticsearch 소개
- Elasticsearch에서의 색인
- Elasticsearch에서의 조회
- Node.js 로 구현된 예제 소개
* 자바카페
자바카페 페이스북 : https://www.facebook.com/groups/javacafe/
자바카페 기술 블로그 : http://tech.javacafe.io/
Understanding MicroSERVICE Architecture with Java & Spring BootKashif Ali Siddiqui
This is a deep journey into the realm of "microservice architecture", and in that I will try to cover each inch of it, but with a fixed tech stack of Java with Spring Cloud. Hence in the end, you will be get know each and every aspect of this distributed design, and will develop an understanding of each and every concern regarding distributed system construct.
Scylla Summit 2022: Scylla 5.0 New Features, Part 1ScyllaDB
Discover the new features and capabilities of Scylla Open Source 5.0 directly from the engineers who developed it. This second block of lightning talks will cover the following topics:
- New IO Scheduler and Disk Parallelism
- Per-Service-Level Timeouts
- Better Workload Estimation for Backpressure and Out-of-Memory Conditions
- Large Partition Handling Improvements
- Optimizing Reverse Queries
To watch all of the recordings hosted during Scylla Summit 2022 visit our website here: https://www.scylladb.com/summit.
This document provides a comparative analysis of the Jetty and Tomcat web servers. It discusses their technical differences, such as architecture (Jetty uses a modular component approach while Tomcat is monolithic) and performance (Jetty scales better with many idle connections). It also covers non-technical comparisons like market share (Jetty is gaining on Tomcat), development community (Jetty's is more stable and collaborative), and how Jetty more closely follows web standards. The document concludes that while Tomcat is widely used, Jetty's flexibility and responsiveness to changes make it a preferable option.
Upgrading to Apache Tomcat 7 covers the key changes in upgrading from older versions of Tomcat to version 7, including specification changes to support Servlet 3.0 and new features like asynchronous servlets and annotations. It outlines new management, performance, security, deployment, and embedding capabilities in Tomcat 7. The presentation also provides an overview of WebSocket support in Tomcat 7 and future plans, as well as useful resources for more information.
Ebs performance tuning session feb 13 2013---Presented by OracleAkash Pramanik
This document discusses performance tuning of Oracle E-Business Suite applications. It covers defining and isolating performance issues, approaches to investigating issues such as using SQL traces and TKPROF output, and AWR/Statspack reports. Best practices for maximizing performance are also presented, including upgrading components, applying recommended patches, performing regular health checks, and tuning the database, forms server, concurrent manager, and applications. The session agenda includes applications architecture, defining and isolating issues, SQL tracing, AWR reports, and best practices.
Performance of Microservice frameworks on different JVMsMaarten Smeets
A lot is happening in world of JVMs lately. Oracle changed its support policy roadmap for the Oracle JDK. GraalVM has been open sourced. AdoptOpenJDK provides binaries and is supported by (among others) Azul Systems, IBM and Microsoft. Large software vendors provide their own supported OpenJDK distributions such as Amazon (Coretto), RedHat and SAP. Next to OpenJDK there are also different JVM implementations such as Eclipse OpenJ9, Azul Systems Zing and GraalVM (which allows creation of native images). Other variables include different versions of the JDK used and whether you are running the JDK directly on the OS or within a container. Next to that, JVMs support different garbage collection algorithms which influence your application behavior. There are many options for running your Java application and choosing the right ones matters! Performance is often an important factor to take into consideration when choosing your JVM. How do the different JVMs compare with respect to performance when running different Microservice implementations? Does a specific framework provide best performance on a specific JVM implementation? I've performed elaborate measures of (among other things) start-up times, response times, CPU usage, memory usage, garbage collection behavior for these different JVMs with several different frameworks such as Reactive Spring Boot, regular Spring Boot, MicroProfile, Quarkus, Vert.x, Akka. During this presentation I will describe the test setup used and will show you some remarkable differences between the different JVM implementations and Microservice frameworks. Also differences between running a JAR or a native image are shown and the effects of running inside a container. This will help choosing the JVM with the right characteristics for your specific use-case!
The venerable Servlet Container still has some performance tricks up its sleeve - this talk will demonstrate Apache Tomcat's stability under high load, describe some do's (and some don'ts!), explain how to performance test a Servlet-based application, troubleshoot and tune the container and your application and compare the performance characteristics of the different Tomcat connectors. The presenters will share their combined experience supporting real Tomcat applications for over 20 years and show how a few small changes can make a big, big difference.
This document provides an agenda and slides for a presentation on Java 10. The agenda includes discussing Java version numbers, Java in containers and open source, migrating to JDK 10, and features of JDK 10. Key features presented are the Java module system, local variable type inference, application class data sharing, root certificates, and the experimental ZGC garbage collector. The slides provide details on each topic and are copyrighted by Oracle.
In this session you will learn:
1. Introduction to Struts Framework
2. Features
3. Evolution
4. Struts Demo
5. Declarative validation
6. Architecture
7. Validators
8. Interceptors
In this Java Hibernate Training session, you will learn Integrating Struts with Hibernate. Topics covered in this session are:
• Struts 2
• Struts Action Class
• Validation
• Control Tags
• Data Tags
For more information, visit this link:
https://www.mindsmapped.com/courses/software-development/learn-hibernate-fundamentals-from-scratch/
Performance of Microservice Frameworks on different JVMsMaarten Smeets
A lot is happening in world of JVMs lately. Oracle changed its support policy roadmap for the Oracle JDK. GraalVM has been open sourced. AdoptOpenJDK provides binaries and is supported by (among others) Azul Systems, IBM and Microsoft. Large software vendors provide their own supported OpenJDK distributions such as Amazon (Coretto), RedHat and SAP. Next to OpenJDK there are also different JVM implementations such as Eclipse OpenJ9, Azul Systems Zing and GraalVM (which allows creation of native images). Other variables include different versions of the JDK used and whether you are running the JDK directly on the OS or within a container. Next to that, JVMs support different garbage collection algorithms which influence your application behavior. There are many options for running your Java application and choosing the right ones matters! Performance is often an important factor to take into consideration when choosing your JVM. How do the different JVMs compare with respect to performance when running different Microservice implementations? Does a specific framework provide best performance on a specific JVM implementation? I've performed elaborate measures of (among other things) start-up times, response times, CPU usage, memory usage, garbage collection behavior for these different JVMs with several different frameworks such as Reactive Spring Boot, regular Spring Boot, MicroProfile, Quarkus, Vert.x, Akka. During this presentation I will describe the test setup used and will show you some remarkable differences between the different JVM implementations and Microservice frameworks. Also differences between running a JAR or a native image are shown and the effects of running inside a container. This will help choosing the JVM with the right characteristics for your specific use-case!
The document provides an overview of Weblogic concepts and administration. It defines key Weblogic terms like domains, admin servers, managed servers, and clusters. It also covers installing and configuring Weblogic, monitoring tools, and managing the application server using the admin console and WLST scripting. The presentation aims to help DBAs understand basic Weblogic architecture and administration.
Arun Gupta: London Java Community: Java EE 6 and GlassFish 3 Skills Matter
This document discusses Java EE 6 and GlassFish 3. It outlines that Java EE 6 and GlassFish 3 aim to provide a light-weight, extensible, and powerful platform. Key goals for Java EE 6 include making it more flexible, extensible by embracing open source frameworks, and easier to use and develop on. GlassFish 3 is the open source reference implementation of Java EE 6 and includes new features like clustering and centralized administration.
Java EE 6 & GlassFish 3: Light-weight, Extensible, and Powerful @ JAX London ...Arun Gupta
This document discusses Java EE 6 and GlassFish 3. It notes that Java EE 6 and GlassFish 3 aim to provide a light-weight, extensible, and powerful platform. Key features of Java EE 6 include improved ease of development through annotations, updated specifications like JSF 2.0 and EJB 3.1, and a new web profile. GlassFish 3 is the open source reference implementation of Java EE 6 and provides modularity, embeddability, and extensibility. Oracle will continue to develop and support GlassFish going forward.
Overview of Java EE 6 by Roberto Chinnici at SFJUGMarakana Inc.
The document provides an overview of the new features in the Java EE 6 platform, including new APIs, the Web Profile specification, improved extensibility, and highlights of APIs like JAX-RS and EJB 3.1. It summarizes the key components and extension points included in the Web Profile and describes how the platform focuses on pluggability, modular web applications, and common design patterns across APIs.
Dan Vega discussed new features and capabilities in Spring Boot 3 and beyond, including support for JDK 17, Jakarta EE 9, ahead-of-time compilation, observability with Micrometer, Docker Compose integration, and initial support for Project Loom's virtual threads in Spring Boot 3.2 to improve scalability. He provided an overview of each new feature and explained how they can help Spring applications.
Comparison between zookeeper, etcd 3 and other distributed coordination systemsImesha Sudasingha
This is a comparison between popular distributed coordination systems including zookeeper (which powers Apache Hadoop), etcd 3 (which powers Kubernetes), consul and hazelcast. This comparison was made in second half of 2016. Therefore, please note that some of these technologies have improved immensely over the time. Anyway, this presentation will provide an initial idea of each distributed coordination systems.
Cloud compiler - Minor Project by students of CBPGEC vipin kumar
The document describes a cloud compiler system that allows users to compile, run, test and debug code in various programming languages like Java, HTML, SQL, and C# without installing compilers locally. It discusses key aspects of the system like the objective, introduction, platforms and technologies used like Tomcat server, Java Server Pages, and Struts framework. Some benefits highlighted are that it is user friendly, supports multiple languages, and allows accessing programs from any device with an internet connection.
Java EE 6 & GlassFish = Less Code + More Power at CEJUGArun Gupta
The document discusses Java EE 6 and GlassFish, which provide developers with more power and flexibility while requiring less code. Key features of Java EE 6 like EJB 3.1, CDI, and JSF 2.0 incorporate more annotations and reduce the need for deployment descriptors. GlassFish is the open source reference implementation of Java EE 6 and offers benefits like modularity, embeddability, and support for cloud computing. Future versions of Java EE and GlassFish will focus on continued standards-based innovation.
Transform Your Future with Front-End Development TrainingVtechlabs
Kickstart your career in web development with our front-end web development course in Vadodara. Learn HTML, CSS, JavaScript, React, and more through hands-on projects and expert mentorship. Our front-end development course with placement includes real-world training, mock interviews, and job assistance to help you secure top roles like Front-End Developer, UI/UX Developer, and Web Designer.
Join VtechLabs today and build a successful career in the booming IT industry!
Why Ivalua: A Relational Acquisition Model (RAM 2025) ComparisonJon Hansen
What makes Jon Hansen’s ProcureTech assessment solution RAM unique?
RAM (short for “Relational Acquisition Model,” based on historical context), stands out due to its pioneering approach to procurement efficiency, developed in the late 1990s and early 2000s. While specific technical details about RAM’s current iteration as of March 1, 2025, are not fully detailed in recent public sources, its uniqueness can be inferred from Hansen’s documented history, writings, and interviews, particularly from Procurement Insights and related discussions.
RAM stands out for its agent-based adaptability, interactive design, early AI intelligence, people-process-tech integration, and proven government success—features ahead of its time in the 1990s and resonant with 2025’s procurement needs. It tackled inefficiencies with a practical, transparent approach, not just tech hype, saving millions and streamlining operations where others failed. While its current form isn’t fully public, its legacy as a ProcureTech pioneer remains unique, blending foresight with results in a way few contemporaries matched then or now.
Today’s ProcureTech solution providers—such as Coupa, GEP, Jaggaer, Sievo, Ivalua—can benefit from the Relational Acquisition Model (RAM) by drawing on its foundational principles and proven strengths, adapting them to enhance their offerings in the context of 2025’s complex procurement landscape. While RAM, developed in the late 1990s, lacks the technological scale of modern platforms, its agent-based design, focus on transparency, and human-centric efficiency offer valuable lessons.
Today’s ProcureTech providers can benefit from RAM by adopting its agent-based adaptability, transparent AI, interactive simplicity, human-tech balance, operational focus, and proven credibility. These could enhance responsiveness (e.g., tariff tweaks), trust (e.g., black box fears), and ROI (e.g., faster savings), potentially lifting efficiency by 10-20% or adoption by 15-30%. RAM’s lessons—distilled from a $12 million success—offer a roadmap to refine, not replace, modern solutions like Ivalua. It’s a legacy worth mining for a market chasing the next big thing.
UiPath Automation Developer Associate Training Series 2025 - Session 2DianaGray10
In session 2, we will introduce you to Data manipulation in UiPath Studio.
Topics covered:
Data Manipulation
What is Data Manipulation
Strings
Lists
Dictionaries
RegEx Builder
Date and Time
Required Self-Paced Learning for this session:
Data Manipulation with Strings in UiPath Studio (v2022.10) 2 modules - 1h 30m - https://academy.uipath.com/courses/data-manipulation-with-strings-in-studio
Data Manipulation with Lists and Dictionaries in UiPath Studio (v2022.10) 2 modules - 1h - https:/academy.uipath.com/courses/data-manipulation-with-lists-and-dictionaries-in-studio
Data Manipulation with Data Tables in UiPath Studio (v2022.10) 2 modules - 1h 30m - https:/academy.uipath.com/courses/data-manipulation-with-data-tables-in-studio
⁉️ For any questions you may have, please use the dedicated Forum thread. You can tag the hosts and mentors directly and they will reply as soon as possible.
Many MSPs overlook endpoint backup, missing out on additional profit and leaving a gap that puts client data at risk.
Join our webinar as we break down the top challenges of endpoint backup—and how to overcome them.
Technology use over time and its impact on consumers and businesses.pptxkaylagaze
In this presentation, I will discuss how technology has changed consumer behaviour and its impact on consumers and businesses. I will focus on internet access, digital devices, how customers search for information and what they buy online, video consumption, and lastly consumer trends.
30B Images and Counting: Scaling Canva's Content-Understanding Pipelines by K...ScyllaDB
Scaling content understanding for billions of images is no easy feat. This talk dives into building extreme label classification models, balancing accuracy & speed, and optimizing ML pipelines for scale. You'll learn new ways to tackle real-time performance challenges in massive data environments.
[Webinar] Scaling Made Simple: Getting Started with No-Code Web AppsSafe Software
Ready to simplify workflow sharing across your organization without diving into complex coding? With FME Flow Apps, you can build no-code web apps that make your data work harder for you — fast.
In this webinar, we’ll show you how to:
Build and deploy Workspace Apps to create an intuitive user interface for self-serve data processing and validation.
Automate processes using Automation Apps. Learn to create a no-code web app to kick off workflows tailored to your needs, trigger multiple workspaces and external actions, and use conditional filtering within automations to control your workflows.
Create a centralized portal with Gallery Apps to share a collection of no-code web apps across your organization.
Through real-world examples and practical demos, you’ll learn how to transform your workflows into intuitive, self-serve solutions that empower your team and save you time. We can’t wait to show you what’s possible!
Bridging the Gap from Telco to Techco with Agile ArchitectureBATbern
The Telco industry is undergoing a major IT transformation, shifting from Telco to Techco. This shift is driven by a breakneck pace of technological change that traditional architectures simply cannot keep up with. In my presentation, I will explore the profound impact of digitization on Telco architecture. Using examples from Swisscom's Network Division, I will show why Agile Architecture is crucial for cutting complexity, accelerating time-to-market, and sparking innovation within the organization. This approach isn't just strategic; it's vital for the future success of our industry. Join me to uncover how Swisscom is navigating this transformation and what lessons can be applied to your organization.
Formal Methods: Whence and Whither? [Martin Fränzle Festkolloquium, 2025]Jonathan Bowen
Alan Turing arguably wrote the first paper on formal methods 75 years ago. Since then, there have been claims and counterclaims about formal methods. Tool development has been slow but aided by Moore’s Law with the increasing power of computers. Although formal methods are not widespread in practical usage at a heavyweight level, their influence as crept into software engineering practice to the extent that they are no longer necessarily called formal methods in their use. In addition, in areas where safety and security are important, with the increasing use of computers in such applications, formal methods are a viable way to improve the reliability of such software-based systems. Their use in hardware where a mistake can be very costly is also important. This talk explores the journey of formal methods to the present day and speculates on future directions.
A Framework for Model-Driven Digital Twin EngineeringDaniel Lehner
Slides from my PhD Defense at Johannes Kepler University, held on Janurary 10, 2025.
The full thesis is available here: https://epub.jku.at/urn/urn:nbn:at:at-ubl:1-83896
There’s a common adage that it takes 10 years to develop a file system. As ScyllaDB reaches that 10 year milestone in 2025, it’s the perfect time to reflect on the last decade of ScyllaDB development – both hits and misses. It’s especially appropriate given that our project just reached a critical mass with certain scalability and elasticity goals that we dreamed up years ago. This talk will cover how we arrived at ScyllaDB X Cloud achieving our initial vision, and share where we’re heading next.
https://ncracked.com/7961-2/
Note: >> Please copy the link and paste it into Google New Tab now Download link
Brave is a free Chromium browser developed for Win Downloads, macOS and Linux systems that allows users to browse the internet in a safer, faster and more secure way than its competition. Designed with security in mind, Brave automatically blocks ads and trackers which also makes it faster,
As Brave naturally blocks unwanted content from appearing in your browser, it prevents these trackers and pop-ups from slowing Download your user experience. It's also designed in a way that strips Downloaden which data is being loaded each time you use it. Without these components
UiPath NY AI Series: Session 1: Introduction to Agentic AI with UiPathDianaGray10
🚀 Embracing the Future: Starting the Course with Agentic AI with UiPath
📢 Event Overview:
Join us for an exciting session on Agentic AI with UiPath! This event is perfect for professionals, tech enthusiasts, and automation leaders eager to learn about autonomous and intelligent digital agents. Discover how UiPath’s Agentic AI is shaping the future of automation! 🤖✨
📅 What You’ll Learn
🔹 UiPath’s Agentic AI Vision - Learn about UiPath’s AI-driven automation future.
🔹 Evolution of UiPath’s Automation - From RPA to AI-powered automation, see the journey! 🚀
🔹 What is Agentic Automation? - Understand how self-adaptive AI is changing workflows.
🔹 Principles of Agentic Automation - Key ideas like autonomy & adaptability.
🔹 Real-World Applications - Success stories & use cases from businesses leveraging AI.
🔹 UiPath’s Agentic AI Architecture - A peek into the technical side of intelligent automation. 🏗️
🔹 Q&A Session
👥 Who Should Attend?
Automation Developers & Tech Enthusiasts 💡
Business Leaders 📊
IT Architects & Tech Innovators 🏗️
UiPath Community Members 🤝
📌 Register now & be part of the future of AI-driven automation! 🔥
Using speech recognition and natural language processing, Automated Minutes creates an accurately transcribed meeting minutes draft in a near real-time, secure environment.
On March 11th at 2 PM EST OnBoard’s product team, Heather Hansson and Philip Hinz, explored the power of OnBoard’s Automated Minutes.
Using this webinar, you can learn:
Why Automated Minutes? Customizable, Secure, and Governance-Built for Boards
How Automated Minutes works to capture and create an initial draft of your minutes
Personalizing and formatting your Minutes through rich text editing tools
CFD Studio Credentials – Branding, Design & Developmenttrannghia2018
CFD STUDIO is an independent creative studio, specializing in Branding, UX/UI Design, Website & Mobile App Development. We craft high-quality digital experiences for brands and business goals.
Our Mission is to transform ideas into impactful brands by blending creativity, technology, and strategic thinking, delivering solutions that not only captivate but also drive success.
3. • The following Java specifications were considered for this analysis:
• Servlet (JSR 369)
• JSP (JSR 152)
• Expression Language (JSR 341)
• Web Sockets (JSR 356)
• Java NIO/NIO.2 (JSR 203)
• HTTP 2 (JEP 110)
3
Features
4. Features
4
Click to edit
Tomcat Undertow Jetty Nginx Unit
Servlet 4.0 4.0 4.0 3.1
JSP 2.3 2.3 2.3 2.3
Expression Language 3.0 3.0 3.0 3.0
Web Sockets 1.1 1.1 1.1 1.1
Java NIO/NIO.2 ✅ ✅ ✅ C backend
HTTP 2 ✅ ✅ ✅ ❌
5. • What is Performance?
• What is Scalability?
• Horizontal/Vertical Scalability
• Summary
5
Performance
6. • There are several definitions for performance
In here, the throughput definition used
6
What is Performance?
“Premature optimization is the root of all evil.”
- Donald Knuth
“Throughput is the rate of
production or the rate at which
something is processed.”
- Wikipedia on Throughput
7. • Any system is a network of queues
7
What is Performance?
8. 8
What is Scalability?
“Scalability is the property of a
system to handle a growing
amount of work by adding
resources to the system.”
- Wikipedia on Scalability
9. 9
Horizontal/Vertical Scalability
“Horizontal scaling means that
you scale by adding more machines
into your pool of resources whereas
Vertical scaling means that
you scale by adding more power
(CPU, RAM) to an existing machine.”
- Stack Overflow answer on Scalability
10. • In general, they have the same performance
• Nginx Unit is still in beta stage as in November 2019
• But it is very promising (multiple programming languages, DPDK, …)
• Jetty, Undertow and Tomcat have some minor performance
differences, but configuration can mitigate it
10
Performance Summary
Tomcat Undertow Jetty Nginx Unit
Keep Tomcat if already using it
Always configure NIO.2
Use Undertow/WildFly (JBoss) if
your webapp requires full JEE
support
Use Jetty when hardware
resources are limited
Not enough data
to recommend
11. • What is software maintainability?
• Used metrics
• Documentation
• Lines of code
• Test coverage
• Summary
11
Maintainability
12. “The ease with which a software
system or component can be
modified to correct faults,
improve performance or other
attributes, or adapt to a changed
environment.”
- IEEE Glossary of Software Eng.
12
What is Software Maintainability?
“The maintainability of software
depends on a few different factors.
In general, it must be easy to
understand the software
(how it works, what it does,
and why it does it the way it does),
easy to find what needs to be
change, easy to make changes
and easy to check
that the changes have not
introduced any bugs.”
- UK Software Sustainability Institute
13. • All projects are well documented
• Tomcat is the winner here once it is the most popular web
application server with many years of documented troubleshooting
including Undertow/Wildfly
13
Documentation
14. • Lines of code is a classic maintainability metric
14
Lines of Code
Total Lines of Code
Tomcat
(9.0.27)
Undertow
(Wildfly 18.0.0)
Jetty
(9.4.22)
Nginx Unit
(master branch 20191023)
430.507
820.318
(contains JEE apis too)
565.122 94.925
“All code is technical debt;
Some code just has a higher interest rate.”
- Paul McMahon
15. • Tomcat and Nginx Unit does not follow the maven project structure
• Undertow and Jetty are maven projects with a cleaner structure and
code base
• Test Coverage could not be checked because each web application
server has a different approach on test
• Tomcat has many tests against regressions
• Nginx Unit has many tests against java specifications (the JSR-XXX)
• Undertow and Jetty use standard maven for most of the components that
are covered but not all (as in 2019-10-23)
15
Test Coverage
16. 16
Maintainability Summary
• Tomcat has more documentation on troubleshooting
• Undertow, Jetty and Nginx Unit have a much cleaner code case with
more coverage
17. • OWASP has several general and specific recommendations
• Common Vulnerabilities and Exposures (CVE) are considered here
17
Security
18. Tomcat Vulnerabilities
18
Click to editYear
# of
Vulnerabiliti
es
DoS
Code
Execution
Overflow XSS
Directory
Traversal
Http
Response
Splitting
Bypass
something
Gain
Information
Gain
Privileges
CSRF
2016 12 2 1 2 5 1 3 1
2017 22 1 3 1 1 1 5 7 2
2018 8 1 1
2019 4 1 1
% Of All 16.4 4.1 3.5 13.5 7.0 0.0 20.5 18.7 4.1 2.3
Source: https://www.cvedetails.com/product/887/Apache-Tomcat.html
19. WildFly Vulnerabilities
19
Click to editYear
# of
Vulnerabiliti
es
DoS
Code
Execution
Overflow XSS
Directory
Traversal
Http
Response
Splitting
Bypass
something
Gain
Information
Gain
Privileges
CSRF
2016 2 1 1
2017 1 1
2018 2 1 1
2019
(N/A)
% Of All 22.2 0.0 11.1 0.0 11.1 11.1 0.0 22.2 0.0 11.1
Source: https://www.cvedetails.com/product/27107/Redhat-Jboss-Wildfly-Application-Server.html
20. Jetty Vulnerabilities
20
Click to editYear
# of
Vulnerabiliti
es
DoS
Code
Execution
Overflow XSS
Directory
Traversal
Http
Response
Splitting
Bypass
something
Gain
Information
Gain
Privileges
CSRF
2016 1 1
2017 2 1 1
2018 5 1 2 1
2019 4 1 1 2
% Of All 8.3 0.0 8.3 8.3 0.0 0.0 25.0 41.7 0.0 0.0
Source: https://www.cvedetails.com/product/34824/Eclipse-Jetty.html
21. 21
Security Summary
• There are no CVE data regarding Nginx Unit (as in November 2019)
• Once it’s written in C, we can infer it may have a greater number of
vulnerabilities than a pure java-based web application server
• Tomcat is clearly more vulnerable than the others
• Jetty comes next
• Undertow/Wildfly is the least vulnerable but there is not data for
2019
23. 23
Servlet Filter
What is a filter?
“A filter is a reusable piece of code that can
transform the content of HTTP requests,
responses, and header information.
Filters do not generally create a response or
respond to a request as servlets do, rather they
modify or adapt the requests for a resource,
modify or adapt responses from a resource.”
- Java Servlet 4.0 specification
24. 24
Tomcat Valve
What is a Tomcat Valve?
“A Valve element represents
a component that will be inserted
into the request processing pipeline
for the associated Catalina container
(Engine, Host, or Context).
Individual Valves have distinct
processing capabilities (…)”
- Tomcat documentation
25. 25
Undertow HttpHandler
Undertow HttpHandler Behaviour
“Handlers are generally chained together by
explicitly specifying the next handler at
construction time, there is no pipeline concept,
which means that a handler can pick the next
handler to invoke based on the current request.”
- Undertow documentation
26. 26
Jetty Handler
Jetty Handler Behaviour
“The Handler is the Jetty
component that deals with
HTTP requests and responses.”
- Jetty documentation
27. Nginx Unit Routes Behaviour
“Nginx Unit configuration offers a routes
object to enable elaborate internal
routing between listeners and apps.
Listeners pass requests to routes
or directly to apps.
Requests are matched against route
step conditions; a request matching all
conditions of a step is passed to the app
or the route that the step specifies.”
- Nginx Unit documentation
27
Nginx Unit Routes
28. 28
Extensibility Summary
• Nginx Unit is a clear winner once the route configuration forces the
web application decoupling
• Tomcat, Undertow, Jetty are equivalent on extensibility but their
architecture are very different
29. 29
Summary
Tomcat Undertow Jetty Nginx Unit
Features
Tomcat, Undertow and Jetty are equivalent
Use Undertow if JEE support is required
Still in development
Performance
Keep Tomcat if you
already have it
Undertow has an
equivalent performance
with Tomcat
Use Jetty for resource
constrained
environments such as
cloud
Not enough data to
recommend
Maintainability
Tomcat wins on
documentation and
troubleshooting
Undertow, Jetty and Unit are pretty much equivalent on maintainability with a
much cleaner code base
Security
Tomcat has more
vulnerabilities than the
others
Undertow is the least
vulnerable but there is no
data for 2019
Jetty is the second most
vulnerable
No CVEs for Unit
Extensibility
Tomcat, Undertow and Jetty are equivalent
Unit has a better approach by proposing decouple web applications to talk to each other with routes
31. • Apache Tomcat
• Undertow
• Jetty
• Nginx Unit
• Tomcat vs. Jetty vs. Undertow: Comparison of Spring Boot Embedded
Servlet Containers
• Top Java Application Servers: Tomcat vs. Jetty vs. GlassFish vs. WildFly
• JBoss vs. Tomcat: Choosing A Java Application Server
• Tomcat vs Jetty vs Wildfly runtime comparision
31
References
32. • Low level programming
Igor Zhirkov
Apress
• Systems Performance – enterprise and the cloud
Brendan Gregg
Prentice Hall
• Performance modeling and design of computer systems
Mor Harchol-Balter
Cambridge University Press
• Operating System Concepts
Silberschatz, Gagne, Galvin
John Wiley & Sons
32
References