Tier1app CEO & Founder, Ram Lakshmanan, spoke at All Day Devops 2017 about Java GC Logs. In this presentation, you can learn how to enable Java GC logs, commonly used GC log formats, tricks, patterns and tools to analyze them effectively.
Are you building high throughput, low latency application? Are you trying to figure out perfect JVM heap size? Are you struggling to choose right garbage collection algorithm and settings? Are you striving to achieve pause less GC? Do you know the right tools & best practices to tame the GC? Do you know to troubleshoot memory problems using GC logs? You will get complete answers to several such questions in this PPT.
MongoDB: Optimising for Performance, Scale & AnalyticsServer Density
MongoDB is easy to download and run locally but requires some thought and further understanding when deploying to production. At scale, schema design, indexes and query patterns really matter. So does data structure on disk, sharding, replication and data centre awareness. This talk will examine these factors in the context of analytics, and more generally, to help you optimise MongoDB for any scale.
Presented at MongoDB Days London 2013 by David Mytton.
Mythbusting: Understanding How We Measure the Performance of MongoDBMongoDB
Benchmarking, benchmarking, benchmarking. We all do it, mostly it tells us what we want to hear but often hides a mountain of misinformation. In this talk we will walk through the pitfalls that you might find yourself in by looking at some examples where things go wrong. We will then walk through how MongoDB performance is measured, the processes and methodology and ways to present and look at the information.
It's 10pm: Do You Know Where Your Writes Are?MongoDB
Speaker: Samantha Ritter, Software Engineer, MongoDB
Level: 200 (Intermediate)
Track: How We Build MongoDB
MongoDB 3.6 delivers three new features to help you develop resilient applications: retriable writes, a cluster-wide killOp command, and zombie cursor cleanup. These features share a common base, an idea called a logical session. This new cluster-wide concept of user state is the quiet magic that allows you to know, with certainty, the status of your operations. MongoDB engineer Samantha Ritter will describe the above features in-depth, discuss when and how logical sessions can be used by applications and administrators, and show you how we implemented sessions for large, distributed systems.
What You Will Learn:
- What logical sessions are and how they are implemented in the server
- How to leverage logical sessions for retriable writes
- How to pull the new cluster-wide killOp emergency break
Ensuring High Availability for Real-time Analytics featuring Boxed Ice / Serv...MongoDB
This will cover what to consider for high write throughput performance from hardware configuration through to the use of replica sets, multi-data centre deployments, monitoring and sharding to ensure your database is fast and stays online.
Robert Pankowecki - Czy sprzedawcy SQLowych baz nas oszukali?SegFaultConf
Wyobraź sobie, że w twojej aplikacji zachodzą jakieś zmiany (domain eventy). Chcielibyśmy te zmiany wystawić na zewnątrz, żebyśmy mogli na ich podstawie robić sobie raporty, read modele, sagi, synchronizować dane. Czy to zadanie okaże się być trudne czy proste, jeśli użyjemy bazy danych SQL. Co zyskaliśmy dzięki temu, że używam RDBMS/SQL a co utraciliśmy, być może, bezpowrotnie. W tej prezentacji opowiem wam jak chciałem zbudować pewną funkcjonalność dla biblioteki Rails Event Store, dlaczego okazało być się to trudniejsze niż myślałem, o modelu MVCC w PostgreSQL, czy jest sposób, żeby go obejść i uzyskać emulację trybu READ UNCOMMITTED. A może możnaby do całego problemu podejśc zupełnie inaczej i podłączyć się pod Write-Ahead-Log (WAL) i wygrać świat w ten sposób? Pokażę też jak moim zdaniem, korzystając z dokładnie tych samych konceptów, które stoją za Event Sourcingiem i bazami danych moglibyśmy budować API, tak bym za każdym razem pisząc integrację z serwisem X nie musiał się zastanawiać czy jego autorzy rozumieją pojęcie idempotent czy nie. Albo jak moglibyśmy osiągnąć prostotę dzięki używaniu Convergent Replicated Data Types (CRDT). Być może jako community stać nas na więcej niż REST nad CRUDem. Zastanowimy się, czy sprzedawcy SQLa zlasowali nam mózgi, sprawili, że zapomnieliśmy o najprostszym sposobie, który może działać i wprowadzili nas w maliny, w których aktualnie się znajdujemy. A może sami jesteśmy sobie winni? TLDR: Czy nasze aplikacje nie mogłyby działać tak jak pod spodem działają bazy danych? Czy to wszystko musi być takie ciężkie i skomplikowane jeśli chcemy mieć mikro-serwisy, zwłaszcza w małym zespole, który niekoniecznie lubi dostawiać 5 bazę danych do stacku technologicznego.
Are you building high throughput, low latency application? Are you trying to figure out perfect JVM heap size? Are you struggling to choose right garbage collection algorithm and settings? Are you striving to achieve pause less GC? Do you know the right tools & best practices to tame the GC? Do you know to troubleshoot memory problems using GC logs? You will get complete answers to several such questions in this PPT.
MongoDB: Optimising for Performance, Scale & AnalyticsServer Density
MongoDB is easy to download and run locally but requires some thought and further understanding when deploying to production. At scale, schema design, indexes and query patterns really matter. So does data structure on disk, sharding, replication and data centre awareness. This talk will examine these factors in the context of analytics, and more generally, to help you optimise MongoDB for any scale.
Presented at MongoDB Days London 2013 by David Mytton.
Mythbusting: Understanding How We Measure the Performance of MongoDBMongoDB
Benchmarking, benchmarking, benchmarking. We all do it, mostly it tells us what we want to hear but often hides a mountain of misinformation. In this talk we will walk through the pitfalls that you might find yourself in by looking at some examples where things go wrong. We will then walk through how MongoDB performance is measured, the processes and methodology and ways to present and look at the information.
It's 10pm: Do You Know Where Your Writes Are?MongoDB
Speaker: Samantha Ritter, Software Engineer, MongoDB
Level: 200 (Intermediate)
Track: How We Build MongoDB
MongoDB 3.6 delivers three new features to help you develop resilient applications: retriable writes, a cluster-wide killOp command, and zombie cursor cleanup. These features share a common base, an idea called a logical session. This new cluster-wide concept of user state is the quiet magic that allows you to know, with certainty, the status of your operations. MongoDB engineer Samantha Ritter will describe the above features in-depth, discuss when and how logical sessions can be used by applications and administrators, and show you how we implemented sessions for large, distributed systems.
What You Will Learn:
- What logical sessions are and how they are implemented in the server
- How to leverage logical sessions for retriable writes
- How to pull the new cluster-wide killOp emergency break
Ensuring High Availability for Real-time Analytics featuring Boxed Ice / Serv...MongoDB
This will cover what to consider for high write throughput performance from hardware configuration through to the use of replica sets, multi-data centre deployments, monitoring and sharding to ensure your database is fast and stays online.
Robert Pankowecki - Czy sprzedawcy SQLowych baz nas oszukali?SegFaultConf
Wyobraź sobie, że w twojej aplikacji zachodzą jakieś zmiany (domain eventy). Chcielibyśmy te zmiany wystawić na zewnątrz, żebyśmy mogli na ich podstawie robić sobie raporty, read modele, sagi, synchronizować dane. Czy to zadanie okaże się być trudne czy proste, jeśli użyjemy bazy danych SQL. Co zyskaliśmy dzięki temu, że używam RDBMS/SQL a co utraciliśmy, być może, bezpowrotnie. W tej prezentacji opowiem wam jak chciałem zbudować pewną funkcjonalność dla biblioteki Rails Event Store, dlaczego okazało być się to trudniejsze niż myślałem, o modelu MVCC w PostgreSQL, czy jest sposób, żeby go obejść i uzyskać emulację trybu READ UNCOMMITTED. A może możnaby do całego problemu podejśc zupełnie inaczej i podłączyć się pod Write-Ahead-Log (WAL) i wygrać świat w ten sposób? Pokażę też jak moim zdaniem, korzystając z dokładnie tych samych konceptów, które stoją za Event Sourcingiem i bazami danych moglibyśmy budować API, tak bym za każdym razem pisząc integrację z serwisem X nie musiał się zastanawiać czy jego autorzy rozumieją pojęcie idempotent czy nie. Albo jak moglibyśmy osiągnąć prostotę dzięki używaniu Convergent Replicated Data Types (CRDT). Być może jako community stać nas na więcej niż REST nad CRUDem. Zastanowimy się, czy sprzedawcy SQLa zlasowali nam mózgi, sprawili, że zapomnieliśmy o najprostszym sposobie, który może działać i wprowadzili nas w maliny, w których aktualnie się znajdujemy. A może sami jesteśmy sobie winni? TLDR: Czy nasze aplikacje nie mogłyby działać tak jak pod spodem działają bazy danych? Czy to wszystko musi być takie ciężkie i skomplikowane jeśli chcemy mieć mikro-serwisy, zwłaszcza w małym zespole, który niekoniecznie lubi dostawiać 5 bazę danych do stacku technologicznego.
Choosing a shard key can be difficult, and the factors involved largely depend on your use case. In fact, there is no such thing as a perfect shard key; there are design tradeoffs inherent in every decision. This presentation goes through those tradeoffs, as well as the different types of shard keys available in MongoDB, such as hashed and compound shard keys
This is a presentation given on October 24 by Michael Uzquiano of Cloud CMS (http://www.cloudcms.com) at the MongoDB Boston conference.
In this presentation, we cover Hazelcast - an in-memory data grid that provides distributed object persistence across multiple nodes in a cluster. When backed by MongoDB, objects are naturally written to Mongo by Hazelcast. The integration points are clean and easy to implement.
We cover a few simple cases along with code samples to provide the MongoDB community with some ideas of how to integrate Hazelcast into their own MongoDB Java applications.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
This is the fifth webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will introduce you to the aggregation framework.
New to MongoDB? We'll provide an overview of installation, high availability through replication, scale out through sharding, and options for monitoring and backup. No prior knowledge of MongoDB is assumed. This session will jumpstart your knowledge of MongoDB operations, providing you with context for the rest of the day's content.
Kenneth Truyers - Using Git as a NoSql database - Codemotion Milan 2018Codemotion
Git is not just a source control system. It's a content tracker we can (ab)use as a NoSQL database. Git has two features that traditional databases don't support: deduplicated storage and automatic history tracking. This talk discusses how to leverage it and what the benefits and drawbacks are. The goal of this talk is three fold: show attendees creative usage of existing tools, demonstrate the capabilities of Git and how to leverage its power and dive into Git's internals to gain a deeper understanding of a system a lot of developers use, but usually only know on a more superficial level.
MongoDB + Java - Everything you need to know Norberto Leite
Learn everything you need to know to get started building a MongoDB-based app in Java. We'll explore the relationship between MongoDB and various languages on the Java Virtual Machine such as Java, Scala, and Clojure. From there, we'll examine the popular frameworks and integration points between MongoDB and the JVM including Spring Data and object-document mappers like Morphia.
This tutorial will guide you through the many considerations when deploying a sharded cluster. We will cover the services that make up a sharded cluster, configuration recommendations for these services, shard key selection, use cases, and how data is managed within a sharded cluster. Maintaining a sharded cluster also has its challenges. We will review these challenges and how you can prevent them with proper design or ways to resolve them if they exist today. There will be lab sessions at the end of some chapters so please have your laptops with you.
The Best and Worst of Cassandra-stress Tool (Christopher Batey, The Last Pick...DataStax
Making sure your Data Model will work on the production cluster after 6 months as well as it does on your laptop is an important skill. It's one that we use every day with our clients at The Last Pickle, and one that relies on tools like the cassandra-stress. Knowing how the data model will perform under stress once it has been loaded with data can prevent expensive re-writes late in the project.
In this talk Christopher Batey, Consultant at The Last Pickle, will shed some light on how to use the cassandra-stress tool to test your own schema, graph the results and even how to extend the tool for your own use cases. While this may be called premature optimisation for a RDBS, a successful Cassandra project depends on it's data model.
About the Speaker
Christopher Batey Consultant / Software Engineer, The Last Pickle
Christopher (@chbatey) is a part time consultant at The Last Pickle where he works with clients to help them succeed with Apache Cassandra as well as a freelance software engineer working in London. Likes: Scala, Haskell, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Hates: Untested software, code ownership. You can checkout his blog at: http://www.batey.info
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...MongoDB
In version 2.4, MongoDB introduces hash-based sharding, a new option for distributing data in sharded collections. Hash-based sharding and range-based sharding present different advantages for MongoDB users deploying large scale systems. In this talk, we'll provide an overview of this new feature and discuss when to use hash-based sharding or range-based sharding.
A quick overview of Elasticsearch usage at Dailymotion for video search
Talk given at Elasticsearch Meetup France #7
June 10, 2014
http://www.meetup.com/elasticsearchfr/events/171946592/
Are you building high throughput, low latency application? Are you trying to figure out perfect JVM heap size? Are you struggling to choose right garbage collection algorithm and settings? Are you striving to achieve pause less GC? Do you know the right tools & best practices to tame the GC? Do you know to troubleshoot memory problems using GC logs? You will get complete answers to several such questions in this presentation.
Choosing a shard key can be difficult, and the factors involved largely depend on your use case. In fact, there is no such thing as a perfect shard key; there are design tradeoffs inherent in every decision. This presentation goes through those tradeoffs, as well as the different types of shard keys available in MongoDB, such as hashed and compound shard keys
This is a presentation given on October 24 by Michael Uzquiano of Cloud CMS (http://www.cloudcms.com) at the MongoDB Boston conference.
In this presentation, we cover Hazelcast - an in-memory data grid that provides distributed object persistence across multiple nodes in a cluster. When backed by MongoDB, objects are naturally written to Mongo by Hazelcast. The integration points are clean and easy to implement.
We cover a few simple cases along with code samples to provide the MongoDB community with some ideas of how to integrate Hazelcast into their own MongoDB Java applications.
Back to Basics Webinar 5: Introduction to the Aggregation FrameworkMongoDB
This is the fifth webinar of a Back to Basics series that will introduce you to the MongoDB database. This webinar will introduce you to the aggregation framework.
New to MongoDB? We'll provide an overview of installation, high availability through replication, scale out through sharding, and options for monitoring and backup. No prior knowledge of MongoDB is assumed. This session will jumpstart your knowledge of MongoDB operations, providing you with context for the rest of the day's content.
Kenneth Truyers - Using Git as a NoSql database - Codemotion Milan 2018Codemotion
Git is not just a source control system. It's a content tracker we can (ab)use as a NoSQL database. Git has two features that traditional databases don't support: deduplicated storage and automatic history tracking. This talk discusses how to leverage it and what the benefits and drawbacks are. The goal of this talk is three fold: show attendees creative usage of existing tools, demonstrate the capabilities of Git and how to leverage its power and dive into Git's internals to gain a deeper understanding of a system a lot of developers use, but usually only know on a more superficial level.
MongoDB + Java - Everything you need to know Norberto Leite
Learn everything you need to know to get started building a MongoDB-based app in Java. We'll explore the relationship between MongoDB and various languages on the Java Virtual Machine such as Java, Scala, and Clojure. From there, we'll examine the popular frameworks and integration points between MongoDB and the JVM including Spring Data and object-document mappers like Morphia.
This tutorial will guide you through the many considerations when deploying a sharded cluster. We will cover the services that make up a sharded cluster, configuration recommendations for these services, shard key selection, use cases, and how data is managed within a sharded cluster. Maintaining a sharded cluster also has its challenges. We will review these challenges and how you can prevent them with proper design or ways to resolve them if they exist today. There will be lab sessions at the end of some chapters so please have your laptops with you.
The Best and Worst of Cassandra-stress Tool (Christopher Batey, The Last Pick...DataStax
Making sure your Data Model will work on the production cluster after 6 months as well as it does on your laptop is an important skill. It's one that we use every day with our clients at The Last Pickle, and one that relies on tools like the cassandra-stress. Knowing how the data model will perform under stress once it has been loaded with data can prevent expensive re-writes late in the project.
In this talk Christopher Batey, Consultant at The Last Pickle, will shed some light on how to use the cassandra-stress tool to test your own schema, graph the results and even how to extend the tool for your own use cases. While this may be called premature optimisation for a RDBS, a successful Cassandra project depends on it's data model.
About the Speaker
Christopher Batey Consultant / Software Engineer, The Last Pickle
Christopher (@chbatey) is a part time consultant at The Last Pickle where he works with clients to help them succeed with Apache Cassandra as well as a freelance software engineer working in London. Likes: Scala, Haskell, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Hates: Untested software, code ownership. You can checkout his blog at: http://www.batey.info
MongoDB San Francisco 2013: Hash-based Sharding in MongoDB 2.4 presented by B...MongoDB
In version 2.4, MongoDB introduces hash-based sharding, a new option for distributing data in sharded collections. Hash-based sharding and range-based sharding present different advantages for MongoDB users deploying large scale systems. In this talk, we'll provide an overview of this new feature and discuss when to use hash-based sharding or range-based sharding.
A quick overview of Elasticsearch usage at Dailymotion for video search
Talk given at Elasticsearch Meetup France #7
June 10, 2014
http://www.meetup.com/elasticsearchfr/events/171946592/
Are you building high throughput, low latency application? Are you trying to figure out perfect JVM heap size? Are you struggling to choose right garbage collection algorithm and settings? Are you striving to achieve pause less GC? Do you know the right tools & best practices to tame the GC? Do you know to troubleshoot memory problems using GC logs? You will get complete answers to several such questions in this presentation.
There are at least 40 to 50 different formats of GC logs. Here, we explained the commonly used GC log formats, tricks, patterns and tools to analyze them effectively.
Description
At Stitch Fix most application logs are output in a structured JSON format for simpler debugging and downstream consumption.
In this talk we’ll cover in more detail why structured logs are useful and provide leverage, caveats to using them, and how simple it is to get one going with Python.
Abstract
At Stitch Fix most application logs are output in a structured JSON format for simpler debugging and downstream consumption. For example, data scientists can add a field to their application log and it will automatically turn up as a parsed field in Elasticsearch for easy dashboarding and querying via Kibana, or be easily found and queried in Presto. In this talk we’ll cover in more detail why structured logs are useful and provide leverage, caveats to using them, and how simple it is to get one going with Python.
Uncover the hidden challenges that plague production environments in this eye-opening session. Join us as we explore the five most common performance problems that emerge in live systems. Gain invaluable insights into detecting these issues early on, before they wreak havoc on your operations. Discover practical solutions that empower you to address these challenges head-on, ensuring optimal performance and seamless user experiences.
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
This session brings to your attention how several millions of dollars are wasted and what you can do to save money. Optimizing garbage collection performance not only saves money, but also improves the overall customer experience as well.
(DAT402) Amazon RDS PostgreSQL:Lessons Learned & New FeaturesAmazon Web Services
Learn the specifics of Amazon RDS for PostgreSQL’s capabilities and extensions that make it powerful. This session begins with a brief overview of the RDS PostgreSQL service, how it provides High Availability & Durability and will then deep dive into the new features that we have released since re:Invent 2014, including major version upgrade and newly added PostgreSQL extensions to RDS PostgreSQL. During the session, we will also discuss lessons learned running a large fleet of PostgreSQL instances, including specific recommendations. In addition we will present benchmarking results looking at differences between the 9.3, 9.4 and 9.5 releases.
Talk for PerconaLive 2016 by Brendan Gregg. Video: https://www.youtube.com/watch?v=CbmEDXq7es0 . "Systems performance provides a different perspective for analysis and tuning, and can help you find performance wins for your databases, applications, and the kernel. However, most of us are not performance or kernel engineers, and have limited time to study this topic. This talk summarizes six important areas of Linux systems performance in 50 minutes: observability tools, methodologies, benchmarking, profiling, tracing, and tuning. Included are recipes for Linux performance analysis and tuning (using vmstat, mpstat, iostat, etc), overviews of complex areas including profiling (perf_events), static tracing (tracepoints), and dynamic tracing (kprobes, uprobes), and much advice about what is and isn't important to learn. This talk is aimed at everyone: DBAs, developers, operations, etc, and in any environment running Linux, bare-metal or the cloud."
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
5. Key Performance Indicators
Latency Throughput
99.925%
Foot Print
Memory: 2GB
CPU: 30%
GC event’s pause time Percentage of time spent in processing customer
transactions vs time spent in GC activity.
i.e. productive work vs non-productive work
Memory and CPU utilization of
the application
1 2 3
6. Enable GC logs (always)
Till Java 8:
-XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:<file-path>
From Java 9:
-Xlog:gc*:file=<file-path>
8. Memory
Young old metaspace others
-Xmn
-Xmx -XX:MetaspaceSize
Young: Newly created Objects
Old: New objects that survived one or more minor
GC promoted here
Metaspace: Classes, Methods, metadata
Others Description
Thread Stacks Each thread has a separate memory space.
Controlled by -Xss
Garbage Collection Threads, Memory to store GC info
Code Generation Converting bytecode to native code
Socket Buffers TCP Connections (Receive buffer ~37k, Send Buffer
~2.5k)
JNI JNI program also allocate memory
9. GC Log format varies
JVM Vendor
Oracle
HP
IBM
Azul
…
Java Version
1.4
5
6
7
8
9
GC algorithm
Serial
Parallel
CMS
G1
Shennandoh
Arguments
-XX:+PrintGC
-XX:+PrintGCDateStamps
-XX:+PrintGCDetails
-XX:+PrintGCTimeStamps
-XX:+PrintPromotionFailure
-
XX:+PrintGCApplicationStoppedT
ime
-XX:+PrintClassHistogram
-XX:PrintFLSStatistics=1
-XX:+PrintCodeCache
11. CMS Log formatBefore GC:
Statistics for BinaryTreeDictionary:
------------------------------------
Total Free Space: 2524251
Max Chunk Size: 2519552
Number of Blocks: 13
Av. Block Size: 194173
Tree Height: 8
2016-05-03T04:27:37.503+0000: 30282.678: [ParNew
Desired survivor size 214728704 bytes, new threshold 1 (max 1)
- age 1: 85782640 bytes, 85782640 total
: 3510063K->100856K(3774912K), 0.0516290 secs] 9371816K->6022161K(14260672K)After GC:
Statistics for BinaryTreeDictionary:
------------------------------------
Total Free Space: 530579346
Max Chunk Size: 332576815
Number of Blocks: 7178
Av. Block Size: 73917
Tree Height: 44
After GC:
Statistics for BinaryTreeDictionary:
------------------------------------
Total Free Space: 2524251
Max Chunk Size: 2519552
Number of Blocks: 13
Av. Block Size: 194173
Tree Height: 8
, 0.0552970 secs] [Times: user=0.67 sys=0.00, real=0.06 secs]
14. Android Dalvik VM GC Log Format
07-01 15:56:20.035: I/Choreographer(30615): Skipped 141 frames! The application may be
doing too much work on its main thread.
07-01 15:56:20.275: D/dalvikvm(30615): GC_FOR_ALLOC freed 4774K, 45% free
49801K/89052K, paused 168ms, total 168ms
07-01 15:56:20.295: I/dalvikvm-heap(30615): Grow heap (frag case) to 56.900MB for
4665616-byte allocation
07-01 15:56:21.315: D/dalvikvm(30615): GC_FOR_ALLOC freed 1359K, 42% free
55045K/93612K, paused 95ms, total 95ms
07-01 15:56:21.965: D/dalvikvm(30615): GC_CONCURRENT freed 6376K, 40% free
56861K/93612K, paused 16ms+8ms, total 126ms
07-01 15:56:21.965: D/dalvikvm(30615): WAIT_FOR_CONCURRENT_GC blocked 111ms
07-01 15:56:21.965: D/dalvikvm(30615): WAIT_FOR_CONCURRENT_GC blocked 97ms
15. Android ART GC Log Format
07-01 16:00:44.690: I/art(801): Explicit concurrent mark sweep GC freed
65595(3MB) AllocSpace objects, 9(4MB) LOS objects, 810% free,
38MB/58MB, paused 1.195ms total 87.219ms
07-01 16:00:46.517: I/art(29197): Background partial concurrent mark sweep
GC freed 74626(3MB) AllocSpace objects, 39(4MB) LOS objects, 1496% free,
25MB/32MB, paused 4.422ms total 1.371747s
07-01 16:00:48.534: I/Choreographer(29197): Skipped 30 frames! The
application may be doing too much work on its main thread.
07-01 16:00:48.566: I/art(29197): Background sticky concurrent mark sweep
GC freed 70319(3MB) AllocSpace objects, 59(5MB) LOS objects, 825% free,
49MB/56MB, paused 6.139ms total 52.868ms
07-01 16:00:49.282: I/Choreographer(29197): Skipped 33 frames! The
application may be doing too much work on its main thread.
16. ‘Free’ GC log analysis tools
1. GCeasy.io
2. IBM Pattern Modeling and Analysis Tool for Java Garbage Collector
3. HP Jmeter
4. Google Garbage Cat - CMS
29. 3. Choice of GC Algorithm
• Serial
• Parallel
• CMS
• G1 GC
• Shenandoah
30. GC Time
• Real is wall clock time – time from start to finish of the call. This is all elapsed
time including time slices used by other processes and time the process spends
blocked (for example if it is waiting for I/O to complete).
• Sys is the amount of CPU time spent in the kernel within the process. This means
executing CPU time spent in system calls within the kernel, as opposed to library
code, which is still running in user-space. Like ‘user’, this is only CPU time used by
the process.
• User is the amount of CPU time spent in user-mode code (outside the kernel)
within the process. This is only actual CPU time used in executing the process.
Other processes and time the process spends blocked do not count towards this
figure.
• User+Sys will tell you how much actual CPU time your process used. Note that
this is across all CPUs, so if the process has multiple threads it could potentially
exceed the wall clock time reported by Real.
[Times: user=11.53 sys=1.38, real=1.03 secs]
32. 4. Process Swapping
• Sometimes due to lack of memory (RAM), Operating system could be
swapping your application from memory.
• Below script will show all the process that are being swapped:
https://blog.gceasy.io/2016/11/22/reduce-long-gc-pauses/
34. 5. Background IO Traffic
• If there is a heavy file system I/O activity (i.e. lot of reads and writes
are happening) it can also cause long GC pauses.
Tit-bit: How to monitor I/O activity?
sar -d -p 1
‘System Activity Report’ command reports read/write activity made every 1 second
35. 6. Less GC Threads
• WARNING: Adding too many GC threads will consume a lot of CPU
and takes away a resource from your application. Thus you need to
conduct thorough testing before increasing the GC thread count.
36. 7. System.gc() calls
• When System.gc() or Runtime.getRuntime().gc() calls causes stop-the-
world Full GCs.
• What triggers System.gc() calls
• Your own application
• 3rd party libraries, frameworks, sometimes even application servers that you
use could be invoking System.gc() method.
• External tools (like VisualVM) through use of JMX
• RMI
– Dsun.rmi.dgc.server.gcInterval=n
– Dsun.rmi.dgc.client.gcInterval=n
• Can be disabled by -XX:+DisableExplicitGC
37. Reactive Proactive analysis @ scale
• GC Log analysis REST API: https://blog.gceasy.io/2016/06/18/garbage-
collection-log-analysis-api/
• Very simple. One single CURL command:
curl -X POST --data-binary @./my-app-gc.log
http://api.gceasy.io/analyzeGC?apiKey= --header "Content-Type:text"