This webinar will discuss migrating from Java EE applications to cloud-native reactive systems. It will cover how reactive and microservice architectures are better suited for today's applications that need to efficiently handle streaming data and frequent updates. The webinar will explore how to utilize reactive principles like messaging and isolation to build resilient distributed systems. It will also provide resources on modernizing Java EE applications using Lightbend technologies and patterns for reactive microservices.
Digital Transformation with Kubernetes, Containers, and MicroservicesLightbend
See the full presentation here: https://www.lightbend.com/blog/digital-transformation-kubernetes-containers-microservices
In this talk by David Ogren, Principal Enterprise Architect at Lightbend, we draw from experiences helping our clients successfully create, migrate to, and manage cloud-native system architectures.
Lessons From HPE: From Batch To Streaming For 20 Billion Sensors With Lightbe...Lightbend
In this guest webinar with Chris McDermott, Lead Data Engineer at HPE, learn how HPE InfoSight–powered by Lightbend Platform–has emerged as the go-to solution for providing real-time metrics and predictive analytics across various network, server, storage, and data center technologies.
FOR THE FULL VIDEO, RECORDING & PRESENTATION:
https://typesafe.com/blog/going-reactive-in-java-with-typesafe-reactive-platform
--
In this presentation by Jamie Allen, we do a deep dive into the Typesafe Reactive Platform from the Java developer’s perspective, to learn how Typesafe supports the entire Reactive application development lifecycle.
Reactive application development is becoming mainstream and considered a mission-critical need for future growth. This new wave of business applications are message-driven, elastic, resilient and responsive by nature, designed to scale elastically and maintain responsiveness during even large failures. With the Typesafe Reactive Platform (RP), including Play Framework and Akka, Java developers can start to use tools designed for building distributed systems that deliver highly-responsive user experiences. Regardless of whether you code in Java or Scala, Typesafe RP provides a resilient and message-driven application stack that scales effortlessly on multicore and cloud computing architectures.
In this webinar by Jonas Bonér, creator of Akka and CTO/Co-Founder of Lightbend, we take a look at Cloudstate, an OSS tool built on Akka, gRPC, Knative, GraalVM, and Kubernetes. Cloudstate lets you model, manage, and scale stateful services while preserving responsiveness by designing for resilience and elasticity.
The Reactive Principles: Eight Tenets For Building Cloud Native ApplicationsLightbend
In this presentation by Jonas Bonér, creator of Akka and founder/CTO of Lightbend, we review a set of eight Reactive Principles that enable the design and implementation of Cloud Native applications–applications that are highly concurrent, distributed, performant, scalable, and resilient, while at the same time conserving resources when deploying, operating, and maintaining them.
How To Build, Integrate, and Deploy Real-Time Streaming Pipelines On KubernetesLightbend
In this webinar with Craig Blitz and Kiki Carter of Lightbend, we review how Lightbend’s Pipelines module enables you to develop components ("streamlets") using the appropriate technology, wire them together as pipelines, and deploy them with Kubernetes without all the manual, time-consuming labor.
Benefits Of The Actor Model For Cloud Computing: A Pragmatic Overview For Jav...Lightbend
As enterprise development teams increase the time they spend using cloud computing, many are challenged by a move from a scale-up (monolithic) to a scale-out (distributed) architecture. Reactive system development and microservices are two evolving answers that architects are embracing, but making them work well at scale calls for a departure from the traditional approach of object-oriented programming models and defensive programming through try-catch, which is now being replaced by a highly-resilient supervision model and a "let it crash" philosophy.
In this webinar for Architects, guest speaker Jeffrey Hammond, Forrester Vice-President and Principal Analyst joins Jonas Bonér, CTO/Co-founder of Lightbend and creator of Akka, the actor-based, message-driven runtime for the JVM, to discuss one emerging programming pattern that’s gaining popularity with teams developing for the cloud––the Actor model. They will discuss some history, why the Actor model is a better fit for large, scale-out systems and microservices delivery, the types of workloads using it today, and how to implement an Actor-based system in your existing Java environment.
Digital Transformation with Kubernetes, Containers, and MicroservicesLightbend
See the full presentation here: https://www.lightbend.com/blog/digital-transformation-kubernetes-containers-microservices
In this talk by David Ogren, Principal Enterprise Architect at Lightbend, we draw from experiences helping our clients successfully create, migrate to, and manage cloud-native system architectures.
Lessons From HPE: From Batch To Streaming For 20 Billion Sensors With Lightbe...Lightbend
In this guest webinar with Chris McDermott, Lead Data Engineer at HPE, learn how HPE InfoSight–powered by Lightbend Platform–has emerged as the go-to solution for providing real-time metrics and predictive analytics across various network, server, storage, and data center technologies.
FOR THE FULL VIDEO, RECORDING & PRESENTATION:
https://typesafe.com/blog/going-reactive-in-java-with-typesafe-reactive-platform
--
In this presentation by Jamie Allen, we do a deep dive into the Typesafe Reactive Platform from the Java developer’s perspective, to learn how Typesafe supports the entire Reactive application development lifecycle.
Reactive application development is becoming mainstream and considered a mission-critical need for future growth. This new wave of business applications are message-driven, elastic, resilient and responsive by nature, designed to scale elastically and maintain responsiveness during even large failures. With the Typesafe Reactive Platform (RP), including Play Framework and Akka, Java developers can start to use tools designed for building distributed systems that deliver highly-responsive user experiences. Regardless of whether you code in Java or Scala, Typesafe RP provides a resilient and message-driven application stack that scales effortlessly on multicore and cloud computing architectures.
In this webinar by Jonas Bonér, creator of Akka and CTO/Co-Founder of Lightbend, we take a look at Cloudstate, an OSS tool built on Akka, gRPC, Knative, GraalVM, and Kubernetes. Cloudstate lets you model, manage, and scale stateful services while preserving responsiveness by designing for resilience and elasticity.
The Reactive Principles: Eight Tenets For Building Cloud Native ApplicationsLightbend
In this presentation by Jonas Bonér, creator of Akka and founder/CTO of Lightbend, we review a set of eight Reactive Principles that enable the design and implementation of Cloud Native applications–applications that are highly concurrent, distributed, performant, scalable, and resilient, while at the same time conserving resources when deploying, operating, and maintaining them.
How To Build, Integrate, and Deploy Real-Time Streaming Pipelines On KubernetesLightbend
In this webinar with Craig Blitz and Kiki Carter of Lightbend, we review how Lightbend’s Pipelines module enables you to develop components ("streamlets") using the appropriate technology, wire them together as pipelines, and deploy them with Kubernetes without all the manual, time-consuming labor.
Benefits Of The Actor Model For Cloud Computing: A Pragmatic Overview For Jav...Lightbend
As enterprise development teams increase the time they spend using cloud computing, many are challenged by a move from a scale-up (monolithic) to a scale-out (distributed) architecture. Reactive system development and microservices are two evolving answers that architects are embracing, but making them work well at scale calls for a departure from the traditional approach of object-oriented programming models and defensive programming through try-catch, which is now being replaced by a highly-resilient supervision model and a "let it crash" philosophy.
In this webinar for Architects, guest speaker Jeffrey Hammond, Forrester Vice-President and Principal Analyst joins Jonas Bonér, CTO/Co-founder of Lightbend and creator of Akka, the actor-based, message-driven runtime for the JVM, to discuss one emerging programming pattern that’s gaining popularity with teams developing for the cloud––the Actor model. They will discuss some history, why the Actor model is a better fit for large, scale-out systems and microservices delivery, the types of workloads using it today, and how to implement an Actor-based system in your existing Java environment.
IBM and Lightbend Build Integrated Platform for Cognitive DevelopmentLightbend
By now you have likely heard the news that IBM has made a strategic investment in Lightbend to bring Reactive solutions to IBM Platforms. So, what does this mean for developers?
During this 30-minute conversation with Karl Wehden, Director of Product Management at Lightbend, and Sebastian Hassinger, from the Developer Partners and Ecosystems team at IBM, will explore the following questions:
1. Why did IBM choose to partner with Lightbend, and vice a versa - what intrigued Lightbend about partnering with IBM?
2. Why is Scala important to this vision of the “Cognitive Era”?
3. What types of companies are creating these types of cognitive applications, and what do you see this partnership doing to help them accelerate their efforts?
4. What tools and technologies will we see begin to collaborate first?
5. In which other IBM products and services will we see Lightbend technologies appear as a joint solution?
6. What is the impact on JVM developers, the tools they use and how they get started with these technologies?
Fan-out, fan-in & the multiplexer: Replication recipes for global platform di...HostedbyConfluent
This session will dive into our most successful (and unsuccessful!) multi-cluster event replication patterns.
An x-ray of the cross cluster distribution model that powers our globally distributed APIs will touch on the benefits that this model has provided in terms of client API experience, delivery agility and developer experience.
We will focus on recipes for effective use of Mirror Maker event replication to power platform distribution including the challenges of managing a 'fan in' event replication workflow - pulling events created in satellite clusters back to a mothership cluster for processing.
We will introduce the elegant technique of replication event multiplexing - which can be used to simplify the burden of managing a 'fan-in' replication topology by eliminating regional awareness from the application domain and improving replication health monitoring & observability.
The eBay Architecture: Striking a Balance between Site Stability, Feature Ve...Randy Shoup
eBay architects Randy Shoup and Dan Pritchett give a guided tour of the eBay architecture. They cover the evolution of the technology stack from Perl to C++ to Java. And they discuss scaling strategies for the data tier, application tier, search, and operations.
The Future of ETL - Strata Data New York 2018confluent
Data integration is a difficult problem. We know this because 80% of the time in every project is spent getting the data you want the way you want it. We know this because this problem remains challenging despite 40 years of attempts to solve it. Software engineering practices have constantly evolved, but in many organizations data engineering teams still party like its 1999.
Gwen Shapira shares design and architecture patterns that are used to modernize data engineering. You’ll learn how modern engineering organizations use Apache Kafka, microservices, and event streams to efficiently build data pipelines that are scalable, reliable, and built to evolve.
Gwen begins with a discussion of how software engineering has changed in the last 20 years, focusing on microservices, stream processing, the cloud, and the proliferation of data stores. These changes represent both a challenge and opportunity for data engineers. Gwen then outlines three core patterns of modern data engineering: building data pipelines from decoupled microservices, the Agile evolution of these pipelines using schemas as a contract for microservices, and enriching data by joining streams of events. She walks you through examples of how organizations are using these patterns to move faster, not break things, and scale their data pipelines and demonstrates how to implement them with Apache Kafka.
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka | J...HostedbyConfluent
As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future.
Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It achieves economies of scale by acquiring data once and consuming it many times. It reduces technical debt by eliminating custom point-to-point connections for producing and consuming data. At the same time, it provides the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately lead to better prevention.
In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title. We’ll share some stream processing techniques, such as filtering and enriching in Kafka to deliver contextually rich data to Splunk and many of our security controls.
Capgemini: Observability within the Dutch governmentElasticsearch
The digital landscape within Dutch government is a complex and heterogeneous mix of technologies. Within this scenario, Capgemini is tasked with continuous integration and maintenance of key infrastructure. The results connect major organizational parts of the country with a large volume of daily traffic. To keep the lights on in operation and allow for quick turn-around times, Elastic is the dominant choice for generating reliable insight. It facilitates a thorough insight into the inner workings of modern amalgamated java deployments, databases and legacy systems spanning a multitude of decades.
Transformation During a Global Pandemic | Ashish Pandit and Scott Lee, Univer...HostedbyConfluent
When the University of California, San Diego launched its largest investment in tech in 2018, they planned to future proof their business processes and systems. Unexpectedly, it also prepared them to handle a global pandemic that changed every norm for the campus. With shelter-in-place orders taking immediate effect, they needed to quickly set up a robust online learning platform - one with powerful analytics to track student success. And, for the times students and staff are on campus, a contact tracing application was essential for their safety. We’d like to offer a conversation with Scott Lee to tell you more about UC San Diego’s rapid transformation from a traditional, on-campus institution to one of the leading examples of remote learning, and the critical role data connectivity played in making this possible.
Apache Kafka and the Data Mesh | Ben Stopford and Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
The world is moving from a model where data sits at rest, waiting for people to make requests of it, to where data is constantly moving and streams of data flow to and from devices with or without human interaction. Decisions need to be made based on these streams of data in real-time, models need to be updated, and intelligence needs to be gathered. In this context, our old-fashioned approach of CRUD REST APIs serving CRUD database calls just doesn't cut it. It's time we moved to a stream-centric view of the world.
https://jonthebeach.com/speakers/71/Markus+Eisele
20 mins to Faking the DevOps Unicorn by Matt williams, DatadogDocker, Inc.
Something changed in job ads over the last few years: everyone wants the DevOps Unicorn. What is that and why did this happen? You probably have a good amount of what is in that description, but is there an easy way to fill in the rest of the 100%? It turns out that it is possible to fake your way to being a DevOps Unicorn. All that you need is a way to know which metrics are the most important. And to know that you need a framework that applies everywhere. No really, it's easier than you think. There is some work needed on your part, but just a few minutes is enough to get started. In this 20 minute session, we will cover what changed in the market, what the framework looks like, and how to apply it to all of the containerized applications you need to monitor.
Comparison of various streaming technologies
This meetup will take us through the various streaming technologies such as Storm, Flink, Infosphere Streams and Spark Streaming.
Agenda
• Characteristics of streaming technologies
• Introduction to Apache Storm, Trident and Flink
• Examples of Code and API
• Deep-dive of Spark Streaming
• Comparison of Spark Streaming with other streaming technologies
• Benchmark of Spark Streaming (with code walkthrough)
We will supplement theory concepts with sufficient examples
The Future of ETL Isn't What It Used to Beconfluent
Speaker: Gwen Shapira, Principal Data Architect, Confluent
Join Gwen Shapira, Apache Kafka® committer and co-author of ""Kafka: The Definitive Guide,"" as she presents core patterns of modern data engineering and explains how you can use microservices, event streams and a streaming platform like Apache Kafka to build scalable and reliable data pipelines designed to evolve over time.
This is part 1 of 3 in Streaming ETL - The New Data Integration series.
Watch the recording: https://videos.confluent.io/watch/q7roRtNZBnjiT9C3ii88fo?.
Part 2: What you should know about Elasticity, Scalability and Location Transparency in Reactive systems
In the second of three webinars with live Q/A, we look into how organizations with Reactive systems are able to adaptively scale in an elastic, infrastructure-efficient way, and the role that location transparency plays in distributed Reactive systems. Reactive Streams contributor and deputy CTO at Typesafe, Inc., Viktor Klang reviews what you should know about:
How Reactive systems enable near-linear scalability in order to increase performance proportionally to the allocation of resources, avoiding the constraints of bottlenecks or synchronization points within the system
How elasticity builds upon scalability in Reactive systems to automatically adjust the throughput of varying demand when resources are added or removed proportionally and dynamically at runtime.
The role of location transparency in distributed computing (in systems running on a single node or on a cluster) and how of decoupling runtime instances from their references can embrace network constraints like partial failure, network splits, dropped messages and more.
In the third and final webinar in the series with Jonas Bonér, we go over resiliency, failures vs errors, isolation (and containment), delegation and replication in Reactive systems.
Airbnb, From Monolith to Microservices: How to Scale Your Architecture, Futur...New Relic
Hear from Melanie Cebula, Software Engineer at Airbnb, on how they utilize microservices to scale their architecture at FutureStack17 NYC.
See the video here: https://youtu.be/N1BWMW9NEQc
Be sure to subscribe and follow New Relic at:
https://twitter.com/NewRelic
https://www.facebook.com/NewRelic
https://www.youtube.com/NewRelicInc
End of the Myth: Ultra-Scalable Transactional Management by Ricardo Jiménez-P...Big Data Spain
The talk will focus on explaining why operational databases do not scale due to limitations in legacy transactional management.
https://www.bigdataspain.org/2017/talk/end-of-the-myth-ultra-scalable-transactional-management
Big Data Spain 2017
November 16th - 17th Kinépolis Madrid
Model-driven and low-code development for event-based systems | Bobby Calderw...HostedbyConfluent
It's a dream as old as business computing: the ability to create a graphical model and then to deploy it as a working information system. Many attempts to realize this dream have come and gone with varying degrees of success, from visual programming languages like Visual Basic and Scratch, to business workflow systems like BPMN and its proprietary commercial variants, to engineering-focused systems like UML.
But let's face it: most low-code and model-based application development tools fall far short of the needs of modern software development teams. At best, they're useful for rapidly testing ideas and creating prototypes. At worst, they're used by "citizen coders" to cynically circumvent good engineering practices, with IT operations left holding the bag of operating, securing, and scaling black-box applications that cut against modern DevSecOps practices.
Event-driven application architecture, enabled by infrastructure like Kafka and its ecosystem, has the potential to dramatically advance toward the age-old, model-driven and low-code dream. But what would an event-centric and developer-friendly low-code look like?
This talk will outline strategies for low-code and model-driven development based on Event Modeling. We'll explore how event-driven application architecture provides a simple yet robust framework for generating DevSecOps-friendly code for the UI, for the web services layer, and for event-processing.
The adoption of container native and cloud native development practices presents new operational challenges. Today’s microservice environments are polyglot, distributed, container-based, highly-scalable, and ephemeral. To understand your system, you need to be able to follow the life of a request across numerous components distributed in multiple environments. Without the proper tools it can feel impossible to determine a root cause of an issue. This requires a new approach to operations. We will review a series of open source observability tools for logging, monitoring, and tracing to help developers achieve operational excellence for running container-based workloads.
Presentazione dello speech tenuto da Carmine Spagnuolo (Postdoctoral Research Fellow - Università degli Studi di Salerno/ ACT OR) dal titolo "Technology insights: Decision Science Platform", durante il Decision Science Forum 2019, il più importante evento italiano sulla Scienza delle Decisioni.
IBM and Lightbend Build Integrated Platform for Cognitive DevelopmentLightbend
By now you have likely heard the news that IBM has made a strategic investment in Lightbend to bring Reactive solutions to IBM Platforms. So, what does this mean for developers?
During this 30-minute conversation with Karl Wehden, Director of Product Management at Lightbend, and Sebastian Hassinger, from the Developer Partners and Ecosystems team at IBM, will explore the following questions:
1. Why did IBM choose to partner with Lightbend, and vice a versa - what intrigued Lightbend about partnering with IBM?
2. Why is Scala important to this vision of the “Cognitive Era”?
3. What types of companies are creating these types of cognitive applications, and what do you see this partnership doing to help them accelerate their efforts?
4. What tools and technologies will we see begin to collaborate first?
5. In which other IBM products and services will we see Lightbend technologies appear as a joint solution?
6. What is the impact on JVM developers, the tools they use and how they get started with these technologies?
Fan-out, fan-in & the multiplexer: Replication recipes for global platform di...HostedbyConfluent
This session will dive into our most successful (and unsuccessful!) multi-cluster event replication patterns.
An x-ray of the cross cluster distribution model that powers our globally distributed APIs will touch on the benefits that this model has provided in terms of client API experience, delivery agility and developer experience.
We will focus on recipes for effective use of Mirror Maker event replication to power platform distribution including the challenges of managing a 'fan in' event replication workflow - pulling events created in satellite clusters back to a mothership cluster for processing.
We will introduce the elegant technique of replication event multiplexing - which can be used to simplify the burden of managing a 'fan-in' replication topology by eliminating regional awareness from the application domain and improving replication health monitoring & observability.
The eBay Architecture: Striking a Balance between Site Stability, Feature Ve...Randy Shoup
eBay architects Randy Shoup and Dan Pritchett give a guided tour of the eBay architecture. They cover the evolution of the technology stack from Perl to C++ to Java. And they discuss scaling strategies for the data tier, application tier, search, and operations.
The Future of ETL - Strata Data New York 2018confluent
Data integration is a difficult problem. We know this because 80% of the time in every project is spent getting the data you want the way you want it. We know this because this problem remains challenging despite 40 years of attempts to solve it. Software engineering practices have constantly evolved, but in many organizations data engineering teams still party like its 1999.
Gwen Shapira shares design and architecture patterns that are used to modernize data engineering. You’ll learn how modern engineering organizations use Apache Kafka, microservices, and event streams to efficiently build data pipelines that are scalable, reliable, and built to evolve.
Gwen begins with a discussion of how software engineering has changed in the last 20 years, focusing on microservices, stream processing, the cloud, and the proliferation of data stores. These changes represent both a challenge and opportunity for data engineers. Gwen then outlines three core patterns of modern data engineering: building data pipelines from decoupled microservices, the Agile evolution of these pipelines using schemas as a contract for microservices, and enriching data by joining streams of events. She walks you through examples of how organizations are using these patterns to move faster, not break things, and scale their data pipelines and demonstrates how to implement them with Apache Kafka.
Building a Modern, Scalable Cyber Intelligence Platform with Apache Kafka | J...HostedbyConfluent
As cyber threats continuously grow in sophistication and frequency, companies need to quickly acclimate to effectively detect, respond, and protect their environments. At Intel, we’ve addressed this need by implementing a modern, scalable Cyber Intelligence Platform (CIP) based on Splunk and Apache Kafka. We believe that CIP positions us for the best defense against cyber threats well into the future.
Our CIP ingests tens of terabytes of data each day and transforms it into actionable insights through streams processing, context-smart applications, and advanced analytics techniques. Kafka serves as a massive data pipeline within the platform. It achieves economies of scale by acquiring data once and consuming it many times. It reduces technical debt by eliminating custom point-to-point connections for producing and consuming data. At the same time, it provides the ability to operate on data in-stream, enabling us to reduce Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). Faster detection and response ultimately lead to better prevention.
In our session, we’ll discuss the details described in the IT@Intel white paper that was published in Nov 2020 with same title. We’ll share some stream processing techniques, such as filtering and enriching in Kafka to deliver contextually rich data to Splunk and many of our security controls.
Capgemini: Observability within the Dutch governmentElasticsearch
The digital landscape within Dutch government is a complex and heterogeneous mix of technologies. Within this scenario, Capgemini is tasked with continuous integration and maintenance of key infrastructure. The results connect major organizational parts of the country with a large volume of daily traffic. To keep the lights on in operation and allow for quick turn-around times, Elastic is the dominant choice for generating reliable insight. It facilitates a thorough insight into the inner workings of modern amalgamated java deployments, databases and legacy systems spanning a multitude of decades.
Transformation During a Global Pandemic | Ashish Pandit and Scott Lee, Univer...HostedbyConfluent
When the University of California, San Diego launched its largest investment in tech in 2018, they planned to future proof their business processes and systems. Unexpectedly, it also prepared them to handle a global pandemic that changed every norm for the campus. With shelter-in-place orders taking immediate effect, they needed to quickly set up a robust online learning platform - one with powerful analytics to track student success. And, for the times students and staff are on campus, a contact tracing application was essential for their safety. We’d like to offer a conversation with Scott Lee to tell you more about UC San Diego’s rapid transformation from a traditional, on-campus institution to one of the leading examples of remote learning, and the critical role data connectivity played in making this possible.
Apache Kafka and the Data Mesh | Ben Stopford and Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
The world is moving from a model where data sits at rest, waiting for people to make requests of it, to where data is constantly moving and streams of data flow to and from devices with or without human interaction. Decisions need to be made based on these streams of data in real-time, models need to be updated, and intelligence needs to be gathered. In this context, our old-fashioned approach of CRUD REST APIs serving CRUD database calls just doesn't cut it. It's time we moved to a stream-centric view of the world.
https://jonthebeach.com/speakers/71/Markus+Eisele
20 mins to Faking the DevOps Unicorn by Matt williams, DatadogDocker, Inc.
Something changed in job ads over the last few years: everyone wants the DevOps Unicorn. What is that and why did this happen? You probably have a good amount of what is in that description, but is there an easy way to fill in the rest of the 100%? It turns out that it is possible to fake your way to being a DevOps Unicorn. All that you need is a way to know which metrics are the most important. And to know that you need a framework that applies everywhere. No really, it's easier than you think. There is some work needed on your part, but just a few minutes is enough to get started. In this 20 minute session, we will cover what changed in the market, what the framework looks like, and how to apply it to all of the containerized applications you need to monitor.
Comparison of various streaming technologies
This meetup will take us through the various streaming technologies such as Storm, Flink, Infosphere Streams and Spark Streaming.
Agenda
• Characteristics of streaming technologies
• Introduction to Apache Storm, Trident and Flink
• Examples of Code and API
• Deep-dive of Spark Streaming
• Comparison of Spark Streaming with other streaming technologies
• Benchmark of Spark Streaming (with code walkthrough)
We will supplement theory concepts with sufficient examples
The Future of ETL Isn't What It Used to Beconfluent
Speaker: Gwen Shapira, Principal Data Architect, Confluent
Join Gwen Shapira, Apache Kafka® committer and co-author of ""Kafka: The Definitive Guide,"" as she presents core patterns of modern data engineering and explains how you can use microservices, event streams and a streaming platform like Apache Kafka to build scalable and reliable data pipelines designed to evolve over time.
This is part 1 of 3 in Streaming ETL - The New Data Integration series.
Watch the recording: https://videos.confluent.io/watch/q7roRtNZBnjiT9C3ii88fo?.
Part 2: What you should know about Elasticity, Scalability and Location Transparency in Reactive systems
In the second of three webinars with live Q/A, we look into how organizations with Reactive systems are able to adaptively scale in an elastic, infrastructure-efficient way, and the role that location transparency plays in distributed Reactive systems. Reactive Streams contributor and deputy CTO at Typesafe, Inc., Viktor Klang reviews what you should know about:
How Reactive systems enable near-linear scalability in order to increase performance proportionally to the allocation of resources, avoiding the constraints of bottlenecks or synchronization points within the system
How elasticity builds upon scalability in Reactive systems to automatically adjust the throughput of varying demand when resources are added or removed proportionally and dynamically at runtime.
The role of location transparency in distributed computing (in systems running on a single node or on a cluster) and how of decoupling runtime instances from their references can embrace network constraints like partial failure, network splits, dropped messages and more.
In the third and final webinar in the series with Jonas Bonér, we go over resiliency, failures vs errors, isolation (and containment), delegation and replication in Reactive systems.
Airbnb, From Monolith to Microservices: How to Scale Your Architecture, Futur...New Relic
Hear from Melanie Cebula, Software Engineer at Airbnb, on how they utilize microservices to scale their architecture at FutureStack17 NYC.
See the video here: https://youtu.be/N1BWMW9NEQc
Be sure to subscribe and follow New Relic at:
https://twitter.com/NewRelic
https://www.facebook.com/NewRelic
https://www.youtube.com/NewRelicInc
End of the Myth: Ultra-Scalable Transactional Management by Ricardo Jiménez-P...Big Data Spain
The talk will focus on explaining why operational databases do not scale due to limitations in legacy transactional management.
https://www.bigdataspain.org/2017/talk/end-of-the-myth-ultra-scalable-transactional-management
Big Data Spain 2017
November 16th - 17th Kinépolis Madrid
Model-driven and low-code development for event-based systems | Bobby Calderw...HostedbyConfluent
It's a dream as old as business computing: the ability to create a graphical model and then to deploy it as a working information system. Many attempts to realize this dream have come and gone with varying degrees of success, from visual programming languages like Visual Basic and Scratch, to business workflow systems like BPMN and its proprietary commercial variants, to engineering-focused systems like UML.
But let's face it: most low-code and model-based application development tools fall far short of the needs of modern software development teams. At best, they're useful for rapidly testing ideas and creating prototypes. At worst, they're used by "citizen coders" to cynically circumvent good engineering practices, with IT operations left holding the bag of operating, securing, and scaling black-box applications that cut against modern DevSecOps practices.
Event-driven application architecture, enabled by infrastructure like Kafka and its ecosystem, has the potential to dramatically advance toward the age-old, model-driven and low-code dream. But what would an event-centric and developer-friendly low-code look like?
This talk will outline strategies for low-code and model-driven development based on Event Modeling. We'll explore how event-driven application architecture provides a simple yet robust framework for generating DevSecOps-friendly code for the UI, for the web services layer, and for event-processing.
The adoption of container native and cloud native development practices presents new operational challenges. Today’s microservice environments are polyglot, distributed, container-based, highly-scalable, and ephemeral. To understand your system, you need to be able to follow the life of a request across numerous components distributed in multiple environments. Without the proper tools it can feel impossible to determine a root cause of an issue. This requires a new approach to operations. We will review a series of open source observability tools for logging, monitoring, and tracing to help developers achieve operational excellence for running container-based workloads.
Presentazione dello speech tenuto da Carmine Spagnuolo (Postdoctoral Research Fellow - Università degli Studi di Salerno/ ACT OR) dal titolo "Technology insights: Decision Science Platform", durante il Decision Science Forum 2019, il più importante evento italiano sulla Scienza delle Decisioni.
DEVNET-1142 Decomposing Monolithic Applications to MicroservicesCisco DevNet
Microservices style architectures provide several benefits, such as enabling shorter delivery cycles, improved elasticity and resiliency. However, most existing applications are not developed using a microservices-style architecture. In this session, we describe how you can incrementally transform a traditional 3-tier monolith application, into a microservices style application. Beyond design and development of microservices, the session will also provide best practices and guidelines on the operations and cultural changes required for a successful transformation to Microservices.
Nine Neins - where Java EE will never take youMarkus Eisele
Virtual JUG Session: http://www.meetup.com/virtualJUG/events/232052100/
With Microservices taking the software industry by storm, classical Enterprises are forced to re-think what they’ve been doing for almost a decade. It’s not the first time, that technology shocked the well-oiled machine to it’s core. We’ve seen software design paradigms changing over time and also project management methodologies evolving. Old hands might see this as another wave that will gently find it’s way to the shore of daily business. But this time it looks like the influence is bigger than anything we’ve seen before. And the interesting part is, that microservices aren’t new from the core. Talking about compartmentalization and introducing modules belongs to the core skills of architects. Our industry also learned about how to couple services and build them around organizational capabilities.
The really new part in microservices based architectures is the way how truly independent services are distributed and connected back together. Building an individual service is easy with all technologies. Building a system out of many is the real challenge because it introduces us to the problem space of distributed systems. And the difference to classical, centralized infrastructures couldn’t be bigger. There are very little concepts from the old world which still fit into a modern architecture.
And there are more differences between Java EE and distributed and reactive systems. For example, APIs are inherently synchronous, so most Java EE app servers have to scale by adding thread pools as so many things are blocking on I/O (remote JDBC calls, JTA calls, JNDI look ups, even JMS has a lot of synchronous parts). As we know adding thread pools doesn't get you too far in terms of scalability.
This talk is going to explore the nine most important differences between classical middleware and distributed, reactive microservices architectures and explains in which cases the distributed approach takes you, where Java EE never would.
Reactive Integrations - Caveats and bumps in the road explained Markus Eisele
Understand the different approaches to integrate fast data and streams based frameworks into your legacy applications and learn about the advantages, disadvantages, caveats, and bumps in the road.
How to Overcome Data Challenges When Refactoring Monoliths to MicroservicesVMware Tanzu
When taking existing monoliths and decomposing their components into new microservices, the most critical concerns have much less to do with the application code and more to do with handling data.
In this webinar, Kenny Bastani from Pivotal and Jason Mimick from MongoDB will focus on various methods of strangling a monolith’s ownership of domain data by transitioning the system of record over time. The new system of record, MongoDB, will fuel rapidly built and deployed microservices which companies can leverage for new revenue streams.
They will use practices from Martin Fowler’s Strangler Application to slowly strangle domain data away from a legacy system into cloud-native MongoDB clusters using microservices built with Spring Boot and Spring Cloud.
Speakers:
Kenny Bastani is a Spring developer advocate at Pivotal. As a passionate blogger and open source contributor, Kenny engages a community of passionate developers on topics ranging from graph databases to microservices. Kenny is a co-author of Cloud Native Java: Designing Resilient Systems with Spring Boot, Spring Cloud, and Cloud Foundry from O’Reilly.
Jason Mimick is the Technical Director for Partners at MongoDB developing new product and technical innovations with a number of companies. He's been at MongoDB nearly 4 years and previously spent the last 20-odd years in various engineering positions at Intersystems, Microsoft, and other companies.
The world is moving from a model where data sits at rest, waiting for people to make requests of it, to where data is constantly moving, streams of data flow to and from devices with or without human interaction. Decisions need to be made based on these streams of data in real time, models need to be updated, intelligence needs to be learned. And our old-fashioned approach of CRUD REST APIs serving CRUD database calls just doesn't cut it, it's trying to fit a square peg into a round hole. It's time we moved to a stream-centric view of the world.
This talk will look at how Reactive Streams is shaping the future of Jakarta EE. I'll talk about some Reactive Streams based specifications that we're currently working on in the JDK, MicroProfile and Jakarta EE communities, as well as some potential big ideas to transform the way developers write their applications, such as event sourcing and CQRS, that Jakarta EE will likely adopt in future. We'll take a look at a hypothetical future Jakarta EE, at what a typical service will look like when streaming is embraced, and get a glimpse of how Jakarta EE can lead the world in standards for Reactive systems.
The world is moving from a model where data sits at rest, waiting for people to make requests of it, to where data is constantly moving and streams of data flow to and from devices with or without human interaction. Decisions need to be made based on these streams of data in real-time, models need to be updated, and intelligence needs to be gathered. In this context, our old-fashioned approach of CRUD REST APIs serving CRUD database calls just doesn't cut it. It's time we moved to a stream-centric view of the world.
From Multi-Cloud and MicroServices to12-Factor Apps, Cloud-Native Applications are designed to be fast, tested and fail safe with continuous deployment to production. Simple policy declaration and enforcement across your stack allow you to move at greater speed, safety, and scale.
Java in the age of containers - JUG Frankfurt/MMarkus Eisele
31.07.2019 Java in the Age of Containers and Serverless
https://sites.google.com/site/jugffm/home/31-07-2019-java-in-the-age-of-containers-and-serverless
How would ESBs look like, if they were done today.Markus Eisele
Looking past former hype topics such as enterprise application integration, ESBs, and SOA, the fact is that the need for reliable integration solutions that are manageable and scalable is growing. More devices and datasources, combined with new and upcoming use cases and exciting wearables in a cloudified and heterogeneous infrastructure, require more bits and pieces than just a central ESB with some rules and point-to-point connections. What would that look like? And how can we keep the resultant solutions manageable? Attend this session to find out.
Modernizing Applications with Microservices and DC/OS (Lightbend/Mesosphere c...Lightbend
**Featuring Aaron Williams, Head of Advocacy at Mesosphere, Inc. and Markus Eisele, Developer Advocate at Lightbend, Inc.**
The traditional architecture that enterprises run their businesses on has typically been delivered as monolithic applications running in a virtualized, on-premise infrastructure. Public and private cloud technologies have changed everything, but if the applications are not designed, or re-designed, appropriately, then it is impossible to take advantage of the advances in both distributed application services and hybrid infrastructure. Consequently, enterprise architects are looking to microservices-based architectures as a means to modernize their legacy applications.
This webinar with Lightbend and partner Mesosphere will introduce a new framework specifically designed to help developers modernize legacy Java EE applications into systems of microservices and then discuss exactly what is required to run these distributed systems at enterprise scale.
The microservice architectural style is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API.
In this slide we have discussed, Monolithic application vs Microservices, applicable scenarios for adopting the architectural pattern, when we need microservices, what are the benefits, case study of an e-commerce platform by compartmentalizing the scopes into different sample microservices and Docker implementations.
The full talk has been recorded here: https://youtu.be/tNlp7HS533g
Architecting for failure - Why are distributed systems hard?Markus Eisele
Devnexus 2017
As we architect our systems for greater demands, scale, uptime, and performance, the hardest thing to control becomes the environment in which we deploy and the subtle but crucial interactions between complicated systems. And microservices obviously are the way to go forward with those complicated systems. But what makes it so hard to build them? And why should you embrace failure instead of doing what we can do best: Preventing failure. This talk introduces you to the problem domain of a distributed system which consists of a couple of microservices. It shows how to build, deploy and orchestrate the chaos and introduces you to a couple of patterns to prevent and compensate failure.
IoT 'Megaservices' - High Throughput Microservices with AkkaLightbend
**********
Watch this presentation on-demand!
https://info.lightbend.com/iot-megaservices-high-throughput-microservices-with-akka-register.html
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In this interactive presentation by Hugh McKee, Developer Advocate at Lightbend, we’ll share our experiences helping our clients create a system architecture that can support high throughput microservices (aka "Megaservices"). We’ll do that using IoT demo applications designed to push cloud service providers like Amazon and Google to their limits. Using sample code that you can later run on your own machine, we’ll look at:
* Modeling real-life digital twins for hundreds of thousands of IoT devices in the field, looking into how these megaservices are implemented in Akka.
* Visualizing Akka Actors–which represent IoT digital twins–in a “crop circle” formation that represents a complete distributed Reactive application, and watching at messages are processed across Akka Cluster nodes using cluster sharding.
* Some code behind the whole set up, which is built using OSS like Akka, Java, JavaScript, and Kubernetes.
Follow us on social:
TW: https://twitter.com/lightbend
LI: https://www.linkedin.com/company/lightbend-inc-/
FB: https://www.facebook.com/lightbendOfficial/
For more about Lightbend:
Blog: https://www.lightbend.com/blog
Newsletter: https://www.lightbend.com/newsletter
How Akka Cluster Works: Actors Living in a ClusterLightbend
Hugh McKee, Developer Advocate at Lightbend, demonstrates how Akka Actors work inside of a cluster, including the code and in-browser visualizations you need to grok it.
See the full content with videos here: https://www.lightbend.com/blog/how-akka-cluster-works-actors-living-in-a-cluster
Putting the 'I' in IoT - Building Digital Twins with Akka MicroservicesLightbend
In this webinar with Hugh McKee, Developer Advocate for Akka Platform, we’ll look at “What on Earth”, a demo exploring how Akka Microservices serves as an ideal solution for high-scale digital twinning for IoT.
For the full presentation, including video, visit: https://www.lightbend.com/blog/iot-building-digital-twins-with-akka-microservices
Akka at Enterprise Scale: Performance Tuning Distributed ApplicationsLightbend
Organizations like Starbucks, HPE, and PayPal (see our customers) have selected the Akka toolkit for their enterprise scale distributed applications; and when it comes to squeezing out the best possible performance, the secret is using two particular modules in tandem: Akka Cluster and Akka Streams.
In this webinar by Nolan Grace, Senior Solution Architect at Lightbend, we look at these two Akka modules and discuss the features that will push your application architecture to the next tier of performance.
For the full blog post, including the video, visit: https://www.lightbend.com/blog/akka-at-enterprise-scale-performance-tuning-distributed-applications
Detecting Real-Time Financial Fraud with Cloudflow on KubernetesLightbend
Deploying a robust streaming data pipeline can be a daunting task when your company’s financial information is at risk. For starters, how do you ensure proper provisioning of resources? How do you preserve end-to-end application and data consistency? How do you make all of this work in the cloud with Kubernetes and avoid YAML hell? Answer: Cloudflow, a new open-source toolkit for simplifying the development, deployment, and operation of streaming data pipelines.
Digital Transformation from Monoliths to Microservices to Serverless and BeyondLightbend
Join this highly-visual presentation by Hugh McKee, Developer Advocate at Lightbend, to learn more about the ramifications and opportunities along the evolution from monolithic systems, to microservices architectures, to serverless (FaaS).
See the video presentation on the Lightbend blog at: https://www.lightbend.com/blog/digital-transformation-from-monoliths-to-microservices-to-serverless-and-beyond
Akka Anti-Patterns, Goodbye: Six Features of Akka 2.6Lightbend
In this special guest webinar with Akka expert and Reactive System Consultant, Manuel Bernhardt, we review Akka 2.6 release highlights and a selection of 6 former anti-patterns that have now been rendered impossible by design.
Microservices, Kubernetes, and Application Modernization Done RightLightbend
In this talk by David Ogren, Enterprise Architect at Lightbend, we draw from experiences helping our clients successfully create, migrate to, and manage cloud-native system architectures. We look at some of the common pitfalls and anti-patterns of modernization efforts, and some of the best practices for taking an incremental approach to transforming legacy systems.
See the full post with video on the Lightbend blog: https://www.lightbend.com/blog/microservices-kubernetes-application-modernization
In this guest webinar by Kevin Webber, we cover the entire architecture of a Reactive system, from a responsive UI implemented with Vue.js, to a fully event sourced collection of microservices implemented with Java, Lagom, Cassandra, and Kafka.
For the full recording, visit: https://www.lightbend.com/blog/full-stack-reactive-in-practice-webinar
Akka and Kubernetes: A Symbiotic Love StoryLightbend
In this webinar by Hugh McKee, Developer Advocate at Lightbend, we take a look at how Akka and Kubernetes enjoy a symbiotic relationship, using live “crop circle” visuals to help. See the full video, slides, and additional resources here:
https://www.lightbend.com/blog/akka-and-kubernetes-a-symbiotic-love-story
Scala 3 Is Coming: Martin Odersky Shares What To KnowLightbend
Join Dr. Martin Odersky, the creator of Scala and co-founder of Lightbend, on a tour of what is in store and highlight some of his favorite features of Scala 3!
Running Kafka On Kubernetes With Strimzi For Real-Time Streaming ApplicationsLightbend
In this talk by Sean Glover, Principal Engineer at Lightbend, we will review how the Strimzi Kafka Operator, a supported technology in Lightbend Platform, makes many operational tasks in Kafka easy, such as the initial deployment and updates of a Kafka and ZooKeeper cluster.
See the blog post containing the YouTube video here: https://www.lightbend.com/blog/running-kafka-on-kubernetes-with-strimzi-for-real-time-streaming-applications
Designing Events-First Microservices For A Cloud Native WorldLightbend
In this talk by Jonas Bonér, Lightbend CTO/Co-Founder and creator of Akka, we will explore the nature of events, what it means to be event-driven, and how we can unleash the power of events and commands by applying an events first, domain-driven design to microservices-based architectures.
For more information, head over to lightbend.com/blog!
Scala Security: Eliminate 200+ Code-Level Threats With Fortify SCA For ScalaLightbend
Join Jeremy Daggett, Solutions Architect at Lightbend, to see how Fortify SCA for Scala works differently from existing Static Code Analysis tools to help you uncover security issues early in the SDLC of your mission-critical applications.
A Glimpse At The Future Of Apache Spark 3.0 With Deep Learning And KubernetesLightbend
In this special guest webinar with Holden Karau, speaker, author and Developer Advocate at Google, we’ll take a walk through some of the interesting JIRAs, look at external components being developed (like deep learning support), and also talk about the future of running real-time Spark workloads on Kubernetes.
Akka and Kubernetes: Reactive From Code To CloudLightbend
In this webinar with special guest Fabio Tiriticco, we will explore how Akka is the perfect companion to Kubernetes, providing the application level requirements needed to successfully deploy and manage your cloud-native services with technologies built specifically for cloud-native applications, like Kubernetes.
Hands On With Spark: Creating A Fast Data Pipeline With Structured Streaming ...Lightbend
In this talk by Gerard Maas, O’Reilly author and Senior Software Engineer at Lightbend, we focus on choosing the right Fast Data stream processing features of Apache Spark, taking a practical, code-driven look at the two APIs available for this: the mature Spark Streaming and its younger sibling, Structured Streaming.
How Akka Works: Visualize And Demo Akka With A Raspberry-Pi ClusterLightbend
In this webinar by Lightbend’s Eric Loots, Scala & Tooling Practice Lead, and Kikia Carter, Principal Enterprise Architect, we use a simple yet powerful visualization of a 5-node, Raspberry Pi-based cluster to reveal the inner workings of Akka Cluster. In a matter of minutes, you will gain a strong understanding of clustering, even if you don’t know anything about Akka.
Machine Learning At Speed: Operationalizing ML For Real-Time Data StreamsLightbend
Audience: Architects, Data Scientists, Developers
Technical level: Introductory
From home intrusion detection, to self-driving cars, to keeping data center operations healthy, Machine Learning (ML) has become one of the hottest topics in software engineering today. While much of the focus has been on the actual creation of the algorithms used in ML, the less talked-about challenge is how to serve these models in production, often utilizing real-time streaming data.
The traditional approach to model serving is to treat the model as code, which means that ML implementation has to be continually adapted for model serving. As the amount of machine learning tools and techniques grows, the efficiency of such an approach is becoming more questionable. Additionally, machine learning and model serving are driven by very different quality of service requirements; while machine learning is typically batch, dealing with scalability and processing power, model serving is mostly concerned with performance and stability.
In this webinar with O’Reilly author and Lightbend Principal Architect, Boris Lublinsky, we will define an alternative approach to model serving, based on treating the model itself as data. Using popular frameworks like Akka Streams and Apache Flink, Boris will review how to implement this approach, explaining how it can help you:
* Achieve complete decoupling between the model implementation for machine learning and model serving, enforcing better standardization of your model serving implementation.
* Enable dynamic updates of the served model without having to restart the system.
* Utilize Tensorflow and PMML as model representation and their usage for building “real time updatable” model serving architecture.
Ready for Fast Data: How Lightbend Enables Teams To Build Real-Time, Streamin...Lightbend
In this webinar with Mike Kelland, VP of Global Services at Lightbend, we will share some details of our specialized enablement strategy that allows teams of all sizes to successfully adopt Fast Data technologies and techniques. Based on over a decade of experience developing technologies that support real-time data streaming applications, Lightbend has the tools, expertise, and training courses you need to ramp up your team for Fast Data.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Modern design is crucial in today's digital environment, and this is especially true for SharePoint intranets. The design of these digital hubs is critical to user engagement and productivity enhancement. They are the cornerstone of internal collaboration and interaction within enterprises.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
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.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
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.
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.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
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
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
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.
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.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Why React Native as a Strategic Advantage for Startup Innovation.pdfayushiqss
Do you know that React Native is being increasingly adopted by startups as well as big companies in the mobile app development industry? Big names like Facebook, Instagram, and Pinterest have already integrated this robust open-source framework.
In fact, according to a report by Statista, the number of React Native developers has been steadily increasing over the years, reaching an estimated 1.9 million by the end of 2024. This means that the demand for this framework in the job market has been growing making it a valuable skill.
But what makes React Native so popular for mobile application development? It offers excellent cross-platform capabilities among other benefits. This way, with React Native, developers can write code once and run it on both iOS and Android devices thus saving time and resources leading to shorter development cycles hence faster time-to-market for your app.
Let’s take the example of a startup, which wanted to release their app on both iOS and Android at once. Through the use of React Native they managed to create an app and bring it into the market within a very short period. This helped them gain an advantage over their competitors because they had access to a large user base who were able to generate revenue quickly for them.
Why React Native as a Strategic Advantage for Startup Innovation.pdf
Migrating From Java EE To Cloud-Native Reactive Systems
1. Migrating From Java EE To Cloud-Native
Reactive Systems
With Markus Eisele, Director of Developer Advocacy at Lightbend, Inc.
WEBINAR | THURSDAY JUN 6TH, 9:00 AM PT / 12:00 ET / 16:00 GMT / 18:00 CET
4. 4
Java developers
worldwide
of the Fortune 500
are using Java EE
of companies use Java to build
over 80% of their applications
10M+ 90% 43%
Stability Specifications Availability of
developers
#1 #2 #3
5. What Technical Direction should Java EE evolve into?
Eclipse Foundation survey of over 1800 developers
5
Top 3
for building microservices include Jersey, Spring, Eclipse
MicroProfile, Node.js & Kubernetes
Currently building microservices or planning to <1 yr
Say large memory requirements most challenging
aspect of working with Java EE
Java EE chosen for Java applications is stability
Say Foundation should prioritize better support for microservices
https://jakarta.ee/news/2018/04/24/jakarta-ee-community-survey/
67%
Top Frameworks
1. Better support for microservices
2. Native integration with Kubernetes
3. A faster pace of innovation
40%
#1 Reason
60%
critical areas cited
for improvement
6. But are Java EE
Applications Still Suitable Today?
8. When Building a New Business Application,
Which Technology do You Use?
Twitter survey on 5.16.19*
8
Other
Reactive (e.g. Play)
Microprofile (services)
Jave EE (monolith) 17%
28%
30%
25%
*962 respondents
9. Cloud Native And The Future Of Java EE
Complexity kills development velocity and only fosters infrequent releases
• Development team agility is constantly blocked.
• Big teams and heavy apps create long release cycles.
• Complex code bases and fearful engineers lead to technical debt.
Scaling monoliths is too expensive for the cloud
• Monoliths are difficult and expensive to scale.
• Monoliths lead to resource inefficiency.
9
10. Streams and ‘data in motion’ need to be supported
• Real-time streaming data is a first-class
citizen in today’s applications.
• Insights and value must be harvested
from data.
• Non-traditional data persistence
models must be used.
• Shortened time-frames for putting
changes into production
• New business models evolve from existing
ones
• New questions need to be answered by
existing applications
• Datacenter costs need to go down
constantly
10
12. Monoliths Have Allowed Us to Take Consistency for Granted
With a single database, the world is easy
Transactions give us an illusion of a single, consistent, current state
• We can think of our data as a static thing
• It sits there at rest, waiting for our operation
• Failure is handled
• No partial updates
• Consistency is enforced
• Concurrency is handled
• No uncommitted reads
12
Transaction 1
Transaction 2
13. With Distributed Applications,
Our Consistent View of the World Breaks Down
With many databases, the world is hard
There are now many states, all constantly changing
• Different services have different
ideas of current state
• Our data is in motion, not at rest, not static
• Failure is not handled for us
• Partial updates likely
• No enforcement of consistency
• Concurrency is inherent
• Operations take time to propagate
13
G
?
C
?
F
?
B
?
E
?
A
?
D
?
14. What worked in monoliths
CRUD
• Depends on consistent single state
Relying on transactions
• Depends on a single database
REST
• Depends on failure and consistency
being handled in the database
14
Needed for distributed applications
Events
• Events convey facts
• Facts remain true regardless of what else happens in
the system
At least once messaging
• Ensures events can be reliably propagated throughout
the system
Stream-centric view
• Our data is the events
• Some may be at rest, some are in motion
• No single state
• Rather, system is constantly converging, propagating
• Control this, using streams
What Worked in Monoliths Will Not Work Anymore
17. Take a lesson from Events-First
Domain Driven Design
• Use encapsulation to improve
flexibility.
• Apply isolation to encourage loose
coupling and avoid the cascade
effect.
• Separate domains of concern to
reduce complexity.
17
Bounded Context Bounded Context
Search
Service
Search
Service
Product
Service
Product
Service
Product
Service
Product
Service
Search
Cache
Product DB
18. Prioritize resilience before thinking about
elastic scaling in the cloud
• Automate supervision to minimize
human intervention.
• Isolate and contain failures to
enable self-healing.
• Master resilience and elasticity to
achieve system responsiveness.
18
19. Utilize a streaming architecture to achieve distribution,
concurrency, supervision, and resilience
19
Kafka
myTopic
.subscribe()
Akka Streams
.map(kafkaMessage ->
new WebSocketMessage(
kafkaMessage.getPayload()
)
)
WebSocket
response
.send(publisher)
Reactive Streams
Backpressure
Reactive Streams
Messages
By modelling a system using streams, we embrace events, no longer need a single state, and can
take eventual consistency for granted
21. 21
“Akka has consistently allowed us to cut
80% of infrastructure, or increase overall
application performance by 5x, when
compared to the traditional systems we
replaced.”
- Akara Sucharitakul, Principal MTS at PayPal
“
22. We enable Product teams to:
• Focus on the business logic, not low-
level protocols.
• Eliminate bottlenecks and single points
of failure.
• Realize true ROI from investing in cloud
infrastructure.
• Focus on what matters to your
business.
22
24. We enable Product teams to:
• Enhancing customer engagement with data-driven insights
• Unleashing innovation to protect or capture markets
• Improving agility and time to value
• Reducing compute costs while scaling elastically
• Increasing developer happiness and productivity
24
25. From Java EE To Cloud Native: The End Of
The Heavyweight Era
How to modernize traditional Java EE
applications for cloud-native infrastructure
WHITE PAPER | BY MARKUS EISELE AND JAMES ROPER, LIGHTBEND INC.
28
http://bit.ly/JavaEE2CloudNative
26. Reactive Microservices
Architecture
29
Written for architects and developers that must quickly
gain a fundamental understanding of microservice-based
architectures, this free O’Reilly report explores the journey from
SOA to microservices, discusses approaches to dismantling your
monolith, and reviews the key tenets of a Reactive microservice:
• Isolate all the Things
• Act Autonomously
• Do One Thing, and Do It Well
• Own Your State, Exclusively
• Embrace Asynchronous Message-Passing
• Stay Mobile, but Addressable
• Collaborate as Systems to Solve Problems
http://bit.ly/ReactiveMicroservice
27. Developing
Reactive Microservices
30
The detailed example in this report is based on Lagom,
a new framework that helps you follow the requirements
for building distributed, reactive systems.
• Get an overview of the Reactive Programming model and
basic requirements for developing reactive microservices
• Learn how to create base services, expose endpoints, and
then connect them with a simple, web-based user interface
• Understand how to deal with persistence, state, and clients
• Use integration technologies to start a successful migration
away from legacy systems
http://bit.ly/DevelopReactiveMicroservice
28. Modern Java EE
Design Patterns
• Understand the challenges of starting a
greenfield development vs tearing apart an
existing brownfield application into services
• Examine your business domain to see if microservices would
be a good fit
• Explore best practices for automation, high availability, data
separation, and performance
• Align your development teams around business capabilities
and responsibilities
• Inspect design patterns such as aggregator, proxy, pipeline,
or shared resources to model service interactions
31
http://bit.ly/SustainableEnterprise