CODEONTHEBEACH_Streaming Applications with Apache Pulsar
https://www.codeonthebeach.com/schedule
Deep Dive into Building Streaming Applications with Apache Pulsar - Timothy Spann
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics.
We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript.
After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache PulsarTimothy Spann
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
tim spann developer advocate
streamnative
datainmotion.dev
OSS EU: Deep Dive into Building Streaming Applications with Apache PulsarTimothy Spann
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
Building Modern Data Streaming Apps with PythonTimothy Spann
Building Modern Data Streaming Apps with Python
https://www.conf42.com/DevOps_2023_Tim_Spann_modern_data_streaming_apps
Share
In my session, I will show you some best practices I have discovered over the last seven years in building data streaming applications, including IoT, CDC, Logs, and more. In my modern approach, we utilize several open-source frameworks to maximize the best features of all. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Pulsar. From there, we build streaming ETL with Apache Spark and enhance events with Pulsar Functions for ML and enrichment. We build continuous queries against our topics with Flink SQL. We will stream data into various data stores. We use Python for microservices as Functions and stand-alone apps. We use the best streaming tools for the current applications with FLiPN. https://www.flipn.app/
Timothy Spann
Developer Advocate
https://datainmotion.dev/
Python web conference 2022 apache pulsar development 101 with python (f li-...Timothy Spann
Python web conference 2022 apache pulsar development 101 with python (FLiP-Py)
What is Apache Pulsar?
Python 3 Coding
Python Consumers
Python Producers
Python via MQTT, Web Sockets, Kafka
Python for Pulsar Functions
Schemas
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)Timothy Spann
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)
https://sixfeetup.com/company/news/90-talks-and-tutorials-from-2022-python-web-conference-released
https://www.youtube.com/playlist?list=PLt4L3V8wVnF7PJ3wfq1rdJWX4ziasHMHl
https://www.youtube.com/watch?v=H88re4p-DoU&list=PLt4L3V8wVnF7PJ3wfq1rdJWX4ziasHMHl&index=62
We will start off with a gentle introduction to Apache Pulsar and setting up your first easy standalone cluster. We will then l show you how to produce and consume message to Pulsar using several different Python libraries including Python client, websockets, MQTT and even Kafka.
After this session you will be building real-time streaming and messaging applications with Python.
#PWC2022 attracted nearly 375 attendees from 36 countries and 21 time zones making it the biggest and best year yet. The highly engaging format featured 90 speakers, 6 tracks (including 80 talks and 4 tutorials) and took place virtually on March 21-25, 2022 on LoudSwarm by Six Feet Up.
Apache Pulsar
Apache Flink
Apache Kafka
MQTT
AMQP/RabbitMQ
WebSockets
Python3
[March sn meetup] apache pulsar + apache nifi for cloud data lakeTimothy Spann
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/283837865/
Learn how to use Apache Pulsar and Apache NiFi to Stream to your Data Lake
Discover how to stream data to and from your data lake or data mart using Apache Pulsar™ and Apache NiFi®. Learn how these cloud-native, scalable open-source projects built for streaming data pipelines work together to enable you to quickly build applications with minimal coding.
|WHAT THE SESSION WILL COVER|
Best Practices for using Pulsar and NiFi
A deep dive on Apache NiFi's Pulsar connector and demos
Building an End-to-End Application in the Hybrid Cloud
Attend for a chance to win a We <3 Pulsar t-shirt! The first 50 registrants who register through here [https://hubs.ly/Q013LTpn0] will be entered in a drawing!
—------------------------
|AGENDA|
6:00 - 7:00 PM EST: Presentation - Tim Spann, StreamNative Developer Advocate
7:00 - 8:00 PM EST: Presentation - John Kuchmek, Cloudera Principal Solutions Engineer
8:00 - 8:30 PM EST: Q&A + Networking
—------------------------
|ABOUT THE SPEAKERS|
John Kuchmek is a Principal Solutions Engineer for Cloudera. Before joining Cloudera, John transitioned to the Autonomous Intelligence team where he was in charge of integrating the platforms to allow data scientists to work with various types of data.
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar™, Apache Flink®, Flink® SQL, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science. He is currently working on a book about the FLiP Stack.
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Spark
DevNexus 2022 Atlanta
https://devnexus.com/presentations/7150/
This talk is a quick overview of the How, What and WHY of Apache Pulsar, Apache Flink and Apache NiFi. I will show you how to design event-driven applications that scale the cloud native way.
This talk was done live in person at DevNexus across from the booth in room 311
Tim Spann
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache PulsarTimothy Spann
ApacheCon2022_Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
tim spann developer advocate
streamnative
datainmotion.dev
OSS EU: Deep Dive into Building Streaming Applications with Apache PulsarTimothy Spann
OSS EU: Deep Dive into Building Streaming Applications with Apache Pulsar
In this session I will get you started with real-time cloud native streaming programming with Java, Golang, Python and Apache NiFi. If there’s a preferred language that the attendees pick, we will focus only on that one. I will start off with an introduction to Apache Pulsar and setting up your first easy standalone cluster in docker. We will then go into terms and architecture so you have an idea of what is going on with your events. I will then show you how to produce and consume messages to and from Pulsar topics. As well as using some of the command line and REST interfaces to monitor, manage and do CRUD on things like tenants, namespaces and topics. We will discuss Functions, Sinks, Sources, Pulsar SQL, Flink SQL and Spark SQL interfaces. We also discuss why you may want to add protocols such as MoP (MQTT), AoP (AMQP/RabbitMQ) or KoP (Kafka) to your cluster. We will also look at WebSockets as a producer and consumer. I will demonstrate a simple web page that sends and receives Pulsar messages with basic JavaScript. After this session you will be able to build simple real-time streaming and messaging applications with your chosen language or tool of your choice.
apache pulsar
Building Modern Data Streaming Apps with PythonTimothy Spann
Building Modern Data Streaming Apps with Python
https://www.conf42.com/DevOps_2023_Tim_Spann_modern_data_streaming_apps
Share
In my session, I will show you some best practices I have discovered over the last seven years in building data streaming applications, including IoT, CDC, Logs, and more. In my modern approach, we utilize several open-source frameworks to maximize the best features of all. We often start with Apache NiFi as the orchestrator of streams flowing into Apache Pulsar. From there, we build streaming ETL with Apache Spark and enhance events with Pulsar Functions for ML and enrichment. We build continuous queries against our topics with Flink SQL. We will stream data into various data stores. We use Python for microservices as Functions and stand-alone apps. We use the best streaming tools for the current applications with FLiPN. https://www.flipn.app/
Timothy Spann
Developer Advocate
https://datainmotion.dev/
Python web conference 2022 apache pulsar development 101 with python (f li-...Timothy Spann
Python web conference 2022 apache pulsar development 101 with python (FLiP-Py)
What is Apache Pulsar?
Python 3 Coding
Python Consumers
Python Producers
Python via MQTT, Web Sockets, Kafka
Python for Pulsar Functions
Schemas
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)Timothy Spann
Python Web Conference 2022 - Apache Pulsar Development 101 with Python (FLiP-Py)
https://sixfeetup.com/company/news/90-talks-and-tutorials-from-2022-python-web-conference-released
https://www.youtube.com/playlist?list=PLt4L3V8wVnF7PJ3wfq1rdJWX4ziasHMHl
https://www.youtube.com/watch?v=H88re4p-DoU&list=PLt4L3V8wVnF7PJ3wfq1rdJWX4ziasHMHl&index=62
We will start off with a gentle introduction to Apache Pulsar and setting up your first easy standalone cluster. We will then l show you how to produce and consume message to Pulsar using several different Python libraries including Python client, websockets, MQTT and even Kafka.
After this session you will be building real-time streaming and messaging applications with Python.
#PWC2022 attracted nearly 375 attendees from 36 countries and 21 time zones making it the biggest and best year yet. The highly engaging format featured 90 speakers, 6 tracks (including 80 talks and 4 tutorials) and took place virtually on March 21-25, 2022 on LoudSwarm by Six Feet Up.
Apache Pulsar
Apache Flink
Apache Kafka
MQTT
AMQP/RabbitMQ
WebSockets
Python3
[March sn meetup] apache pulsar + apache nifi for cloud data lakeTimothy Spann
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/283837865/
Learn how to use Apache Pulsar and Apache NiFi to Stream to your Data Lake
Discover how to stream data to and from your data lake or data mart using Apache Pulsar™ and Apache NiFi®. Learn how these cloud-native, scalable open-source projects built for streaming data pipelines work together to enable you to quickly build applications with minimal coding.
|WHAT THE SESSION WILL COVER|
Best Practices for using Pulsar and NiFi
A deep dive on Apache NiFi's Pulsar connector and demos
Building an End-to-End Application in the Hybrid Cloud
Attend for a chance to win a We <3 Pulsar t-shirt! The first 50 registrants who register through here [https://hubs.ly/Q013LTpn0] will be entered in a drawing!
—------------------------
|AGENDA|
6:00 - 7:00 PM EST: Presentation - Tim Spann, StreamNative Developer Advocate
7:00 - 8:00 PM EST: Presentation - John Kuchmek, Cloudera Principal Solutions Engineer
8:00 - 8:30 PM EST: Q&A + Networking
—------------------------
|ABOUT THE SPEAKERS|
John Kuchmek is a Principal Solutions Engineer for Cloudera. Before joining Cloudera, John transitioned to the Autonomous Intelligence team where he was in charge of integrating the platforms to allow data scientists to work with various types of data.
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar™, Apache Flink®, Flink® SQL, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science. He is currently working on a book about the FLiP Stack.
Designing Event-Driven Applications with Apache NiFi, Apache Flink, Apache Spark
DevNexus 2022 Atlanta
https://devnexus.com/presentations/7150/
This talk is a quick overview of the How, What and WHY of Apache Pulsar, Apache Flink and Apache NiFi. I will show you how to design event-driven applications that scale the cloud native way.
This talk was done live in person at DevNexus across from the booth in room 311
Tim Spann
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar, Apache Flink, Flink SQL, Apache NiFi, MiniFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
The Next Generation of Streaming
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/291048765/
https://www.meetup.com/risingwave-community/events/291294056/
The Next Generation of Streaming
David Kjerrumgaard, Developer Advocate
Tim Spann
Building a cloud-native streaming application requires a team, from the start of events to the final analytics. I'll walk you through using Apache Pulsar as your central messaging hub to distribute events and real-time messages from and to everywhere it needs to be. All instantly. The next step is to stream into continuous SQL.
Agenda
9:00 -- 9:20 The Next Generation of Streaming by Tim Spann,
Developer Advocate at StreamNative
9:20 -- 9:40 RisingWave: Cloud-Native Streaming SQL over Pulsar by Rayees Pasha, Head of Product at RisingWave Labs
23-feb-2023 12:15pm EST
https://github.com/tspannhw/Flow-SGP30-MLX90640
Apache NiFi, Apache Pulsar, Apache Kafka, MQTT, RabbitMQ, AMQP, Source, Sink, Stream Processing
Conf42 Python_ ML Enhanced Event Streaming Apps with Python MicroservicesTimothy Spann
Conf42 Python_ ML Enhanced Event Streaming Apps with Python Microservices
https://www.conf42.com/Python_2023_Tim_Spann_David_Kjerrumgaard_ml_enhanced_event_streaming_apps_microservices
Build ML Enhanced Event Streaming Apps with Python Microservices
TIM SPANN
PRINCIPAL DEVELOPER ADVOCATE @ STREAMNATIVE
Tim Spann's LinkedIn account Tim Spann's twitter account
DAVID KJERRUMGAARD
DEVELOPER ADVOCATE @ STREAMNATIVE
David Kjerrumgaard's LinkedIn account
Share
The easy way to build and scale machine learning apps.
PythonWebConference_ Cloud Native Apache Pulsar Development 202 with PythonTimothy Spann
PythonWebConference_ Cloud Native Apache Pulsar Development 202 with Python
Developers want to develop real-time applications that can turn raw text data into analyzed sentences and smart sentiment? Have you heard of real-time analytics, let's leverage your Python skills to make it happen now.
In this talk I will show developers how to develop real-time applications that use Pulsar functions to turn live event data into live NLP results and sentiment analyzed output.
We will walk through how to setup various scenarios to feed live data from apps and webapps to Apache Pulsar for real-time analytics and NLP.
At the end of the talk, developers will be able to use Python for real-time NLP analytics and have gained insight on how and when to use various streaming protocols, platforms, libraries and systems including Apache Pulsar, Apache Kafka, MQTT, Websockets, AMQP and Apache Spark.
https://2023.pythonwebconf.com/presentations/apache-pulsar-development-202-with-python
Apache Pulsar Development 101 with PythonTimothy Spann
Apache Pulsar Development 101 with Python PS2022_Ecosystem_v0.0
There is always the fear a speaker cannot make it. So just in case, since I was the MC for the ecosystem track I put together a talk just in case.
Here it is. Never seen or presented.
All Day DevOps - FLiP Stack for Cloud Data LakesTimothy Spann
https://www.alldaydevops.com/addo-speakers/timothy-spann
Timothy Spann
StreamNative
MODERN INFRASTRUCTURE
SHARE THIS SESSION
Session Name: FLiP Stack for Cloud Data Lakes
Utilizing an all Apache stack for Rapid Data Lake Population and querying utilizing Apache Flink, Apache Pulsar, and Apache NiFi. We can quickly stream data to and from any datalake, data lake house, lakehouse, database or any datamart regardless of cloud or size. FLiP allows for Java and Python developers to build scalable solutions that span messaging and streaming in cloud native fashion with full monitoring.
Speaker Bio:
Tim Spann is a Developer Advocate @ StreamNative where he works with Apache Pulsar, Apache Flink, Apache NiFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, Pulsar, NiFi, the blockchain, and Spark.
Data science online camp using the flipn stack for edge ai (flink, nifi, pu...Timothy Spann
Data science online camp using the flipn stack for edge ai (flink, nifi, pulsar)
Dec 3, 2021
Apache NiFi
Apache Flink
Apache Pulsar
Edge AI
Cloud Native Made Easy
StreamNative
Living the Stream Dream with Pulsar and Spring BootTimothy Spann
Living the Stream Dream with Pulsar and Spring Boot
https://events.geekle.us/java23
feb 21, 2023
https://geekle.us/schedule/java23
Living the Stream Dream with Pulsar and Spring Boot
For building Java applications, Spring is the universal answer as it supplies all the connectors and integrations one could want. The same is true for Apache Pulsar as it provides connectors, integration and flexibility to any use case. Apache Pulsar has a robust native Java library to use with Spring as well as other protocol options.
Apache Pulsar provides a cloud native, geo-replicated unified messaging platform that allows for many messaging paradigms. This lends itself well to upgrading existing applications as Pulsar supports using libraries for WebSockets, MQTT, Kafka, JMS, AMQP and RocketMQ. In this talk I will build some example applications utilizing several different protocols for building a variety of applications from IoT to Microservices to Log Analytics.
We will build Spring Boot microservices that utilize Apache Pulsar as a central data hub for communications and enrichment. This utilizes the new Spring for Pulsar framework.
https://github.com/spring-projects-experimental/spring-pulsar
We talked about it on Josh Long's podcast https://spring.io/blog/2022/09/15/a-bootiful-podcast-big-data-legend-former-pivot-and-friend-to-the-spring-community-tim-spann
programming real-time applications with Java 17, Spring Boot and Apache Pulsar 2.11
Apache Pulsar with MQTT for Edge Computing - Pulsar Summit Asia 2021StreamNative
Today we will span from edge to any and all clouds to support data collection, real-time streaming, sensor ingest, edge computing, IoT use cases and edge AI. Apache Pulsar allows us to build computing at the edge and produce and consume messages at scale in any IoT, hybrid or cloud environment. Apache Pulsar supports MoP which allows for MQTT protocol to be used for high speed messaging.
We will teach you to quickly build scalable open source streaming applications regardless of if you are running in containers, pods, edge devices, VMs, on-premise servers, moving vehicles and any cloud.
Let's keep it simple and streaming.pdfVMware Tanzu
I’ll walk through how to build a simple streaming application using JDK 17, Spring Boot 3, and Apache Pulsar 2.11. At the end of this talk, you’ll have a simple streaming application running and ready for testing and beyond.
Speaker: Timothy Spann, Developer Advocate, StreamNative
Princeton Dec 2022 Meetup_ StreamNative and Cloudera StreamingTimothy Spann
Princeton Dec 2022 Meetup_ StreamNative and Cloudera Streaming
https://www.meetup.com/new-york-city-apache-pulsar-meetup/
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/289674210/
|WHAT THE SESSION WILL COVER|
Apache NiFi
Apache Pulsar
Apache Flink
Flink SQL
We will show you how to build apps, so download beforehand to Docker, K8, your Laptop, or the cloud.
Cloudera CSP Setup
Getting Started with Cloudera Stream Processing Community Edition
You may download CSP-CE here:
Cloudera Stream Processing Community Edition
The Cloudera CDP User's page:
CDP Resources Page
https://youtu.be/s80sz3NWwHo
https://docs.cloudera.com/csp-ce/latest/index.html
https://www.cloudera.com/downloads/cdf/csp-community-edition.html
Apache Pulsar
https://pulsar.apache.org/docs/getting-started-standalone/
or
https://streamnative.io/free-cloud/
Cloudera + Pulsar
https://community.cloudera.com/t5/Cloudera-Stream-Processing-Forum/Using-Apache-Pulsar-with-SQL-Stream-Builder/m-p/349917
https://community.cloudera.com/t5/Community-Articles/Using-Apache-NiFi-with-Apache-Pulsar-for-Streaming/ta-p/337891
|AGENDA|
6:00 - 6:30 PM EST: Food, Drink, and Networking!!!
6:30 - 7:15 PM EST: Presentation - Tim Spann, StreamNative Developer Advocate
7:15 - 8:00 PM EST: Presentation - John Kuchmek, Cloudera Principal Solutions Engineer
8:00 - 8:30 PM EST: Round Table on Real-Time Streaming, Q&A
|ABOUT THE SPEAKERS|
John Kuchmek is a Principal Solutions Engineer for Cloudera. Before joining Cloudera, John transitioned to the Autonomous Intelligence team where he was in charge of integrating the platforms to allow data scientists to work with various types of data.
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar™, Apache Flink®, Flink® SQL, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming.
See:
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/283837865/
https://github.com/tspannhw/SpeakerProfile
https://www.meetup.com/futureofdata-newyork/
https://github.com/tspannhw/pulsar-transit-function
https://www.meetup.com/futureofdata-princeton/
https://github.com/tspannhw/create-nifi-pulsar-flink-apps
https://medium.com/@tspann/using-apache-pulsar-with-cloudera-sql-builder-apache-flink-b518aa9eadff
https://github.com/tspannhw/meetups/blob/main/15December2022.md All resources for the meetup
Fast Streaming into Clickhouse with Apache PulsarTimothy Spann
https://github.com/tspannhw/SpeakerProfile/tree/main/2022/talks
Fast Streaming into Clickhouse with Apache Pulsar
https://github.com/tspannhw/FLiPC-FastStreamingIntoClickhouseWithApachePulsar
https://www.meetup.com/San-Francisco-Bay-Area-ClickHouse-Meetup/events/285271332/
Fast Streaming into Clickhouse with Apache Pulsar - Meetup 2022
StreamNative - Apache Pulsar - Stream to Altinity Cloud - Clickhouse
May the 4th Be With You!
04-May-2022 Clickhosue Meetup
CREATE TABLE iotjetsonjson_local
(
uuid String,
camera String,
ipaddress String,
networktime String,
top1pct String,
top1 String,
cputemp String,
gputemp String,
gputempf String,
cputempf String,
runtime String,
host String,
filename String,
host_name String,
macaddress String,
te String,
systemtime String,
cpu String,
diskusage String,
memory String,
imageinput String
)
ENGINE = MergeTree()
PARTITION BY uuid
ORDER BY (uuid);
CREATE TABLE iotjetsonjson ON CLUSTER '{cluster}' AS iotjetsonjson_local
ENGINE = Distributed('{cluster}', default, iotjetsonjson_local, rand());
select uuid, top1pct, top1, gputempf, cputempf
from iotjetsonjson
where toFloat32OrZero(top1pct) > 40
order by toFloat32OrZero(top1pct) desc, systemtime desc
select uuid, systemtime, networktime, te, top1pct, top1, cputempf, gputempf, cpu, diskusage, memory,filename
from iotjetsonjson
order by systemtime desc
select top1, max(toFloat32OrZero(top1pct)), max(gputempf), max(cputempf)
from iotjetsonjson
group by top1
select top1, max(toFloat32OrZero(top1pct)) as maxTop1, max(gputempf), max(cputempf)
from iotjetsonjson
group by top1
order by maxTop1
Tim Spann
Developer Advocate
StreamNative
DBCC 2021 - FLiP Stack for Cloud Data LakesTimothy Spann
DBCC 2021 - FLiP Stack for Cloud Data Lakes
With Apache Pulsar, Apache NiFi, Apache Flink. The FLiP(N) Stack for Event processing and IoT. With StreamNative Cloud.
DBCC International – Friday 15.10.2021
Powered by Apache Pulsar, StreamNative provides a cloud-native, real-time messaging and streaming platform to support multi-cloud and hybrid cloud strategies.
bigdata 2022_ FLiP Into Pulsar Apps
In this session, Timothy will introduce you to the world of Apache Pulsar and how to build real-time messaging and streaming applications with a variety of OSS libraries, schemas, languages, frameworks, and tools.
FLiP Into Pulsar Apps
08:30 – 09:15
•
23 Nov, 2022
In this session, Timothy will introduce you to the world of Apache Pulsar and how to build real-time messaging and streaming applications with a variety of OSS libraries, schemas, languages, frameworks, and tools.
Open Source Big Data Ingestion - Without the Heartburn!Pat Patterson
Big Data tools such as Hadoop and Spark allow you to process data at unprecedented scale, but keeping your processing engine fed can be a challenge. Upstream data sources can 'drift' due to infrastructure, OS and application changes, causing ETL tools and hand-coded solutions to fail, inducing heartburn in even the most resilient data scientist. This session will survey the big data ingestion landscape, focusing on how open source tools such as Sqoop, Flume, Nifi and StreamSets can keep the data pipeline flowing.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
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https://www.conf42.com/Python_2023_Tim_Spann_David_Kjerrumgaard_ml_enhanced_event_streaming_apps_microservices
Build ML Enhanced Event Streaming Apps with Python Microservices
TIM SPANN
PRINCIPAL DEVELOPER ADVOCATE @ STREAMNATIVE
Tim Spann's LinkedIn account Tim Spann's twitter account
DAVID KJERRUMGAARD
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The easy way to build and scale machine learning apps.
PythonWebConference_ Cloud Native Apache Pulsar Development 202 with PythonTimothy Spann
PythonWebConference_ Cloud Native Apache Pulsar Development 202 with Python
Developers want to develop real-time applications that can turn raw text data into analyzed sentences and smart sentiment? Have you heard of real-time analytics, let's leverage your Python skills to make it happen now.
In this talk I will show developers how to develop real-time applications that use Pulsar functions to turn live event data into live NLP results and sentiment analyzed output.
We will walk through how to setup various scenarios to feed live data from apps and webapps to Apache Pulsar for real-time analytics and NLP.
At the end of the talk, developers will be able to use Python for real-time NLP analytics and have gained insight on how and when to use various streaming protocols, platforms, libraries and systems including Apache Pulsar, Apache Kafka, MQTT, Websockets, AMQP and Apache Spark.
https://2023.pythonwebconf.com/presentations/apache-pulsar-development-202-with-python
Apache Pulsar Development 101 with PythonTimothy Spann
Apache Pulsar Development 101 with Python PS2022_Ecosystem_v0.0
There is always the fear a speaker cannot make it. So just in case, since I was the MC for the ecosystem track I put together a talk just in case.
Here it is. Never seen or presented.
All Day DevOps - FLiP Stack for Cloud Data LakesTimothy Spann
https://www.alldaydevops.com/addo-speakers/timothy-spann
Timothy Spann
StreamNative
MODERN INFRASTRUCTURE
SHARE THIS SESSION
Session Name: FLiP Stack for Cloud Data Lakes
Utilizing an all Apache stack for Rapid Data Lake Population and querying utilizing Apache Flink, Apache Pulsar, and Apache NiFi. We can quickly stream data to and from any datalake, data lake house, lakehouse, database or any datamart regardless of cloud or size. FLiP allows for Java and Python developers to build scalable solutions that span messaging and streaming in cloud native fashion with full monitoring.
Speaker Bio:
Tim Spann is a Developer Advocate @ StreamNative where he works with Apache Pulsar, Apache Flink, Apache NiFi, Apache MXNet, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData, and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, Pulsar, NiFi, the blockchain, and Spark.
Data science online camp using the flipn stack for edge ai (flink, nifi, pu...Timothy Spann
Data science online camp using the flipn stack for edge ai (flink, nifi, pulsar)
Dec 3, 2021
Apache NiFi
Apache Flink
Apache Pulsar
Edge AI
Cloud Native Made Easy
StreamNative
Living the Stream Dream with Pulsar and Spring BootTimothy Spann
Living the Stream Dream with Pulsar and Spring Boot
https://events.geekle.us/java23
feb 21, 2023
https://geekle.us/schedule/java23
Living the Stream Dream with Pulsar and Spring Boot
For building Java applications, Spring is the universal answer as it supplies all the connectors and integrations one could want. The same is true for Apache Pulsar as it provides connectors, integration and flexibility to any use case. Apache Pulsar has a robust native Java library to use with Spring as well as other protocol options.
Apache Pulsar provides a cloud native, geo-replicated unified messaging platform that allows for many messaging paradigms. This lends itself well to upgrading existing applications as Pulsar supports using libraries for WebSockets, MQTT, Kafka, JMS, AMQP and RocketMQ. In this talk I will build some example applications utilizing several different protocols for building a variety of applications from IoT to Microservices to Log Analytics.
We will build Spring Boot microservices that utilize Apache Pulsar as a central data hub for communications and enrichment. This utilizes the new Spring for Pulsar framework.
https://github.com/spring-projects-experimental/spring-pulsar
We talked about it on Josh Long's podcast https://spring.io/blog/2022/09/15/a-bootiful-podcast-big-data-legend-former-pivot-and-friend-to-the-spring-community-tim-spann
programming real-time applications with Java 17, Spring Boot and Apache Pulsar 2.11
Apache Pulsar with MQTT for Edge Computing - Pulsar Summit Asia 2021StreamNative
Today we will span from edge to any and all clouds to support data collection, real-time streaming, sensor ingest, edge computing, IoT use cases and edge AI. Apache Pulsar allows us to build computing at the edge and produce and consume messages at scale in any IoT, hybrid or cloud environment. Apache Pulsar supports MoP which allows for MQTT protocol to be used for high speed messaging.
We will teach you to quickly build scalable open source streaming applications regardless of if you are running in containers, pods, edge devices, VMs, on-premise servers, moving vehicles and any cloud.
Let's keep it simple and streaming.pdfVMware Tanzu
I’ll walk through how to build a simple streaming application using JDK 17, Spring Boot 3, and Apache Pulsar 2.11. At the end of this talk, you’ll have a simple streaming application running and ready for testing and beyond.
Speaker: Timothy Spann, Developer Advocate, StreamNative
Princeton Dec 2022 Meetup_ StreamNative and Cloudera StreamingTimothy Spann
Princeton Dec 2022 Meetup_ StreamNative and Cloudera Streaming
https://www.meetup.com/new-york-city-apache-pulsar-meetup/
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/289674210/
|WHAT THE SESSION WILL COVER|
Apache NiFi
Apache Pulsar
Apache Flink
Flink SQL
We will show you how to build apps, so download beforehand to Docker, K8, your Laptop, or the cloud.
Cloudera CSP Setup
Getting Started with Cloudera Stream Processing Community Edition
You may download CSP-CE here:
Cloudera Stream Processing Community Edition
The Cloudera CDP User's page:
CDP Resources Page
https://youtu.be/s80sz3NWwHo
https://docs.cloudera.com/csp-ce/latest/index.html
https://www.cloudera.com/downloads/cdf/csp-community-edition.html
Apache Pulsar
https://pulsar.apache.org/docs/getting-started-standalone/
or
https://streamnative.io/free-cloud/
Cloudera + Pulsar
https://community.cloudera.com/t5/Cloudera-Stream-Processing-Forum/Using-Apache-Pulsar-with-SQL-Stream-Builder/m-p/349917
https://community.cloudera.com/t5/Community-Articles/Using-Apache-NiFi-with-Apache-Pulsar-for-Streaming/ta-p/337891
|AGENDA|
6:00 - 6:30 PM EST: Food, Drink, and Networking!!!
6:30 - 7:15 PM EST: Presentation - Tim Spann, StreamNative Developer Advocate
7:15 - 8:00 PM EST: Presentation - John Kuchmek, Cloudera Principal Solutions Engineer
8:00 - 8:30 PM EST: Round Table on Real-Time Streaming, Q&A
|ABOUT THE SPEAKERS|
John Kuchmek is a Principal Solutions Engineer for Cloudera. Before joining Cloudera, John transitioned to the Autonomous Intelligence team where he was in charge of integrating the platforms to allow data scientists to work with various types of data.
Tim Spann is a Developer Advocate for StreamNative. He works with StreamNative Cloud, Apache Pulsar™, Apache Flink®, Flink® SQL, Big Data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming.
See:
https://www.meetup.com/new-york-city-apache-pulsar-meetup/events/283837865/
https://github.com/tspannhw/SpeakerProfile
https://www.meetup.com/futureofdata-newyork/
https://github.com/tspannhw/pulsar-transit-function
https://www.meetup.com/futureofdata-princeton/
https://github.com/tspannhw/create-nifi-pulsar-flink-apps
https://medium.com/@tspann/using-apache-pulsar-with-cloudera-sql-builder-apache-flink-b518aa9eadff
https://github.com/tspannhw/meetups/blob/main/15December2022.md All resources for the meetup
Fast Streaming into Clickhouse with Apache PulsarTimothy Spann
https://github.com/tspannhw/SpeakerProfile/tree/main/2022/talks
Fast Streaming into Clickhouse with Apache Pulsar
https://github.com/tspannhw/FLiPC-FastStreamingIntoClickhouseWithApachePulsar
https://www.meetup.com/San-Francisco-Bay-Area-ClickHouse-Meetup/events/285271332/
Fast Streaming into Clickhouse with Apache Pulsar - Meetup 2022
StreamNative - Apache Pulsar - Stream to Altinity Cloud - Clickhouse
May the 4th Be With You!
04-May-2022 Clickhosue Meetup
CREATE TABLE iotjetsonjson_local
(
uuid String,
camera String,
ipaddress String,
networktime String,
top1pct String,
top1 String,
cputemp String,
gputemp String,
gputempf String,
cputempf String,
runtime String,
host String,
filename String,
host_name String,
macaddress String,
te String,
systemtime String,
cpu String,
diskusage String,
memory String,
imageinput String
)
ENGINE = MergeTree()
PARTITION BY uuid
ORDER BY (uuid);
CREATE TABLE iotjetsonjson ON CLUSTER '{cluster}' AS iotjetsonjson_local
ENGINE = Distributed('{cluster}', default, iotjetsonjson_local, rand());
select uuid, top1pct, top1, gputempf, cputempf
from iotjetsonjson
where toFloat32OrZero(top1pct) > 40
order by toFloat32OrZero(top1pct) desc, systemtime desc
select uuid, systemtime, networktime, te, top1pct, top1, cputempf, gputempf, cpu, diskusage, memory,filename
from iotjetsonjson
order by systemtime desc
select top1, max(toFloat32OrZero(top1pct)), max(gputempf), max(cputempf)
from iotjetsonjson
group by top1
select top1, max(toFloat32OrZero(top1pct)) as maxTop1, max(gputempf), max(cputempf)
from iotjetsonjson
group by top1
order by maxTop1
Tim Spann
Developer Advocate
StreamNative
DBCC 2021 - FLiP Stack for Cloud Data LakesTimothy Spann
DBCC 2021 - FLiP Stack for Cloud Data Lakes
With Apache Pulsar, Apache NiFi, Apache Flink. The FLiP(N) Stack for Event processing and IoT. With StreamNative Cloud.
DBCC International – Friday 15.10.2021
Powered by Apache Pulsar, StreamNative provides a cloud-native, real-time messaging and streaming platform to support multi-cloud and hybrid cloud strategies.
bigdata 2022_ FLiP Into Pulsar Apps
In this session, Timothy will introduce you to the world of Apache Pulsar and how to build real-time messaging and streaming applications with a variety of OSS libraries, schemas, languages, frameworks, and tools.
FLiP Into Pulsar Apps
08:30 – 09:15
•
23 Nov, 2022
In this session, Timothy will introduce you to the world of Apache Pulsar and how to build real-time messaging and streaming applications with a variety of OSS libraries, schemas, languages, frameworks, and tools.
Open Source Big Data Ingestion - Without the Heartburn!Pat Patterson
Big Data tools such as Hadoop and Spark allow you to process data at unprecedented scale, but keeping your processing engine fed can be a challenge. Upstream data sources can 'drift' due to infrastructure, OS and application changes, causing ETL tools and hand-coded solutions to fail, inducing heartburn in even the most resilient data scientist. This session will survey the big data ingestion landscape, focusing on how open source tools such as Sqoop, Flume, Nifi and StreamSets can keep the data pipeline flowing.
Similar to CODEONTHEBEACH_Streaming Applications with Apache Pulsar (20)
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
DATA SUMMIT 24 Building Real-Time Pipelines With FLaNKTimothy Spann
Building Real-Time Pipelines With FLaNK
Timothy Spann, Principal Developer Advocate, Streaming - Cloudera Future of Data meetup, startup grind, AI Camp
The combination of Apache Flink, Apache NiFi, and Apache Kafka for building real-time data processing pipelines is extremely powerful, as demonstrated by this case study using the FLaNK-MTA project. The project leverages these technologies to process and analyze real-time data from the New York City Metropolitan Transportation Authority (MTA). FLaNK-MTA demonstrates how to efficiently collect, transform, and analyze high-volume data streams, enabling timely insights and decision-making.
Apache NiFi
Apache Kafka
Apache Flink
Apache Iceberg
LLM
Generative AI
Slack
Postgresql
Generative AI on Enterprise Cloud with NiFi and MilvusTimothy Spann
Gen AI on Enterprise Cloud
Apache NiFi
Milvus
Apache Kafka
Apache Flink
Cloudera Machine Learning
Cloudera DataFlow
https://medium.com/@tspann/building-a-milvus-connector-for-nifi-34372cb3c7fa
https://www.meetup.com/futureofdata-princeton/events/300737266/
https://lu.ma/q7pcfyjn?source=post_page-----34372cb3c7fa--------------------------------&tk=TTyakY
If you're interested in working with Generative AI on the cloud, this virtual workshop is for you.
Tim Spann from Cloudera and Yujian Tang from Zilliz will cover how you can implement your own GenAI workflows on the cloud at enterprise scale.
9:00 - 9:05: Intro
9:05 - 9:15: What is Milvus
9:15 - 9:25: Cloudera Development Platform
9:25 - 10:00: Demo
Location
https://www.youtube.com/watch?v=IfWIzKsoHnA
https://github.com/tspannhw/SpeakerProfile
https://www.linkedin.com/in/yujiantang/
Conf42-LLM_Adding Generative AI to Real-Time Streaming PipelinesTimothy Spann
Conf42-LLM_Adding Generative AI to Real-Time Streaming Pipelines
https://www.youtube.com/watch?v=Yeua8NlzQ3Y
https://www.conf42.com/Large_Language_Models_LLMs_2024_Tim_Spann_generative_ai_streaming
Adding Generative AI to Real-Time Streaming Pipelines
Abstract
Let’s build streaming pipelines that convert streaming events into prompts, call LLMs, and process the results.
Summary
Tim Spann: My talk is adding generative AI to real time streaming pipelines. I'm going to discuss a couple of different open source technologies. We'll touch on Kafka, Nifi, Flink, Python, Iceberg. All the slides, all the code and GitHub are out there.
Llm, if you didn't know, is rapidly evolving. There's a lot of different ways to interact with models. That enrichment, transformation, processing really needs tools. The amount of models and projects and software that are available is massive.
Nifi supports hundreds of different inputs and can convert them on the fly. Great way to distribute your data quickly to whoever needs it without duplication, without tight coupling. Fun to find new things to integrate into.
So what we can do is, well, I want to get a meetup chat going. I have a processor here that just listens for events as they come from slack. And then I'm going to clean it up, add a couple fields and push that out to slack. Every model is a little bit of different tweaking.
Nifi acts as a whole website. And as you see here, it can be get, post, put, whatever you want. We send that response back to flink and it shows up here. Thank you for attending this talk. I'm going to be speaking at some other events very shortly.
Transcript
This transcript was autogenerated. To make changes, submit a PR.
Hi, Tim Spann here. My talk is adding generative AI to real time streaming pipelines, and we're here for the large language model conference at Comp 42, which is always a nice one, great place to be. I'm going to discuss a couple of different open source technologies that work together to enable you to build real time pipelines using large language models. So we'll touch on Kafka, Nifi, Flink, Python, Iceberg, and I'll show you a little bit of each one in the demos. I've been working with data machine learning, streaming IoT, some other things for a number of years, and you could contact me at any of these places, whether Twitter or whatever it's called, some different blogs, or in person at my meetups and at different conferences around the world. I do a weekly newsletter, cover streaming ML, a lot of LLM, open source, Python, Java, all kinds of fun stuff, as I mentioned, do a bunch of different meetups. They are not just in the east coast of the US, they are available virtually live, and I also put them on YouTube, and if you need them somewhere else, let me know. We publish all the slides, all the code and GitHub. Everything you need is out there. Let's get into the talk. Llm, if you didn't know, is rapidly evolving. While you're typing down the things that you use, it
2024 XTREMEJ_ Building Real-time Pipelines with FLaNK_ A Case Study with Tra...Timothy Spann
2024 XTREMEJ_ Building Real-time Pipelines with FLaNK_ A Case Study with Transit Data
https://xtremej.dev/2023/schedule/
Building Real-time Pipelines with FLaNK: A Case Study with Transit Data
Overview of the problem, the application (code walkthru and running), overview of FLaNK, introduction to NiFi, introduction to Kafka, and introduction to Flink.
28March2024-Codeless-Generative-AI-Pipelines
https://www.meetup.com/futureofdata-princeton/events/299440871/
https://www.meetup.com/real-time-analytics-meetup-ny/events/299290822/
******Note*****
The event is seat-limited, therefore please complete your registration here. Only people completing the form will be able to attend.
-----------------------
We're excited to invite you to join us in-person, for a Real-Time Analytics exploration!
Join us for an evening of insights, networking as we delve into the OSS technologies shaping the field!
Agenda:
05:30-06:00: Pizza and friends
06:00- 06:40: Codeless GenAI Pipelines with Flink, Kafka, NiFi
06:40- 07:20 Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders
07:20-07:30 QNA
Codeless GenAI Pipelines with Flink, Kafka, NiFi | Tim Spann, Cloudera
Explore the power of real-time streaming with GenAI using Apache NiFi. Learn how NiFi simplifies data engineering workflows, allowing you to focus on creativity over technical complexities. I'll guide you through practical examples, showcasing NiFi's automation impact from ingestion to delivery. Whether you're a seasoned data engineer or new to GenAI, this talk offers valuable insights into optimizing workflows. Join us to unlock the potential of real-time streaming and witness how NiFi makes data engineering a breeze for GenAI applications!
Real-Time Analytics in the Corporate World: How Apache Pinot® Powers Industry Leaders | Viktor Gamov, StarTree
Explore how industry leaders like LinkedIn, Uber Eats, and Stripe are mastering real-time data with Viktor as your guide. Discover how Apache Pinot transforms data into actionable insights instantly. Viktor will showcase Pinot's features, including the Star-Tree Index, and explain why it's a game-changer in data strategy. This session is for everyone, from data geeks to business gurus, eager to uncover the future of tech. Join us and be wowed by the power of real-time analytics with Apache Pinot!
-------
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera.
He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more.
TCFPro24 Building Real-Time Generative AI PipelinesTimothy Spann
https://princetonacm.acm.org/tcfpro/
18th Annual IEEE IT Professional Conference (ITPC)
Armstrong Hall at The College of New Jersey
Friday, March 15th, 2024 | 10:00 AM to 5:00 PM
IT Professional Conference at Trenton Computer Festival
IEEE Information Technology Professional Conference on Friday, March 15th, 2024
TCFPro24 Building Real-Time Generative AI Pipelines
Building Real-Time Generative AI Pipelines
In this talk, Tim will delve into the exciting realm of building real-time generative AI pipelines with streaming capabilities. The discussion will revolve around the integration of cutting-edge technologies to create dynamic and responsive systems that harness the power of generative algorithms.
From leveraging streaming data sources to implementing advanced machine learning models, the presentation will explore the key components necessary for constructing a robust real-time generative AI pipeline. Practical insights, use cases, and best practices will be shared, offering a comprehensive guide for developers and data scientists aspiring to design and implement dynamic AI systems in a streaming environment.
Tim will show a live demo showing we can use Apache NiFi to provide a live chat between a person in Slack and several LLM models all orchestrated with Apache NiFi, Apache Kafka and Python. We will use RAG against Chroma and Pinecone vector data stores, Hugging Face and WatsonX.AI LLM, and add additional context with NiFi lookups of stocks, weather and other data streams in real-time.
Timothy Spann
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Pulsar, Apache Kafka, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming.
Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark.
Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipel...Timothy Spann
2024 February 28 - NYC - Meetup Unlocking Financial Data with Real-Time Pipelines
https://www.meetup.com/futureofdata-newyork/events/298660453/
Unlocking Financial Data with Real-Time Pipelines
(Flink Analytics on Stocks with SQL )
By Timothy Spann
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data. I will be utilizing NiFi 2.0 with Python and Vector Databases.
Timothy Spann
Principal Developer Advocate, Cloudera
Tim Spann is a Principal Developer Advocate in Data In Motion for Cloudera. He works with Apache NiFi, Apache Kafka, Apache Pulsar, Apache Flink, Flink SQL, Apache Pinot, Trino, Apache Iceberg, DeltaLake, Apache Spark, Big Data, IoT, Cloud, AI/DL, machine learning, and deep learning. Tim has over ten years of experience with the IoT, big data, distributed computing, messaging, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal DataFlow Field Engineer at Cloudera, a Senior Solutions Engineer at Hortonworks, a Senior Solutions Architect at AirisData, a Senior Field Engineer at Pivotal and a Team Leader at HPE. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton & NYC on Big Data, Cloud, IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as ApacheCon, DeveloperWeek, Pulsar Summit and many more. He holds a BS and MS in computer science.
https://twitter.com/PaaSDev
https://www.linkedin.com/in/timothyspann/
https://medium.com/@tspann
https://github.com/tspannhw/FLiPStackWeekly/
Conf42-Python-Building Apache NiFi 2.0 Python Processors
https://www.conf42.com/Python_2024_Tim_Spann_apache_nifi_2_processors
Building Apache NiFi 2.0 Python Processors
Abstract
Let’s enhance real-time streaming pipelines with smart Python code. Adding code for vector databases and LLM.
Summary
Tim Spann: I'm going to be talking today, be building Apache 9520 Python processors. One of the main purposes of supporting Python in the streaming tool Apache Nifi is to interface with new machine learning and AI and Gen AI. He says Python is a real game changer for Cloudera.
You're just going to add some metadata around it. It's a great way to pass a file along without changing it too substantially. We really need you to have Python 310 and again JDK 21 on your machine. You got to be smart about how you use these models.
There are a ton of python processors available. You can use them in multiple ways. We're still in the early world of Python processors, so now's the time to start putting yours out there. Love to see a lot of people write their own.
When we are parsing documents here, again, this is the Python one I'm picking PDF. Lots of different things you could do. If you're interested on writing your own python code for Apache Nifi, definitely reach out and thank.
Conf42Python -Using Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg with Stock Data and LLM
Abstract
In this talk, we’ll discuss how to use Apache NiFi, Apache Kafka, RisingWave, and Apache Iceberg to process and analyze stock data. We demonstrated the ingestion, processing, and analysis of stock data. Additionally, we illustrated how to use an LLM to generate predictions from the analyzed data.
Karin Wolok
Developer Relations, Dev Marketing, and Community Programming @ Project Elevate
Karin Wolok's LinkedIn account Karin Wolok's twitter account
Tim Spann
Principal Developer Advocate @ Cloudera
Tim Spann's LinkedIn account Tim Spann's twitter account
https://www.conf42.com/Python_2024_Karin_Wolok_Tim_Spann_nifi__kafka_risingwave_iceberg_llm
2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI PipelinesTimothy Spann
2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines
https://www.aicamp.ai/event/eventdetails/W2024022214
apache nifi
llm
generative ai
gen ai
ml
dl
machine learning
apache kafka
apache flink
postgresql
python
AI Meetup (NYC): GenAI, LLMs, ML and Data
Feb 22, 05:30 PM EST
Welcome to the monthly in-person AI meetup in New York City, in collaboration with Microsoft. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers
Agenda:
* 5:30pm~6:00pm: Checkin, Food/drink and networking
* 6:00pm~6:10pm: Welcome/community update
* 6:10pm~8:30pm: Tech talks
* 8:30pm: Q&A, Open discussion
Tech Talk: Searching and Reasoning Over Multimedia Data with Vector Databases and LMMs
Speaker: Zain Hasan (Weaviate LinkedIn)
Abstract: In this talk, Zain Hasan will discuss how we can use open-source multimodal embedding models in conjunction with large generative multimodal models that can that can see, hear, read, and feel data(!), to perform cross-modal search(searching audio with images, videos with text etc.) and multimodal retrieval augmented generation (MM-RAG) at the billion-object scale with the help of open source vector databases. I will also demonstrate, with live code demos, how being able to perform this cross-modal retrieval in real-time can enables users to use LLMs that can reason over their enterprise multimodal data. This talk will revolve around how we can scale the usage of multimodal embedding and generative models in production.
Tech Talk: Codeless Generative AI Pipelines
Speaker: Timothy Spann (Cloudera LinkedIn)
Abstract: Join us for an insightful talk on leveraging the power of real-time streaming tools, specifically Apache NiFi, to revolutionize GenAI data engineering. In this session, we’ll explore how the integration of Apache NiFi can automate the entire process of prompt building, making it a seamless and efficient task.
Speakers/Topics:
Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics
Sponsors:
We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 20,000+ local or 300K+ developers worldwide.
Venue:
Microsoft NYC - Times Square, 11 Times Square, New York, NY 10036
Room Name: Central Park West 6501
Community on Slack/Discord
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
Join Slack (search and join the #newyork channel) | Join Discord
DBA Fundamentals Group: Continuous SQL with Kafka and FlinkTimothy Spann
DBA Fundamentals Group: Continuous SQL with Kafka and Flink
20-Feb-2024
In this talk, I will walk through how someone can set up and run continuous SQL queries against Kafka topics utilizing Apache Flink. We will walk through creating Kafka topics, schemas, and publishing data.
We will then cover consuming Kafka data, joining Kafka topics, and inserting new events into Kafka topics as they arrive. This basic overview will show hands-on techniques, tips, and examples of how to do this.
Tim Spann
Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science.
OSACon 2023_ Unlocking Financial Data with Real-Time PipelinesTimothy Spann
OSACon 2023_ Unlocking Financial Data with Real-Time Pipelines
Unlocking Financial Data with Real-Time Pipelines
Financial institutions thrive on accurate and timely data to drive critical decision-making processes, risk assessments, and regulatory compliance. However, managing and processing vast amounts of financial data in real-time can be a daunting task. To overcome this challenge, modern data engineering solutions have emerged, combining powerful technologies like Apache Flink, Apache NiFi, Apache Kafka, and Iceberg to create efficient and reliable real-time data pipelines. In this talk, we will explore how this technology stack can unlock the full potential of financial data, enabling organizations to make data-driven decisions swiftly and with confidence.
Introduction: Financial institutions operate in a fast-paced environment where real-time access to accurate and reliable data is crucial. Traditional batch processing falls short when it comes to handling rapidly changing financial markets and responding to customer demands promptly. In this talk, we will delve into the power of real-time data pipelines, utilizing the strengths of Apache Flink, Apache NiFi, Apache Kafka, and Iceberg, to unlock the potential of financial data.
Key Points to be Covered:
Introduction to Real-Time Data Pipelines: a. The limitations of traditional batch processing in the financial domain. b. Understanding the need for real-time data processing.
Apache Flink: Powering Real-Time Stream Processing: a. Overview of Apache Flink and its role in real-time stream processing. b. Use cases for Apache Flink in the financial industry. c. How Flink enables fast, scalable, and fault-tolerant processing of streaming financial data.
Apache Kafka: Building Resilient Event Streaming Platforms: a. Introduction to Apache Kafka and its role as a distributed streaming platform. b. Kafka's capabilities in handling high-throughput, fault-tolerant, and real-time data streaming. c. Integration of Kafka with financial data sources and consumers.
Apache NiFi: Data Ingestion and Flow Management: a. Overview of Apache NiFi and its role in data ingestion and flow management. b. Data integration and transformation capabilities of NiFi for financial data. c. Utilizing NiFi to collect and process financial data from diverse sources.
Iceberg: Efficient Data Lake Management: a. Understanding Iceberg and its role in managing large-scale data lakes. b. Iceberg's schema evolution and table-level metadata capabilities. c. How Iceberg simplifies data lake management in financial institutions.
Real-World Use Cases: a. Real-time fraud detection using Flink, Kafka, and NiFi. b. Portfolio risk analysis with Iceberg and Flink. c. Streamlined regulatory reporting leveraging all four technologies.
Best Practices and Considerations: a. Architectural considerations when building real-time financial data pipelines. b. Ensuring data integrity, security, and compliance in real-time pipelines. c. Scalability an
Building Real-time Travel Alerts
In this session, we will walk through how to build a complete streaming application to send alerts based on travel advisories from public data. We will also join in other data sources of relevance and push out alerts.
We will show you how to build this streaming application with Apache NiFi, Apache Kafka, and Apache Flink and show you when/why/how, and what to build to maximize performance, productivity, and ease of development.
Let's get streaming.
Apache Flink
Apache Kafka
Apache NiFi
FLaNK Stack
Tim Spann
Big Data Conference Europe 2023
JConWorld_ Continuous SQL with Kafka and FlinkTimothy Spann
JConWorld: Continuous SQL with Kafka and Flink
In this talk, I will walk through how someone can setup and run continous SQL queries against Kafka topics utilizing Apache Flink. We will walk through creating Kafka topics, schemas and publishing data.
We will then cover consuming Kafka data, joining Kafka topics and inserting new events into Kafka topics as they arrive. This basic over view will show hands-on techniques, tips and examples of how to do this.
Tim Spann is the Principal Developer Advocate for Data in Motion @ Cloudera where he works with Apache Kafka, Apache Flink, Apache NiFi, Apache Iceberg, TensorFlow, Apache Spark, big data, the IoT, machine learning, and deep learning. Tim has over a decade of experience with the IoT, big data, distributed computing, streaming technologies, and Java programming. Previously, he was a Developer Advocate at StreamNative, Principal Field Engineer at Cloudera, a Senior Solutions Architect at AirisData and a senior field engineer at Pivotal. He blogs for DZone, where he is the Big Data Zone leader, and runs a popular meetup in Princeton on big data, the IoT, deep learning, streaming, NiFi, the blockchain, and Spark. Tim is a frequent speaker at conferences such as IoT Fusion, Strata, ApacheCon, Data Works Summit Berlin, DataWorks Summit Sydney, and Oracle Code NYC. He holds a BS and MS in computer science. https://www.datainmotion.dev/p/about-me.html https://dzone.com/users/297029/bunkertor.html
https://www.youtube.com/channel/UCDIDMDfje6jAvNE8DGkJ3_w?view_as=subscriber
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
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.
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.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
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.
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.
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
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
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.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
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.
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.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
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.
3. Tim Spann
Developer Advocate
● FLiP(N) Stack = Flink, Pulsar and NiFi Stack
● Streaming Systems/ Data Architect
● Experience:
○ 15+ years of experience with batch and streaming
technologies including Pulsar, Flink, Spark, NiFi, Spring,
Java, Big Data, Cloud, MXNet, Hadoop, Datalakes, IoT
and more.
4. FLiP Stack Weekly
This week in Apache Flink, Apache Pulsar, Apache
NiFi, Apache Spark and open source friends.
https://bit.ly/32dAJft
5. Apache Pulsar is a Cloud-Native
Messaging and Event-Streaming Platform.
8. ● “Bookies”
● Stores messages and cursors
● Messages are grouped in
segments/ledgers
● A group of bookies form an
“ensemble” to store a ledger
● “Brokers”
● Handles message routing and
connections
● Stateless, but with caches
● Automatic load-balancing
● Topics are composed of
multiple segments
●
● Stores metadata for both
Pulsar and BookKeeper
● Service discovery
Store
Messages
Metadata &
Service Discovery
Metadata &
Service Discovery
Key Pulsar Concepts: Architecture
MetaData
Storage
9. Component Description
Value / data payload The data carried by the message. All Pulsar messages contain raw bytes, although
message data can also conform to data schemas.
Key Messages are optionally tagged with keys, used in partitioning and also is useful for
things like topic compaction.
Properties An optional key/value map of user-defined properties.
Producer name The name of the producer who produces the message. If you do not specify a producer
name, the default name is used. Message De-Duplication.
Sequence ID Each Pulsar message belongs to an ordered sequence on its topic. The sequence ID of
the message is its order in that sequence. Message De-Duplication.
Messages - the basic unit of Pulsar
10. Key Pulsar Concepts:
Messaging vs Streaming
Message Queueing - Queueing systems are ideal
for work queues that do not require tasks to be
performed in a particular order.
Streaming - Streaming works best in situations
where the order of messages is important.
12. Schema Registry
Schema Registry
schema-1 (value=Avro/Protobuf/JSON) schema-2 (value=Avro/Protobuf/JSON) schema-3
(value=Avro/Protobuf/JSON)
Schema
Data
ID
Local Cache
for Schemas
+
Schema
Data
ID +
Local Cache
for Schemas
Send schema-1
(value=Avro/Protobuf/JSON) data
serialized per schema ID
Send (register)
schema (if not in
local cache)
Read schema-1
(value=Avro/Protobuf/JSON) data
deserialized per schema ID
Get schema by ID (if
not in local cache)
Producers Consumers
18. Pulsar Functions
● Lightweight computation
similar to AWS Lambda.
● Specifically designed to use
Apache Pulsar as a message
bus.
● Function runtime can be
located within Pulsar Broker.
A serverless event streaming
framework
19. ● Consume messages from one or
more Pulsar topics.
● Apply user-supplied processing
logic to each message.
● Publish the results of the
computation to another topic.
● Support multiple programming
languages (Java, Python, Go)
● Can leverage 3rd-party libraries
to support the execution of ML
models on the edge.
Pulsar Functions
20. Function Mesh
Pulsar Functions, along with Pulsar IO/Connectors, provide a powerful API for ingesting,
transforming, and outputting data.
Function Mesh, another StreamNative project, makes it easier for developers to create
entire applications built from sources, functions, and sinks all through a declarative API.
37. Using Connection URLs
Java:
PulsarClient client = PulsarClient.builder()
.serviceUrl("pulsar://broker1:6650")
.build();
C#:
var client = new PulsarClientBuilder()
.ServiceUrl("pulsar://broker1:6650")
.Build();
38. Auth
C#
// Create the auth class
var tokenAuth = AuthenticationFactory.token("<jwttoken>");
// Pass the authentication implementation
var client = new PulsarClientBuilder()
.ServiceUrl("pulsar://broker1:6650")
.Authentication(tokenAuth)
.Build();
40. import java.util.function.Function;
public class MyFunction implements Function<String, String> {
public String apply(String input) {
return doBusinessLogic(input);
}
}
Your Code Here
Pulsar
Function Java
41. import org.apache.pulsar.client.impl.schema.JSONSchema;
import org.apache.pulsar.functions.api.*;
public class AirQualityFunction implements Function<byte[], Void> {
@Override
public Void process(byte[] input, Context context) {
context.getLogger().debug("File:” + new String(input));
context.newOutputMessage(“topicname”,
JSONSchema.of(Observation.class))
.key(UUID.randomUUID().toString())
.property(“prop1”, “value1”)
.value(observation)
.send();
}
}
Your Code Here
Pulsar
Function SDK
43. Subscribing to a Topic and setting
Subscription Name Java
Consumer<byte[]> consumer = pulsarClient.newConsumer()
.topic(topic)
.subscriptionName(“subscriptionName")
.subscribe();
45. Building Pulsar SQL View
bin/pulsar sql
show catalogs;
show schemas in pulsar;
show tables in pulsar."conf/ete";
select * from pulsar."conf/ete"."first";
exit;
https://github.com/tspannhw/FLiP-Into-Trino
46. Spark + Pulsar
https://pulsar.apache.org/docs/en/adaptors-spark/
val dfPulsar = spark.readStream.format("
pulsar")
.option("
service.url", "pulsar://pulsar1:6650")
.option("
admin.url", "http://pulsar1:8080
")
.option("
topic", "persistent://public/default/airquality").load()
val pQuery = dfPulsar.selectExpr("*")
.writeStream.format("
console")
.option("truncate", false).start()
____ __
/ __/__ ___ _____/ /__
_ / _ / _ `/ __/ '_/
/___/ .__/_,_/_/ /_/_ version 3.2.0
/_/
Using Scala version 2.12.15
(OpenJDK 64-Bit Server VM, Java 11.0.11)
47. ● Unified computing engine
● Batch processing is a special case of stream processing
● Stateful processing
● Massive Scalability
● Flink SQL for queries, inserts against Pulsar Topics
● Streaming Analytics
● Continuous SQL
● Continuous ETL
● Complex Event Processing
● Standard SQL Powered by Apache Calcite
Apache Flink?
48. Building Pulsar Flink SQL View
CREATE CATALOG pulsar WITH (
'type' = 'pulsar',
'service-url' = 'pulsar://pulsar1:6650',
'admin-url' = 'http://pulsar1:8080',
'format' = 'json'
);
select * from anytopicisatable;
https://github.com/tspannhw/FLiP-Into-Trino
49. SQL
select aqi, parameterName, dateObserved, hourObserved, latitude,
longitude, localTimeZone, stateCode, reportingArea from
airquality;
select max(aqi) as MaxAQI, parameterName, reportingArea from
airquality group by parameterName, reportingArea;
select max(aqi) as MaxAQI, min(aqi) as MinAQI, avg(aqi) as
AvgAQI, count(aqi) as RowCount, parameterName, reportingArea
from airquality group by parameterName, reportingArea;
54. Metrics: Broker
Broker metrics are exposed under "/metrics"
at port 8080.
You can change the port by updating
webServicePort to a different port in the
broker.conf configuration file.
All the metrics exposed by a broker are labeled
with cluster=${pulsar_cluster}.
The name of Pulsar cluster is the value of
${pulsar_cluster}, configured in the
broker.conf file.
These metrics are available for brokers:
● Namespace metrics
○ Replication metrics
● Topic metrics
○ Replication metrics
● ManagedLedgerCache metrics
● ManagedLedger metrics
● LoadBalancing metrics
○ BundleUnloading metrics
○ BundleSplit metrics
● Subscription metrics
● Consumer metrics
● ManagedLedger bookie client metrics
For more information: https://pulsar.apache.org/docs/en/reference-metrics/#broker
55. Use Cases
● Unified Messaging Platform
● AdTech
● Fraud Detection
● Connected Car
● IoT Analytics
● Microservices Development
59. Hosted by
Save Your Spot Now
Use code CODEONTHEBEACH20
to get 20% off.
Pulsar Summit
San Francisco
Hotel Nikko
August 18 2022
5 Keynotes
12 Breakout Sessions
1 Amazing Happy Hour
60. Pulsar Summit
San Francisco
Sponsorship
Prospectus
Community Sponsorships Available
Help engage and connect the Apache Pulsar
community by becoming an official sponsor for
Pulsar Summit San Francisco 2022! Learn more
about the requirements and benefits of
becoming a community sponsor.
Hosted by
62. Python For Pulsar on Pi
● https://github.com/tspannhw/FLiP-Pi-BreakoutGarden
● https://github.com/tspannhw/FLiP-Pi-Thermal
● https://github.com/tspannhw/FLiP-Pi-Weather
● https://github.com/tspannhw/FLiP-RP400
● https://github.com/tspannhw/FLiP-Py-Pi-GasThermal
● https://github.com/tspannhw/FLiP-PY-FakeDataPulsar
● https://github.com/tspannhw/FLiP-Py-Pi-EnviroPlus
● https://github.com/tspannhw/PythonPulsarExamples
● https://github.com/tspannhw/pulsar-pychat-function
● https://github.com/tspannhw/FLiP-PulsarDevPython101
● https://github.com/tspannhw/airquality
63. streamnative.io
Passionate and dedicated team.
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Apache Pulsar.
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manage, and leverage data using Pulsar’s
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platform.
64. Apache Pulsar Training
● Instructor-led courses
○ Pulsar Fundamentals
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○ Pulsar Operations
● On-demand learning with labs
● 300+ engineers, admins and architects trained!
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Academy.StreamNative.io
65.
66. Let’s Keep
in Touch!
Tim Spann
Developer Advocate
PaaSDev
https://www.linkedin.com/in/timothyspann
https://github.com/tspannhw