Java Pub House Freddy Guime & Bob Paulin

So we continue to have guests in our show to talk to us about interesting things... This time is about Apache Tika. This is an incredible tool to do search file processing and metadata extraction. Think about that you have tons of unstructured files, like emails, or documents, and you want to extract, index and then search theses. This is Tika's purpose. And who best to walk us through how it does its magic that its Project Management Committee (PMC) Chair, Tim Allison!
So take a listen as we go deeper on ingesting tons of content (which is fundamental for things like training LLMs).
http://www.javapubhouse.com/datadog
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Apache Tika
* https://tika.apache.org/
OpenSearch Project and OpenSearch Neural Plugin Tutorials
* https://opensearch.org/
* https://opensearch.org/docs/latest/search-plugins/neural-search/
* https://opster.com/guides/opensearch/opensearch-machine-learning/how-to-set-up-vector-search-in-opensearch/ 
* https://opster.com/guides/opensearch/opensearch-machine-learning/opensearch-hybrid-search/
* https://sease.io/2024/01/opensearch-knn-plugin-tutorial.html
* https://sease.io/2024/04/opensearch-neural-search-tutorial-hybrid-search.html
Selected Advanced File Processing toolkits/services
* https://unstructured.io/
* https://aws.amazon.com/textract/
* https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence
Selected Hybrid Search/RAG toolkits (there are _MANY_ others!)
* Haystack: https://haystack.deepset.ai/
* LangChain: https://www.langchain.com/
* LangStream: https://langstream.ai/
Search/Relevance Conferences
* https://haystackconf.com/
* https://2024.berlinbuzzwords.de/
* https://mices.co/
Tim's personal project
* JavaFX (ahem) tika-config writer UI: https://github.com/tballison/tika-gui-v2

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We have a great time talking to Matt Topol from Voltron Data on one of his Apache Software Foundation projects called Apache Arrow. It's both a spec and implementation of a columnar data format that is not only efficient, but cross-language compatible. We walk through the scenarios that it covers and how is becoming more and more pivotal for things like ML and LLMs. So come listen to this JPH episode on one of the best and free ways to distribute data and integrate services working on top of that data!
http://www.javapubhouse.com/datadog
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 - Apache Arrow Project (https://arrow.apache.org/)
 - Java implementation (https://arrow.apache.org/docs/java/index.html)
 - In-Memory Analytics with Apache Arrow (https://www.oreilly.com/library/view/in-memory-analytics-with/9781801071031/)
 - Matt Topol X (Twitter!) Account (https://twitter.com/zeroshade)
 - 
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Ok, so it's an incredible time to be in the Java Ecosystem, and one of the biggest frameworks out there just dropped their three-point-oh version! That's right! So Spring Boot is not officially 3.0, and it has as a Baseline Java 17! (oohh!!). So we brought in the big guns to talk about what does it mean to Upgrade to Spring Boot 3, and what are the new cool toys we can expect from that upgrade! 
In all, an amazing interview full of great things that are available NOW (so whatcha waiting for! Upgrade!)
http://www.javapubhouse.com/datadog
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 - Dan Vega's own What's new in Spring Boot 3 (https://www.danvega.dev/newsletter/whats-new-spring-boot-3/)
 - Official Spring Framework 6 Wiki (https://github.com/spring-projects/spring-framework/wiki/What's-New-in-Spring-Framework-6.x)
 - Spring Boot 3, and Spring Framework 6, What's new? (https://www.baeldung.com/spring-boot-3-spring-6-new)
 - Spring Boot 3 goes GA (https://spring.io/blog/2022/11/24/spring-boot-3-0-goes-ga)
 - Preparing for Spring Boot 3 (https://spring.io/blog/2022/05/24/preparing-for-spring-boot-3-0)
 - 
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Whew! So we took a big break over summer (like Bob said, we were just swamped with work.. oof), but we are BACK! and like always we are ready to explore even deeper Java topics for the professional developer.
This time we set our sights in Apache Kafka, one of the (if not THE) dominant distributed messaging framework / broker. If you have been integrating webservices, you might have been running into message brokers (and applying Enterprise Integration Patterns), well if so, you most likely have run into Kafka. 
We dive into "What does Kafka Solve", into what it is (and isn't), and why you should use it (or not use it), and how it differs from traditionalling Messaging systems.
In all, this is another episode of "Cloud stuff", and, like you know, that's where everything interesting is at! So have a listen! 
http://www.javapubhouse.com/datadog
We thank DataDogHQ for sponsoring this podcast episode

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Apache Kafka
https://kafka.apache.org/
Kafka Quick Start
https://developer.confluent.io/quickstart/kafka-on-confluent-cloud/
What IS Apache Kafka
https://developer.confluent.io/what-is-apache-kafka/
Apache Kafka Quickstart (With Tim Berglund, Hi!!!)
https://kafka.apache.org/quickstart 
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Yeah! so we have been working with the cloud for a while, terms like K8s, EC2, Route53, BlobData, CLI has been swinged around... and is a little mysterious, and sometimes looks like a black box where you just click buttons, add things, type commands, until it finally something good happens. But if something bad happens, we tend not to have the slightest idea on why!
Never fear, on this episode of PubHouse we start from the very beginning on describing (And dismantling) what the "Cloud" really is... Starting on how we got there, what are the different "components" of most clouds, and how to reason about them.
This way, the next time something unpredictable happens, you will know exactly where to start troubleshooting and how to navigate this space! This is the first episode of a series (probably a series of 2) on Cloud technologies. So if you never been exposed to the cloud and you're curious, or even if you've been working on it but everything sounds mysterious, then dive in!
http://www.javapubhouse.com/datadog

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Intro to AWS 
https://docs.aws.amazon.com/whitepapers/latest/aws-overview/introduction.html
What is Elastic Load Balancing
https://docs.aws.amazon.com/elasticloadbalancing/latest/userguide/what-is-load-balancing.html
What is Amazon Route 53
https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/Welcome.html
EC2 vs ECS vs Lambda
https://www.cloudzero.com/blog/ecs-vs-ec2
Intro to Azure Fundamentals
https://docs.microsoft.com/en-us/learn/modules/intro-to-azure-fundamentals/
Azure Containter Registry
https://azure.microsoft.com/en-us/services/container-registry/#features
Azure Compute
https://azure.microsoft.com/en-us/services/virtual-machines/#overview
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Ok, so is time to talk about something secretive! Like API Passwords, Auth tokens, or keys... these are things that we want to have as a Secret within our microservice. And yeah, adding them into your source code is a big no-no
Here we cover the dos (and dont's) of secret management, what are the benefits and drawbacks of the different solutions and we explore some of our favorite open source (and Cloud tools) for keeping secrets. We answer some important questions on how to effectively store and manage these secrets (the short answer is don't try to do it yourself!), and end up with the list of best practices for it.
If you are building a non-trivial (or interesting) web service, this is a must-listen episode!
http://www.javapubhouse.com/datadog
We thank DataDogHQ for sponsoring this podcast episode
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Language Features
Using AWS Secrets Manager to manage secrets in Spring Boot
https://raymondhlee.wordpress.com/2019/10/11/using-aws-secrets-manager-to-manage-secrets-in-spring-boot-applications/
AWS Secrets Manager
https://aws.amazon.com/secrets-manager/
Spring Cloud AWS
https://cloud.spring.io/spring-cloud-aws/reference/html/
Hashicorp Vault
https://www.vaultproject.io/
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