Building a Multi-Tenant Managed Platform For Streaming Data With Pulsar at Datastax
Data Engineering Podcast - Un pódcast de Tobias Macey - Domingos
Categorías:
Summary Everyone expects data to be transmitted, processed, and updated instantly as more and more products integrate streaming data. The technology to make that possible has been around for a number of years, but the barriers to adoption have still been high due to the level of technical understanding and operational capacity that have been required to run at scale. Datastax has recently introduced a new managed offering for Pulsar workloads in the form of Astra Streaming that lowers those barriers and make stremaing workloads accessible to a wider audience. In this episode Prabhat Jha and Jonathan Ellis share the work that they have been doing to integrate streaming data into their managed Cassandra service. They explain how Pulsar is being used by their customers, the work that they have done to scale the administrative workload for multi-tenant environments, and the challenges of operating such a data intensive service at large scale. This is a fascinating conversation with a lot of useful lessons for anyone who wants to understand the operational aspects of Pulsar and the benefits that it can provide to data workloads. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management You listen to this show to learn about all of the latest tools, patterns, and practices that power data engineering projects across every domain. Now there’s a book that captures the foundational lessons and principles that underly everything that you hear about here. I’m happy to announce I collected wisdom from the community to help you in your journey as a data engineer and worked with O’Reilly to publish it as 97 Things Every Data Engineer Should Know. Go to dataengineeringpodcast.com/97things today to get your copy! When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! RudderStack’s smart customer data pipeline is warehouse-first. It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Their SDKs and plugins make event streaming easy, and their integrations with cloud applications like Salesforce and ZenDesk help you go beyond event streaming. With RudderStack you can use all of your customer data to answer more difficult questions and then send those insights to your whole customer data stack. Sign up free at dataengineeringpodcast.com/rudder today. We’ve all been asked to help with an ad-hoc request for data by the sales and marketing team. Then it becomes a critical report that they need updated every week or every day. Then what do you do? Send a CSV via email? Write some Python scripts to automate it? But what about incremental sync, API quotas, error handling, and all of the other details that eat up your time? Today, there is a better way. With Census, just write SQL or plug in your dbt models and start syncing your cloud warehouse to SaaS applications like Salesforce, Marketo, Hubspot, and many more. Go to dataengineeringpodcast.com/census today to get a free 14-day trial. Your host is Tobias Macey and today I’m interviewing Prabhat Jha and Jonathan Ellis about Astra Streaming, a cloud-native streaming platform built on Apache Pulsar Interview Introduction How did you get involved in the area of data management? Can you describe what the Astra platform is and the story behind it? How does streaming fit into your overall product vision and the needs of your customers? What was your selection process/criteria for adopting a streaming engine to complement your existing technology investment? What are the core use cases that you are aiming to support with Astra Streaming? Can you describe the architecture and automation of your hosted platform for Pulsar? What are the integration points that you have built to make it work well with Cassandra? What are some of the additional tools that you have added to your distribution of Pulsar to simplify operation and use? What are some of the sharp edges that you have had to sand down as you have scaled up your usage of Pulsar? What is the process for someone to adopt and integrate with your Astra Streaming service? How do you handle migrating existing projects, particularly if they are using Kafka currently? One of the capabilities that you highlight on the product page for Astra Streaming is the ability to execute machine learning workflows on data in flight. What are some of the supporting systems that are necessary to power that workflow? What are the capabilities that are built into Pulsar that simplify the operational aspects of streaming ML? What are the ways that you are engaging with and supporting the Pulsar community? What are the near to medium term elements of the Pulsar roadmap that you are working toward and excited to incorporate into Astra? What are the most interesting, innovative, or unexpected ways that you have seen Astra used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Astra? When is Astra the wrong choice? What do you have planned for the future of Astra? Contact Info Prabhat LinkedIn @prabhatja on Twitter prabhatja on GitHub Jonathan LinkedIn @spyced on Twitter Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Links Pulsar Podcast Episode Streamnative Episode Datastax Astra Streaming Datastax Astra DB Luna Streaming Distribution Datastax Cassandra Kesque (formerly Kafkaesque) Kafka RabbitMQ Prometheus Grafana Pulsar Heartbeat Pulsar Summit Pulsar Summit Presentation on Kafka Connectors Replicated Chaos Engineering Fallout chaos engineering tools Jepsen Podcast Episode Jack VanLightly BookKeeper TLA+ Model Change Data Capture The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast