From startups to big-business: Using functional programming techniques to transform line of business applications

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Technologies like F#, microservices and event sourcing can build fast and efficient cloud platforms for data intensive applications. Hear from Scott Havens, Director of Engineering for Jet.com and Walmart Labs, on why they chose this approach to build their ecommerce platform and how after being acquired by Walmart, the same approaches are transforming internal systems for the world’s largest retailer.

Event streamsCommands Process command Events
Snapshot event
stream
Event stream
snapshots

Event streamsCommands Exec command Events
Snapshot event
stream
Event stream
snapshots

Event streams
(CosmosDB)
Raw sellable
inventory
(Kafka)
Commands
(Kafka)
Process command
Events
(Kafka)
Change Feed
Snapshot event
stream
Map raw sellable
inventory
Process command
(reservations only)
Commands
(HTTP)
Customer
front-end
checkout
Event stream
snapshots
(CosmosDB)
Inventory & order
updates (Kafka)
Marts
(Walmart.com,
Jet.com)
Filter available
inventory per mart
External to
Panther system
Communication
channel
Panther μs
Data
store
Map msg to
command

From startups to big-business: Using functional programming techniques to transform line of business applications

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Streams are a fundamental programming primitive for representing the flow of data through your system. It's time we brought this powerful tool to the web. What if we could stream data from a HTTP request, through a web worker that transforms it, and then into a <video> tag? Over the last year, I've been working on the WHATWG streams specification, which builds upon the lessons learned in Node.js, to provide a suitable abstraction for needs of the extensible web. I'll discuss briefly why streams are important, what they enable, and the role we envision them playing in the future of the web platform. Mostly, though, I want to help you understand streams, at a deep level. In the course of writing this specification, I've learned a lot about streams, and I want to share that knowledge with you. At the core, they are a very simple and beautiful abstraction. I think we've done a good job capturing that abstraction, and producing an API the web can be proud of. I'd love to tell you all about it.

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This LF Energy webinar took place June 20, 2024. It featured: -Alex Thornton, LF Energy -Hallie Cramer, Google -Daniel Roesler, UtilityAPI -Henry Richardson, WattTime In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms. This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups. Three primary specifications will be discussed: -Discovery and client registration, emphasizing transparent processes and secure and private access -Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure -Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data

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kafka-streams-cassandra-state-store' is a drop-in Kafka Streams State Store implementation that persists data to Apache Cassandra. By moving the state to an external datastore the stateful streams app (from a deployment point of view) effectively becomes stateless. This greatly improves elasticity and allows for fluent CI/CD (rolling upgrades, security patching, pod eviction, ...). It also can also help to reduce failure recovery and rebalancing downtimes, with demos showing sporty 100ms rebalancing downtimes for your stateful Kafka Streams application, no matter the size of the application’s state. As a bonus accessing Cassandra State Stores via 'Interactive Queries' (e.g. exposing via REST API) is simple and efficient since there's no need for an RPC layer proxying and fanning out requests to all instances of your streams application.

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Are you spending more time wrestling with your data than actually using it? You’re not alone. For many organizations, managing data from various sources can feel like an uphill battle. But what if you could turn that around and make your data work for you effortlessly? That’s where FME comes in. We’ve designed FME to tackle these exact issues, transforming your data chaos into a streamlined, efficient process. Join us for an introduction to All Data Enterprise Integration and discover how FME can be your game-changer. During this webinar, you’ll learn: - Why Data Integration Matters: How FME can streamline your data process. - The Role of Spatial Data: Why spatial data is crucial for your organization. - Connecting & Viewing Data: See how FME connects to your data sources, with a flash demo to showcase. - Transforming Your Data: Find out how FME can transform your data to fit your needs. We’ll bring this process to life with a demo leveraging both geometry and attribute validation. - Automating Your Workflows: Learn how FME can save you time and money with automation. Don’t miss this chance to learn how FME can bring your data integration strategy to life, making your workflows more efficient and saving you valuable time and resources. Join us and take the first step toward a more integrated, efficient, data-driven future!

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6. Event streamsCommands Process command Events Snapshot event stream Event stream snapshots

7. Event streamsCommands Exec command Events Snapshot event stream Event stream snapshots

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13. Event streamsCommands Exec command Events Snapshot event stream Event stream snapshots

14. Event streams (CosmosDB) Raw sellable inventory (Kafka) Commands (Kafka) Process command Events (Kafka) Change Feed Snapshot event stream Map raw sellable inventory Process command (reservations only) Commands (HTTP) Customer front-end checkout Event stream snapshots (CosmosDB) Inventory & order updates (Kafka) Marts (Walmart.com, Jet.com) Filter available inventory per mart External to Panther system Communication channel Panther μs Data store Map msg to command

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18. Event streams (CosmosDB) Raw sellable inventory (Kafka) Commands (Kafka) Process command Events (Kafka) Change Feed Snapshot event stream Map raw sellable inventory Process command (reservations only) Commands (HTTP) Customer front-end checkout Event stream snapshots (CosmosDB) Marts (Walmart.com, Jet.com) Filter available inventory per mart External to Panther system Communication channel Panther μs Data store Enqueue reservation expirations Map reservation expirations Res expirations (Azure Queue) Inventory & order updates (Kafka) Map msg to command

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