Managing a Distributed Electrical Grid in Real Time with Kafka
- prerequisites
- Advanced Java/Scala, Basics of JVM build systems, Basics of Docker, Basics of Apache Kafka.
- skills learned
- Fundamentals of IoT stream processing with Kafka Streams, Schema management & evolution with Apache Avro, Building distributed query engine to support real-time energy grids.
Look inside
In this liveProject, you'll take on the role of a backend data engineer working for a rapidly growing startup. Your company installs battery packs for solar panels, as well as IoT devices monitor energy usage. These devices can help users and utilities companies better manage their energy, saving your customers money and providing clean power to the wider grid. You’ve been given a big task: build the infrastructure from the ground up that can handle the streaming events of thousands of these IoT devices. This infrastructure will be expected to scale as your company grows, and so your team has chosen to work with Apache Kafka for stream processing of all the data. Your challenges will include efficiently ingesting IoT events, managing corner cases in IoT data processing, developing fleet-wide monitoring, and providing REST services to answer questions about battery energy capacity.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
book resources
When you start your liveProject, you get full access to the following books for 90 days.
In MEAP, you get immediate access to a liveProject under development, so you can participate while it is created, tested, and improved. Get started today, and pick up right where you've left off whenever we update the project!
Prerequisites
For developers with several years of Java or Scala experience and an understanding of the core principles of Apache Kafka. Knowledge of web-servers, databases, build systems and Docker will be helpful, but not essential.TOOLS
- Intermediate with Java/Scala
- Basics of Maven, SBT, or other JVM build systems
- Basics of Docker
- Basics of Apache Kafka
TECHNIQUES
- Basics of partitioning and hashing data
- Basics of pub/sub system design
you will learn
In this liveProject, you’ll learn how to get started with stream processing and master advanced techniques around real-time data access, and streaming fault management.- Kafka Streams
- Fundamentals of IoT stream processing
- Advanced IoT stream processing techniques
- Error handling for IoT devices
- Schema management & evolution with Apache Avro
- Trading off latency and throughput in Kafka
- Design patterns for resilient stream processing
- Evolving real-time processing for real-world use cases
- Advanced partitioning schemes
- Distributed, low-latency streaming queries
features
- Self-paced
- You choose the schedule and decide how much time to invest as you build your project.
- Project roadmap
- Each project is divided into several achievable steps.
- Get Help
- While within the liveProject platform, get help from other participants and our expert mentors.
- Compare with others
- For each step, compare your deliverable to the solutions by the author and other participants.
- book resources
- Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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