27 Kafka courses

This course is structured to give you both the theoretical and coding experience of developing Kafka Streams applications using Streams API. It also covers the techniques to use Enterprise Standard Kafka Streams application using Spring Boot and Streams API. You will build a real-time Kafka Streams application by the end of this course. Prior experience building Kafka applications is necessary.

This course will help you explore the world of Big Data technologies and frameworks. You will develop skills that will help you to pick the right Big Data technology and framework for your job and build the confidence to design robust Big Data pipelines.

Get to grips with real-time stream processing using PySpark as well as Spark structured streaming and apply that knowledge to build stream processing solutions. This course is example-driven and follows a working session-like approach.

Learn the process to design and develop big data engineering projects using Apache Spark. This example-driven advanced-level course will help you understand real-time stream processing using Apache Spark and you can apply that knowledge to build real-time stream processing solutions.

This course brings together all the important topics related to modern distributed applications and systems in one place. Explore the common challenges that appear while designing and implementing large-scale distributed systems, and how big-tech companies solve those problems. Throughout the course, we are going to build a distributed URL shortening service.

The course helps you learn Snowflake from scratch and explore a few of its important features. You will build automated pipelines with Snowflake and use the AWS cloud with Snowflake as a data warehouse. You will also explore Snowpark to be worked on the data pipelines.

Streaming telemetry training course description An introduction to streaming telemetry. The course progresses from a brief look at the weaknesses of SNMP onto what streaming telemetry is, how it differs from the xflow technologies, the data formats available and how to configure it. What will you learn Describe streaming telemetry. Explain how streaming telemetry works. Describe the data presentation formats available. Configure streaming telemetry. Streaming telemetry training course details Who will benefit: Network engineers. Prerequisites: TCP/IP foundation for engineers. Duration 1 day Streaming telemetry training course content What is streaming telemetry? SNMP weaknesses, Netflow, sflow, polling and the old models, push vs pull, What is streaming telemetry? Telemetry streaming architecture Model driven versus event driven telemetry, subscriptions, publications. Periodic versus on change, model selection and scalability. Telemetry streaming protocols TCP, UDP, SSH, HTTP, HTTP2, NETCONF, RESTCONF, gRPC, gNMI. Models and Encoding The role of YANG. YANG models and tools. XML/ NETCONF, JSON/RESTCONF, JSON over UDP. Protocol buffers/gRPC. Google Protocol Buffers Decoder ring, protocol definition file. GPB-KV, GPB-Compact. Keys. Streaming telemetry configuration Router: Destination, Sensor, subscription. Collector: YANG models, .proto file. Pipeline. ELK: Consume, store, visualise streaming data. Collection tools APIs, YANG development Kit, Downstream consumers, influxdata, Grafana, Kafka, Prometheus, others.

This course will show you why Hadoop is one of the best tools to work with big data. With the help of some real-world data sets, you will learn how to use Hadoop and its distributed technologies, such as Spark, Flink, Pig, and Flume, to store, analyze, and scale big data.

Better than REST APIs! Build a fast and scalable HTTP/2 API for a Go microservice with gRPC and protocol buffers (protobufs)

Better than REST APIs! Build a fast and scalable HTTP/2 API for your microservice with gRPC and protocol buffers (protobufs).