
Master production-ready web deployment using Bottle framework with Gunicorn and NGINX. Configure secure environments, implement reverse proxying, and optimize performance for scalable Python applications.

Explore universal/forwarding references in C++, from perfect forwarding to their role in range-based for loops and generic code for containers and views. Master T&&, auto&&, and decltype(auto).

Explore advanced C++ range techniques, including efficient stacking, self-contained adaptors, internal iteration, and optimized text formatting for improved code expressiveness and performance.

Explore observability strategies to optimize engineering team workload, including proxy, OpenTelemetry, and eBPF approaches for effective monitoring and performance management.

Explore Kubernetes Operators, from control loops to custom resources. Master advanced concepts, frameworks like Kubebuilder and Operator SDK, and see a practical demo for hands-on learning.

Explore AWS optimization strategies for media production workloads. Learn about SES, workload analysis, evolution, rightsizing, scaling, and database management to enhance cloud performance and efficiency.

Explore engineering productivity frameworks to measure and enhance team performance, focusing on DORA, SPACE, and DevEx methodologies.

Learn how to contribute to Apache Solr with guidance from experienced committers. Explore the contribution process, best practices, and ways to get involved in this open-source search engine project.

Learn how to contribute to Apache Solr with guidance from experienced committers. Explore the contribution process, best practices, and ways to get involved in this open-source search engine project.

Explore MLOps deployment for scaling machine learning at M&S, covering personalization and enterprise functions. Learn about ML maturity, testing, and monitoring for production-ready systems.

Deploy your GitHub portfolio to cloud hosting using Infrastructure as Code. Learn Terraform, avoid pitfalls, and follow best practices in this interactive workshop on cloud deployment.

Supercharge ML experimentation with PyTorch Lightning and DVC, and streamline production using Kubeflow. Learn to overcome challenges in complex ML model development and deployment.

Explore native and containerized microservices using Java and Quarkus. Learn to build efficient, scalable applications with cutting-edge technologies.

Build a real-time data streaming pipeline using Apache Airflow, Kafka, Spark, and Cassandra. Learn end-to-end data engineering, from ingestion to processing and storage, all containerized with Docker.

Build an end-to-end data engineering pipeline for real-time YouTube Analytics, using Python, Google Cloud, Docker, and Kafka. Learn to fetch, process, and stream data, with instant Telegram notifications.

Build a real-time data streaming pipeline using TCP/IP Socket, Apache Spark, OpenAI LLM, Kafka, and Elasticsearch. Process 7 million records for sentiment analysis and efficient data indexing.

Build end-to-end data engineering projects using Apache Airflow, Docker, Spark, and multiple programming languages. Learn to create and submit jobs to Spark clusters for processing and view real-time results.

Implement real-time Change Data Capture streaming using Docker, Postgres, Debezium, Kafka, Apache Spark, and Slack. Create an efficient data pipeline for responsive data engineering projects.

Explore advanced integration patterns for microservices beyond REST and CRUD, enhancing system design and communication in distributed architectures.

Explore server-side WebAssembly's potential in cloud computing. Learn its basics, advantages over containers, and practical applications through a demonstration of current capabilities.

Explore WebAssembly's potential in cloud computing, its comparison to containers, and how to start with server-side WebAssembly. Includes a demonstration of capabilities and future possibilities.