
Discover JobRunr: transform Java 8 lambdas into distributed background tasks. Run CPU-heavy or I/O-intensive jobs asynchronously, scale effortlessly, and focus on delivering value to end users.

Insights from 6 years of serverless development for IoT devices, covering best practices, trade-offs, and lessons learned in building scalable real-time systems using AWS technologies.

Explore Azure Kubernetes Services for developers, covering advantages, debugging, security, scaling, load balancing, multi-cloud, resiliency, and local development in this comprehensive overview.

Explore distributed application development with Orleans framework, covering virtual actors, grains, shared state, and scalability through a code-heavy introduction and real-world implementation example.

Explore scaling solutions for flight search APIs using GCP PubSub and Broadway. Learn to reduce processing time variance and improve service reliability in Elixir.

Optimize AWS DevOps using Python and machine learning techniques for efficient cloud infrastructure scaling and performance improvement.

Explore scaling ML models to handle millions of daily requests, covering MLOps fundamentals, cloud-agnostic architecture, and real-world production challenges in eKYC SaaS APIs.

Explore JRuby's latest features for Ruby 3.1, including improved performance, scaling, and resource efficiency for Rails applications.

Explore enterprise consortium design, governance, and scaling on Hyperledger Fabric with Zeeve CEO Ravi Chamria. Learn topology challenges, implementation strategies, and stakeholder management.

Learn to scale applications using goroutines, from a simple setup to handling 100x traffic. Explore concurrency, deployment strategies, and real-world examples through an accessible coffee shop analogy.

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 techniques to enhance LLM performance, scale models in production, and improve structured outputs. Learn from experts about information extraction, scaling challenges, and innovative programming approaches for better AI results.