Learn to build production-ready GenAI pipelines on Snowflake with delta-aware ingestion, scalable retrieval, and observability for reliability and cost control.
The technical limitations that created the divide between the inner and outer loops are being solved just in time for agentic workflows to make merging them a necessity.
Tested K8s 1.35's four key features on Azure VM: zero-downtime pod resizing, gang scheduling, structured auth, and node capabilities. All scripts and configs on GitHub.
Autoscaling is reactive, not resilient. Without caps, metrics, or overrides, it can worsen failures. True elasticity requires policy, testing, and bottleneck awareness.
S/4HANA migrations break custom ABAP code and interfaces unless you proactively refactor code, SQL, and integrations to support the new data model and semantics.
While many developers run containers on bare metal in development, in production, it's almost all VMs. What does this mean for the broader cloud landscape?
Bridge the gap between Big Data and production ML. Learn to integrate Azure Databricks with Azure Machine Learning for a seamless, scalable end-to-end MLOps workflow.
Terraform is an Infrastructure as Code tool that allows teams to define AWS infrastructure using declarative configuration files instead of manual console clicks.
Troubleshoot Kubernetes database connectivity using a layered diagnostic framework and achieve rapid root-cause identification and production stability.
Docker’s cagent is a new open-source, low-code/ YAML-centric AI agent builder and runtime. Instead of writing code, you describe agents and cagent runs them.
A practical engineering guide to integrating an AI chatbot into your application, covering architecture, backend flow, NLP handling, security, testing, and deployment.