Archives: Episode

GenAI at production scale: Why GenAI POCs fail and how AWS thinks about production readiness

We’re joined by two GenAI experts from AWS and DoiT to understand why GenAI POCs fail at production scale, how to evaluate LLMs, and how to approach GenAI production readiness. The discussion covers four GenAI workload migration patterns, AWS Bedrock’s systematic migration framework, enterprise compliance challenges including HIPAA and GDPR requirements, and practical approaches to evaluating model performance across speed, cost, and quality.

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Cloud unit economics: Making unpredictable cloud costs forecastable

We cover how unit economics transforms unpredictable cloud costs into forecastable spending patterns. To do so, we go over examples of how connecting cloud spending to business demand drivers (ex. customers served; transactions processed) creates predictable patterns that finance teams can budget for. The conversation also covers practical implementation strategies and common mistakes companies make when starting with unit economics.

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Istio Ambient Mesh: Eliminate sidecar proxies and reduce service mesh costs

We cover how Istio Ambient Mesh eliminates sidecar proxies to significantly reduce Kubernetes resource consumption. This episode covers the architectural differences between traditional service mesh and ambient mesh, practical migration strategies for different workload types, key metrics for measuring performance improvements, and real-world operational benefits like simplified troubleshooting and easier version upgrades.

Read More »

Amazon RDS performance optimization: Instance types, storage, and monitoring best practices

Learn how AWS database experts diagnose and solve the most common RDS performance bottlenecks, from storage configuration to instance type selection. Discover practical strategies to optimize your database costs while ensuring reliability, including when to choose between RDS and Aurora, how to pick the right storage type, and which metrics actually matter for monitoring.

Read More »

Amazon S3 Tables explained: Better storage for AWS Analytics workloads

AWS Analytics expert Swapnil Bhoite joins us to break down of Amazon S3 Tables. From comparing Parquet and Apache Iceberg formats to explaining critical features like compaction and snapshot management, Swapnil explores how this fully-managed service streamlines data lake operations. Learn when to adopt S3 Tables, understand its cost-performance benefits, and discover key migration considerations from existing Glue catalog implementations — essential knowledge for teams looking to scale their analytics workloads on AWS.

Read More »

Archives: Episode

GenAI at production scale: Why GenAI POCs fail and how AWS thinks about production readiness

We’re joined by two GenAI experts from AWS and DoiT to understand why GenAI POCs fail at production scale, how to evaluate LLMs, and how to approach GenAI production readiness. The discussion covers four GenAI workload migration patterns, AWS Bedrock’s systematic migration framework, enterprise compliance challenges including HIPAA and GDPR requirements, and practical approaches to evaluating model performance across speed, cost, and quality.

Read More »

Cloud unit economics: Making unpredictable cloud costs forecastable

We cover how unit economics transforms unpredictable cloud costs into forecastable spending patterns. To do so, we go over examples of how connecting cloud spending to business demand drivers (ex. customers served; transactions processed) creates predictable patterns that finance teams can budget for. The conversation also covers practical implementation strategies and common mistakes companies make when starting with unit economics.

Read More »

Istio Ambient Mesh: Eliminate sidecar proxies and reduce service mesh costs

We cover how Istio Ambient Mesh eliminates sidecar proxies to significantly reduce Kubernetes resource consumption. This episode covers the architectural differences between traditional service mesh and ambient mesh, practical migration strategies for different workload types, key metrics for measuring performance improvements, and real-world operational benefits like simplified troubleshooting and easier version upgrades.

Read More »

Amazon RDS performance optimization: Instance types, storage, and monitoring best practices

Learn how AWS database experts diagnose and solve the most common RDS performance bottlenecks, from storage configuration to instance type selection. Discover practical strategies to optimize your database costs while ensuring reliability, including when to choose between RDS and Aurora, how to pick the right storage type, and which metrics actually matter for monitoring.

Read More »

Amazon S3 Tables explained: Better storage for AWS Analytics workloads

AWS Analytics expert Swapnil Bhoite joins us to break down of Amazon S3 Tables. From comparing Parquet and Apache Iceberg formats to explaining critical features like compaction and snapshot management, Swapnil explores how this fully-managed service streamlines data lake operations. Learn when to adopt S3 Tables, understand its cost-performance benefits, and discover key migration considerations from existing Glue catalog implementations — essential knowledge for teams looking to scale their analytics workloads on AWS.

Read More »

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