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Carolyn Weitz

Carolyn began her cloud career at a fast-growing SaaS company, where she led the migration from on-prem infrastructure to a fully containerized, cloud-native architecture using Kubernetes.
Since then, she has worked with a range of companies from early-stage startups to global enterprises helping them implement best practices in cloud operations, infrastructure automation, and container orchestration. Her technical expertise spans across AWS, Azure, and GCP, with a focus on building scalable IaaS environments and streamlining CI/CD pipelines.
Carolyn is also a frequent contributor to cloud-native open-source communities and enjoys mentoring aspiring engineers in the Kubernetes ecosystem.

Object Storage for Modern Applications: The Complete Guide to Scaling Your Data

Object Storage for Modern Applications: The Complete Guide to Scaling Your Data

According to a Statista report, by 2029, the global data generation is projected to reach 527.5 zettabytes, roughly triple the 2025 levels. At the same time, Kubernetes underpins a large share of modern cloud-native stacks and Gartner projects that by 2028, 80% of GenAI business apps will be developed on existing data management platforms. Object storage is becoming the […]

December 11, 2025
5 Benchmarks Before Choosing Block Storage for Inference Workloads

5 Benchmarks Before Choosing Block Storage for Inference Workloads

Block storage for inference is critical to production AI performance, so your evaluation must go well beyond GPU specifications. Modern inference pipelines often stall on storage rather than compute slowing responses and inflating spend. Use five practical benchmarks to validate storage choices that capture throughput, IOPS, tail latency, elasticity and workflow integration. Start by measuring […]

December 9, 2025
How HPC Can Help Build Better AI Applications?

How HPC Can Help Build Better AI Applications?

High-performance computing (HPC) is the engine behind modern AI scaling data-intensive training and delivering the performance today’s models demand. HPC for AI allows teams to train larger models, shorten iteration cycles and improve unit economics from day one. It also exposes real constraints: scarce GPUs, long training windows, rising inference costs and brittle clusters. According […]

December 9, 2025
Application-Consistent Block Storage Snapshots for Critical Workloads

Application-Consistent Block Storage Snapshots for Critical Workloads

Block storage snapshot is a point-in-time copy of your block storage volume. You can either create them manually before or schedule them automatically as part of your backup and DR strategy. The first snapshot you take is the full snapshot of your data volume. Whereas the subsequent snapshot captures only those data that have changed […]

December 3, 2025
Kafka vs RabbitMQ: A Complete Comparison of Architecture, Performance & Use Cases

Kafka vs RabbitMQ: A Complete Comparison of Architecture, Performance & Use Cases

Apache Kafka and RabbitMQ are both open-source messaging technologies. However, they are built for different jobs. Kafka is a distributed commit log optimized for high-throughput event streaming and replay. RabbitMQ is a general-purpose message broker optimized for push delivery, protocol flexibility and workflow routing. In Confluent’s cross-broker benchmark: While Kafka is a distributed commit log optimized […]

November 28, 2025
Docker Swarm vs Kubernetes: Which Orchestrator Fits Your Stack?

Docker Swarm vs Kubernetes: Which Orchestrator Fits Your Stack?

Docker Swarm and Kubernetes are popular container orchestration platforms that help you deploy, scale and manage containerized applications at ease. You can choose Docker Swarm when you want speed, a minimal control plane and a familiar Docker-native workflow embedded in Docker Engine, while Kubernetes offers a more comprehensive, extensible platform suited to complex, multi-team and […]

November 28, 2025
How to Choose the Right Foundation Model for Generative AI

How to Choose the Right Foundation Model for Generative AI

A foundation model for generative AI is a large pretrained model adapted through prompting, tool usage or additional training to produce outputs like text, code or images. While choosing a foundational model, you should weigh factors like expected outcomes, openness, modality support, cost, deployment requirements and an objective scorecard. This matters because: Let’s dive deeper […]

November 26, 2025
Best Open-Source LLMs in 2026: Models Ranked & Compared

Best Open-Source LLMs in 2026: Models Ranked & Compared

Quick Answer As of October 2026, Kimi K3 is one of the strongest open-weight LLMs for frontier reasoning, long-context work and agentic workloads, while DeepSeek-V4.1-Flash stands out for coding, agents and efficient production inference. GLM-5.2 remains strong for long-horizon reasoning, Qwen3.6-27B is more practical for smaller self-hosted systems, and Gemma 4 fits local and edge […]

November 18, 2025
Hypervisors in Cloud Computing: A Comprehensive Guide

Hypervisors in Cloud Computing: A Comprehensive Guide

Cloud computing, as it is apparent in managing, storing, and accessing data, is spreading widely among business organizations. Below this change lies a key technology: “Hypervisor.” Its role is most important to understand in grasping how cloud environments work and support virtualization. This blog gives a step-by-step overview of hypervisors, including the different kinds and […]

November 16, 2025