Operations | Monitoring | ITSM | DevOps | Cloud

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Cloud Control Ep #32 It's Not Quite Rocket Science Randall Hunt's Journey from NASA to Open Source

Today, Shon speaks with Randall Hunt, CTO of Kaelin. From his unconventional journey starting as a NASA physicist to becoming a key player in MongoDB's early days and later at AWS, Hunt shares invaluable insights on cloud architecture, DevOps practices, and the future of tech leadership. This episode explores everything from maintaining developer passion after decades in tech to practical advice for newcomers, while offering exclusive insider perspectives on AWS re:Invent and the changing landscape of cloud providers.

Step by Step Guide to Monitoring Apache Spark with MetricFire

Apache Spark is a powerful tool for processing and analyzing large datasets quickly, whether you're cleaning data for a report, running machine learning models, or analyzing real-time data streams. It's widely used for everything from building big data pipelines to crunching numbers for advanced analytics, thanks to its speed and ability to scale across clusters.

Introducing Network Summary Reports: Network Insights Delivered Weekly

Tidal LightMesh is excited to introduce Network Summary Reports, delivering actionable network insights directly to your inbox. This powerful new feature streamlines IP management, allowing your team to focus on strategic initiatives while maintaining complete visibility into your network’s health.

Top 8 Docker Alternatives to Consider in 2025

Containerization platforms have evolved beyond Docker's initial implementation, offering specialized solutions for diverse enterprise requirements. Modern container runtimes focus on enhanced security models, optimized resource utilization, and seamless integration with cloud-native architectures. This analysis examines key alternatives that address Docker's technical limitations and provide advanced features for production workloads.

Optimizing ClickHouse Performance: Diagnosing and Resolving Common Bottlenecks

ClickHouse, a columnar database designed for high-performance real-time analytics, is excellent at handling large datasets with speed and efficiency. However, performance issues can occur due to factors like unoptimized queries, resource contention, or improper configuration. As data and query complexity grow, keeping ClickHouse fast can be challenging. This blog will explore common bottlenecks, how to diagnose and resolve them, and include a Python script for automating diagnostics. Lets get started!

Investigating RPA Realities and the Hype of Hyper-Automation

In recent years, hyper-automation has emerged as a buzzword in the world of business process optimization. Promising a fully automated, intelligent enterprise, hyper-automation leverages technologies like artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) to streamline operations and enhance efficiency. But while it often sits at the center of these conversations, RPA’s limitations have become increasingly apparent.