Operations | Monitoring | ITSM | DevOps | Cloud

Managing technology in K-12 schools has become increasingly complex. With dozens of educational platforms, administrative systems, and communication tools running simultaneously, IT teams need a comprehensive k12 it monitoring dashboard to maintain visibility across their entire technology ecosystem.

As Kubernetes environments continue to grow in scale and complexity, having a robust monitoring strategy is no longer just good practice, it’s essential for survival. For engineering teams in 2025, effective monitoring and observability is the bedrock of performance, reliability, and cost control. This guide dives into the critical aspects of modern Kubernetes monitoring, from key metrics to the top tools/frameworks and the rising role of AI in managing these complex systems.

Every IT team knows the feeling: your phone buzzes at 3 AM with yet another alert. Is it critical? Can it wait until morning? With dozens of monitoring tools and hundreds of potential failure points, incident alert management has become one of the most challenging aspects of maintaining reliable systems.

Amazon SageMaker makes it easy to prepare data for machine learning (ML) and then train, deploy, and modify ML models. SageMaker is a fully managed service that automates much of the ML lifecycle. So, if you want a single partner to help you through all stages of your Artificial Intelligence (AI) lifecycle, SageMaker might be the answer. Perhaps more important for this post is the promise that Amazon SageMaker can reduce your machine learning model costs. But does SageMaker pricing reflect this?

AI coding assistants are already transforming how developers work, helping them write code faster, answer tough questions, and automate repetitive tasks. It’s exciting, it’s powerful… and it’s just the beginning. Cortex MCP connects your AI assistant directly to your live service data, ownership, and organizational standards so it can give accurate, context-rich answers right in your IDE.

‍ The ilert AI Voice Agent is designed to transform how on-call engineers handle urgent calls. Instead of waking engineers at 3 a.m. with minimal context, the AI Voice Agent collects essential details first and routes calls intelligently based on relevant, up-to-date information. ‍ The agent works hand in hand with ilert’s Call Flow Builder – a visual tool that lets users design custom call flows by connecting configurable nodes.

SSL Certificate Verification Failed errors are one of the most common and frustrating issues for developers, DevOps engineers, and system administrators. Whether you're building a Python application, running a Docker container, or managing a web server, this guide will help you.

DORA Metrics are widely regarded as the gold standard for measuring the performance of software development teams. The metrics themselves though are generic, high-level pointers – they are not an instruction manual. Adopting the DORA approach is the first step down the path to continuous improvement. The next steps are deciding how the measures should be defined in the context of your own organisations processes and then figuring out how to retrieve (and present) the relevant data.

Andy Jiang is a JavaScript engineer with nearly 10 years of experience. He’s interested in making JavaScript and TypeScript simpler to use. He currently works at Deno as a product marketing manager. Outside of work, Andy likes cooking, writing, and playing tennis. Observability is essential for modern applications. Metrics, logs, and traces allow you to troubleshoot production issues, monitor performance, and understand usage patterns.

As Government agencies modernize IT operations, many are adopting hybrid cloud and multi-tenant environments to drive agility and resilience. But as environments scale, so does complexity, especially when aligning with overlapping frameworks like FedRAMP, NIST, and CMMC. Today’s cybersecurity landscape—rising threats, shrinking budgets, and expanding compliance demands—requires more than manual oversight.