Operations | Monitoring | ITSM | DevOps | Cloud

Being in the cloud is table stakes in 2025, and simply lifting and shifting workloads to the cloud barely scratches the surface of what's possible. Yet many engineering teams find themselves managing glorified data centers in the cloud—missing out on key capabilities like auto-scaling, serverless computing, and cloud-native security features. Cloud modernization is the true game-changer for turning legacy systems into agile, scalable architectures.

Not too long ago, engineering organizations were in a headlong rush to “innovate or die” by hiring more developers and shipping more code at breakneck speed. This expansion brought short-term velocity gains—but also created a tangle of orphaned services, inconsistent processes, and developers spending more time firefighting than innovating. Today, the reality is that you can’t just keep throwing headcount at complexity.

Cloud infrastructure powers everything from streaming services to enterprise databases, yet many organizations still run critical workloads on legacy systems. With the cloud migration market projected to reach $806.41 billion by 2029, growing at a CAGR of 28.24%, organizations of all sizes are racing to modernize their infrastructure and applications. This shift means companies need to stay competitive in a landscape where agility and scalability are non-negotiable.

MySQL logs are basically your database's diary – they record everything happening behind the scenes. Think of them as the black box of your database operations. You've got error logs showing you when things go sideways, query logs documenting every question asked of your database, and binary logs tracking changes like they're gossip in a small town.

Choosing between New Relic and Datadog? Here's what you need to know: Let's break it down. If you're comparing New Relic and Datadog for observability, you might also find this guide on microservices monitoring tools helpful.

Debugging is rarely anyone's idea of a good time. You're cruising along, building something cool, when suddenly your code breaks and you're stuck digging through console outputs that look like they were written by a robot having an existential crisis. Enter Loguru – the Python logging library that feels like it was built for humans, not machines.

If you’ve worked with VMware Horizon (now Omnissa Horizon), you know it’s a common way for enterprise users to connect to remote desktops. But for IT engineers and DevOps teams? It’s a whole different story. Horizon’s custom protocols and complex connection requirements make load balancing a bit tricky. With its recent sale to Omnissa, the technology hasn’t changed—but neither has the headache of managing it effectively.

If you’re new to Kubernetes or looking to modernize your cluster management workflows, Cluster API and SUSE Rancher Prime make it easier than ever to provision and manage clusters declaratively. This guide walks you through enabling Cluster API in SUSE Rancher Prime, deploying your first cluster and exploring advanced features like GitOps. Some helpful documentation can be found here and a few pre-requisites for this hands-on walkthrough.

Google Cloud Platform (GCP) launched in April 2008 with Google App Engine. This developer-centric Platform as a Service (PaaS) offering allowed developers to build and host web applications on Google’s cloud infrastructure. Initially, App Engine only supported Python, but in 2009, Google added Java support, offering more programming flexibility. In 2010, GCP expanded further with Cloud Storage, its second major cloud product.

Breaches in software artifact integrity can have severe consequences. Bad actors poison artifacts by injecting malicious code into software packages, libraries, or container images, tricking developers and users into downloading compromised artifacts. These attacks can lead to data breaches, system takeovers, and widespread supply chain disruptions. Continued artifact poisoning incidents highlight the increasing risk to software supply chains.