Operations | Monitoring | ITSM | DevOps | Cloud

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.

I recently had a conversation with one of our customers at AWS re:Invent that made me rethink the true value of automation. This customer told me, “You’ve automated so much for us that we almost forget about Qovery. Nobody even asks how to do things anymore.” That statement stuck with me.

High-performance computing (HPC) configuration has become paramount for AI workloads. Companies investing in AI workloads often find themselves with predictable problems: Lots of nodes that are hard to integrate and harder to manage together, under-utilized resources, deployment struggles, inconsistent configurations, and drift.

In today’s digital-first world, organizations are constantly pressured to deliver faster, more reliable, and secure network services. Yet, with a staggering 65% of enterprise network activities still performed manually, the journey toward network automation is more critical than ever.

In today’s fast-paced digital environment, Network Operations Centers (NOCs) are critical for maintaining uptime, optimizing performance, and ensuring seamless communication. For NOCs to excel, tracking the right Key Performance Indicators (KPIs) is essential. These metrics guide decision-making, highlight inefficiencies, and keep networks resilient.

As the demands of modern software development continue to grow, so too does the complexity of DevOps. To keep pace, many organizations are turning to AI-powered assistants that help manage infrastructures, streamline pipelines, and automate repetitive tasks. These assistants are known as copilots, and they promise to enhance productivity while reducing operational overhead. But not all of them are created equal.

Configuration management tools can help you track and manage changes to systems within your infrastructure, making sure that your software and hardware runs reliably and smoothly.

As organizations scale, managing IT systems and resolving incidents efficiently becomes increasingly complex. Manual processes, while functional in smaller setups, often fall short in speed, accuracy, and scalability. Enter Runbook Automation (RBA)—a transformative approach to streamline and standardize incident resolution. This blog explores what Runbook Automation is, its significance in modern IT operations, and best practices to implement it effectively.