Operations | Monitoring | ITSM | DevOps | Cloud

Backing up files in the cloud or locally is a crucial step you must take when managing your files. Protecting your files with multiple types of data backup methods will help you recover your files instantly, protect against ransomware, and ensure you can always access your files no matter what happens to your device. But what are the two types of cloud storage backup solutions which are fast, simple to use, and the best way to protect your files?

Today, we’re announcing the general availability of Lumigo Copilot, the most intelligent AI-powered observability assistant on the market, built for the complexities of modern microservices. Copilot emerged from a simple realization: Distributed systems produce too much fragmented data across too many layers, making troubleshooting slow, reactive, and deeply manual. Copilot changes that.

AWS gives you the power to scale, deploy, and innovate at speed. However, with that speed comes a good amount of complexity. Services multiply, resources balloon, and performance issues sneak in when you least expect them. That’s where monitoring comes in. But it isn’t about checking boxes on dashboards. It’s about getting the most value for every dollar you spend or, maximizing your return on investment (ROI) from AWS monitoring. So, how do you actually do that?

In this blog series we are examining the Five Myths of Kubernetes Resource Optimization. So far we’ve looked at Myth 1: Observability and Monitoring and Myth 2: Cluster Autoscaling. Stay tuned for the entire series! The third myth addresses another common assumption of many Kubernetes practitioners: Choosing the right instances will eliminate waste in a cluster.

Shopware is a powerful platform, but its performance depends entirely on how it is used. In this article, we explore the most common and avoidable causes of slowdowns in production environments, including plugin overload, cache fragmentation, and misconfigured admin settings. Whether you are preparing for a high-traffic event or simply aiming to keep your storefront fast and responsive, this guide will help you identify the root causes of performance regressions.

Running workloads on Google Kubernetes Engine (GKE) delivers impressive scalability and flexibility. Yet, it can also introduce a tricky challenge: tracking GKE costs accurately. Remember, GKE costs rarely scale linearly. Overprovisioned nodes, idle autoscalers, and orphaned workloads can quietly balloon your bill in the background. And while GKE’s native tools offer some visibility, they often miss the full picture.

Private cloud infrastructure adoption is accelerating rapidly. This move is driven by the ongoing “cloud reset” as leaders rethink their hybrid and multi-cloud strategies, seeking greater control, security, and flexibility for their IT workloads. As a matter of fact, leaders in 69% of organizations are considering repatriating workloads, and one-third already have.

A decade after launching Reserved Instances (RIs), Amazon Web Services (AWS) introduced Savings Plans as a more flexible alternative to RIs. AWS Savings Plans are not meant to replace Reserved Instances; they are complementary. SPs and RIs have some significant differences that make each better suited to specific uses. For example, while Savings Plans apply to both EC2 and Fargate instances, RIs only apply to EC2 instances. Let’s break down AWS Savings Plans vs.