Operations | Monitoring | ITSM | DevOps | Cloud

Andreessen Horowitz recently published a blog about the Heavy Cloud Costs and Scaling Challenges of The New Business of AI, in which they describe how AI companies are facing cloud cost challenges, which are impacting their margins. As someone who used to manage a fully home-grown on-site distributed speech recognition platform for an industry leader, I know firsthand that ML can be expensive and challenging to maintain. However, it doesn’t have to be.

When I read Greg Ferro’s infamous “Why I hate ITIL so much” blog back in 2015, I have to admit that I agreed with many (albeit not all) of what he said. Maybe it’s the issues that I have with authority in general, or maybe it’s my many years of working within the constraints of ITIL and ITSM in operating systems and services – but I truly believed (and still do) that well-educated, experience and consensus-based pragmatism is what actually gets things done.

The first means to collect security-relevant information at Cloud SIEM Enterprise (CSE) was our Network Sensor. It was built to analyze network traffic and provide visibility beyond traditional SIEM's down to the network-level. Beyond organizing packets into flows, the sensor supports more advanced features such as decoding of common protocols, file carving, SSL certificate validation, OS fingerprinting, clustered deployment and more.

VMware vSphere is a server virtualization platform that enables organizations to provision and manage virtual machines at scale. With its comprehensive suite of products, vSphere helps companies manage datacenter resources, migrate workloads without downtime, run applications with high availability, and more. To keep tabs on dynamic vSphere environments and effectively address resource bottlenecks, you need deep visibility across every part of your infrastructure.

Monitoring has moved from a simple proactive practice to a necessity on any product launch checklist. It is crucial to pick a tool that meets your observability needs & ensures reliability of your service to your customers. Over the years, with an increase in adoption of DevOps and SRE practices, Monitoring has moved from a simple proactive practice to a necessity on any product launch checklist.

It was a cloudy winter morning when I had arrived at the office and found, to our horror, that a Kubernetes cluster was suffering from extremely high CPU and network usage and had become almost completely non-functional. To make things worse, restarting the nodes (the go-to DevOp solution), seemed to have absolutely no effect on the issue. Something was poisoning the network and we had to find out what it was and fast.

Prometheus is an open-source system for monitoring and alerting originally developed by Soundcloud. It moved to Cloud Native Computing Federation (CNCF) in 2016 and became one of the most popular projects after Kubernetes. It can monitor everything from an entire Linux server to a stand-alone web server, a database service or a single process. In Prometheus terminology, the things it monitors are called Targets. Each unit of a target is called a metric.

This is a guest post from Kamesh Pemmaraju of Platform9. As organizations move to a containerized world, whether by producing containerized software, consuming it or both, the need for a managed Kubernetes offering and an Enterprise-tested private Docker registry is apparent. With the introduction of Platform9‘s new Freedom Plan for managed Kubernetes, you can combine it with JFrog Container Registry and power up your containerization transformation for free.

At re:Invent in December, Amazon announced the AWS Graviton2 processor and its forthcoming availability powering Amazon EC2 M6g instances. While the first-generation Graviton processor that powered A1 instances was better suited to less compute-intensive workloads, this processor is intended to offer AWS customers a compelling alternative to conventional x86-powered instances on both performance and cost.