Operations | Monitoring | ITSM | DevOps | Cloud

We get it. FinOps can be challenging to understand, implement, and optimize, whether you’ve done it before or are just getting started. Everybody needs help from time to time. If this describes you right now, then check out the following FinOps services companies to get started. But first, a quick background.

Telecommunications companies (telcos) are well on their way to transforming their infrastructure from the legacy, unadaptable, complex network of dedicated hardware from yesteryears to agile, modular and scalable software-defined systems running on common off-the-shelf (COTS) servers. Within this space, the current trend, driven by 5G deployments, is to complement tried and tested network function virtualisation (NFV) infrastructure with cloud-native network functions (CNFs).

In our previous post, we discussed how to generate Images using Stable Diffusion on AWS. In this post, we will guide you through running LLMs for text generation in your own environment with a GPU-based instance in simple steps, empowering you to create your own solutions. Text generation, a trending focus in generative AI, facilitates a broad spectrum of language tasks beyond simple question answering.

Ciara Carey reflects on her experience at the KubeCon event in Paris including her top 10 talks and current industry trends.

Traditionally, data centers have been managed using on-premises software – and for many companies, this solution has been sufficient. However, as the data center environment becomes more intricate and dynamic, a new approach to management is required. Cloud-based Data Center Infrastructure Management (DCIM) software has emerged as the next generation of management tools, offering unmatched flexibility, scalability, and cost-effectiveness.

Last November, Dimitris and Giordano Ricci wrote a blog post about CI/CD observability that looked into ways to extract traces and metrics in order to get a better understanding of possible issues inside a CI/CD system. That post focused on getting data from a continuous integration (CI) system, and it really resonated with the community.

In one of our latest posts, StackState Co-Founder Mark Bakker described how eBPF revolutionizes observability and how StackState’s agents rely heavily on eBPF to capture and analyze the data moving through your cluster. Today, we’re looking at an example where our eBPF code failed and — by diving deep into the intricacies of eBPF implementation in the Linux kernel — share the tale of how we fixed it using even more eBPF.

Platform engineering metrics and/or platform engineering KPIs (Key Performance Indicators) can help us measure the success of this evolving approach and its impact on DevOps. According to our 2024 State of DevOps Report: The Evolution of Platform Engineering — 43% of organizations report that they have had a platform team from 3-5 years already. With this maturity, it’s important to measure what’s working and what isn’t working using the same indicators of success across the board.