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The latest News and Information on Cost Management and related technologies.

How To Hire In FinOps: Roles, Responsibilities, Skills, Interview Questions, And More

FinOps is booming as a function. The global cloud FinOps market will grow from $13.5 billion in 2024 to $23.3 billion in 2029 — a compounded annual growth rate (CAGR) of 11.4%, according to Research and Markets. That’s in response to sharp increases in cloud spend. About $723 billion is expected to be spent on public cloud services in 2025, up from $596 billion the year before according to a Gartner report.

Building Systems For AI: Lessons On Governance From DevOps History

In 2008, Nuance hired me to join their Healthcare Speech Recognition team as a “Release Engineer.” DevOps wasn’t a thing yet — Patrick Debois and Andrew Shafer wouldn’t hold their first “DevOpsDays” until 2009. But I was lucky that “Release Engineer” at Nuance meant “jack of all trades” who wrote Makefiles, bash scripts, Perl, and Java to build and release code to a fleet of hundreds of on-premise Linux machines.
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Streamlining multi-cloud complexity with unified observability

A wave of businesses are embracing multi-cloud strategies to gain flexibility and scalability. By combining on-premises infrastructure, private clouds, and public platforms like AWS, Azure, and Google Cloud Platform (GCP), IT teams can experiment, deploy, transform, and improve their IT applications significantly. On the down side, this modern IT approach of employing multiple clouds (in both public and private forms) also brings significant complexity, making it challenging to monitor systems, control costs, and secure environments. There are just too many threads to track and tie together to ensure a taut IT fabric.

Build Smarter With Cloud-Native Tools: Your 2025 Guide

Cloud-native tools promise speed, scalability, and resilience. The catch is you have to pick the right ones and use them well. Without the right foundation, they can mean more complexity, hidden costs, and a false sense of control. In this guide, we’ll help you avoid that trap. From infrastructure to observability and CI/CD tools, we’ll cover the solutions shaping modern cloud stacks.

Evaluating Serverless Vs. Containers And How To Choose

Containers and serverless computing are two of the most popular methods for deploying applications. With the rise of microservices and modern DevOps, teams need faster, leaner ways to build and release software. However, selecting the wrong architecture can slow down delivery, increase cloud costs, or lock you into tools that don’t scale with your business. Both methods have their advantages and disadvantages.

In The AI Era, The Winning Teams Track Cloud Unit Costs From Day 1

Everyone’s obsessed with speed right now. Ship fast. Stack features. Slap an LLM on it and call it v1. Amirite? But in the AI era, where cloud costs can spiral in a weekend, moving fast isn’t enough. The teams that track cloud unit costs from Day 1? They’re the ones who come out ahead. Most teams don’t start there though. They focus on building features and chasing traction, and the cloud bill just shows up like that subscription you forgot to cancel. Maybe someone glances at it.

Top Terraform Alternatives And Competitors To Know

A few weeks ago, a lead DevOps engineer at a fast-growing SaaS company hit an unexpected wall. “It used to just work… until we scaled,” the lead noted after their Terraform setup began buckling under the weight of a growing cloud footprint. Another chimed in: “We’re spending thousands on infrastructure every week, but we can’t trace it back to who deployed what, or why.” Sound familiar? You’re not alone.

FinOps For AI: How Crawl, Walk, Run Works For Managing AI Costs

“It started as an experiment.” That’s how it begins at most companies. A small team spins up a few GPU instances to train a proof-of-concept model. Maybe it’s a fraud detection algorithm. Maybe it’s GenAI for support tickets. Either way, it’s just a test. Then the results come in, and they’re promising. Suddenly, that model is powering new features. Teams are fine-tuning LLMs in parallel.

Vertical Pod Autoscaling: How It Compares to Pepperdata Capacity Optimizer

Vertical Pod Autoscaling (VPA) is a component within Kubernetes designed to automatically resize the CPU and memory requests of pods based on their observed, historical usage patterns. While Pepperdata Capacity Optimizer and VPA both change the resource requests of pods in response to changing application resource requirements, there are several key differences.

The Three Constraints Of AI Adoption: Code, Servers, And Wallets

Earlier this year, OpenAI’s CEO Sam Altman admitted something that should make every engineering leader pause: they’re “currently losing money” on ChatGPT Pro subscriptions, which run $200 per month. Let that sink in. A company charging two hundred dollars a month for AI access — 10 times what most SaaS products dare to ask — is still bleeding cash on every user. This isn’t a pricing problem. It’s a physics problem.