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Still reporting spend after the damage is done? Cloudability shows cloud spend after it happens.

FinOpsly is built for proactive AI cost governance so teams can control spend before it turns into waste, budget overruns, or surprise bills.

See how FinOpsly helps you:

- Estimate before launch. Model AI workloads, data pipelines, and infrastructure costs before they go live.

- Govern more than cloud. Control spend across AWS, Azure, GCP, Kubernetes, Snowflake, Databricks, GPUs, models, and AI workloads.

- Act with confidence. Turn savings opportunities into approved, policy-governed actions.

Eligible Cloudability customers may qualify for up to 6 months free.

AfriLogix had a $34,000 monthly AWS bill and no idea who was spending what. Eighty-five percent of their cloud resources had no labels at all. The company built a tagging system to fix this problem.

Every resource got labels for Environment, Project, Team, Owner, Cost Center, and Compliance needs.

They used AWS Tag Editor to label resources in bulk, turning a messy pile of servers into a clean, organized list.

Next, they turned on cost allocation tags in AWS Billing, so every dollar spent could be traced back to a team or project.

To stop people from skipping tags in the future, they set up AWS Config rules that flag any resource missing a label. An automatic alert then emails the owner so nothing gets forgotten.

Finally, they built a reporting pipeline using Cost and Usage Reports and Athena, letting them query spending by team or project in seconds. By the end, 92 percent of resources were tagged and costs were clearly split between Engineering, Data Science, and Operations.

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FinOpsX Interviews continue to drop every day, here’s what you haven’t watched already:

Discover how to measure the real business value of AI, optimize cloud spend, and prove the ROI of your AI initiatives with practical FinOps strategies and expert insights.

📅 July 16
🕚 6:00 PM CEST (Spain) / 12:00 AM EST

Attend

Our next meetup will explore a topic many organizations are already facing: how to integrate AI, automation, and new operating models without losing control, efficiency, or visibility.

This session is designed for professionals working in Cloud, FinOps, AI, Digital Transformation, and Operations. Expect technical talks, engaging discussions, and networking with the community.

October 7 – Madrid (Utopicus Nuevos Ministerios)
https://luma.com/036wqk98

SentinelFinOps is an open-source tool that helps companies find and fix wasted cloud spending in AWS.

The platform automatically scans your AWS accounts to find EC2 instances and storage volumes that are sitting idle or barely used. When it spots waste, it sends alerts to your team through Slack with simple buttons to take action. Here's what makes it useful for FinOps teams:

Automated Waste Detection. The system looks across all your AWS accounts and regions to find resources that are costing you money but not doing much work.

Safe Cost Reduction. Before it shuts anything down, the tool creates backups of your data. It uses locks to prevent two people from accidentally fixing the same thing at once.

Multi-Account Support. If you use AWS Organizations with multiple accounts, this tool can scan all of them at once.

Built-In Safety Features. The platform includes health checks to make sure everything is working correctly. You can set up allow and deny lists to protect critical environments like disaster recovery systems.

Easy Setup. The project includes Terraform code to set up the required AWS infrastructure like databases and scheduled tasks. Configuration uses simple YAML files that you can customize for your needs.

The tool runs on AWS Lambda, so you only pay for the time it actually spends scanning your accounts.

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A team found $22,000 in AWS Glue charges on their monthly bill after just 23 days. No alerts fired. No jobs failed. Data kept flowing normally. The cost just kept climbing. This is the kind of cloud spend problem that doesn't show up until someone looks at the numbers carefully.

The investigation started with a simple question: which jobs are actually driving this cost? Two jobs stood out right away.

A job that ran for 1-2 minutes was using 4 processing units (DPUs) when it only needed 2. Cutting the DPUs in half saved about $6,000 per month with zero change in performance.

The second job was scanning billions of rows of data to return about 29,000 records. The table was partitioned by date, which should have let the system skip most of the data. But it wasn't working. The team ran test queries to find out why.

Same data. Same logical filter. Completely different behavior. The root cause was a data type mismatch. The table stored timestamps without timezone info (TIMESTAMP_NTZ in Spark terms). The query was sending a regular TIMESTAMP with timezone assumptions baked in. Spark couldn't match the types, so it skipped partition pruning and read everything.

Changing one keyword in the WHERE clause from TIMESTAMP to TIMESTAMP_NTZ fixed it. Runtime dropped from 15 minutes to 30 seconds. Rows scanned dropped from billions to hundreds of thousands. S3 data retrieval costs dropped too, since fewer files were being opened.

In this case, a single word in a WHERE clause was costing more than most people's monthly salary, and nobody knew until someone looked. If one of your data jobs scanned 5 billion rows today, would you know before the bill arrived?

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Visit FinOps Weekly Hub, the place for discovering leading FinOps platforms and cloud cost management solutions. Compare vendors, explore new tools, and find the best fit for your cloud optimization and governance needs.

All in one site, completely free.

EC2 Auto Scaling now tries Reserved Capacity first, using ODCRs and Capacity Blocks before balancing across zones to maximize your committed spend.

Redshift added All Upfront and Partial Upfront payment options for 1- and 3-year reserved instances, giving FinOps teams more ways to capture savings.

OpenSearch's new log analytics engine delivers up to 4x better price-performance and 70% lower storage costs at no extra charge.

Read All AWS Updates

Azure Copilot and a FinOps MCP Server bring automated, policy-guided optimization to help teams scale FinOps without adding manual work.

Azure Files now has a provisioned v2 billing model that lets you size IOPS and throughput independently, lowering cost per inference for AI workloads.

Read All Azure Updates

BigQuery can now route queries to specific reservations by user or service account, giving teams finer control over who spends what.

Read All GCP Updates

Cloud spending is spread across many places today. Think cloud platforms, SaaS tools, on-prem systems, and support teams. This makes it hard for companies to know what value they get for every dollar spent.

This article talks about a new way to fix that problem, the Value Management Framework, or VMF. It connects all IT spending to real business results. At the center is the Unit Value Model.

This model turns raw spending data into simple numbers like cost per customer, cost per API call, or cost per order. These numbers help leaders compare choices clearly.

The framework also helps with forecasting, tagging, and governance. It grows in stages, starting small and expanding across the whole business. Strong tagging and clear ownership are the building blocks that make it work.

Companies that adopt this thinking can spend smarter, cut waste, and grow with more confidence.

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