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Why FinOps Fails — How We’re Fixing It
We experienced it firsthand: cloud cost responsibility usually ends up with someone who didn’t ask for it. In 99% of companies using AWS or GCP, there’s a Designated FinOps often a staff engineer, a lead infra, or even the CTO who’s the only one with enough technical and business context to do the job. And…
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How Pennylane Took the FinOps Burden Off Engineers
Cloud spend doesn’t break your infra, it breaks your focus. At Pennylane, a next-generation accounting platform built to simplify financial management, cloud cost visibility had become a growing distraction. As AWS and Datadog costs scaled, so did internal friction. Senior infrastructure engineers were spending too much time explaining cloud cost drivers, time that could have…
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2024 State of FinOps for European Tech Companies: Insights and Best Practices
FinOps for European tech companies
Read more about 2024 State of FinOps for European Tech Companies: Insights and Best Practices
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DBT and BigQuery: How to gain visibility and control over your data cost (Episode 2)
In Episode 1, we covered foundational BigQuery costs and how to use dbt metadata to improve visibility and cloud cost management. In this second episode, we’ll explore BigQuery’s built-in cost optimization techniques, which are essential for FinOps professionals looking to efficiently manage cloud spending on BigQuery workloads. We’ll dive into Partitioning and Clustering, Incremental Processing…
Read more about DBT and BigQuery: How to gain visibility and control over your data cost (Episode 2)
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DBT and BigQuery: How to gain visibility and control over your data cost (Episode 1)
The Basics of BigQuery Costs Managing costs in BigQuery begins with understanding the fundamentals. BigQuery charges users primarily for storage and processing, each with unique considerations that affect the total spend. Let’s dive into the details of each. Storage Costs BigQuery storage charges are based on the amount of data stored, measured in terabytes per…
Read more about DBT and BigQuery: How to gain visibility and control over your data cost (Episode 1)