Data Center Usage Tracking

the missing picture on prem to gain a complete and holistic view of your finops footprint, it is not enough to focus solely on cloud costs many organizations still operate critical workloads on on premise infrastructure or run internal applications that generate meaningful resource consumption unlike the public cloud, these environments do not come with built in billing reports as a result, visibility into usage and cost is often incomplete, limiting accountability and making it difficult to implement effective cost management strategies to bridge this gap, it is essential to instrument your on premise infrastructure and applications to capture granular usage data but instrumentation alone is not sufficient you also need a powerful rating engine to convert raw usage into accurate cost, and a billing layer to support chargebacks, showbacks, and cost allocation amberflo is the only provider that delivers this full stack usage metering, rating, and billing this enables finops teams to unify visibility and accountability across both cloud and on prem environments simple but powerful gaining visibility into your on premise infrastructure with amberflo is straightforward it only takes two simple steps create meters define meters that capture the usage signals most relevant to your infrastructure, such as cpu hours, storage consumed, or job execution time these meters serve as the foundation for understanding how resources are being used set rates assign unit costs to each meter so that usage can be accurately translated into spend this allows you to calculate the true cost of resource consumption in real time with this setup, you can gain deep insights into usage patterns, identify cost drivers, and implement chargebacks or showbacks for departments, teams, or projects find your blind spot amberflo supports metering for a wide range of infrastructure and workloads here are some common examples compute usage for ai factories track gpu hours or node utilization across clusters dedicated to training or serving ai models this includes inference jobs, scheduled pipelines, and high throughput workloads storage consumption by department or application meter san, nas, or object storage systems to show which teams or services are using capacity and how it changes over time cpu and memory usage on bare metal or vms capture compute usage metrics from physical servers, virtual machines, or kubernetes workloads for detailed cost attribution high performance computing (hpc) workloads allocate costs for hpc resources based on core hours, queue time, or wall clock runtime grouped by user, project, or lab network bandwidth and data transfer track internal and external traffic across switches, firewalls, and gateways to monitor usage and uncover potential bottlenecks shared platform services meter internal tools like databases, ci/cd runners, or service meshes to determine which business units are driving usage license restricted applications monitor usage of software licensed by user, feature, or interaction to ensure compliance and support internal cost recovery next steps the following sections will walk you through the core steps to enable metering for your on prem resources docid\ tylcs7m2lvyze4clguwqp define meters to track specific types of usage across infrastructure docid 4hlujhpayi od6ksbwj e send usage events to amberflo using sdks, apis, or supported integrations like prometheus with amberflo metering in place, you gain complete, real time visibility into your infrastructure, whether cloud based or on prem this unlocks accurate cost attribution, helps drive accountability, and supports better financial governance across your organization