 Hi, I'm Matt Ray. I'm the OpenCost Community Manager and I work for KubeCost. So I'm here to talk about OpenCost. OpenCost is the open-source Kubernetes and cloud-cost monitoring project. We are both a specification and an implementation, so I'll talk about that in a second. But what's important to note is we are a CNCF Sandbox project, and we are also the only CNCF and FNAT-certified solution. So we're at that nice intersection of CNCF, FinOps, open-source, and all that goodness. There's our website, our GitHub, and our link on the CNCF site. So OpenCost started, we joined the CNCF in June of 2022. We started as a specification. A bunch of smart Kubernetes folks got together from different organizations, AWS, Red Hat, GCP, KubeCost, and they got together and determined like, this is how we should measure how costs are allocated in Kubernetes. So on the left you have the things that you get from your cloud provider and what you get from the node itself, how much CPU, how much memory, how much GPU is taken by your workloads. And then on the right is how you can split that up. So you can say, hey, I want to see all the cost of all my applications per namespace or I could do multi-aggregation, I want to see per namespace with the pods in each namespace. So we give you a lot of flexibility, you can also do tags and labels of course. But really you can slice and dice your Kubernetes data pretty much any way you want. And so that's the specification, it talks about how things are shared equally. But it also talks about how to record all these things. And so that's how Apocost got started, focused strictly on Kubernetes. But today I'm excited to announce that this week we're going to be releasing carbon cost. That is a new feature. We're going to be bringing in the ability to measure the carbon footprint of your workloads. It's still pretty rough, a work of progress, thank you. I didn't write it but I'm happy about it. It's based off the open source cloud carbon footprint project. So CCF, cloudcarbonfootprint.org. We've been working with the fine folks over ThoughtWorks on that. And so the codes in Mainline will have it out in our next release. Maybe this week, maybe next week, but we're working on that. We're also going to be announcing this week that we have a new plugin architecture. And what this new plugin architecture allows you to do is to bring in your external costs. Some sort of SaaS or pass or whatever it might be that you care about. Your cloud costs are there. We're bringing in the ability to bring those in to open cost, add them to the API, and eventually into the UI as well. And our first reference implementation is going to be Datadog. So that'll be available. It's already in the code but it'll be in the next release. Our current release is 1.109. And 1.108 we introduced cloud cost. And so this is, as far as I know, the first open source implementation of going and processing your AWS, GCP, and Azure cost and usage reports. So if you're familiar with cloud billing, your cloud providers are pushing out a huge amount of JSON or CSVs or whatever it might be of how you're actually spending your cloud costs. These are large and complex. I mean, I've seen terabyte-sized files from some of the customers. Cloud cost gives you the ability to parse those and actually put an API in front of them for reporting. So that's a new feature. As far as I know, not available anywhere else. It's not tied to your Kubernetes cost just yet. So you have your Kubernetes cost allocation, your cloud cost. The carbon costs are going to be next to your Kubernetes cost and your cloud cost. And the open cost plugins, we're going to let you mix and match where you see that data. So that's what's monitored today if you went to mainline in the 1.10 release. We also have a UI, of course. The UI, it's not exciting. It's reacting and just pretty much a front-end for the API. That allows you to drill down into everything. But what's really important is getting access to all that data. We have an API. We try to document everything that's available with the open cost plugins who will be able to extend the API to give access to Datadog or whatever it might be that you feel like getting added. We have CSV and Parquet exports. So we're sitting on a whole lot of useful data. You probably have other tools that like to consume that, whether it's something like Athena or a BI tool or what have you. We make it easy to access our data. If you prefer to visualize it in Grafana, obviously we're running on top of Prometheus for a lot of this. So you can go and access Prometheus directly. We have a Prometheus open cost exporter that's part of the Prometheus community charts. And so you can go and just use open costs as an exporter for Kubernetes data. All you want is raw monitoring data. And then we also have a CLI, Kube-Cuttle Cost, that allows you to pull that data out as well. We have a backstage plugin that is a port of the UI. If you are a UI person, follow up with me because we really need UI help. But that's how you can access all the data that we're sitting on top of. And so you probably have a lot of great ways to use this data. Installation is pretty simple. We depend on Prometheus. It's our data store for metrics. You can use other compatible backends like Thanos, Mimir, Cortex, Victoria Metrics. Those all have limited amounts of documentation, but they all work. There's a Helm chart that is our preferred installation technique. It allows you to do all the configuration you need. And we recently added support for running in Docker. So if you don't want to have Kubernetes cost allocations, if you just want access to your cloud cost, your carbon footprint, what have you, you can run everything inside of Docker. So we are in the Project Pavilion Wednesday and Friday afternoons this week. Be sure to stop by. I'll have some stickers, maybe some t-shirts. Love to catch up with you and talk about how we can make this project better. We are in the CNCF Slack. We're on GitHub. We have five repositories on GitHub. We have fortnightly community meetings. Those are documented. We record them and dump them to YouTube. And then we're on all the social medias. So thank you very much. Talk to you soon.