GreenOps and AI #2 : Train your AI models more sustainably by optimizing server usage in 4 steps

Training AI models chomps data, and in turn, energy. That's heavy on our planet, and we're not keen on that. However, like you, we're all about powering ahead with AI. By trimming the workload, fine-tuning server use, and pinpointing optimal timing and locations, you can significantly curb emissions. This approach intertwines with a rising vision in development known as GreenOps. GreenOps, a revolutionary operational management method, zeroes in on eco-awareness and sustainability within the IT sector. Instead of just chasing efficiency and performance, GreenOps steers toward shrinking the ecological footprint, and in turn, cost of server use.

The principles of GreenOps encompass energy optimization, waste reduction, and slashing CO2 emissions. One of the prime methods to achieve this practically is by optimizing server configurations. Tailoring servers to the specific needs of workloads prevents excessive energy consumption. GreenOps isn't solely an ethical stance in IT management; it brings tangible benefits to businesses, such as cost savings, enhanced operational efficiency, and reduced negative environmental impact. It's a stride toward a more sustainable and responsible IT industry. Thus, in a series of blogs, we're doling out tips on making your AI models as sustainable as can be. In our previous blog, we looked at trimming your workload. In this one, we're focusing on honing server usage. Often, that could use a tune-up for efficiency. Let's dive into the advantages first.

Benefits of Optimal Server Use

You probably know most of the benefits that come with optimal server use. But, just in case you need to win over the rest of the crew, let's line them up. Because yes, it might demand some extra effort and time from your IT crew, but it packs a punch in returns, such as:

  • Cost Savings: Optimized server use means paying for precisely what you need.
  • Enhanced Performance: Efficient systems mean improved performance and faster responsiveness, like a well-maintained car driving smoother than an old clunker.
  • Scalability: Optimization lets you swiftly respond to shifting workloads, flexing your infrastructure as needed, similar to highway lanes opening up based on traffic volume.
  • Reduced Waste: Efficient server use ultimately calls for fewer server productions, contributing to less electronic waste.

In essence, optimizing server use isn't just an environmental win; it yields advantages in cost, performance, scalability, and ultimately, service quality. Enough reasons to fine-tune your server use. How do you go about it? Here are four concrete steps.

Step 1: Tweak Your Resource Requests and Limits

Your AI application might gulp down more resources than necessary. When multiple teams work on an app, they might create multiple replicas to artificially trim latency, an easier route than writing efficient code. But efficient code-writing is the long-term champion. It circumvents issues. Additionally, Kubernetes can aid in managing control over resource requests and limits.

Step 2: Scale Down Your Cluster and Leverage Autoscaling

Autoscaling is the ace in cloud automation. Without it, manually toggling resources with changing conditions seldom optimizes resource use, often leading to unnecessary expenses. Autoscaling ensures your cluster stays precisely sized for your data traffic, translating to more efficient server use, a flexible infrastructure, and a greener environment!

Step 3: Automate Stopping Staging and Test Environments

Test environments are easily forgotten once they're no longer needed. Amidst the chaos of a new release, you might overlook them. You can't always shut them down immediately. However, you can automatically deactivate unused staging and test environments after a set time, say a month. Tools like Ansible, Puppet, or Terraform can assist. Clearly define the criteria for inactivity triggering the tool to shut down the test environment. By judiciously shutting these environments down, you free up valuable resources and ensure servers aren't idling needlessly. Less cost, less CO2 emission, and a cleaner planet! The cloud lends a hand here.

Step 4: Evaluate After a Month

To optimize server use, regular evaluation is a must. Periodically check, say monthly, if the set limits remain relevant and if everyone is utilizing resources sustainably. Start by setting KPIs for evaluation, covering predetermined limits, and more specific metrics like resource use per workload, server energy consumption, or used-to-unused resource ratio. The more precise, the better for pinpointing areas needing more efficiency, ranging from curbing excessive resource use to consolidating servers and improving virtualization. Collect not just server load data but also energy consumption and costs. It helps communicate the impact of your efforts to the rest of the organization. Converting CO2 emissions into everyday terms makes it concrete for your colleagues and motivates action.

Tip: You can calculate your savings in, for instance, converted kilometers on this website.

Where You Host Your Server Matters Too!

Optimizing server use contributes to a greener world, but the location of your server determines a significant portion of your CO2 emissions. Not all data centers are equally green. The difference is substantial, whether you process and store data locally or across the ocean. Also crucial is your cloud provider's energy use, how they cool servers, and if they reuse residual heat. Leafcloud, a Dutch cloud provider, scores high on all these fronts. Our servers reside locally in buildings hooked into central heating systems. We power these servers with green energy. 85% of the heat they generate serves as warm tap water in the building. No new construction for our data centers, and fewer fossil fuels for the residents above our servers. At each location, we save up to 1,691 tons of CO2 yearly – equivalent to the energy consumption of over 200 households. So, if you're keen on training your AI models with reduced CO2 emissions, opt for Leafcloud as your cloud provider. The more organizations use our services, the more locations we can set up. Together, we magnify the impact!