“Smarter Data for a Greener Future”

Tag: Petrichor

  • Sustainable computing practices: When “clean” tools aren’t clean

    Most people think the sustainability fight is about switching to electric cars, ditching plastic straws, or planting trees in some far-off offset program. But the hard truth? Even the tools built to save the planet quietly siphon energy, burn carbon, and leave their own digital soot behind. A focus on sustainable computing practices is the best way to reduce your impact.

    Sustainable computing practices make a difference when it comes to environmental impact.

    Why it hurts when clean tech feels dirty

    You know that uneasy feeling when you do something good but suspect it might not be good enough? That’s the elephant in the server room of modern sustainable computing practices. We’re surrounded by tools and platforms that promise to shrink our environmental footprints. But peel back the interface, and you might find a fat carbon bill quietly humming under the hood.

    Sustainability dashboards. Eco-optimizing apps. Footprint trackers. They all swear they’re fighting climate change. And maybe they are. But too often, the tech built to save the planet ends up burning it a little more instead.

    The myth beneath the glossy interface

    Clean tech doesn’t come from a magic wand. It comes from mining, manufacturing, and machines running hot. Solar panels degrade. Wind turbines require rare materials. AI models that predict energy usage often consume more training power than a family home uses in a year.

    And the apps? The dashboards? The “insights”? They aren’t free. Just because something helps you reduce emissions doesn’t mean it cost nothing to build or maintain. In digital sustainability, most of the burn happens behind the scenes.

    Building Petrichor meant building with constraint

    When I was building Petrichor, a platform to help users understand and reduce their digital footprint, I wanted to include AI features. But not at the cost of increasing the very thing we were trying to fight.

    So we ran the math. We mapped out what features we really needed. Then we hunted for smaller, leaner AI models that could deliver just enough intelligence without chewing through unnecessary power. No massive LLMs guzzling GPU time. Just purpose-fit models doing quiet, effective work.

    We applied core principles like energy efficiency and carbon awareness, similar to the Green Software Foundation’s sustainability principles, to ensure every feature justified its environmental cost.

    Every feature had to earn its place. If it couldn’t prove it was net-positive for the environment, it got the axe.

    Where most sustainable computing teams still get it wrong

    Too many so-called “sustainable” platforms are green in name, not in architecture. They love to brag about the emissions users avoid, but never disclose the emissions their backends generate to make that calculation.

    It’s like driving a hybrid car to a climate summit, but forgetting to mention you flew first-class to get there. The issue isn’t deception. It’s habit. We measure what’s visible. We market what photographs well. We don’t ask if our interventions actually deliver a net gain.

    What real sustainable computing practices in tech look like

    Here’s what we’ve learned on the ground:

    • Track the full lifecycle: Code, compute, cloud hosting; it all has a footprint.
    • Design for less: More features mean more complexity. More complexity means more energy.
    • Use intent as a constraint: Every idea must answer a tough question: does this reduce impact or just make us feel better?

    You don’t need to be perfect. But if you’re flying a green flag, you damn well better mean it.

    The invisible wins that make the real difference

    The biggest gains weren’t glamorous. They came from small, disciplined choices:

    • Optimizing queries so servers work less
    • Spinning down idle instances to save power
    • Avoiding redundant data tracking that bloats storage and compute cycles

    Those changes don’t make the slide deck. But they make the difference between clean tech and performative tech.

    Build with honesty and sustainable practices, or don’t bother

    If your roadmap includes a sustainability slide but not a single question about your server architecture, start over. Digital sustainability in tech isn’t about marketing optics. It’s about taking real responsibility for what your product burns, not just what it says.

    And if you’re staring at a feature backlog that includes words like “AI,” “insights,” and “dashboard,” but haven’t yet calculated their carbon toll, we should talk.

    Because if your product claims to be a cure, but ends up being another form of quiet pollution, the planet won’t care how clean your font is. It’ll just feel the heat.

    Let’s build something real. Something intentional. Something that stays clean behind the scenes.

  • Carbon cloud footprint: The hidden cost of cloud data

    Have you ever thought about your cloud storage’s impact on the environment? Like most people, I never considered the storage of my data or the negative consequences thereof. The cloud was an ephemeral entity that absorbed my data into lightweight nothingness. It turns out I was very wrong. As my tech prowess grew, so did my awareness of the true weight of the cloud. The good news is that it doesn’t take much to reduce your monthly costs and the carbon cloud footprint all at the same time.

    Carbon cloud footprint hidden costs

    How data inefficiency can quickly impact your bottom line and your carbon cloud footprint

    Let me give you a common example I see. You have a company with 100 employees and use Google Drive for file sharing. You deal with a lot of marketing, which means you have video files averaging 200mb. Employees worry about causing harm to the original file, so they make a copy. This copy is only used for small edits or formatting. Now you have the same file on 10 drives. That means the weight of just one file has ballooned to consume 2 gigabytes of space! Play this out over 100s of files, over multiple months, and pretty soon your company has terabytes of redundant storage.

    This small inefficiency might seem trivial at first glance, but consider this:

    Cloud data storage costs

    The Google Cloud platform cost of 1TB of data is $20 per month. As your redundant storage expands, so does the cost. This can translate to 100s or 1000s of dollars every year, unnecessarily.

    Electricity usage and environmental impact of cloud storage

    Cloud storage isn’t environmentally free. Data centers consume vast amounts of energy. One gigabyte of data produces approximately 3 kg of CO₂ and 5-7 kWh of electricity per year. That’s like fully charging your cell phone 600 times! This significant carbon cloud footprint contributes to global warming and environmental degradation. Digital storage isn’t going anywhere. Now is the time to focus on minimizing the impact.

    AI and processing impact on your carbon footprint

    The scanning of entire storage sets with AI is happening daily. Every redundancy adds computational time. The increased processing contributes to energy consumption, CO2 emissions, and monthly costs. With the rise of AI, there’s never been a more important time to have lean data practices.

    To put this even more in perspective, most SMBs store thousands of gigabytes of data without realizing the energy and financial cost. 10 TB of redundant data is equivalent to powering 5 average US homes for a year all while emitting ~20 metric tons of CO2! Increasing your data efficiency means reducing costs and lowering your carbon cloud footprint.

    What can you do about your inefficient cloud storage?

    Most small and medium-sized businesses don’t realize their storage impact. The overlooked redundancies cost you time and resources. They can even go against your core values. These unnoticed issues can hinder growth, productivity, and competitiveness in the market.

    Evergreen Analytics Partners offers solutions and insights geared toward SMBs. Our bespoke systems focus on your objectives and goals. We want to help you cut expenses, use less electricity, and reduce your carbon footprint. Our methods are realistic, immediate, actionable, and designed for efficiency.

    More ways to reduce your cloud carbon footprint

    For a deeper look at practical enterprise strategies, this guide from TechAhead outlines actionable ways to cut cloud-related emissions, ranging from workload optimization to architecture redesign.

    Additionally, our ground-breaking technology, Petrichor, is in its second beta phase. Designed to identify and manage data inefficiencies, it’s one way we can combat the rise of heavy data. We’re looking for SMBs that want to be proactive with their storage. While in beta, you can try this novel software for free. Early users can impact Petrichor’s development and gain from its potent insights.

    Ready to improve your data efficiency?

    Evergreen Analytics Partners is here to assist SMBs. We will be your partner in sustainability initiatives. At the same time, we can cut expenses and streamline your data management procedures. Arrange your customized data audit or find out more about our consulting services. Get in touch with us today.

    Your data doesn’t have to cost the Earth, or your bottom line.