Watching Your Apps? Don’t Let the Bill Watch You Back!
Hey everyone, John here! Today, we’re diving into a topic that might sound a bit technical, but trust me, it’s something that affects a lot of companies: the cost of keeping an eye on their technology. Imagine you have a very complex, modern car. You’d want a dashboard that tells you everything, right? Speed, fuel, engine temperature… but what if it also told you about every single tiny vibration, the temperature of each individual tire tread, and the air pressure changes every millisecond? That’s a ton of information! It’s incredibly useful for spotting problems early, but recording and storing all that data 24/7 can get very, very expensive.
In the world of technology, this is a real issue. Companies need to “observe” their applications and websites to make sure they’re running smoothly for you, the user. But the cost of this observation can spiral out of control. Today, we’re going to break down six simple techniques to lower these costs without flying blind. And as always, my wonderful assistant Lila is here to help us keep things clear.
Hi everyone! I’m ready to ask the questions we’re all thinking.
First, What is “Cloud Observability” Anyway?
Great question to start with, Lila. In simple terms, cloud observability is the ability to understand what’s happening inside a complex digital service (like a shopping website or a mobile banking app) just by looking at the data it produces. It’s like a doctor understanding a patient’s health by looking at their heart rate, temperature, and blood tests. This lets engineers find and fix problems before they affect you.
To do this, they collect something called “telemetry data.”
Lila: Hold on, John. “Telemetry data”? That sounds like something from a spaceship.
Haha, it does, doesn’t it? But it’s simpler than it sounds. Telemetry is just the data the application sends out to tell us how it’s doing. It mainly comes in three flavors:
- Logs: Think of this as a detailed diary or journal. It’s a running text file that says, “User A logged in at 10:01 AM,” “Page B loaded successfully,” or “Oops, an error happened in the payment system!”
- Metrics: These are numbers that track performance. For example: “CPU usage is at 50%,” “5,000 people are on the website right now,” or “The average page load time is 1.2 seconds.”
- Traces: This one is a bit like a package tracker. It follows a single request—like you clicking “Buy Now”—as it travels through all the different parts of the application. It helps pinpoint exactly where things are slowing down.
Collecting all these logs, metrics, and traces is what costs so much money. Companies are often charged for how much data they send, how much they store, and how long they keep it. Now, let’s get into how to control those costs.
Technique 1: Be a Data Bouncer – Only Let the Important Stuff In
The most effective way to save money is to simply collect less data. But you have to be smart about it! Think of yourself as a bouncer at an exclusive party. You don’t just let anyone in; you have a guest list and only let the VIPs through. You need to do the same with your data.
- Filter Your Data: Set up rules to automatically ignore useless information. For example, you can tell your system, “Don’t bother recording the thousands of ‘everything is fine’ messages, but please shout it from the rooftops if you see an ‘ERROR’ message.”
- Try Strategic Sampling: For very busy applications, you don’t need to record every single user action. Instead, you can use “intelligent sampling.”
Lila: “Intelligent sampling”? What does that mean?
It means instead of recording data from 100% of your users, you might only record data from a random 10%. For a big website, that 10% is still a huge amount of information and will give you a very accurate picture of what’s going on, but it reduces your data volume—and your bill—by 90%! It’s about capturing a representative sample, not every single drop of water in the ocean.
- Adjust How Often You Check: Do you really need to check your server’s temperature every 10 seconds? Or is checking every minute good enough to spot a problem? Changing this “scrape interval” from 10 seconds to 60 seconds can cut that specific data by over 80%.
Technique 2: Tidy Up Your Data – Don’t Be a Digital Hoarder
Okay, so you’ve collected your data. The next question is: how long do you keep it? Storing data, especially in a way that’s fast to access, is expensive. You need a smart retention policy.
Think of it like your own personal files. You keep this week’s important documents right on your desk where you can grab them instantly. Last year’s tax returns might be in a filing cabinet in your office. And documents from ten years ago? They’re probably in a dusty box in the attic.
You should treat your data the same way:
- Short-Term Storage: Keep very detailed, recent data (from the last 7-30 days) in expensive, “hot” storage. This is the data you need for immediate problem-solving.
- Long-Term Archiving: Older data that you rarely need but have to keep (for legal reasons, perhaps) can be moved to very cheap “cold” storage. It might take a few hours to get it back, but it costs a tiny fraction of hot storage.
Lila: The original article mentions things like “S3” and “Glacier.” Are those different types of storage?
Exactly! Those are names of products from Amazon Web Services (AWS), a huge cloud provider. Think of “S3 Standard” as your office filing cabinet—pretty fast and reasonably priced. “S3 Glacier” is the deep-freeze archive, like that box in the attic. It’s incredibly cheap for long-term storage. Using a mix of these based on the age and importance of the data is a huge money-saver.
Technique 3: Right-Sizing Your Engine – Don’t Overpay for Power
One of the cool things about observability data is that it can help you save money on your other cloud costs! By analyzing your metrics, you can see if you’re paying for more server power than you actually need.
It’s like paying for a giant V8 engine in a truck when you only drive to the local grocery store. Your observability data can tell you that you only need a small, efficient V4 engine. You can then “right-size” your servers and save a bundle.
Another trick is autoscaling. This is a magical feature where your application can automatically get more server power during busy times (like Black Friday) and then automatically shrink back down during quiet times (like 3 AM on a Tuesday). You only pay for the power you actually use, moment to moment.
Lila: The article also mentioned “Spot Instances” and “Reserved Instances.” More fancy terms?
You got it. They’re just discount plans offered by cloud providers.
- Reserved Instances: This is like pre-paying for a one-year or three-year rental on a car. Because you’re committing for a long time, you get a massive discount. It’s perfect for predictable, steady workloads.
- Spot Instances: This is the wild one. It’s like bidding on leftover, unused server power. You can get discounts of up to 90%! The catch? The cloud provider can take that server power back with only a two-minute warning. It’s fantastic for tasks that can be easily stopped and started without causing problems.
Technique 4: Mix and Match Your Tool-Kit
You don’t have to rely on a single, super-expensive, one-size-fits-all tool for your observability. Instead, you can use a mix of different tools for different jobs.
For your most critical, money-making applications, you might use a powerful commercial platform. But for less critical internal tools, you could use cheaper (or even free!) open-source tools like Prometheus and Grafana, or the basic monitoring tools that come built-in with your cloud provider (like AWS CloudWatch).
Lila: What exactly is “open-source”?
Good question! Open-source software is software where the source code is made available to the public for free. Anyone can use it, inspect it, and modify it. Tools like Prometheus (for collecting metrics) and Grafana (for creating beautiful dashboards) are incredibly powerful and popular. You have to manage them yourself, but it can save a lot of money in subscription fees.
Technique 5: Get Everyone on the Same Page – Make Saving a Team Sport
This might be the most important technique of all. Saving money on the cloud isn’t just a job for the tech team; it’s a cultural issue. This is where a concept called FinOps comes in.
Lila: FinOps? Is that a mix of Finance and Operations?
That’s it exactly! FinOps is a practice where everyone—developers, finance managers, and business leaders—works together to be accountable for their cloud spending. It’s about building a cost-conscious culture. This means:
- Educating teams on how much their decisions cost.
- Setting budgets for different projects and getting alerts when they’re close to being exceeded.
- Tagging costs so you can see exactly which team or product is spending what. This creates accountability.
- Regularly reviewing spending to find new ways to optimize.
When every developer knows that adding a new, very “chatty” log message could cost the company thousands of dollars a month, they start to think more carefully. It’s like managing a household budget—if everyone in the family is mindful of their spending, the whole family saves money.
Technique 6: Let AI Be Your Cost-Cutting Detective
Finally, you can use the power of Artificial Intelligence (AI) and Machine Learning (ML) to help you out. Modern observability platforms are starting to build these features in.
- Anomaly Detection: AI can monitor your data volumes and costs 24/7. If it suddenly detects a bizarre, unexpected spike—maybe a bug is causing an application to create a million log entries per minute—it can alert you immediately so you can fix it before you get a shocking bill.
- Predictive Analytics: AI can also look at your historical trends and predict your future costs, helping you budget more effectively and act proactively if it looks like you’re going to overspend.
Our Final Thoughts
John: For me, the key lesson here is that you don’t have to sacrifice visibility to save money. It’s about being strategic and proactive. The shift towards a FinOps culture, where everyone feels responsible for costs, is probably the most powerful and lasting solution. It’s a change in mindset from “move fast and break things” to “move fast and be efficient.”
Lila: As a beginner, I found the analogies really helpful! It makes sense that this isn’t just about technology, but also about people and planning. The idea of using a mix of tools—the expensive Swiss Army knife for some things and a simple hammer for others—seems so practical. It’s empowering to know there are so many ways to be smarter about spending!
This article is based on the following original source, summarized from the author’s perspective:
6 techniques to reduce cloud observability cost