14 tiny tricks for big cloud savings

When the cost of cloud computing is listed in cents or even fractions of a cent, it’s hard to remember that even small numbers can add up to big bills. Yet they do, and every month it seems CFOs come close to dying of multiple heart attacks when the cloud computing bill arrives.

To save the health of these bean counters, and also the necks of the engineers on the receiving end of their ire, here’s a list of small ways organizations can save money on the cloud. None of these tricks is likely to lead to big savings on its own, but together they can add up—or should we say subtract down?—to lower the overall cloud bill.

Shut down development clusters when they’re not in use

Some developers work eight hours a day, and some work more. But it’s rare for anyone to use a development cluster for more than 12 hours a day for a sustained period. There are 168 hours in a week but if you and your team work only a quarter of those hours, it’s possible to save 75% on the cost of running your development clusters. Yes, shutting down big clusters can take time. Yes, some types of odd machines may be hard to spin up immediately. Consider writing scripts that run in the background and manage it all for you.

Smart mock your microservices

Many cloud applications are constellations of machines running microservices. Instead of firing up all your machines, you can employ a smart set of mock services to imitate machines that are not the focus of the daily work. Mock instances of microservices can significantly shrink what is required to test new code. Smart developers can often configure these mock instances to offer better telemetry for debugging by tracking all the data that comes their way.

Cap local disk storage

Many cloud instances come with standard disks or persistent storage with default sizes. This can be some of the most expensive disk space for your computation, so it makes sense to limit how much you assign to your machines. Instead of choosing the default, try to get by with as little as possible. This may mean clearing caches or deleting local copies of data after it’s safely stored in a database or object storage. In other words, try to build very lightweight versions of your servers that don’t need much local storage.

Right-size cloud instances

Good algorithms can boost the size of your machine when demand peaks. But clouds don’t always make it easy to shrink all the resources on disk. If your disks grow, they can be hard to shrink. By monitoring these machines closely, you can ensure that your cloud instances consume only as much as they need and no more.

Choose cold storage

Some cloud providers include services for storing data that does not need fast access. AWS’s Glacier and Scaleway, for instance, charge a very low price but only if you accept a latency of several hours or more. It makes sense to carefully migrate cold data to these cheaper locations. In some cases, security could be another argument for choosing this option. Scaleway boasts of using a former nuclear fallout shelter to physically protect data.

Choose cheaper providers

Some competitors offer dramatically lower prices for services like object storage. Wasabi claims to offer prices that are 80% less than the competition. Backblaze says its services cost one-fifth of what you might pay elsewhere. Those are big savings. These services also compete on access latency offering faster “hot storage” response times. Of course, you’ll still have to wait for your queries to travel over the general Internet instead of just inside one data center, but the difference can still be significant. Affordable providers also sometimes offer competitive terms for data access. Some cut out the egress fees, which can be valuable for data that is downloaded frequently.

Spot machines

Some cloud providers run auctions on spare machines and the price tags can be temptingly low. Because you can run tasks without firm deadlines when the spot price is low, spare machines are great for background work like generating monthly reports. On the other hand, it’s important to know these spot instances may be shut down without much warning. Applications that run on spare machines should be idempotent. It’s also worth noting that when demand is high, the spot prices can soar. Just think of using them as a bit of a financial adventure.

Reserved instances

Cloud providers can offer significant discounts for organizations that make a long-term commitment to using hardware. These are sometimes called reserved instances, or usage-based discounts. They can be ideal when you know just how much you’ll need for the next few years. The downside is that the commitment locks in both sides of the deal. You can’t just shut down machines in slack times or when a project is canceled.

Be transparent

Engineers are pretty good at solving problems, especially numerical ones, and in the end, cloud cost is just another metric to optimize. Many teams leave the cloud costs to some devops pro who might have a monthly meeting with someone from finance. A better solution is to broadcast the spending data to everyone on the team. Let them drill down into the numbers and see just where the cash is going. A good dashboard that breaks down cloud costs may just spark an idea about where to cut back.

Go serverless

The cloud computing revolution has always been about centralizing resources and then making it easy for users to buy only as much as they need. The logical extreme of this is billing by each transaction. The poorly named “serverless” architecture is a good example of saving money by buying only what you need. A friend of mine brags that one of his side hustles costs him only 3 cents per month but one day he hopes it will go viral and the bills will spiral into the tens or even hundreds of dollars. Businesses with skunk work projects or proofs of concept love these options because they can keep computing costs quite low until the demand arrives.

Store less data

Programmers like to keep data around in case they might ever need it again. That’s a good habit until your app starts scaling and it’s repeated a bazillion times. If you don’t call the user, do you really need to store their telephone number? Tossing personal data aside not only saves storage fees but limits the danger of releasing personally identifiable information. Stop keeping extra log files or backups of data that you’ll never use again.

Store data locally

Many modern browsers make it possible to store data in object storage or even a basic version of a classic database. The WebStorage API offers a simple key-value store while the IndexedDB stores hierarchical tables and indexes them too. Both solutions were intended to be smart, local caches for building more sophisticated web applications that also responded quickly without overloading the network connection. But they can also be used to save storage costs. If the user wants to save endless drafts, well, maybe they can pay for it themselves.

Move the work elsewhere

While many cloud providers charge the same no matter where you store your data, some are starting to change the price tag based on location. AWS, for instance, charges $0.023 per gigabyte in Northern Virginia but $0.026 in Northern California for S3 storage. Alibaba recently cut its prices in offshore data centers much more than the onshore ones. Location matters quite a bit in these examples. Unfortunately, it may not be easy to take advantage of these cost savings for large blocks of data. Some cloud providers have exfiltration charges for moving data between regions. Still, it’s a good idea to shop around when setting up new programs.

Offload cold data

Cutting back on some services will save money, but the best way to save cash is to go cold turkey. There’s nothing stopping you from dumping your data into a hard disk on your desk or down the hall in a local data center. Hard disk prices can be just above $10 per terabyte for a new hard disk or below $7 for a used disk. And that’s not a monthly price or even an annual one; it’s for as long as the disk keeps spinning. Of course, you only get that price in return for taking on all the responsibility and the cost of electricity. It won’t make sense for your serious workloads, but the savings for not-so-important tasks like very cold backup data can be significant. You might also note some advantages in cases where compliance rules favor having physical control of the data.