Cloud Spend Management: What Is It and Can It Really Help to Cut Your Bill?

The pay-per-use model of the public cloud seemed too good to be true. And you probably quickly caught onto its catch: analyzing and predicting your cloud costs is like driving blindfolded hoping that the street traffic would stay the same. 

A person holding a calculator in front of a cloud cost spreadsheet.

A solid cloud cost management strategy and tooling solves this problem – but only partially. Knowing what your costs are and where your costs come from isn’t going to reduce them magically. 

It’s a good start, but you still need engineering resources to implement the changes. And not just once, but on a regular basis – or whenever you see a savings opportunity, note a peak usage scenario, or too much shadow IT starts creeping in.

Is there a better way to control your cloud spend? Keep on reading to find out.

Read this guide to see why cost management isn’t enough in the cloud world:

Why are companies struggling with cloud costs?

Jumping on the public cloud bandwagon too fast can make that wagon tip over.

Most teams find controlling cloud costs challenging because they never had so much freedom in spinning up new instances and experimenting with different things. Even those who never used anything other than the public cloud struggle to control their cloud spend.

Here are some common reasons why cloud costs spiral out of control:

  • Companies overlook the risks of the pay-per-use,
  • They have no visibility into their costs,
  • They don’t budget for the cloud and let their bill surprise them each month.

Legacy cost visibility, allocation, and management dashboards helped to solve some of these problems, but not all.

So, what exactly is cloud cost management?

Cloud cost management is an umbrella term for cost monitoring, reporting, visibility, allocation, budgeting, and forecasting.

The goal here is to understand and manage the costs associated with public cloud resources. It means knowing where costs come from, to which teams they can be allocated, and how much you’re likely to spend in the future. 

The last one is particularly important for CFOs, who aren’t too pleased when they have to restate the quarterly results because someone left an expensive instance running for too long.

Cloud cost management is all about control – or, gaining more granular control over the cloud spend while keeping the same level of performance. 

Most cloud providers offer basic cloud cost management solutions to help them achieve that. There are also plenty of specialized third-party tools that offer extra visibility and insight into your cloud expenses.

But here’s where cloud cost management falls short

5 reasons why cloud cost management falls short

1. Cloud costs are always changing

Predicting cloud expenses is hard, even if you’re a tech giant like Pinterest. During the 2018 holiday season, the company’s cloud spend went way beyond the initial estimates due to increased usage. Pinterest had to pay AWS $20 million on top of the $170 million worth of cloud resources it already reserved. 

2. Resource demands never stay the same either

Using the public cloud is all about striking the balance between cost and performance. Traffic spikes can either generate a massive and unforeseen cloud bill if you leave your check open or cause your application to crash if you put rigid limits over its resources. Cloud cost management doesn’t get you anywhere near to solving this issue.

3. Cost visibility is harder than it sounds

Decision-making about cloud spend is often decentralized in large organizations. This makes visibility more challenging than it seems. Add to that shadow IT projects popping up all over the place and you’ll have to deal with costs that can’t be explained just by taking a look at a dashboard or report. 

4. Multi cloud makes cost management even more challenging

Companies that use multi cloud combinations need to consider the costs of several different public cloud providers at the same time. It’s like doubling or tripling the effort you’re doing for one cloud, there are no shortcuts here. 

5. Cloud cost management requires manual work

And lots of it. Analyzing your setup, allocating costs to teams, understanding how much you’ve spent on what, finding better options, migrating your applications to better resources, and then checking whether it’s all working – this is what you need to do. And not once, on a regular basis.

What else is there to help with my cloud costs?

There’s cloud cost optimization. The best way to understand what optimization is all about is knowing what tactics it offers to teams looking to control their cloud spend.

Here are a few of them:

  • Instance rightsizing
  • Automatic scaling (autoscaling) 
  • Resource scheduling
  • Removing unused resources
  • Spot instance use

Not only does optimization help you achieve all of these things, but it can make the process automatic – without adding repetitive tasks for engineers. Some things just aren’t supposed to be managed manually.

Optimizing cloud costs is a point-in-time exercise. You need to keep an eye on your application demands and the available resources 24/7 to identify savings opportunities.

Let’s look into some of the named cost optimization points to see why automation brings so much value there.

1. Instance rightsizing and type selection – or, picking the best instance for the job

Selecting the right virtual machine size can drive your bill down by a lot if compute is your biggest expense. 

But how can you expect a human engineer to do that when AWS alone has some 400 different EC2 instances alone that come in many sizes?

Similar instance types deliver different performance levels depending on which provider you pick. Even in the same cloud, a more expensive instance doesn’t always come with higher performance.

choosing virtual machines

Here’s what you usually need to do when picking an instance manually

1. Establish your minimal requirements

Make sure you do it for all compute dimensions, including CPU (architecture, count, and processor choice), memory, SSD, and network connection.

2. Choose the right instance type

You may select from a variety of CPU, memory, storage, and networking configurations that are bundled in instance types that are optimized for a certain capability.

3. Define your instance’s size.

Remember that the instance should have adequate capacity to handle your workload’s requirements and, if necessary, incorporate features such as bursting.

4. Examine various pricing models

On-demand (pay-as-you-go), reserved capacity, spot instances, and dedicated hosts are all available from the three major cloud providers. Each of these alternatives has its own set of benefits and cons. This guide covers them all in detail: How to choose the best VM type for the job and save on your cloud bill 

Considering that you need to do that on a regular basis, that’s a lot of work!

2. Autoscaling instances as soon as demand changes

If you’re running an e-commerce application, you need to prepare for sudden traffic spikes (think mentioned by a Kardashian on Instagram) yet scale things down when the need is gone.

Manually scaling your cloud capacity is difficult and time-consuming. You must keep track of everything that happens in the system, which may leave you with little time to explore cloud cost reductions. 

When demand is low, you run the risk of overpaying. And when demand is high, you’ll offer poor service to your customers.

Here’s what you need to take care of when scaling resources manually:

  • Gracefully handle traffic increases and keep costs at bay when the need for resources drops,
  • Ensure that changes applied to one workload don’t cause any problems in other workloads or teams,  
  • Configure and manage resource groups on your own, making sure that they all contain resources suitable for your workloads.

When scaling manually, you’d have to scale up or down your resources for each and every virtual machine across every cloud service you use. This is next to impossible. And you have better things to do anyway.

That’s where autoscaling comes into play.

Autoscaling does all the tasks listed above automatically. All you need to do is define your policies related to horizontal and vertical autoscaling, and the autonomous optimization tool will do the job for you.

3. Managing spot instance interruptions 

managing spot instances

Spot instances are up to 90% cheaper than on-demand instances, so buying idle capacity from cloud providers makes sense.

There’s a catch, though: the provider may reclaim these resources at any time. If you’re an AI-driven SaaS, this is fine while you’re doing some background data crunching that you can delay. 

But what if you need the workload to avoid the interruption? You need to make sure your application is ready for that and have a plan in place when your spot instance is interrupted.

Here’s how you can take advantage of spot instances:

1. Check to see if your workload is ready for a spot instance.

Will you be able to tolerate interruptions? How long will it take to finish the project? Is this a life-or-death situation? These and other questions are useful in determining if a workload is suitable for spot instances.

2. Examine your cloud provider offer.

Examining less popular instances is a good idea because they’re less likely to be interrupted and can run for longer periods of time. Before deciding on an instance, look at how often it is interrupted.

3. Make a bid

Set the maximum price you’re willing to spend for your preferred spot instance. The rule of thumb is to set the maximum price at the level of on-demand pricing.

4. Manage spot instances in groups

You’ll be able to request a variety of instance types at the same time, boosting your chances of securing a spot instance. Learn more about managing spot instances here: Spot instances: How to reduce AWS, Azure, and GCP costs by 90%

To make all of the above work, you’ll have to dedicate a lot of time and effort to configuration, setup, and maintenance tasks.

And none of that management guarantees savings, unless you decide to automate optimization

Traditional methods like cost tracking and reporting can only get you halfway there – and at a hefty cost in engineer time.

Cloud cost management doesn’t guarantee savings, automated optimization does.

Discover the benefits of autonomous cloud cost optimization for your company. Book a demo with CAST AI, the world’s leading cloud optimization platform for Kubernetes.

Cut your cloud bill in half without
spending hours of engineer time

P.S. You can always test out the platform and see what it would automate in your environment. To get started, simply register here.

How can you reduce your cloud spend? 

Your cloud bill can easily spiral out of control, so the first step should be to get better visibility into your usage and costs. Once you understand how you use your resources, you can start looking for savings. 

Most cloud providers offer basic cost management tools to help you with that, you can also gain extra insights into your expenses with many third-party solutions.  

What is cloud spend management?

Cloud spend management is the practice of monitoring, reporting, visibility, allocation, budgeting, and forecasting cloud costs to ensure that you achieve a maximum ROI. 

The main objective of cloud cost management is usually to understand, manage, and reduce expenses associated with public cloud resources.

Why is managing your cloud costs so challenging?

Many companies struggle with cloud spend management because both costs and resource demands change continuously. 

Low cost visibility, complex billing, and the fact cost management recommendations need to be implemented manually also don’t help to fix the challenge of soaring expenses. 

And if that wasn’t difficult enough for one cloud, the issue gets even more acute in multi cloud environments.

Why is cloud spend management important?

Teams never had so much freedom in spinning up new instances and experimenting with different things. But as great as pay-per-use sounds, it doesn’t help control cloud costs.

A solid cloud spend management strategy and tooling helps to relieve this problem. And as you you generate more savings, you have more resources for new initiatives that can improve your bottom line.

However, just knowing what your costs are and where they come from won’t reduce them magically. You need to act on these findings – and implementing changes usually involves a lot of manual work of your engineers.

What are the best tools for managing your cloud costs?

Apart from the native tools offered by each Cloud Service Provider, you can also find many great vendor-neutral solutions. 

The most popular choices include CAST AI, Cloudability, CloudChekr, Cloudhealth by VMWare, Densify, Harness, Kubecost, and Spot by NetApp.

What features should a good cost optimization solution have?

First of all, it’s important to ensure that the solution supports your cloud platform. While the support for CSPs like AWS, Google Cloud, and Azure is now a standard, things may not be that obvious if you use a less popular vendor.

Secondly, pay attention to cost allocation and visibility features. Detailed reporting is a must, and so is the ability to view your costs across multiple clouds. 

Having actionable recommendations is great, but being able to implement them effortlessly is even better. 

Even if you don’t consider introducing cloud automation today, it’s worth checking out what options each tool gives you. Some of the automated cloud optimization features worth taking note of include automated rightsizing, horizontal pod autoscaling, resource scheduling, and spot instance automation. 

Last but not least, investigate what multi-cloud optimization features you can get. Ideally, the tool should let you distribute apps and traffic across multiple clouds, always choosing the up and healthy endpoints.

What is the difference between cloud cost management and optimization?

Both cloud spend management and optimization are indispensable to keeping costs under control. 

However, as useful as cost management can be, it still requires a fair deal of manual work. Analyzing your setup, allocating costs to teams, understanding how much you’ve spent, finding better options, migrating your applications, and then checking up on them takes a lot of time and money.  

While platforms like Kubecost take much of that work off your plate and provide you with outstanding recommendations for change, your engineers still need to implement these manually.

Cloud cost optimization is the process of reducing your overall cloud spend by identifying mismanaged resources and eliminating waste. All of that can happen without lifting a finger if you go for an automated solution.

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2022-01-17 7:20 AM

There are some great points in this article, especially about manual work force needed to allocate cloud resources and constantly work around the clock to optimise them for best cost efficiency. Automated tools are definitely the future, but we have to take a big leap to get there without any issues, that’s why I think you guys are taking a bold move being the first ones in the market and I like it.

2022-01-17 7:24 AM

Picking your instance type does seem to be complicated in your explanaition, but its like riding a bike, it comes with time and you get used to it. But you could also argue, that the worst answer to anything could be “thats how we’ve always done it” and looking to optimizing it is definitely worth the time.

2022-01-21 8:14 AM

DevOps, SRE’s and cloud engineers/managers are the most growing specialty nowadays, so I think that the young startups are seeking these people from almost day one. And that I think is because people know the price that the cloud businesses come with.. Making tools to help these poeple and businesses are a key factor as the market expands, thats how I landed here

2022-01-21 8:18 AM

WE didnt even look for software that could help us out with the cloud bills just because we were centered and locked in to aws savings plans and thought thats the best thing we could go for (including using spot instances) but now its like an eye opening experience, seeing this tool at work, doing things we didint know how to..

2022-01-31 7:09 AM

We are talking a lot in our company about going multicloud, but its managment is the thing that scares us the most since we lack knowledge within azure. This would result in more staff building and expenses just to understand the costs better. Thats where I put my faith in tools like CAST that allow that visability without any further expenses.

2022-01-31 7:11 AM

This article addresses some great aspects and problems people sometimes dont consider when scaling and using tools for cloud management

2022-02-04 8:02 AM

Your content is next level, so many great topics covered, keep it up!

2022-02-04 8:19 AM

Spot instance management has been just pain for our team. Those short notices are too short and the more we use it, the more we are unlikely to deploy new things on them.. If CAST spot instance automation is correct, this solves all of our problems and removes the head ache

2022-02-11 11:06 AM

“predicting your cloud costs is like driving blindfolded hoping that the street traffic would stay the same. ” Great analogy

2022-02-11 11:10 AM

I feel like our team is speding too much time on figuring out who and where used which resources for what exactly and it might be internal issue that we need to solve but at the same time I see other companies and my friends in the same field struggling with

2022-04-21 6:02 AM

the title says it all, spending so much time on just figuring out the bill and reasonings behind it consumes so much time that could be allocated else where..

2022-04-21 6:14 AM

helpful Insights, thank you Laurent!

2022-04-21 6:24 AM

I know that for some people, this list of things to check on and what to do might seem obvious but not for me, so thanks to Laurent taking his time to share his knowledge

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