With incredibly complex cloud architecture — that may even includes Kubernetes and multi-tenant infrastructure — organizations are finding it hard to measure and monitor the performance and cost of their cloud environments.
To stay competitive, organizations should aim to be as efficient as possible — which can help companies to lower costs, increase margins, and improve cloud efficiency.
In this guide, we cover the basics of cloud efficiency as well as six advanced data-driven strategies you can use to make your cloud environment more efficient.
Table Of Contents
What Is Cloud Efficiency?
To some cloud users, cloud efficiency entails attaining remote connectivity to their business infrastructure. Others use it to describe resource utilization in their data centers, while many understandably link it to performance and robustness.
Although all these are admissible definitions, cloud efficiency is best described by combining all of them. Think of it as a holistic concept that relies on multiple dynamic factors.
Simply put, you could say that cloud efficiency refers to your capacity to utilize cloud resources in the best possible way and at the lowest possible cost while, at the same time, minimizing cloud wastage.
Attaining cloud efficiency has become particularly critical in recent times, as organizations continue to take up more resources than they actually need. Over the past few years, businesses have developed a tendency to blindly expand their cloud deployments when they grow. This is is how they ultimately find themselves with extensively complex cloud architectures that are marred with idle resources — which then leads to wasted cloud spend.
In 2020, for instance, early research by Gartner established that while the market for Infrastructure as Service (IaaS) would grow to $50 billion by the end of the year, companies were set to lose over $17 billion in wasted cloud spending due to idle resources.
What Are The Cost Challenges Of The Cloud?
Some of the principal issues that make it particularly difficult for organizations to achieve cost efficiency are:
- Lack of cloud spend insight – While total usage costs can be obvious, many companies are unable to break down the figures to reveal the precise cost metrics for each resource. This lack of visibility leads to what is popularly known as cloud sprawl — where organizations keep haphazardly upscaling their cloud resources without proper management.
- Billing complexity – For users that hope to generate cloud spend insights from their bills, it turns out that cloud platforms are never that forthcoming. You’ll receive your monthly cloud bill but it’ll come with incomprehensible details about your cloud spending.
Amazon Web Services (AWS) is one example of a platform that’s infamous for this. Although its default cost and usage reports appear exhaustive, users often have a hard time making sense of the sophisticated technical specifications. So far-reaching is the problem that, from a survey of 7,500 AWS users, 95% admitted that bills are the most confusing part of the Amazon Cloud platform.
- Misaligned cost optimization strategies across teams – Some organizations mistakenly assume that cloud cost management is exclusively meant for IT teams. As such, they introduce cost reduction strategies that are one-sided — with other departments taking the back seat.
- Manual cost management and optimization – Until recently, it was common for DevOps to manually analyze their cloud usage trends and work out the cost figures, before proceeding to tweak the provisions for each application.
This whole approach is not only time-consuming and burdensome, but also error-prone — consequently making it impossible to guarantee cloud ffficiency.
6 Ways To Improve Your Cloud Efficiency
Now that we’ve ruled out traditional approaches, here are six proven strategies that the most advanced enterprises are using to improve their cloud efficiency. These are the steps you should follow to boost performance, reduce cloud costs, and increase your overall output:
1. Minimize the movement of data
With hybrid being one of the most preferred cloud setups across organizations, huge volumes of data are regularly transferred between the public cloud and on-premise environments.
This whole to-and-from process requires both time and resources. So, the more the data you choose to transfer between environments, the more resources you stand to consume, and the longer it’ll take to relay everything.
For optimal system performance, you should minimize the movement of data between your cloud servers and the company’s on-premise environment. You could start by carefully classifying your data, and then selecting the ideal environment for each category.
Mission-critical data, for instance, ought to be held by on-premise servers, with remote data centers being reserved for non-mission-critical data and applications.
2. Select the most appropriate instances
Leading IaaS providers offer varying types of computing instances to cater to different kinds of workloads.
On the AWS, you’ll find EC2 instances that provide varying combinations of networking, storage, CPU, and memory capacities. Some instances are optimized for general computing, while others are meant for storage, accelerated computing, etc.
To retain the best resources at the lowest possible cost, you should take the time to choose the most suitable instances based on your cloud computing objectives.
If the instance is too small, you may save money but then end up impeding performance. And if it happens to be too big, your workload will benefit from increased performance, but you’ll be drowning in wasted cloud spend.
3. Take advantage of autoscaling
You don’t have to restrict your computing to the default capacities provided by instances. To cater to dynamically changing needs, cloud platforms are capable of automatically scaling user resources on demand. Google Cloud Platform (GCP), Microsoft Azure, and AWS are all known to add or remove instances and related resources as workloads shift.
For example, you can capitalize on their load balancers to avoid overloading your instances during workload spikes. Once you set the appropriate autoscaling rules based on the expected utilization trends, the load balancer will monitor and then distribute the incoming traffic across multiple instances.
4. Track performance
A load balancer will monitor your traffic and workloads, but it won’t give you all the metrics that you need. To comprehensively optimize your cloud performance, you should collect and analyze all the relevant metrics on your workloads and utilization trends.
This is where you leverage not only built-in analytical tools, but also third-party services that are capable of tracking performance in real-time. You should be able to keep tabs on everything that’s going on in your cloud environment.
5. Supplement the cloud network with caches
While storing data in cloud servers is a good way to conveniently facilitate remote access, transferring it all to and from your local network is another problem altogether. Moving the data takes time, which could hamper your applications’ responsiveness.
One way you could effectively speed up the transfer process is to utilize cache services that are compatible with your cloud platform. This will mirror your cloud data across a content delivery network with multiple cache servers — minimizing the relative data transfer distance.
Instead of loading files from the original cloud server, your applications will quickly retrieve data from the nearest located cache server.
6. Implement cloud cost intelligence
Since cloud efficiency is not achievable without minimizing costs, cloud performance optimization should always go hand-in-hand with cloud cost management.
For the best possible outcome, consider using a cloud cost intelligence platform like CloudZero.
CloudZero isn’t just a better way to slice and dice your bill. By enriching your cost with services metadata, telemetry, and more, the CloudZero cost intelligence platform lets you see your costs from any angle. You can unlock previously impossible unit cost metrics (like cost per feature, cost per customer, etc.), and drill down and zoom out on cost — with way less effort than legacy cost reporting tools.
CloudZero gives you the what, why, and where of your AWS investment. Engineering can self-serve and explore the cost of their architecture and apps — enabling them to make cost-aware engineering decisions that ensure profitability for your company. Finance can measure the ROI of your technical investments — and differentiate between an out-of-control cloud bill and economies of scale.