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For Hypergrowth Startups, Is the Cloud Worth the Cost?

Cloud computing has long been the favored infrastructure choice among startups, but as businesses rapidly scale, hypergrowth startups—also known as scale-ups—may suffer under the weight of large and unexpected bills. In addition, a lack of real-time analytics and cloud complexity can inhibit digital innovation for companies seeking to create disruptive products. For hypergrowth startups seeking scalable, cost-effective infrastructure, is there another way forward? Read on to learn more about the long-term challenges scale-ups face when scaling cloud applications, and find out how you can get up to $120,000 in service credits for your startup.

Cloud Costs and Pricing Complexity

Both average valuation[1] and funding from VCs[2] have declined in recent months, as reported by TechCrunch earlier this year. This means it’s crucial for startups to control and accurately predict cloud costs to ensure that they work at a sustainable burn rate. Taking advantage of cloud providers’ free tier cloud services is an economical choice for early-stage startups, but as businesses scale, costs rapidly increase, often in ways that are difficult to predict.

As Forbes recently noted, “the pricing of cloud services is often complex and opaque. There is no standardization, so it can be hard to compare prices across providers.”[3] An article from Cisco cites 27 separate pricing factors that affect cloud costs for the most common resource types—and this is only the tip of the iceberg.[4] Costs also vary by factors such as region and pricing model, and are multiplied by each resource type used for each workload, resulting in exponentially greater possibilities. In fact, one researcher found that a single AWS instance could result in over a million different pricing variations.[5]

These complexities mean that accurately estimating or optimizing costs is not always possible, resulting in surprise fees and cloud spend waste that can eat into startups’ runway. Forbes recently cited an example of one startup that received a $72,000 bill after testing Google Cloud Platform[3], and respondents in Flexera’s 2022 State of the Cloud Report estimated that they waste almost a third of cloud resources[6].

Without a way to control these costs, startups risk dedicating an outsize percentage of their budgets to operations, leaving less for innovative new initiatives and features.

Barriers to Innovation

The Need for Speed and Reliability

Technologies like artificial intelligence and extended reality are increasingly powering today’s most innovative applications, requiring large-scale data processing capabilities that the cloud is well-suited for. However, these technologies rely not only on the ability to process large amounts of data, but do so in real time. And this is not possible in the cloud due to the high network latency of transferring data to and from faraway cloud data centers, which are centralized in a few regions and typically located far away from end users, where land is cheaper.

In addition, new classes of 5G-enabled technology, like ultra-reliable low-latency communications (URLLC) demand mission-critical availability, which can be difficult to ensure in the cloud. Uptime Institute’s 2022 Outage Analysis revealed that third-party providers were responsible for 70% of all publicly reported outages in 2021 and that outages of 24 hours or more—has increased 22% in the past five years.[7] Even for startups that do not provide mission-critical services, this kind of prolonged downtime can ruin the brand reputation of a business in its early stages.

Operational Complexity

In addition to the complexity of pricing, managing applications across one or more cloud environments comes with its own complications. In order to maximize the performance, scalability, and cost savings of the cloud, many businesses use a microservices architecture with apps hosted in containers.

As businesses scale, however, managing these individual units becomes increasingly difficult as the number of containers multiplies (or, less desirably, as microservices balloon into distributed monoliths). As a recent McKinsey article noted, “Software developers using containers, for example, need to build and maintain an exponential mesh of integrations between a range of applications, a hugely complex task that provides no material business benefits.”[8] In fact, the Cloud Native Computing Foundation’s recent survey of top companies and startups revealed that complexity is the top challenge of using containers.[9] And this focus on operations takes away from time that could be spent developing value-added features.

Solving Cloud Challenges at the Edge

Businesses have long used CDNs to reduce data transfer costs by delivering static content and filtering out malicious traffic at the edge. But although this allows startups to partially reduce cloud costs, the the computing capabilities of CDN PoPs are limited. Unable to process these requests at the edge, CDNs forward these requests back to the cloud, resulting in increased data transfer costs, latency, and vulnerability to outages and attacks. To enable dynamic content delivery with high performance and real-time analytics, startups need to perform complex computing tasks at the edge of the network—in other words, to embrace edge computing.

As Gartner explains, “Edge computing tackles a growing demand to address lower latency, process the growing amount of data on the edge, and support resilience to network disconnection.”[10] By running low-latency and mission-critical workloads at the edge, businesses can explore a wider range of innovative use cases.

And with a serverless edge platform, startups can gain even more operational efficiency and scalability. Like microservices, serverless functions make applications more efficient by atomizing them into self-contained units that can be deployed and scaled automatically. But unlike microservices, serverless functions do not run in containers with resources that need to be partitioned in advance for specific regions. Instead, functions run when and where they’re needed and scale automatically, simplifying pricing and resource management. And these savings in time and money allow startups to focus on creating innovative new features.

A summary of benefits cloud vs edge

Conclusion

When it comes to startups and the cloud, a recent article from VentureBeat summarizes the dilemma best: “You’re crazy if you don’t start in the cloud; you’re crazy if you stay on it.”[11] For growing startups, moving workloads out of the cloud and into the edge can not only save time and money, but gain greater performance and a wider range of use cases.

Interested in trying out the edge for yourself? Enroll in Azion’s Scale Up program and get up to $120,000 in service credits and free integration services for your startup, or sign up for our newsletter to learn more about the benefits of edge computing.

References

[1] TechCrunch

[2] TechCrunch

[3] Forbes

[4] Cisco

[5] Infracost

[6] Flexera

[7] Uptime Institute

[8] McKinsey

[9] CNCF

[10] Gartner

[11] VentureBeat