When masses of data form the very backbone of today's business, startups are typically faced with the Great Cloud Question right out of the gate. Startup CTOs know that as bang-to-buck ratios go, a cloud-based solution is going to perform better and for less, but after that, it can be hard to identify the right platform. While there are a ton of factors that could lead you to choose Google Cloud, we’ve found that for startups, Amazon Web Services (AWS) is often the smartest choice.
Anyone in the software biz knows that as cloud computing is typically the more affordable and increasingly customizable solution than in-house servers, so millions of businesses are shifting to cloud-based operations. Cloud computing is more scalable, giving your company access to unlimited computing power and storage as you grow. It's leaner, more efficient, and more cost-effective.
But AWS for startups in particular? Let's just say we have opinions.
You only pay for what you actually use
Maintaining private servers requires a lot of upfront cost in hardware and installation, followed by ongoing costs like maintenance and physical storage. For startups in need of budget-conscious solutions, private servers are therefore a non-starter. With AWS, your monthly bill will reflect only the individual resources you choose. Let's say, for example, that you're looking to modernize your data infrastructure, but you're not looking for ML solutions right now. AWS lets you pick straight from its marketplace the applications you need. It also lets you search not just by category, but by use case, which is particularly handy when you're looking for a targeted solution.
Then, customization over time gives startups leeway to adjust their cloud solution as their needs evolve. Case in point: One gaming company we worked with had hit a plateau with customer analytics. We built out an AWS integration that gave the company the 360° view of user data they needed for new insights, improved engagement, and made data management more efficient. Plus, the platform can be expanded further if they decide to add additional features to their new infrastructure.
AI and machine learning integration
With machine learning and AI solutions seeing widespread adoption over the last two years across the tech sector, you likely need to not just build those proficiencies as you grow your team, but identify where infrastructure integration can benefit your team. That's simply a competitive necessity. AWS has a suite of services organized around doing just that.
Best-in-class performance
With traditional hosting services, if your server goes down, so does your site or application — which means major disruptions and lost revenue. With AWS Cloud, data infrastructure is secured with the world's largest redundancy system, at both the regional and global levels; if one server goes down, another is already in place to prevent service outages. Combine this performance advantage with AWS Auto Scaling to build effective scaling plans that are monitored automatically, and now you're running a system that adapts intuitively to the needs of your business growth, provides top-notch security, and simultaneously reduces the chance of server interruption altogether.
Reliability, any time and all the time
When any gap in service means lost revenue, waiting days to provision a server in-house makes an already bad situation worse. Cloud infrastructure in general is always going to make for faster, smoother transitions in that regard, but AWS Cloud is built particularly with the business necessity of cloud continuity in mind. CodeDeploy automates customized software deployment so processes like rolling out new features, application deployments, and application updates are all a cinch, eliminating downtime and the risk associated with manual adjustments.
Extensive features
The AWS product list includes over 200 resources that an experienced dev team can take advantage of, many of which are built to the needs of specific industries and target goals. There's a wide array of specialized tools for your team, including computing, data management, databases, analytics, networking, mobile access, developer and manager tools, IoT, security, and enterprise applications.
One of the really standout features is the aptly-named Fault Injection Simulator, which allows your team to simulate the occurrence of errors that otherwise wouldn't be identified until launch. The value-add of catching breakdowns before they catch you is immense, both in product performance capability and money saved by avoiding costly interruptions.
That means the only limit is the level of your dev team's AWS Cloud skills — and if you want to add some world-class AWS engineers to your team? We might know a few.
Try it out for free
It just makes sense to take a trial run before you commit to any long-term cloud plan, particularly if your company is really young. That's why AWS lets development teams get free, hands-on experience with the platform and a chance to explore 100+ products using the AWS Free Tier. For example, a prospective adopter can try EC2 to run a micro instance for a full month to see how the API works with existing software. No investment needed while still field-testing AWS to assess its value-add.
As a helpful extra: AWS also provides over 500+ free digital courses to help your development team build their AWS Cloud skills at no additional cost.
The competition
There's no shortage of options when you're in the market for cloud platforms, and sure, Microsoft Azure and Google Cloud are also sound choices. But AWS powers more than 33% of the entire cloud computing market (it was, after all, introduced in 2006, making it the most mature cloud provider by several years), largely because of the sophistication of the its resources.
An example of this is container management. Data containers are packages of data that include the data itself as well as instructions on how to deploy or affect the contained data. (Think IKEA furniture but for data structures: all the components as well as how to put them together, only in this case the instructions are for a computing environment instead of a writer who’s very bad at assembling furniture.)
Google wins some points here for developing the now widely-adopted Kubernetes software that all of the Big 3 platforms use for managing containers, in part because it's open-source. As our AWS consultants like to point out though, while Kubernetes is impressive, it shines because it facilitates the creation of the tools that AWS developed to cater to specific workloads, such as the Elastic Container Service (ECS), Elastic Kubernetes Service (EKS), AWS Fargate, and Kops for AWS.
As our lead DevOps engineer, Semyon Gordeev, explains, AWS offers tools that streamline container optimization. "No matter how simple or complex a project is, the core scalability remains consistent and reliable, leaving more time for application development," he says, adding that AWS makes diverse deployment options relatively simple. For example, 'serverless' running containers are doable with AWS, as are scalable clusters, and complex clusters in hybrid networks.
The best on the market for startups
With a number of platforms entering the cloud provider space, there are a lot of factors to consider. From our perspective, the unparalleled range of services, the ease of access, competitive and modular pricing, as well as a best-in-class client list make AWS Cloud the choice for fledgling businesses. That doesn't mean that other options on the market are bad by any stretch, but we've found that for ambitious startups, AWS is most often the best choice.
Ultimately, AWS is the most nimble cloud platform, which is really what startups need given the prospect of scaling fast and the demands of adding new features and applications quickly. In addition to being adaptable, AWS is reliable: You’ll never have to worry about technical limitations when you really need to focus on growing the business, assessing your strategy, and performing at the highest possible level.
