By enabling global data storage and access, cloud computing has transformed the way companies operate. Organizations now host their solutions on cloud providers like Amazon Web Services (AWS), Google Cloud Platform (GCP) and Microsoft Azure Cloud (Azure) rather than dealing with the hassle of maintaining hardware and on-premises solutions. These suppliers offer a variety of managed options, saving what could otherwise take months of engineering work, as well as being trustworthy. Still, businesses must be aware of possible obstacles they may encounter and how to maximize the benefits of their cloud-based solutions to remain competitive.
Being successful in the cloud can involve multitasking, but it can be broken down into certain key topics:
• Choosing services: Pick services to solve business needs and choice of managed services versus open-source software.
• Handling scale: Design your cloud-based architecture to be optimized and scaled to the needs of your business objectives.
• Observability: Not only monitor or collect logs of your system but also understand why something went wrong.
• Security: Ensure sensitive data and internal tools and services are not compromised.
• Developer effectiveness: Automate and maintain the integrity of deployments to the system so your engineers can focus on building new features, rather than focusing on updating production.
As AWS is the most popular cloud platform, our examples will predominantly feature it. But the same logic strategy applies to any cloud platform.
Choosing services
While GCP offers well over 100 services, Amazon and Azure each offer over 200 services. How does one begin to choose? There are many methods to select a group of services to carry out the same task, but this decision should always be based on business needs. For instance, you may wish to start a React single-page application. Using Amazon S3 and CloudFront is one way to guarantee that everyone in the world receives your website promptly. Let’s assume, though, that as your application adds more and more intricate UI features, users will find the rendering process to be a pain, particularly if their computers are slow. Then hosting a React service with server-side rendering on an AWS ECS cluster might be a preferable option.
One may also need to know whether they should use an open-source option that they self-host on the cloud or a managed service from a cloud provider. Lambda’s use of AWS API Gateway differs, for instance, with ECS hosting and an API powered by a well-liked framework like Flask. Although they both address the same issues, they have distinct costs and advantages. For instance, Lambda can be lightweight and economical, but to reliably connect to databases, one now needs to comprehend its drawbacks, including runtime and memory as well as other nuances like cold starts and RDS proxies.
This may seem like a lot of information to absorb, but it’s crucial to remember that the cloud is constantly expanding with new services, so one must stay informed of the most recent developments. By doing this, businesses can embrace newer services and implement better cost- and reliability-saving measures.
Handling scale
The difference between the 100 daily users you currently have and the 100,000 you will have in the future is significant as businesses expand. Similar distinctions exist between transforming and transferring data that is only a few megabytes and moving it once it has grown to several gigabytes. You must utilize equipment that meets both today’s and tomorrow’s requirements. The secret is to design your cloud architecture so that the cost and performance scale with your requirements. Popular solutions for dealing with this involve utilizing services and features like load sharing and auto-scaling.
Observability
When something goes wrong, setting up log collection and monitoring can be a wonderful source of information. This does not go far enough, though. You want to know not only whether your system has failures but also the reason for the failure as things get larger and more important. It’s known as observability. Observability is proactive, whereas monitoring is reactionary. This is particularly crucial because there are numerous resources operating and connected to one another in a complex cloud architecture. Popular tools like DataDog and Dynatrace, as well as cloud-native tools like AWS X-Ray, can assist in locating the source of errors and determining their causes. Best practices, such as setting up Slack and email alerts so you’re aware, are another crucial element in this.
Security
You might want certain crucial information and services to remain private. In this case, you must implement access rules that limit access to sensitive resources, isolate them in private cloud networks, set up IP whitelisting and blacklisting or even add Oauth and SSO authentication layers to ensure that they are not accessible via the public internet. Additionally, before implementing any open-source dependencies in production, you should make sure to check them for vulnerabilities. These scans would be a wonderful addition to your CI/CD pipelines. Once again, the services you choose to use and the requirements of your company will determine how you choose to protect things.
Developer effectiveness
The last step in developing your strategy is to configure your system so that engineers can concentrate more on creating new features rather than fretting about how to implement them. You can accomplish this with the aid of crucial DevOps ideas. Infrastructure as code comes first. You will find it simpler to manage multiple environments, such as development, staging and production, as well as spin up new cloud resources as a result. Continuous integration and release comes second. This makes it possible for programmers to automate the deployment of new features as soon as they are created. Choosing the appropriate cloud platforms that don’t complicate the development process is another crucial factor.
We frequently observe businesses making service selection decisions that cause excessive conflict during the development process. One typical example is choosing AWS Lambda over a straightforward cron job operating in an EC2. Certainly, one might be more affordable or simpler to set up initially, but as we’ve already discussed, there are a lot of other difficulties one might run into, and if one is set up improperly, testing it will be difficult and time-consuming for engineers. This ultimately means that even though some services may initially “cost less,” you will ultimately have to spend more in time and engineering hours, resulting in much higher overall costs.
All of these difficulties ought to motivate you rather than frighten you. Modern company operations must include cloud computing. It is still changing, and new technologies like Bitcoin, machine learning and artificial intelligence are enabling businesses to accomplish more. Businesses must overcome the difficulties of implementing cloud applications and enhancing cloud efficiency; if they do so successfully, they will profit greatly from this technology.
