Introduction Link to heading

Cloud computing has grown from its initial concept of offering software over the internet into a vast array of services and infrastructure options for businesses, developers, and individuals to create custom solutions. Despite its maturity, misconceptions, poor practices, and less-than-ideal usage of cloud computing persist. It’s crucial to understand how cloud computing can be advantageous and recognize scenarios where it might not deliver as much value.

Consider the setup of typical enterprise software today. The once-common “fat-client” installations on local PCs have given way to web applications accessed through browsers. The backend usually consists of an application server and a database. This configuration works well initially, but challenges arise when the software becomes critical to operations, user load increases, or it needs to support activities across different time zones. The difficulty in scheduling maintenance, the impact of outages, and the need for high availability become more pressing issues to address. Backend morphs from single server to a micro-services. Queues start popping up. Event streams, object storages, integrations, and so on. The complexity of the system grows exponentially. As demand and the need for high availability rise, companies typically scale their infrastructure. They might start by adding extra application servers and a load balancer to distribute the workload. This improves availability, but soon the database or multiple databases start to struggle with the load.

Investing in a more robust database servers, virtualiztion is next step, but this also introduces the risk of having a single point of failure. To mitigate this, database replication and investment in storage area network (SAN) switches and disk systems follow, along with additional licensing costs. This duplication can provide peace of mind until an unforeseen event, like a power outage, reveals that the data center itself wasn’t redundant. How should companies handle this?

This leads to a cycle of problem-solving meetings and the eventual decision to build or more commonly lease a new data center, a project that requires specialized knowledge and a significant investment. After construction, distributing services between the two centers is another complex task. MPLS lines, routing… The amount of specialized skills keeps increasing. DBAs, developers, project managers, security experts and network specialists. Headcount and costs increases. What once was an IT budget of thousands can quickly escalate to millions. With this growth comes increasing complexity, slowing down development and innovation. The company is now spending more time and money on maintaining the status quo than on developing new features and products.

Navigating the world of IT can be quite complex. You might deal with international operations, backup systems spread across multiple regions, data replication, network routing, content delivery networks, dedicated communication lines, and various types of network technology. On top of the technical setup, there’s a web of contracts, licenses, service level agreements (SLAs), and more.

But the challenges aren’t just technical. Different departments within an organization can have cultural clashes, divergent goals, and even incentive systems that encourage conflicting outcomes. The IT department may aim for standardization and control, while the business side pushes for innovation, new applications, and wants to leverage data across different systems. IT might be cautious about rapid changes, whereas the business side is often frustrated by slow progress.

Often, irrational fears and a lack of knowledge can hinder progress. Additionally, businesses and individuals may focus on the less important aspects of cloud computing. To illustrate, let’s examine a few examples.

Costs and cost savings Link to heading

Cost calculations in cloud computing are often misleading because they don’t always represent the full picture. Comparing on-premise to cloud costs is frequently flawed due to several reasons:

  • Initial vs. Ongoing Expenses: On-premise infrastructures have significant upfront costs for hardware, software licenses, and facilities. These are capital expenditures (CapEx). Cloud services usually operate on a pay-as-you-go model, which is an operational expenditure (OpEx). Comparing CapEx to OpEx directly is like comparing the cost of buying a car to renting one; the expenses accrue differently over time.

  • Scaling Costs: With on-premise solutions, scaling up requires purchasing additional hardware and may have a delay due to setup and deployment. In cloud computing, scaling can be almost instantaneous and is often more cost-effective at smaller scales, but it can become expensive as you scale up or if not managed properly.

  • Maintenance and Upgrade Costs: On-premise solutions require ongoing maintenance, staff, and periodic upgrades, which can be costly and difficult to predict. In contrast, cloud services include maintenance and upgrades in their subscription cost, making them more predictable but often underestimated when planning budgets.

  • Utilization and Efficiency: On-premise hardware often has fixed capacity, leading to underutilization or overprovisioning “just in case.” Cloud resources can be adjusted to match demand more closely, potentially offering better cost efficiency, but this requires active management and monitoring to avoid overuse.

  • Indirect Costs: There are numerous indirect costs associated with on-premise solutions, such as power, cooling, and physical security, which are often overlooked in comparisons. Cloud computing typically includes these in the service cost.

  • Labor Costs: The expertise required to manage on-premise solutions can be more costly in terms of labor than cloud services, which offer a more managed environment. However, cloud environments also require expertise, particularly for complex configurations and cost optimization, which can lead to unexpected expenses.

  • Business Continuity and Disaster Recovery: Implementing robust disaster recovery and business continuity plans on-premise can be prohibitively expensive. Cloud providers generally offer these services, which can be more cost-effective but may still require additional spending to meet specific business requirements.

  • Flexibility and Opportunity Costs: The flexibility of cloud computing can lead to faster deployment and more innovative and agile development of services and products, which has an opportunity cost that is often omitted from comparisons. On-premise solutions might inhibit agility, impacting the business’s ability to adapt to market changes quickly.

Overall, a direct cost comparison between on-premise and cloud computing can be flawed without considering all the factors that affect long-term expenses. This doesn’t mean that cloud computing is always more cost-effective, but it’s essential to understand the full picture before making a decision.

Agility and development speed Link to heading

Cloud services can significantly accelerate development speed and enable engineers to achieve more with less for several reasons:

  • Managed Services: Cloud providers offer a very wide variety of managed services such as databases, machine learning, analytics, and container orchestration, workflows and storage. These services reduce the time engineers spend on setup, maintenance, and scaling of infrastructure, allowing them to focus on writing application code and business logic.

  • Automation and Integration: Cloud platforms often come with tools that support automation of deployment, scaling, and management processes. This integration reduces manual overhead and the potential for human error, increasing the efficiency of development workflows.

  • Scalability: Cloud environments can be scaled up or down with ease, which means that engineers don’t need to spend time planning and implementing scaling strategies. This elasticity allows them to experiment more freely and adapt quickly to changing demands without worrying about capacity planning. It also reduces the risk of overprovisioning, which can lead to wasted resources.

  • Global Reach: Cloud services are usually distributed across the globe, enabling engineers to deploy applications in multiple regions. This eliminates the need for complex network setups and negotiations with local hosting providers, thus speeding up the process of going global.

  • DevOps and Continuous Integration/Continuous Deployment (CI/CD): The cloud facilitates DevOps practices by providing a suite of tools for continuous integration and continuous deployment. Computing environments can be expressed as code and setup can be completely automated. These practices promote more frequent and reliable releases, reducing the development cycle time.

  • Collaboration and Accessibility: Cloud platforms enhance collaboration by allowing engineers to access the environment from anywhere, making it easier to work together and share resources across teams, regardless of location. Hardware failures are handled by the cloud provider, reducing the need for on-call rotations and allowing engineers to focus on development.

  • Innovation: With access to the latest technologies and services in the cloud, engineers can explore new approaches like serverless architectures. Abstraction level increases. This can lead to innovation and the creation of solutions that were not feasible with traditional infrastructure.

  • Cost-Effectiveness: Since cloud services operate on a pay-as-you-go model, engineers can provision exactly what they need without upfront investments. This cost structure can lead to more efficient use of resources and lower financial barriers to experimenting with new ideas. However, it can also lead to unexpected expenses if not managed properly and very stable and predictable workloads can be more cost-effective on-premise. It’s important to understand the cost structure of cloud services and how to optimize it.

  • Security and Compliance: Cloud providers invest heavily in security and compliance measures. By leveraging these investments, engineers can ensure that applications are secure and compliant with less effort than would be required to achieve the same standards on-premise. However, it’s important to understand the shared responsibility model and how to configure security settings properly.

By using cloud services, engineers can develop applications and features faster. Faster development allows organizations to react to market changes more swiftly and spend more time on creating value rather than managing infrastructure. This leads to a more productive use of engineering talent and potentially a smaller team accomplishing what would require a larger and perhaps multiple team in a traditional setup.

Conclusion Link to heading

It’s important to acknowledge that the public cloud isn’t a one-size-fits-all solution. While on-premise computing is becoming increasingly specialized, there are specific scenarios where using a public cloud may not be suitable nor cost-effective.