Kinesis Network Saves Costs

In recent years, serverless computing has emerged as a transformative approach to running applications and workloads in the cloud. This model shifts responsibility for infrastructure provisioning and management from the end user to the cloud provider. In this post, we are exploring how Kinesis Network with its serverless architecture saves costs.

1. Over-Provisioning and Idle Capacity

One of the most notable causes of waste in an instance-based computing model is over-provisioning. When organizations provision specific virtual machines or containers, they frequently allocate more resources—CPU, memory, or storage—than the application actively needs. This over-allocation often aims to ensure enough capacity is available for peak usage, even if those peaks only occur sporadically. Unfortunately, during low-traffic intervals, these resources remain largely underutilized, creating wasted capacity. Our experience has shown us that a large portion of instances see less than 20% utilization on average, sometimes as bad as only 1%. In contrast, a serverless environment scales automatically based on demand. The Kinesis Network spins up or tears down resources as needed, eliminating over-provisioning and shrinking the idle footprint significantly.

2. Pay-For-Idle vs. Pay-Per-Use

Hand-in-hand with over-provisioning is the pay-for-idle model inherent in instance-based services. Organizations pay for entire virtual machines regardless of whether they are actively processing tasks or sitting idle. This can be a significant cost drain for applications with unpredictable traffic or infrequent usage patterns. By contrast, Kinesis services follow a pay-per-use billing model. This means that costs accrue only when the application processes requests. With no fixed cost for idle time, developers can benefit from substantial cost savings, making serverless the more financially efficient option.

3. Operational Complexity

In an instance-based model, DevOps teams are responsible for provisioning, configuring, patching, and maintaining virtual machines. This operational complexity often leads to less predictable results and potential inefficiencies. Each instance must be monitored, and scaling must be managed carefully. This level of manual oversight not only consumes time and resources but also increases the likelihood of human error. In our serverless architecture, Kinesis Network handles most of these operational responsibilities—provisioning, scaling, fault tolerance, and more. The result is less overhead in terms of both personnel and budget, leading to a more focused environment where developers can prioritize core business logic.

4. Environmental Impact

The wasteful nature of running underutilized or idle virtual machines has broader implications beyond cost. Modern data centers require substantial energy resources to power servers and maintain cooling systems. When capacity is over-allocated, these underutilized servers continue to consume power, leaving a significant carbon footprint. Kinesis Network, with its on-demand approach, reduces total operating hours of hardware. Because Kinesis Network allocate resources dynamically, computing resources remain dormant until needed, cutting down on energy usage and subsequent environmental impact.

5. Flexibility and Agility

From a software development perspective, serverless computing enables agile development. Functions can be deployed quickly without detailed infrastructure management, allowing teams to iterate faster. In an instance-based setup, teams must often navigate lengthy processes to provision and configure additional instances or adjust the size of existing ones. This overhead can stifle innovation and extend deployment cycles. In contrast, Kinesis Network streamlines these processes, ensuring teams can rapidly experiment, test, and roll out new features with fewer constraints—and less waste.

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Despite these advantages, it's important to note that serverless computing isn't a silver bullet for all workloads. Long-running processes or applications with consistent, predictable loads might still benefit from instance-based deployments. However, for the vast majority of modern applications with variable workloads, serverless architectures offer a more environmentally sustainable approach to cloud computing.