Scalability issues (results, how to prevent, how to fix)
One of the pain points for many IT startups is the inadequacy of their infrastructure for scaling. In the absence of scalability, any sudden increase in traffic or a DDoS attack, often unforeseen, can lead to server downtime, slow response times, or even prolonged service outages. It causes client dissatisfaction and affects the project’s reputation and team, which can incur significant losses.
To ensure infrastructure scalability, it’s essential to implement tools specifically designed for scaling and the automated orchestration of containerized code. Cloud services configured in advance significantly simplify this task. If configuring container orchestration with Kubernetes is not feasible but scalability is crucial, using Cloud Kubernetes as a Service (KaaS) or AWS Fargate and GKE Autopilot is preferable to Docker with a plethora of non-standard, often custom utilities that do not guarantee stability in production conditions and prolonged high-load.
Scalability issues can extend beyond infrastructure to impact databases. If developers haven’t accounted for the application’s ability to work with a load balancer and multiple replicas of the database concurrently, the database’s performance under a high volume of simultaneous queries becomes unstable, leading to potential failure. Vertical scaling is an option, but it shouldn’t be overestimated. Vertical scaling towards increasing the server’s database power does not occur automatically and requires migration time. Moreover, the temporary and random nature of traffic spikes demands overpaying for often unnecessary capacities.
In most cases, replication and load balancing are the preferred methods of database scaling, especially if database replicas are distributed across different hosts. However, establishing an effective database balancing and replication scheme is not efficient without scaling the infrastructure. It’s crucial to address these aspects comprehensively.
Another issue indirectly related to scalability in startup infrastructure is the lack of monitoring coverage and log processing, even for critical processes. The earlier a monitoring system is set up, and the more comprehensive it is, the quicker and more efficiently problems can be identified, resolved, and prevented.
These three crucial scalability directions: load balancing and infrastructure scaling; database replication; and configuring a log processing and monitoring system for critical infrastructure processes — prevent service failures due to overloads in high-load conditions. Rectifying architectural shortcomings in an already established infrastructure or reworking its mechanisms takes much longer. It is more expensive than planning for scalability using cloud platform orchestration tools and services from the outset. This might require slightly larger initial investments, but these investments will pay off through stable performance during excessive loads, bringing long-awaited profits to your business and preserving its reputation.
