Aperture in Action: How We Solved PostgreSQL Performance Challenges

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Even thirty years after its inception, PostgreSQL continues to gain traction, thriving in an environment of rapidly evolving open-source projects. While some technologies appear and vanish swiftly, others, like the PostgreSQL database, prove their longevity, illustrating that they can withstand the test of time. It has become the preferred choice by many organizations for data storage, from general data storage to an asteroid tracking database. Companies are running PostgreSQL clusters with petabytes of data.

Operating PostgreSQL on a large scale in a production environment can be challenging. Companies have experienced downtime and performance problems, resulting in financial losses and diminished trust, especially if the outages extend beyond a few hours. A case in point is the GitLab database outage in Jan 2017. Though there were many attributes to how this outage happened, to emphasize how overload can play a significant role, in their timeline, they explained how much time it took to control overload happening at that time, which cost them hours to control it.

Implementing Adaptive Concurrency Limits

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Highly available and reliable Services are a hallmark of any thriving business in today’s digital economy. As a Service owner, it is important to ensure that your Services stay within SLAs. But when bugs make it into production or user traffic surges unexpectedly, services can slow down under a large volume of requests and fail. If not addressed in time, such failures tend to cascade across your infrastructure, sometimes resulting in a complete outage.

At FluxNinja, we believe that adaptive concurrency limits are the most effective way to ensure services are protected and continue to perform within SLAs.