Have you ever wondered what happens after your application or platform goes live? Traditionally, support is one of the most crucial challenges in the post-launch stage. This is the moment when the true robustness and quality of your system is revealed.
At Imagine Apps, we always recommend and perform load testing and quality testing as preventive measures. However, once the platform is live, the appearance of an error can trigger a process that, to be honest, is quite frustrating for everyone involved.
The traditional path to fixing an error
When an issue appears, the path to solving it typically goes through the following stages:
Diagnosis: Identifying what is happening and, most importantly, where it’s happening. Surprisingly, this is often the most time-consuming phase. It involves replicating the error, reviewing logs, or analyzing the developer’s local environment.
Proposing Solutions: Hypotheses are formed regarding the root cause, and the impact of each potential fix is evaluated to determine the best course of action.
Experimentation and Testing: This is where the chosen solution is implemented and rigorously tested in development or local environments to ensure it behaves as expected.
Deployment (Hotfix): Once validated, the correction is deployed to the production environment.
Depending on the complexity of the error, this entire cycle can take anywhere from several hours to multiple days.
The impact of observability: From reactive to proactive
This is where observability changes the game. Instead of waiting for errors to occur — and for users to report them — observability provides a proactive system that alerts you when, where, and with what impact something has failed in your application.
Consider a common use case for a marketplace like the ones we build at Imagine Apps: payments. If the billing system fails, you simply stop selling. It’s the equivalent of closing your business doors for an unknown number of hours.
An observability platform like Grafana allows you to detect and fix these issues quickly, accelerating the deployment of the solution into production. This reduces correction times from days to hours — and in many cases, even minutes.
What do you need to implement an observability system?
Willingness: Haha! Yes, the first step is being committed to improving your processes.
Good Error Handling in Your Code: Everything starts with code that properly logs and manages failures.
Log Storage Policies: It’s essential to establish rules for saving logs and optimizing storage costs. For example, you probably don’t need error logs from several weeks ago.
Implementation and Configuration: You’ll need a process to set up the tools, define alerts, and establish the normal operating thresholds for your system.
If this resonates with you and you’re looking to optimize your application support, we’re ready to explore how we can help.
