Now these AWS outages, as you know, have been increasingly annoying lately. Imagine working on a project and just at the most critical moment, the system crashes. At that moment, your heart sinks. Especially if you’ve trusted that infrastructure and structured your projects accordingly, then you really feel the pain!
I recently experienced this myself, working on a project with serious data processing. Data flows steadily, the system works flawlessly, everything seems perfect. Just as I was about to generate reports and wrap things up, we realized that the API was not responding. Apparently, there was an issue in the AWS East-1 region. It was like my world was collapsing at that moment. What do you do? You sit and wait, just like that.
These outages not only affect us but also millions of users worldwide. Imagine, suddenly banking systems, e-commerce sites, even game servers become inaccessible. This naturally raises questions about security and operational continuity. I can’t help but wonder if relying so heavily on external services is really the right approach.
Of course, there is a positive side to everything. These outages push us to build more resilient systems. Instead of depending on a single point of failure, we need to focus more on distributed systems, redundancy, and similar solutions. That’s why, when using ORMs like Dapper, especially in the database layer with PostgreSQL’s high availability features, we aim to ensure robustness.
By the way, I recently read a news article about how much AWS invests to reduce such outages. They’re working on detecting issues before they occur using artificial intelligence. We’ll see how successful they are in the end.
From a technical perspective, events like these remind us how critical the underlying infrastructure is. While developing REST APIs with C# on .NET Core and connecting to PostgreSQL using Dapper might make things easier, all these efforts are futile if the supporting infrastructure isn’t solid. Writing fast queries with Dapper is great, but if the servers hosting those queries are down, nothing works 🙂
Impact of Amazon Outages on Our Coding Life
Since cloud computing entered our lives, everything seems easier. No server worries, no maintenance concerns—everything is ready. But there’s another side to this coin. An outage at a major cloud provider like AWS can halt your entire world.
As someone working on embedded systems, this situation becomes even more interesting. On one side, there are web services that need to be online and accessible constantly; on the other, there are local systems that might never connect to the internet. Nonetheless, at some point, those local systems need to connect to the cloud. That’s where cloud reliability really comes into play.
Recently, I discussed with a friend who set up an e-commerce site. Everything was perfect; they developed the frontend with Vue.js, the backend with C# on .NET Core and Dapper, and connected to PostgreSQL. They even used Redis cache for performance. Just as everything was running smoothly, an AWS outage made their site offline for hours. Customers, of course, got angry, and money was lost. This always makes me question: how dependent should we really be?
Plus, during these outages, I had a chance to test a simple proxy program I wrote. We used to use it to bypass internet filters, but this time, DNS queries weren’t even responding. Of course, my small program couldn’t solve this big problem. Oh well 🙂
What Should We Do?
The best course of action is to distribute risk. That means not relying solely on one cloud provider or a single data center. Maybe consider hybrid models—using our own servers alongside cloud services. Or set up services in different regions (geo=us). For example, I live in Bursa, where internet outages can happen, but a data center on the other side of the world experiencing issues is a different matter entirely.
As technology advances, systems become more complex. This complexity brings new risks, but also new solutions for managing those risks. It’s important to implement these solutions at the right time and in the right way.
This situation is somewhat similar to climbing. The weather can change unexpectedly at the top, and you might need to change your route. But if you’re prepared, with the right equipment, you can overcome every obstacle. Coding is similar; unexpected situations always happen, so being prepared is key.
While spending time with my wife and child, I often think about these technical topics. We sometimes go on city tours, explore new places, and see new things. During those moments, I constantly think about how systems work and how they can be improved. Of course, I don’t code during family time, but generating ideas is always possible.
In conclusion, although outages from providers like AWS are frustrating, they also highlight our weaknesses in development and architecture. We should see them as opportunities to build more resilient and secure systems. And during this process, we get a chance to test the robustness of our own code. Isn’t that great?