My experience as a backend engineer has been nothing short of interesting. Throughout my career, I've worked in various fields, ranging from e-commerce to fintech, and I have been faced with numerous challenges. There have been days when I've celebrated small victories, like squashing pesky syntax errors that seemed to elude me for hours. On other days, I've faced heart-pounding moments where critical bugs threatened to bring down entire systems. The adrenaline rush of troubleshooting production issues at 2 AM, knowing that every second counts, is an experience that only a fellow backend engineer can truly understand. Among the many challenges, one particular issue stands out: the task of optimizing endpoint speeds on a server. I remember the first time I encountered this issue—our users were experiencing significant delays, and it was up to me to find a solution.
To tackle this, I started by tracking response times. I noticed that some queries, albeit non-resource-intensive, were taking as long as 20 seconds to complete. I further deduced that the majority of the endpoints experiencing this problem had services making multiple write requests to the database, and extensive read queries from multiple records. This analysis helped pinpoint the problematic areas and provided a clear understanding of where improvements were needed.
The next crucial step was optimizing our database queries. I set up indexing which ensured that frequently accessed data could be retrieved more efficiently. Indexes allowed the database to locate the needed data without scanning the entire table, which significantly reduced execution times. Additionally, I optimized the queries themselves by refining the SQL statements to be more efficient. This included reducing the complexity of joins, eliminating unnecessary subqueries, and using more efficient data retrieval methods.
Furthermore, I implemented query caching strategies with Redis to store the results of frequent queries in memory. This allowed for rapid retrieval of data without repeatedly hitting the database, thus minimizing load and reducing latency. These combined efforts in optimizing the database queries not only improved the performance of individual queries but also enhanced the overall efficiency of our system, leading to faster response times and a better user experience.
One of the reasons I love what I do is because I see growth and steady progress in my career. I have observed a significant improvement in my skills, taken on projects I wouldn't have thought possible earlier in my career, and I feel that my future holds even more potential. Recently, I joined the HNG Internship. I'm nervous, yet excited about the opportunity to learn and grow in this environment, and I believe that this internship will further contribute to my professional development. I'm looking forward to gaining valuable experience, meeting amazing professionals, and unlocking new career opportunities. In the coming weeks, I'll delve into the tasks and challenges that await me during the HNG11 internship. I am eager to see what lies in store for me. Thanks for reading!
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