Black Friday is coming up, and you're probably wondering whether your e-commerce application is fast enough to handle that workload. These 4 tools will help you monitor and improve your website's and database's speed, to better convert your users into customers.
A friend of mine who runs an e-commerce website in Germany told me he had to let go of a software engineer because his code didn’t run "fast enough." Yep, he wasn’t the strongest developer on his team but my friend really wished he had the time and tools to help him mentor them to write faster code.
These days it isn’t easy to be a software engineer or an analyst. Customers don’t have patience and if an app or a website doesn’t respond within milliseconds, they will stop using it and will move on to the next e-commerce site. Brand loyalty almost doesn’t exist.
If you are an analyst or an engineer that works with a large databases, you should consider the following tools and methods:
- Pingdom - Pingdom helps you gain instant insights into your website’s availability and performance so that you can monitor your end-user experience.
- Slow logs - Enable slow logs in your database - most of the databases allow you to run the system in a diagnostic mode, so you can get a log called slow query log. This log will show you the queries that takes most of the time and resources. The downside of this tool is that slow log doesn’t recommend you on how to fix these slow queries.
- Percona Monitoring and management - If you don’t have in-house DBAs, Percona PMM may be a good tool for you. Percona PMM is an open-source relational database management system that helps you monitor and diagnose your database, to help you understand where are the bottlenecks.
- EverSQL query optimizer - EverSQL is a tool that helps you to fix slow queries in an automated way as if you had a team of DBAs sitting next to you and reviewing your SQL queries. EverSQL enables you to upload complex queries or your entire slow log file and in return, you will receive new faster queries and recommendations for optimal database indexes.