Databases are an essential part of many corporate activities. It’s interacting with consumers in an online store, and access resources on a website. And also using internal software programs. Even the tiniest of database issues can slow down or even shut down operations. The average cost of IT downtime is $5,600 per minute, according to Gartner.
Even small companies can incur expenditures of up to $100,000 per hour of downtime. The bigger businesses might incur costs of more than $1 million per hour of delay. On the other side, slow operations inflict less harm – around one-sixth of the hourly downtime costs are anticipated. But they occur 10 times more frequently. This kind of expense can mount up rapidly, so being able to see it early in the process. Figure out what caused it, fixing it, and keeping it from happening again is invaluable to any organization.
The performance of a database can be affected by a variety of different operations. A wide variety of techniques and procedures are used by many companies. To uncover issues that might affect or cause database performance. If utilized incorrectly, these may look adequate for day-to-day operations. But this can lead to more work and money. Companies should consequently take a close look at their monitoring tools:
Tools for Application Performance Management
Many technologies are available now that make it easier to monitor application performance. And offer a high-level picture of IT infrastructure health. Most users agree that APM tools can lead in the right direction. They are unable to pinpoint the core causes of issues on the data platform. Additional manual data must consequently be gathered to diagnose and ultimately fix issues.
The APM tools don’t always go deep enough into the database to find the core causes of performance issues. Root cause analysis takes longer and is more difficult to carry out in the long run.
Expert DBAs tend to have an extensive library of scripts they’ve either found online or written themselves. To supplement other tools like APM, fill in lacking functionality, or handle ad hoc difficulties, these scripts are commonly utilized.
If the majority of the performance monitoring is done using a script library, there are still certain drawbacks. Because they can only be employed in extremely rare circumstances. After only one use, many programs become redundant. They were only written to address a single problem in depth. However, long-term investments are generally tough to keep up with.
Maintaining the scripts may rapidly become a full-time job as the environment evolves and new technologies are implemented. In light of the minimal possibility that the scripts would offer sufficient granularity and/or historical knowledge to locate the source of the issue, this is an unnecessary amount of work.
Wait times recorded by SQL Server
In SQL Server, a “resource wait time” is accrued by processes waiting for a certain resource to become available. As a result, SQL Server’s wait statistics reveal where severe bottlenecks are developing. Some IT professionals are inclined to rely solely on wait stats to get a sense of their databases’ performance.
When it comes to queries, this might lead to erroneous findings. Like gazing at just one automobile stuck in traffic gridlock, it’s a little disconcerting. Running an automobile is a simple matter of moving it around. However, the truck in front of you is attempting to do a U-turn.
At the absolute least, they provide an excellent starting point for gaining an understanding of the server’s performance profile and identifying potential trouble spots.
Tools for Data Performance Monitoring
Database performance monitoring tools appear to be the best option at first look, as that is exactly what they are meant for. The downside is that if you don’t know how to make the most of them, you’ll find yourself constrained.
In addition, scalability is frequently a problem. The number of servers monitored by a single DPM tool is often limited. In fact that all the data gathered is stored in an SQL Server database presents a bottleneck. Thus, these systems are unable to cope with more than 200-300 SQL servers under monitoring. As a result, a bigger company may require many set-ups to cover all of its servers. Several DPM solutions allow various back-end databases from a single user interface. However, this is very expensive and time-consuming to administer.
So it is critical to ensure that the tools being utilized are performing at their best and delivering the most value. The following factors can be used to determine whether a company’s database monitoring system is effective:
Is there enough depth and precision in the solution to swiftly fix and prevent any issues??
How well can it handle the anticipated increase in data?
Is the solution applicable in every situation?
Is it effective in resolving the issue, or does it raise more questions than it answers?
What about the backers? If something goes wrong, can I get help from seasoned engineers?
It’s important to conduct regular reviews of current solutions to create more effective ones. It guards against the occurrence where solutions appear adequate but ends up resulting in extra costs as a result of delays or failures.