The performance of your applications is a complex, multi-layered puzzle. Performance can be negatively impacted at the application layer or even by remote calls to networked services. However, the most common bottleneck for applications is the data storage layer. The most common data storage tier for applications is a relational database, whose performance can vary widely depending on query optimization.

Imagine every time you visited the service desk to submit a ticket, you were greeted by the boisterous drums from the medley of the Olympics—you’d feel like a gold medalist! Though a theme song may seem far-fetched, rolling out white glove treatment can elevate the service desk in the eyes of your users. Let’s explore how you can land a 10 out of 10 in service delivery by embracing more user-centric service management strategies.

Some classics never go out of style, like a good pair of boat shoes or cowboy boots, depending on where you live. In the logging world, syslog is this classic. For more than 30 years, the syslog protocol has been a standard for logging. When we talk to users about what type of logs they collect and how they send them to SolarWinds ® Papertrail ™ , syslog always comes up. “Our application logs and server system logs are sent to Papertrail.

Experienced SQL Server database administrators and developers spend years learning best practices within SQL Server and how to identify performance pitfalls in the query optimizer. Starting with SQL Server 2017, Microsoft introduced a family of features called “Intelligent Query Processing” to provide more consistent performance for your queries.

Each year, SolarWinds® surveys IT professionals around the world to gauge what’s most pressing on their minds, but also to understand their organization’s challenges and how they intend to overcome them. In 2021, we wanted to know what organizations think of the increasing risks they face from both the reality of supporting the hybrid workplace and the expanding cyberthreat landscape—and how they’ve prepared to address them.

When you issue a query to SQL Server or Azure SQL, it internally tries to optimize a query plan through calculations such as whether to use an index. Much of SQL Server’s query plans are based on its best guess of what will happen at run time when your query executes. Even when SQL Server guesses right, as your data changes (especially as the volume of data increases), optimal plans can end up performing so poorly, they can drag your whole system’s performance down.

An important skill in database performance tuning is capturing, reading, and understanding query execution plans. The query execution plan is a roadmap of the resources allocated and operations performed when the database engine gathers the results of your query.