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Application Performance Starts with the Database

Gerardo Dada

Whether they know it or not, every department, group or function within a business, from marketing to sales to the executive leadership, relies on a database in some way or another.

How? Applications are the heart of all critical business functions and an essential component to nearly every end user’s job, affecting productivity, end user satisfaction and ultimately revenue. In fact, in a recent SolarWinds survey of business end users, 93 percent of respondents said application performance and availability affects their ability to do their job, with 62 percent saying it is absolutely critical.

And at the heart of nearly every application is a database.

This means when an application performance or availability problem arises — something end users have little patience for (67 percent of end users also said they expect IT to resolve such issues within an hour or less) — there’s a good chance it’s associated with the underlying database’s performance. So, to not only keep end users happy, but productivity and revenue humming, application performance should be a paramount concern, and database performance must be a key element of that concern.

As validation of this point, another SolarWinds survey found that 71 percent of IT pros agree that a significant amount of application performance issues are related to databases and that application performance should start with the database. In addition, 71 percent also said application response time is a primary challenge they are trying to solve by improving database performance.

Why? There are three primary reasons. First, database engines are very complex — from complex queries and execution plans to replication and the inner workings of the database.

Second, there is a shortage of skilled performance-oriented database administrators (DBAs) in the market, resulting in many “accidental DBAs”.

Finally, compute and network resources can easily scale vertically or horizontally with today’s virtualization and cloud technologies, the same cannot be said for databases.

If you’re experiencing database-related application performance issues, or simply want to improve application performance by optimizing underlying databases, you should consider the following tips.

1. Get a full view of the application stack

The days of discrete monitoring tools are over. The use of tools that provide visibility across the entire application stack, or the application delivery chain comprised of the application and all the backend IT that supports it — software, middleware and extended infrastructure required for performance, especially the database — is a must in today’s complex, highly interconnected IT environment.

2. Be proactive and align the team behind end user experience

No one likes fighting fires. One way to minimize them is to be proactive and look at performance continuously, not only when it becomes a major problem. The entire team supporting applications should understand end user experience goals in terms of page-load and response times so it becomes a shared objective with very concrete business impact. Without a scoreboard everyone can see, it’s hard to know if you are winning.

3. Stop guessing

It’s not uncommon to default to adding hardware to hopefully improve performance — for example, switching to SSD drives. However, this is a gamble that has cost more than a few people their jobs. If the bottleneck is memory or a really bad SQL query, investing in SSD drives is unlikely to improve application performance.

4. Go beyond traditional monitoring

Most traditional monitoring tools focus on health and status, providing many charts and a lot of data, most of which is hard to interpret and time consuming to tease out performance insights from. Instead, tools with wait-time analysis capability can help identify how an application request is executed step-by-step, and what the processes and resources are that the application is waiting on. It provides a different view into performance, one that is more actionable than traditional infrastructure dashboards.

5. Establish baselines

It’s important to establish historic baselines of application and database performance that look at how applications performed at the same time on the same day last week, and the week before that, to detect any anomalies before they become larger problems. By so doing, if a variation is identified, it’s much easier to track the code, resource or configuration change that could be the root cause.

6. Get everyone on the same page

Today’s complex applications are supported by an entire stack of technologies that is only as good as its weakest link. And yet, most IT operations teams are organized in silos, each person or group supporting a part of the stack. To avoid finger pointing, get every team in the organization a unified view of application performance, ideally based on wait-time analysis, so everyone can focus on solving application problems quickly.

As the backbone of nearly all business-critical applications, the impact of database performance on application performance cannot be underestimated. Following these tips can help eliminate many potential bottlenecks.

Gerardo Dada is VP Product Marketing and Strategy at SolarWinds.

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Application Performance Starts with the Database

Gerardo Dada

Whether they know it or not, every department, group or function within a business, from marketing to sales to the executive leadership, relies on a database in some way or another.

How? Applications are the heart of all critical business functions and an essential component to nearly every end user’s job, affecting productivity, end user satisfaction and ultimately revenue. In fact, in a recent SolarWinds survey of business end users, 93 percent of respondents said application performance and availability affects their ability to do their job, with 62 percent saying it is absolutely critical.

And at the heart of nearly every application is a database.

This means when an application performance or availability problem arises — something end users have little patience for (67 percent of end users also said they expect IT to resolve such issues within an hour or less) — there’s a good chance it’s associated with the underlying database’s performance. So, to not only keep end users happy, but productivity and revenue humming, application performance should be a paramount concern, and database performance must be a key element of that concern.

As validation of this point, another SolarWinds survey found that 71 percent of IT pros agree that a significant amount of application performance issues are related to databases and that application performance should start with the database. In addition, 71 percent also said application response time is a primary challenge they are trying to solve by improving database performance.

Why? There are three primary reasons. First, database engines are very complex — from complex queries and execution plans to replication and the inner workings of the database.

Second, there is a shortage of skilled performance-oriented database administrators (DBAs) in the market, resulting in many “accidental DBAs”.

Finally, compute and network resources can easily scale vertically or horizontally with today’s virtualization and cloud technologies, the same cannot be said for databases.

If you’re experiencing database-related application performance issues, or simply want to improve application performance by optimizing underlying databases, you should consider the following tips.

1. Get a full view of the application stack

The days of discrete monitoring tools are over. The use of tools that provide visibility across the entire application stack, or the application delivery chain comprised of the application and all the backend IT that supports it — software, middleware and extended infrastructure required for performance, especially the database — is a must in today’s complex, highly interconnected IT environment.

2. Be proactive and align the team behind end user experience

No one likes fighting fires. One way to minimize them is to be proactive and look at performance continuously, not only when it becomes a major problem. The entire team supporting applications should understand end user experience goals in terms of page-load and response times so it becomes a shared objective with very concrete business impact. Without a scoreboard everyone can see, it’s hard to know if you are winning.

3. Stop guessing

It’s not uncommon to default to adding hardware to hopefully improve performance — for example, switching to SSD drives. However, this is a gamble that has cost more than a few people their jobs. If the bottleneck is memory or a really bad SQL query, investing in SSD drives is unlikely to improve application performance.

4. Go beyond traditional monitoring

Most traditional monitoring tools focus on health and status, providing many charts and a lot of data, most of which is hard to interpret and time consuming to tease out performance insights from. Instead, tools with wait-time analysis capability can help identify how an application request is executed step-by-step, and what the processes and resources are that the application is waiting on. It provides a different view into performance, one that is more actionable than traditional infrastructure dashboards.

5. Establish baselines

It’s important to establish historic baselines of application and database performance that look at how applications performed at the same time on the same day last week, and the week before that, to detect any anomalies before they become larger problems. By so doing, if a variation is identified, it’s much easier to track the code, resource or configuration change that could be the root cause.

6. Get everyone on the same page

Today’s complex applications are supported by an entire stack of technologies that is only as good as its weakest link. And yet, most IT operations teams are organized in silos, each person or group supporting a part of the stack. To avoid finger pointing, get every team in the organization a unified view of application performance, ideally based on wait-time analysis, so everyone can focus on solving application problems quickly.

As the backbone of nearly all business-critical applications, the impact of database performance on application performance cannot be underestimated. Following these tips can help eliminate many potential bottlenecks.

Gerardo Dada is VP Product Marketing and Strategy at SolarWinds.

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...