Last page insert contention is common in a busy SQL Server environment where multiple users are inserting data simultaneously in a table and that table has clustered index on a identity column. When multiple sessions try to add data in the same data page file, the data page becomes "hotspot". As a result, processes queue up to acquire access to the last page, which leads to latch contention, high wait times, and overall reduced throughput.
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As DBAs, we all know how frustrating deadlocks can be. One moment everything looks fine, and the next, SQL Server decides to kill a perfectly good query just to break the deadlock cycle. Hunting down the cause often means digging through error logs, setting up Extended Events, and piecing together XML deadlock graphs that feel more like puzzles than solutions.
That is where sp_BlitzLock comes to the rescue. It takes the pain out of deadlock analysis by reading deadlock graphs for you and turning them into a clear, easy-to-understand report. Instead of spending hours trying to figure out who blocked whom, you get a straightforward breakdown of the queries, resources, and victims involved. In short, sp_BlitzLock makes a DBA’s life much easier when dealing with deadlocks.
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In the world of SQL Server, ensuring data consistency, and concurrency is critical — but it often comes with challenges like locking, blocking and deadlocking. These negatively impact on performance. As databases grow in size and usage, understanding how SQL Server handles concurrent data access becomes essential for any DBA.
In this first part of the series, we will dive deep into the core concepts of locks and blocks, explore how they work, and examine why they occur. Through real-world examples and practical scripts, this article aims to equip you with the knowledge to identify, analyze, and handle common blocking scenarios. Mastering these fundamentals will prepare you for the more complex topic of deadlocks, which we will cover in Part 2.
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As a human being, your SQL Server tries to express its pain point with you — but not in words. It whispers through wait stats, sending subtle signals when something is off. But, you have to learn how to decode these signals.
In this article, we will decode the most common SQL Server wait types—like CXPACKET, PAGEIOLATCH, and SOS_SCHEDULER_YIELD—and understand what they are quietly telling you about your server’s workload, health, and bottlenecks. If you have ever wondered why your queries slow down despite healthy hardware, the answer might just be in these whispers.
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As a DBA, you are often alert to the usual suspects—blocking, deadlocks, or long-running queries. But sometimes, performance issues creep in silently, and one of the quietest yet most impactful culprits is latch contention. Unlike locks, latches are lightweight synchronization primitives that protect internal memory structures. When these get overwhelmed, even the most well-tuned queries can slow to a crawl.
In this guide, you will explore what latch contention is, how it differs from locks, when it occurs, how to detect it, and most importantly—how to tune your system to minimize its impact. Whether you are running a high-throughput OLTP workload or managing a reporting environment, understanding latches could be the missing piece in your performance puzzle.
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In the world of SQL Server performance tuning, intuition is helpful—but data is essential. Without a solid performance baseline, DBAs are left guessing whether a system slowdown is an anomaly or just another busy working day. Creating a baseline gives you a point of comparison to understand what "normal" looks like for your SQL Server environment. This article will guide you through what to capture, how to capture it, and how to turn that information into actionable insight—so the next time someone says, "the database is slow", you will have data to prove or disprove it.
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In today’s data-driven environments, SQL Server performance is not just about fast queries, efficient indexes — it also heavily depends on how well your database communicates over the network. Whether it is a slow application response, timeout errors, or replication delays, the network often plays an invisible but critical role. As DBAs, we tend to focus on CPU, memory, and disk — yet overlooking network performance can leave significant bottlenecks unresolved.
This guide will walk you through essential network-related metrics, troubleshooting techniques, and tuning tips to ensure your SQL Server operates smoothly. Let’s decode what is happening between your servers — and keep the data flowing efficiently.
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When it comes to SQL Server performance, disk I/O is often one of the most critical and overlooked components. While CPU and memory get much of the spotlight, the underlying storage subsystem plays a foundational role in how efficiently SQL Server can read and write data. Slow or misconfigured disk I/O can lead to query bottlenecks, long transaction times, and degraded user experience—especially under heavy workloads.
This guide helps DBAs understand how SQL Server interacts with storage, how to monitor disk I/O, and how to optimize it for better performance. From key metrics to practical tuning tips, you will gain the insights needed to keep your SQL Server running smoothly at the storage layer.
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I was reviewing my index rebuild and recreate activities. Some index rebuilding tasks are scheduled once or twice a week. I followed the best practices for the activities. However, it was not yielding expected performance gain. So, wondering what could be going wrong! Are there any hidden issues hindering the performance? I kept searching for potential clues in my favourite SQL Server gurus writing and compiled the hidden facts. Let's share my findings with you.
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When it comes to SQL Server performance tuning, few settings spark as much debate as MAXDOP—Maximum Degree of Parallelism. This small but powerful configuration controls how many processors SQL Server can use to execute a single query in parallel. While parallelism can speed up queries, it can also lead to unexpected issues like CPU pressure, query blocking, or inconsistent performance across workloads.
In this article, we will explore what MAXDOP really does, why it matters, and how to configure it wisely to strike the right balance between speed and stability in your SQL Server environment.
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