What do you do if your boss is unhappy with your database performance?

Boss would be unhappy when an escalation happens. If it happens, listen to your boss carefully, identify the gaps, get into the call with the customer and clear the ask and expectation. Once done with the ask, if something is out of your scope like hardware upgrade, disk issues etc., communicate clearly and redirect customer to the right team. If it's indeed database issue, work on it- check for table stats, missing indexes, duplicate & unused indexes, stored procedures recompilation, cpu and memory usage and settings, other system config and parameters, wait stats, if needed set an extended events or traces to capture the events. Ensure you collect enough info and troubleshooted, discussed with your boss before presenting it to customer.

it’s important to systematically assess and address the issues. Gather information about the specific performance issues being observed. Is it slow query response times, high CPU usage, or something else? Use tools to monitor the database management system and the applications accessing it to find problems as they arise. Keep your boss updated throughout the process, and ensure that you’re addressing the specific concerns they have raised.

First of all you must check top waits in your database. sometimes it comes from network issues, then you should check it by network admin. sometimes it comes from disk(i/o) or latch(i/o), maybe your indexes got fragmented, then you should rebuild or reorganize them. sometimes it comes from memory allocation and you are under memory pressure, in this situation maybe your statistics are not optimal and you should update them. And so on...

If your boss is unhappy with your database performance first, acknowledge their concerns and gather specific feedback on the issues. Analyze the performance metrics to identify bottlenecks, such as slow queries, inefficient indexing, or hardware limitations. Prioritize tasks by addressing the most critical issues first. Optimize queries by refining SQL, adding or updating indexes, and reviewing execution plans.Consider database tuning techniques, like partitioning large tables or adjusting memory allocation. Communicate your action plan and progress to your boss regularly. Additionally, explore upgrading hardware or migrating to more efficient database solutions if necessary. Continuously monitor performance and adjust strategies as needed.

Keep your boss informed about what you've found and your strategy for addressing the issues. Providing regular updates can help manage expectations and demonstrate proactive engagement.

We create an action plan where we propose to have separate files per hard disk, tempdb on one disk, logs on another, database on another, operating system on another and backups on another, this ensures that the speed of reading and writing will not be compromised.

Se debe fijar una unidad de criterios en función de los requerimientos y evaluar las solicitudes a fin de establecer una comunicación mas eficiente en función del problema a resolver

Report Findings: Communicate your initial findings to your boss and stakeholders. Explain the issues you’ve identified and how they affect the overall performance. Outline the Plan: Present a clear plan of action to address the performance issues. Ensure your boss understands the steps you will take and the expected timeline for improvements.

First you need to find slow queries, in sql server you can find them by enabling and configuring query store or creating an new extended events session. After finding queries, you need to see their execution plans, and find bottlenecks in query such as reading unnecessary columns join or where clause on unindexed columns or using unnecessary sorts and so on...

Analyze Slow Queries: Use query performance tools to identify which queries are running slowly. Look for long-running queries, queries that are run frequently, and queries that use a lot of resources. Use Indexes Effectively: Ensure that your tables are properly indexed. Indexes can greatly improve query performance by allowing the database to find data more efficiently. Optimize Query Structure: Rewrite queries to be more efficient. For example, use joins instead of subqueries where appropriate, and ensure that the joins are using indexed columns. Avoid Selecting Unnecessary Data: Be specific about the data you need. Instead of using SELECT *, specify only the columns you actually need to reduce the amount of data processed.

Review and optimize the SQL queries being used. Look for inefficient queries that can be rewritten, and consider indexing strategies to speed up data retrieval.

I differ a little if we do not configure the server to optimize will not make sense, because if we have on the same hard drive all the files that mecionen above will be slow because we will have a bottleneck in writing and reading, so optimize queries requires even creation of indexes which subsequently require maintenance plans that should be executed and consume processing the database tempdb which if this on the same disk as the database logs and operating system will be a slow process Translated with DeepL.com (free version)

dependiendo de la cantidad de información de la base de datos en uso y teniendo siempre en cuenta las tablas de mas movimientos generalmente hay consultas que debido al uso de muchas tablas en una misma consulta hace que se haga mas lenta, para esto recomiendo trabajar sobre búsquedas encadenadas mas peque?as a fin de aligerar el proceso

If hardware limitations are impacting performance, propose upgrading your database servers. Increasing RAM, using faster storage solutions, and improving network capabilities might be necessary.

Generalmente cuando se depende de un solo servidor habrá que mejorar el file system, ya que este problema se nos presento en una oportunidad cuando se enviaba a imprimir bloques grande de nomina

Evaluate Current Hardware: Assess whether the current hardware meets the demands of your database workload. Consider Upgrades: If necessary, propose hardware upgrades such as more RAM, faster CPUs, or SSD storage to improve performance.

You must have routine jobs to every day check: -indexes fragmentation and if necessary rebuild or reorganize indexes. -statistics deprecations in if your statistics are out of date then update them.

Establish routine maintenance practices such as updating stats, rebuilding indexes, and cleaning up old data to keep the database running smoothly.

Database Maintenance: Perform regular maintenance tasks such as updating statistics, defragmenting indexes, and cleaning up unused space. Scheduled Downtime: Plan maintenance during off-peak hours to minimize disruption.

Assess Current Performance: Start by assessing the current performance of the database. Use monitoring tools to identify bottlenecks and areas that need improvement. Update Statistics: Ensure that the database statistics are up-to-date. These statistics are crucial for the database optimizer to make informed decisions. Analyze Queries: Review and analyze the most resource-intensive queries. Look for ways to optimize them for better performance. Index Management: Evaluate the use of indexes. Remove any unused indexes and consider adding new ones that could improve performance.

Utilize tools and techniques for performance tuning. Adjust configurations, fine-tune server settings, and consider partitioning data to improve performance.

1) Enable Query Store: We will enable Query Store for all relevant databases. 2) Identify Poor-Performing Queries: We will analyze the data captured by Query Store to identify queries that exhibit poor performance metrics such as high execution times, CPU usage, or I/O operations. 3) Analyze Execution Plans: For each identified poor-performing query, we will analyze its execution plan to understand the underlying query execution strategy. Specifically, we will check for index seeks or scans, and evaluate whether appropriate indexes are in place. 4) Create Appropriate Indexes: Based on our analysis, we will create or modify indexes as needed. This may include creating clustered indexes, non-clustered indexes, or covered indexes.

Configuration Tuning: Adjust database configuration settings (e.g., memory allocation, cache size) to optimize performance. Query Execution Plans: Review and optimize query execution plans. Use tools like SQL Profiler or EXPLAIN (in SQL) to understand how queries are being executed and where they can be improved.

Be open to other solutions like migrating to a more efficient database system or incorporating new technologies that can better handle your workload