– Scanning large tables<\/p>\n\n\n\n
– Fetching unnecessary data<\/p>\n\n\n\n
– Sorting large datasets<\/p>\n\n\n\n
– Missing indexes<\/p>\n\n\n\n
Resolution:<\/p>\n\n\n\n
1. Access the Google Console <\/p>\n\n\n\n
2. Log in to Cloud SQL >> Instance >> Query Insights<\/p>\n\n\n\n
3. To check this further, we need to check the query execution time and how many times the query is run.<\/p>\n\n\n\n 2. High CPU utilization<\/strong><\/p>\n\n\n\n The CPU utilization is increased on the application, which means the SQL<\/a> query may take longer to execute.<\/p>\n\n\n\n Common reasons:<\/p>\n\n\n\n – Large query size<\/p>\n\n\n\n – Too many simultaneous queries<\/p>\n\n\n\n – Missing indexes<\/p>\n\n\n\n Please follow the steps below to check CPU usage<\/p>\n\n\n\n – Log in to >> Metrics Explorer >> Cloud SQL<\/p>\n\n\n\n – In this option, you can see the CPU usage, database load, and query execution time. <\/p>\n\n\n\n In case the CPU usage shows 80 to 90%, we need to check further<\/p>\n\n\n\n Resolution,<\/p>\n\n\n\n Time-taking query<\/p>\n\n\n\n Log in to Cloud SQL Insights >> Query Analysis. <\/p>\n\n\n\n The resolution depends on the query execution time.<\/p>\n\n\n\n 3. Solving High Memory Usage<\/strong><\/p>\n\n\n\n Here is the main role of RAM: it is a frequently used database.<\/p>\n\n\n\n Slow query response<\/p>\n\n\n\n Application delay issue<\/p>\n\n\n\n Reduce disk cache issues.<\/p>\n\n\n\n Common reasons:<\/p>\n\n\n\n Incorrect database connection<\/p>\n\n\n\n Too many simultaneous connections<\/p>\n\n\n\n Log in to Cloud Monitoring >> Cloud SQL Metrics. <\/p>\n\n\n\n 4. Connection limit issue:<\/strong><\/p>\n\n\n\n If the Cloud SQL limit is exceeded, it’s because too many simultaneous connections cause it<\/p>\n\n\n\n Common Reason<\/p>\n\n\n\n Too many idle connections<\/p>\n\n\n\n Incorrect application configuration<\/p>\n\n\n\n No connection pooling<\/p>\n\n\n\n To set connection pooling<\/p>\n\n\n\n Apply the solution.<\/p>\n\n\n\n Set connection timeout values.<\/p>\n\n\n\n Configure the application connection pool.<\/p>\n\n\n\n Kindly do this to open a new request for the database. Kindly do the steps below<\/p>\n\n\n\n Application >> Connection Pool >> Database<\/p>\n\n\n\n 5. Input\/output delay problem<\/strong><\/p>\n\n\n\n Database performance, especially speed, is directly affected by disk performance.<\/p>\n\n\n\n There may be noticeable delays.<\/p>\n\n\n\n Increased application response time<\/p>\n\n\n\n 6. Improper Indexing <\/strong><\/p>\n\n\n\n Indexes can improve query performance, but having two or more indexes can cause issues and impact DB performance.<\/p>\n\n\n\n Create indexes for frequently searched columns.<\/p>\n\n\n\n 7. High Disk Latency<\/strong><\/p>\n\n\n\n Common problems,<\/p>\n\n\n\n High write workload<\/p>\n\n\n\n Large updates<\/p>\n\n\n\n Storage almost full<\/p>\n\n\n\n Investigation:<\/p>\n\n\n\n Review disk latency metrics.<\/p>\n\n\n\n How full is your storage?<\/p>\n\n\n\n Are there really write-heavy queries?<\/p>\n\n\n\n The database performance, specifically speed, is directly affected by disk performance.<\/p>\n\n\n\n There may be noticeable delays.<\/p>\n\n\n\n Increased application response time<\/p>\n\n\n\n These can be caused by:<\/p>\n\n\n\n Missing indexes<\/p>\n\n\n\n Bad SQL<\/p>\n\n\n\n Accessing large datasets<\/p>\n\n\n\n These require:<\/p>\n\n\n\n Checking logs for slow queries<\/p>\n\n\n\n Looking at execution plans<\/p>\n\n\n\n Comparing past execution times<\/p>\n\n\n\n Optimizations can include:<\/p>\n\n\n\n Adding indexes<\/p>\n\n\n\n Adjusting SQL<\/p>\n\n\n\n Restricting the number of output rows<\/p>\n\n\n\n Implementing pagination<\/p>\n\n\n\n In the case of unused indexes,<\/p>\n\n\n\n Delete them. <\/p>\n\n\n\n Regularly checking indexes<\/p>\n\n\n\n You can fix problems like these by using the monitoring tool in GCP.<\/p>\n\n\n\n ========================================<\/p>\n\n\n\n Cloud SQL Insights monitors slow queries and looks at patterns in a workload.<\/p>\n\n\n\n Query Insights: Monitor query performance and resource usage.<\/p>\n\n\n\n Cloud monitoring: Keep a check on CPU and memory consumption, storage and disk delay, and the number of connections.<\/p>\n\n\n\n The Cloud SQL logs are used to monitor the database slow query logs and check the database errors. <\/p>\n\n\n\n =======================================<\/p>\n\n\n\n Kindly use the following steps to avoid the same issue in the future<\/p>\n\n\n\n Also monitor the database regularly.<\/p>\n\n\n\n Kindly optimize the databases and indexes regularly.<\/p>\n\n\n\n For better performance, use connection pooling<\/p>\n\n\n\n Set alerts for high usage of CPU, memory, storage, and connections.<\/p>\n\n\n\n Please follow the instructions below to optimize the database.<\/p>\n\n\n\n Return only the columns that are required.<\/p>\n\n\n\n Don’t use SELECT *<\/p>\n\n\n\n Make appropriate use of the WHERE clause.<\/p>\n\n\n\n Reduce subqueries<\/p>\n\n\n\n Use pagination when returning large datasets.<\/p>\n\n\n\n Cloud SQL primarily detects the root causes of performance problems; to ensure performance and scalability, a monitoring tool must be set up, which is done through database maintenance.<\/p>\n\n\n\n =============================<\/p>\n\n\n\n Facing issues? <\/p>\n\n\n\n Our technical support![\"\"](\"https:\/\/www.supportpro.com\/blog\/wp-content\/uploads\/2026\/08\/image-20.png\")
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engineers can solve it. <\/p>\n\n\n\n<\/a><\/span>