The queries WordPress runs most, straight against MySQL/MariaDB.
Category DatabaseStack MySQL / MariaDBJobs 16
About this WordPress database load test
Runs the queries WordPress executes most straight against MySQL or MariaDB: the size of autoloaded options, recent published posts, posts joined to postmeta, a LIKE search on content and a count of expired transients. It finds database bottlenecks without PHP in the way.
It holds 16 ready-made jobs: 5 single scenarios and an enterprise test plan of 11 stages to run in order, 9 of them with pass/fail targets (SLOs). Each job is a plain request pattern you can change before running.
Scenarios include autoloaded options size, recent published posts, posts joined to postmeta, LIKE search on content and expired transients count.
How to load test WordPress database
Open the template in BLASTA.
Check the settings so they point at your own WordPress database system, ideally a staging copy.
Pick a job and choose the rate and duration.
Start the run and watch requests per second, latency percentiles and errors live; the result is saved to your history.
Enterprise plan, step 1 of 10. One request a second for 30 seconds. Run this first, every time: it proves the address, credentials and headers are right and that the environment is up before any real load is applied. Gate: zero errors. Reference request: recent published posts.
Step 2 of 10. About a fifth of normal traffic for 5 minutes: the uncontended latency of this request. Every later result is judged against it, so record p50 and p95. Gate: at most 0.5% errors and the default latency targets. Reference request: recent published posts.
Step 3 of 10. Normal busy-hour traffic for 10 minutes. The rate is the reference job's rate: raise it to your measured production peak-hour rate. This is the run that proves (or breaks) your SLO. Gate: at most 1% errors, p95 and p99 inside the targets. Reference request: recent published posts.
Step 4 of 10. Twice the average for 10 minutes: the busiest hour of the year plus headroom. Latency may rise, but must stay in SLO; if it does not, you have no headroom. Gate: at most 2% errors, latency targets doubled. Reference request: recent published posts.
Step 5 of 10. Ramps to four times average over 10 minutes, then holds for 2. Finds where it degrades and HOW: gracefully (latency rises, errors stay low) or badly (errors, timeouts, crashes, restarts). Observation only, no gate. Reference request: recent published posts.
Step 6 of 10. Reaches ten times average within 10 seconds and holds for 2 minutes: a campaign email, a news link, a failover. Checks autoscaling, queue limits and load shedding. Gate: at most 5% errors, because shedding load is acceptable and crashing is not. Reference request: recent published posts.
Step 7 of 10. Run IMMEDIATELY after the spike, at average load for 5 minutes. Latency and errors must return to the baseline from step 2. If they do not, something is stuck: queues, connection pools, GC, an autoscaler cool-down. Gate: same as average load. Reference request: recent published posts.
Step 8 of 10. One hour of steady load. Finds leaks and slow decay in memory, connections, file descriptors, disk, log volume and cache churn. Watch the resource graphs: any line that climbs and never flattens is a finding. Gate: at most 0.5% errors. Reference request: recent published posts.
Step 9 of 10. Ramps to twenty times average over 20 minutes. Stop it when errors pass about 5%: the rate at that moment is your ceiling, and ceiling divided by peak is your capacity margin. Use a production-like environment, never production. Reference request: recent published posts.
Step 10 of 10. Average load for 15 minutes. About 5 minutes in, cause the event you are testing: kill a pod or node, fail over the database, roll out a new version, drain a zone. Errors in the window are your real availability loss. Gate: at most 1% errors overall; read the time series for how long the dip lasted. Reference request: recent published posts.
Runs four times more workers than the pool has connections, so most requests queue for a connection. Shows how the database and your pool behave when the app is slower than the traffic: latency should rise smoothly, not fall off a cliff. Reference request: recent published posts.
Frequently asked questions
What does the WordPress database load test cover?
The WordPress database template has 16 jobs: 5 single scenarios and an enterprise test plan of 11 stages (smoke, baseline, load, stress, spike, soak, breakpoint and failover window). Scenarios include autoloaded options size, recent published posts, posts joined to postmeta and LIKE search on content. 9 of them have pass/fail targets (SLOs), so a run can be judged against limits you set.
How do I load test WordPress database with BLASTA?
Open the template in BLASTA, enter the address of your WordPress database system, then pick a job and start it. Results stream live: requests per second, latency percentiles and errors, and the run is kept in your history. To run from the command line, use blasta preset new wordpress-db with your address.
Is it safe to run the WordPress database load test against production?
All 16 jobs in this template are read-only: they request pages or data and do not change anything. Even so, a load test can slow a live system down, so start with a low rate and prefer a staging copy. Only test systems you own or have permission to test.
Set up a target above and press Start test. Charts and numbers appear here as the test runs.
Load generator resources
CPU used by BLASTA % of capacity
RAM used by BLASTA
Requests per second
Latency p95 lower is better
Response time
Status codes
Errors
Pick a template
Ready-made jobs for common systems. Search by system, protocol or what you want to test
(wordpress, saml, redis, spike, login storm…), pick a job, and it opens on the Test page ready to run.
You are browsing as a visitor: you can read every template and job. Sign in or create an account to use them.
No templates match
Try a shorter search, or a system name such as keycloak, postgres or soap.