Discourse forum: categories, topics and the JSON API.
Category ForumStack Ruby on Rails + PostgreSQL + RedisJobs 19
About this Discourse load test
Load tests a Discourse forum: the latest topics list, a category, a single topic as JSON, JSON search and the latest JSON feed. Discourse runs on Rails with PostgreSQL and Redis, so this shows how caching and the JSON API hold up as readers arrive.
It holds 19 ready-made jobs: 5 single scenarios and an enterprise test plan of 14 stages to run in order, 12 of them with pass/fail targets (SLOs). Each job is a plain request pattern you can change before running.
Scenarios include discourse latest, discourse category, discourse topic JSON, discourse search JSON and discourse latest JSON.
How to load test Discourse
Open the template in BLASTA.
Set url to point at your own Discourse 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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
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: discourse topic JSON.
Sends Connection: close, so every request pays for a new TCP and TLS handshake: the cost for clients that do not reuse connections (scripts, some mobile SDKs, health checkers). Shows load balancer and TLS termination limits. Reference request: discourse topic JSON.
Same request identified as a search crawler. Tests WAF and bot-management rules and whether crawlers get cached or origin responses. Crawlers can easily be a third of all traffic. Reference request: discourse topic JSON.
Adds a 4 KB Cookie header, like a logged-in user with many tracking cookies. Proxies and servers reject headers around 8 KB, so this shows how close you are to that limit. Reference request: discourse topic JSON.
A fleet of synthetic monitors checking the URL with HEAD requests every 30 seconds from 20 locations, plus load balancer probes. Cheap each, constant in total. Reference request: discourse topic JSON.
Frequently asked questions
What does the Discourse load test cover?
The Discourse template has 19 jobs: 5 single scenarios and an enterprise test plan of 14 stages (smoke, baseline, load, stress, spike, soak, breakpoint and failover window). Scenarios include discourse latest, discourse category, discourse topic JSON and discourse search JSON. 12 of them have pass/fail targets (SLOs), so a run can be judged against limits you set.
How do I load test Discourse with BLASTA?
Open the template in BLASTA and set url, 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 discourse with your address.
Is it safe to run the Discourse load test against production?
All 19 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
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