PerfBrains automatically converts performance test scripts to Gatling, JMeter, BlazeMeter and Azure Load Testing — with full correlation detection, validated output, and zero re-scripting.
Trusted by performance engineers at Fortune 500 companies · SOC 2 compliant · On-premise available
Every performance engineer who has tried to migrate a LoadRunner script to Gatling manually knows the pain. Correlations that took months to tune, re-scripted from scratch. Think times re-calibrated by hand. Feeder files rebuilt from logs.
LoadRunner's .lrp correlation rules don't map cleanly to Gatling or JMeter. Engineers must reverse-engineer each extractor from request/response logs — a multi-day process per script.
Think time policies (replay / random / ignore) and pacing configurations live in the .lrp file. Importing only the log means every think time must be re-configured manually.
After spending days on a manual migration, how do you know the converted script replays the original flow correctly? Most teams don't find out until the first load test run fails.
Upload your files and PerfBrains' conversion pipeline handles everything — from parsing multi-VU logs to generating production-ready scripts with verified correlations.
Detects format, version, protocol, and log level. Hard-blocks unsupported inputs with clear error messages.
Parses .log, .lrp, .c, .nlp, .yaml, and .har. Each parser extracts the full request model including bodies and headers.
Merges all inputs using strict precedence rules. LRP rules override heuristics. NeoLoad extractors override cross-VU diff.
Detects dynamic values across VU threads. Generates JSONPath, boundary, regex, and header extractors with confidence scores.
Produces Gatling Scala DSL or JMeter XML with feeder CSVs, think times, transactions, and env-var base URLs.
Not a stub generator. PerfBrains produces output you can run immediately, with correlations verified and performance tested.
Upload log + .lrp + .c source together. PerfBrains fuses all three, applying strict precedence rules so authoritative .lrp correlation rules always win over heuristic detection.
Detects JSONPath, boundary, regex, and response-header extractors. Cross-VU diff analysis identifies which values change between users. Every extractor carries a confidence score.
Run the converted script against a mock server seeded from the original recording. A 96% validation score means your correlations are firing correctly — before you ever touch staging.
HIGH / MEDIUM / LOW fidelity rating tells you immediately how complete the correlation detection is. Upload .lrp + 2 VUs for HIGH fidelity — the difference is measurable.
REST API with API key auth. Poll for completion. Download the ZIP. Trigger validation. The whole flow works in a shell script, GitHub Action, or Jenkins pipeline.
Multi-tenancy, OIDC/SSO, audit log, webhooks, rate limiting, and data retention policies. On-premise Docker Compose or Helm chart. Deployable in air-gapped environments.
From LoadRunner 12 through 2023, NeoLoad ZIP archives and YAML, browser HAR captures — to all five modern target frameworks.
Most migration tools ship output and say "trust us." PerfBrains ships output and then proves it's correct — with an automated replay validation and a PDF report you can share with stakeholders.
Parses the output script before execution. Verifies all correlation variables are defined, all extractors have consumers, and no orphan parameters exist. Runs in milliseconds.
Seeds a local HTTP server from the original recording. Runs the converted script against it. Detects correlation failures, unmatched requests, and status mismatches — completely offline.
PerfBrains runs the script against your TARGET_HOST and compares live HTTP responses to the recording. For internal apps, install perfbrains-cli inside your network — the agent runs locally and streams results back with no inbound firewall access required.
PerfBrains generates idiomatic, production-ready code — not a skeleton that needs days of manual work to make runnable.
// VuGen Action.c — checkout flow Action() { web_add_cookie("JSESSIONID={JSESSIONID}"); lr_start_transaction("Login"); web_submit_data("login", "Action=https://{HOST}/api/auth", "EncType=application/json", ITEMDATA, "Name=username", "Value={username}", ENDITEM, LAST); lr_end_transaction("Login", LR_AUTO); web_reg_save_param("auth_token", "LB=token\":", "RB=\",", LAST); }
class CheckoutFlowSimulation extends Simulation { val httpProtocol = http .baseUrl(sys.env.getOrElse("TARGET_HOST", "")) .acceptHeader("application/json") .disableCaching val users = csv("users.csv").circular val login = group("Login") { exec(http("POST /api/auth") .post("/api/auth") .body(StringBody("""{"username":"${username}"}""")) .check(jsonPath("$.data.token") .saveAs("auth_token"))) // ← extracted .pause(1200.milliseconds) } }
PerfBrains doesn't have a signup page. Every engagement starts with a technical conversation — so we understand your scripts, your environment, and your target frameworks before we agree on scope or price.
We convert one of your actual LoadRunner or NeoLoad scripts live on the call — no canned demo, no slide deck. You see the exact output PerfBrains produces for your codebase before you make any commitment.
→ No commitment requiredWe run a full POC on a representative sample of your scripts — typically 3 to 5. You receive the converted output, validation reports, and a fidelity summary you can share with your engineering leadership.
→ Usually 5–10 business daysPricing is agreed based on your migration scope — number of scripts, deployment model (SaaS or on-premise), and support level required. No per-seat tiers. No surprise overages. One clear statement of work.
→ Fixed-scope or retainer optionsBring a LoadRunner or NeoLoad script to the call. We'll convert it live, walk through the validation report, and answer every technical question your team has.
Migration guides, framework comparisons, and practical tutorials from the PerfBrains team.
Meridian's performance team faced an impossible deadline: migrate a decade of LoadRunner scripts before their licence expired. Here's how they found PerfBrains, ran a POC in a week, and converted their entire test suite — with a 97% validation score on first run.
Everything you need to know about migrating LoadRunner scripts to Gatling OSS — from extended log recording to correlation extraction, feeder CSV generation, and running your first load test.
A practical guide to converting NeoLoad user paths, extractors, and load models to JMeter .jmx format — with step-by-step instructions for handling conditions, loops, and SLA thresholds.
An objective comparison of Gatling and JMeter for modern performance engineering teams — covering scripting model, CI/CD integration, reporting, cloud execution, and total cost of ownership.
Start with a live demo on your actual scripts. No slides. No canned walkthrough. Just PerfBrains converting your LoadRunner or NeoLoad scripts so you can evaluate the output yourself.
We'll take your actual LoadRunner or NeoLoad scripts and convert them live, so you see exactly what PerfBrains produces for your codebase.
Not a canned demo. We use your files so you can validate the output immediately.
We run the Tier-2 mock validation live and walk through the score, extractor results, and any coverage warnings.
If you're in a regulated environment, we'll show the Docker Compose and Helm deployment paths.
No sales deck. We answer technical questions and you walk away with the output files.
We'll reach out to within one business day to confirm a time.
In the meantime, you can learn more about how we scope engagements at our get started section.