Best Load Testing Tools for Apache Kafka

Parasoft helps organizations continuously deliver high-quality software with its AI-powered software testing platform and automated test solutions. Supporting embedded and enterprise markets, Parasoft’s proven technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.

PFLB is an AI-powered load testing platform where you can simulate massive traffic to your websites, and applications. It’s easy to use and super helpful for teams that want to ensure their product is ready to scale. Features: Realistic testing with scenario-based traffic simulation. Importing your production load profile with Google Analytics integration. Easy scripting with an intuitive no-code editor. Executing advanced JMeter scenarios at scale. Resolving bottlenecks with AI-powered performance insights. Discovering load testing results with Grafana dashboards. Protocols: HTTP, HTTPS, gRPC, JDBC, JMS, AMQP, MQTT, Kafka.

Anchored in artificial intelligence (AI) and machine learning (ML), Parasoft SOAtest simplifies the complexity of functional testing across APIs, UIs, databases, and more. Change management systems continuously monitor quality, making the API and web service testing tool a perfect fit for Agile DevOps environments. Parasoft SOAtest delivers fully integrated API and web service testing tools that automate end-to-end functional API testing. Streamline automated testing with advanced functional test-creation capabilities for applications with multiple interfaces (REST & SOAP APIs, microservices, databases, and more). The tools reduce the risk of security breaches and performance outages by transforming functional testing artifacts into security and load equivalents. Such reuse, along with continuous monitoring of API for change, allows faster and more efficient testing.