The New QA

How Modern Applications Are Changing Traditional QA

DevOps and microservices architectures have dramatically increased the speed of software development. However, they have also massively increased application complexity.

As a result, traditional QA and software testing practices are no longer fully capable of ensuring the reliability of modern software.

In this white paper, we explore the widening gap between conventional QA and modern application development. We then discuss bridging that gap using modern testing disciplines like Chaos Engineering.

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What's inside?

In this white paper, we explore:

  • How DevOps and microservices have contributed to development velocity and architectural complexity
  • Why legacy testing and QA fall short in these new environments
  • Modern testing alternatives like Chaos Engineering to bridge the gap between emerging development trends and legacy testing methods

Modern applications are changing, and traditional testing practices are no longer up to the task.

In order to validate the reliability of distributed architectures in DevOps organizations we need a new testing methodology.

In this white paper, we explore the changing landscape of testing as a consequence of DevOps and microservices, and how Chaos Engineering provides the necessary framework for testing modern applications.

Over a decade of collective experience unleashing chaos at companies like

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Improve reliability at every level of your stack

Use Gremlin's comprehensive set of failure modes to experiment across your system, including bare metal, any cloud provider, containerized environments, kubernetes, applications, and serverless.

Build resilient infrastructure

  • Resource Gremlins
    Throttle CPU, Memory, I/O, and Disk
  • State Gremlins
    Reboot hosts, kill processes, travel in time
  • Network Gremlins
    Introduce latency, blackhole traffic, lose packets, fail DNS

Test for application failure

  • Test for failure in your code
  • Fail or delay serverless functions
  • Narrow the impact to a single user, device, or percentage of traffic

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