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Key Takeaways
- A successful microservice testing strategy must effectively manage the interdependent components involved. This may involve isolation, mocking, virtualization, or other techniques
- Organizational characteristics have an impact on which testing techniques to choose, such as the maturity of the team and the required pace of change e.g. brownfield versus greenfield
- We believe that from a business perspective there are three primary consequences of a testing approach: time to market, costs, and risks.
- Each testing technique has advantages and disadvantages. Which approach should be used for your application, depends on your context.
The first part of this series, “Testing Microservices Part 1: Overview of 12 Useful Techniques” explored techniques for managing microservice-dependent components when testing microservices. This article will compare the techniques based on the maturity of a team, pace of change, time to market, costs, and risks.
This comparison is based on our experience on 14+ projects, but we might have missed something or our experience might not reflect yours. So, please help us improve this summary so that we can help more people together as a community. Please comment below the article, post on LinkedIn or Tweet with tag #TestingMicroservices
The following table compares the techniques for testing microservices from a manager’s point of view. A plus sign (+) indicates advantages, a minus sign (-) indicates negative impact, and a tilde (~) indicates little or neutral effect.
| Technique | Organizational characteristics | Consequences of using a given testing approach | |||
| Maturity of the team | Pace of change | Time to market | Costs | Risks | |
| 1. Testing your microservice with a test instance of another microservice. | Low impact. | Low impact. | + Quick to start. – Slows projects as complexity grows. | + Low cost when complexity is low. – Can get costly as complexity grows | + Reduces the chances of introducing issues in test doubles. – Risk of not following the testing pyramid. |
| 2. Testing your microservice with a production instance of another microservice | Moderate impact. | Low impact. | + Quick to start. – Slows projects as complexity grows. | + Low cost when complexity is low. – Can get costly as complexity grows. | + Reduces the chances of introducing issues in test doubles. – Risk of not following the testing pyramid. – Can change the state of production systems. ~ Hard to simulate hypothetical scenarios. |
| 3. Testing a microservice with third-party dependencies. | Moderate impact. | Low impact. | + Quick to start. – Slows projects as complexity grows. | + Low cost when complexity is low. – Can get costly as complexity grows. ~ Calls to third-party APIs can generate costs. | + Reduces the chances of introducing issues in test doubles. – Risk of not following the testing pyramid. – Can change the state of production systems. ~ Hard to simulate hypothetical scenarios. |
| 4. Testing a microservice with legacy non-microservice internal dependencies. | Moderate impact. | Low impact. | + Quick to start. – Slows projects as complexity grows. | + Low cost when complexity is low. – Can get costly as complexity grows. | + Reduces the chances of introducing issues in test doubles. – Risk of not following the testing pyramid. – Can change the state of production systems. ~ Hard to simulate hypothetical scenarios. |
| 5. Testing a microservice with non-software (hardware) dependencies. | Moderate impact. | Low impact. | + Quick to start. – Slows projects as complexity grows. | ~ Test-only hardware can be costly. | + Fast feedback loop. |
| 6. Mocks (in-process or over the wire/remote). | Moderate impact. | Moderate impact. | ~ A moderate amount of time to start. + Reduces complexity. | ~ Might need in-house development efforts. | + Increases test coverage. – Can become obsolete. |
| 7. Stubs (in-process or over the wire/remote). | Moderate impact. | Moderate impact. | ~ A moderate amount of time to start. + Reduces complexity. | ~ In-house can be moderately costly. | + Increases test coverage. – Can become obsolete. |
| 8. Simulators (in-process or over the wire/remote). | Moderate impact. | Low impact. | + Quick to start with off-the-shelf simulations. – In-house efforts can take a lot of time | + Off-the-shelf simulations can be cost effective. – In-house efforts can be costly. | + Hypothetical scenarios can increase your test coverage. – In-house efforts can introduce discrepancies. |
| 9. Service virtualization (over the wire/remote), also called API simulation or API mocks. | Moderate impact. | Low impact. | + Off-the-shelf products help you get to market faster. | + Off-the-shelf products can be cost effective. ~ Commercial off-the-shelf products can get expensive. | + Reduces the risk of making common mistakes. + Allows simulation of network issues. ~ Open-source products come without a support contract. ~ Virtual services can become obsolete. |
| 10. In-memory database | Moderate impact. | Low impact. | + Reduces time to market where provisioning new databases is problematic | + Reduces the cost of licensing commercial databases. | ~ In-memory databases can behave differently than the real ones. |
| 11. Test container. | Moderate impact. | Low impact. | + Allows teams to move at their own pace. + Reduces time to market where provisioning new environments is problematic. | + Can reduce licensing costs. + Can reduce infrastructure costs. ~ Can have licensing-cost implications. | ~ Test containers can have a different configuration than the real production dependency. |
| 12. Legacy in a box | Moderate to high impact. | Low impact. | + Quick to start. – Slows projects as complexity grows. + Provisioning containers is an order of magnitude faster than provisioning hardware environments. ~ Time spent up front to configure containers. – Potential time for refactoring. | + Quick to start. – Slows projects as complexity grows. + Provisioning containers is an order of magnitude faster than provisioning hardware environments. ~ Up-front cost to configure containers. – Potential time for refactoring. | |
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