As the world becomes progressively more sophisticated due to advancements in technology, organizations must take ownership of how internal systems operate and function. With nearly every industry using distributed computing systems, identifying potential areas of weakness and deficiencies is of the utmost concern. Chaos Engineering was created as a tool to identify failures before they become widespread problems.
Today’s highly intricate software systems must be tested for potential weaknesses and faults. Chaos Engineering, like the name implies, is a process that involves testing a software’s ability to handle failures without affecting systematic functionality. By testing a software’s resiliency, Chaos Engineering can identify failures and correct them as needed.
Chaos tests can be performed as a means of proactively experimenting on a software’s infrastructure. Inducing failures can help improve organizational confidence if systems are able to overcome and mitigate turbulent conditions and outages.
Do your systems have the real world capabilities needed to overcome latency and performance issues?
Testing your system’s capability is imperative for ensuring your software can withstand any issues that come your way. With these principles in mind, we’ve reviewed some of the top Chaos Engineering tools on the market today. In this blog, we’ll help you figure out the best Chaos Engineering tool for your use case.
Why Use Chaos Engineering Tools?
Chaos Engineering tools are a relatively new approach to software testing used to establish confidence in systems. Software platforms will inevitably fail, therefore it’s critical to pinpoint weaknesses and fix them before they substantially impact business operations.
Top tech organizations such as Amazon, Netflix, and Microsoft utilize chaos engineering to achieve a better understanding of internal systematic behavior and flaws. The principles of Chaos Engineering are predicated on the idea of testing system architectures through various hypotheses and performance-based metrics. Through the deployment of assumptions and experiments, Chaos Engineering can provide a roadmap for uncovering infrastructural failures or unresponsive systems.
Chaos Engineering follows a general set of guidelines that includes each of these steps:
- Creating a steady-state hypothesis: Think of potential system issues that could occur. Set up failure injection testing protocols and predict various potential outcomes.
- Simulate real-world scenarios: Create a set of tests that will determine how systems react to different variables. Use an experimental group to test various conditions and factors.
- Review system metrics: Review system outcomes related to system performance and metrics. Determine failure rates against hypothesis and figure out a path forward to correct and fix reoccurring issues.
- Implement changes as needed: Upon conclusion of experiments, you should be able to ascertain what the best course of action is. Attempt to fix any issues and repeat the process until systems are operating with little to no errors.
Creating an effective and well-rounded chaos toolkit can help your organization test resiliency and discover potential fault tolerances. Let’s take a look at some of the tools that can be utilized to optimize your systems.
Chaos Mesh is an open-source cloud-native tool specifically designed for Chaos Engineering. Using various fault simulations, Chaos Mesh helps organizations determine system abnormalities that may occur during various portions of the development, testing, and production stages.
As an open-source tool that’s created with a web user interface known as the Chaos Dashboard, Chaos Mesh can be added to DevOps workflows to spot potential areas of weakness and timeouts. To ensure resiliency, Chaos Mesh utilizes chaos experiments within Kubernetes environments. It’s able to use various types of scenarios related to fault simulations within a distributed system.
Chaos Mesh is able to deploy attacks that test network latency, system time manipulation, resource utilization, and more. The Chaos Dashboard can be used to modify and manage various forms of experiments within set timeframes.
Chaos Mesh is widely regarded as one of the industry’s premiere Chaos testing platforms with a number of key features, including:
- Easy-to-use system: Chaos Mesh uses a Kubernetes-based interface that’s supported with full automation and graphical capabilities.
- Fully authenticated technology: Used in the testing of high visibility distribution systems such as Apache APSIX and RabbitMQ.
- Fault simulation detection: Chaos Mesh technology is able to test various scenarios using event-driven fault simulations.
- Customizable experiments: Chaos Mesh provides the ability to design experiments on the platform using different variables and status checks.
- Scalable technology: Chaos Mesh is an open source technology that’s easily scalable to enterprise-level needs.
As an open-source software, Chaos Mesh is free to use without a commercial license.
Should I Use Chaos Mesh?
Predicting failures can be a cumbersome task due to complexities in cloud operations. Unreliable functions and outages can result in a downgraded reputation and a loss of consumer trust. Chaos Mesh offers a convenient open-source technology that can be used in Kubernetes to design and manage automated experiments. However, be wary of certain limitations to the technology.
- Easy-to-use functionality and automation
- The user interface supports many different configurations
- Experiments can be paused and resumed at will
- Experiments run indefinitely as there is no ability to schedule attacks
- Node-level attacks cannot be run
- Cannot control user access within the dashboard; as a result, there are increased security risks
Chaos Monkey is an open-source chaos tool originally created by Netflix developers. It was developed to help test their system reliability and resiliency after moving to the AWS cloud. The software functions by implementing continuous unpredictable attacks. Chaos Monkey uses the basic fundamental approach of terminating one or more virtual machine instances.
The configurability of Chaos Monkey allows for easy scheduling and close monitoring. The technology is easily replicable, but can cause headaches if users are unprepared for the aftermath of attacks. Users can check for outages prior to deployment, but must be able to write and edit custom Go code.
Chaos Monkey was one of the early chaos tools and the first open-source technology to help initiate the Chaos Engineering movement. After its inception, Netflix later developed additional fault injection tools collectively known as the Simian Army.
Some of the key features of Chaos Monkey include:
- Detects systems bottlenecks to help limit disruption to production environments
- The ability to test resiliency and availability of applications at an infra level
- Tests can be scheduled during certain timeframes
- Allows for easy monitoring
Chaos Monkey is a free open-source software that doesn’t require a commercial license.
Should I Use Chaos Monkey?
Chaos Monkey was one of the first Chaos Engineering tools of its kind. While it may have revolutionized the open-source Chaos Engineering community, its contemporary application is far less practical today. Chaos Monkey is useful to an extent, but users must take into account its limitations and arduous deployment capabilities.
- Configurable technology allows for easy monitoring and scheduling of attacks
- Open-source software has no licensing costs
- Extensive development history
- Can only perform one type of experiment
- Attacks are randomized and users have limited control of blast radius
- Requires writing custom code
Gremlin is the first hosted Chaos Engineering service designed to improve web-based reliability. Offered as a SaaS (Software-as-a-Service) technology, Gremlin is able to test system resiliency using one of three attack modes. Users provide system inputs as a means of determining which type of attack will provide the most optimal results. Tests can be performed in conjunction with one another as a means of facilitating comprehensive infrastructural assessments.
The beauty of Gremlin lies in its ability to test entire systems on a variety of parameters and conditions. Gremlin can also be automated within CI/CD and integrated with Kubernetes clusters and public clouds. By harnessing chaos and building resilient systems, Gremlin can empower users to root out failures and minimize potential downtime.
Gremlin provides users with the tools and resources necessary to safely and easily simulate system outages within a simplified framework. Gremlin first tests the resiliency of services in their current state. Then, it provides recommendations for repairing and improving systems afterwards.
Some of the many features of Gremlin include:
- Controlling failures in a precise and controlled manner
- Custom scenarios that include multi-levels of system attacks and scenarios
- Testing for memory leaks, latency injections, disk fill-ups and more
Should I Use Gremlin?
As the world’s first managed enterprise Chaos Engineering technology, Gremlin provides users with the ability to launch dozens of attack vectors, stop and roll back attacks, and improve system security. Designed with the mission of creating a sustainable and reliable internet, Gremlin pinpoints software weaknesses to minimize revenue loss and negative systematic impacts.
- Customizable UI configurations allow for various attacks and tests to be ran simultaneously
- Automation support with CLI, API, and UI
- Evaluates resiliency based on a variety of different factors
- Although there is a free version, complete software use requires a licensing cost
- Software is not customizable
- No reporting capabilities
Litmus is an open-source Chaos Engineering platform designed for cloud-native infrastructures and applications. It assists teams with identifying system deficiencies and outages by performing controlled chaos tests. Litmus uses a cloud-native strategy to closely control and manage chaos.
Developers use Litmus as a set of tools to create, facilitate, and analyze chaos within Kubernetes. Litmus allows developers to develop chaos experiments, find errors, and remediate them prior to reaching full-scale production. The Litmus technology allows users to deploy a variety of experiments to the Kubernetes cluster as a means of preparing for future use.
Litmus was created as an open source chaos engineering platform used within Kubernetes. Designed to pinpoint bugs and deficiencies in Kubernetes, Litmus can easily be added to CI/CD pipelines for a fully end-to-end testing strategy.
The most prominent features of Litmus include:
- The ability to perform both chaos and functional tests
- Allows users to run test suites, perform log capturing, and generate reports
- The ability to monitor application health before, during, and upon conclusion of an experiment
Should I Use Litmus?
Litmus is a Kubernetes-native tool that facilitates experiments ranging from testing docker containers to specific Pods. As a versatile tool with a variety of monitoring capabilities through Prometheus, Litmus is useful but requires a significant depth of knowledge prior to getting started.
- Centralized repository containing a variety of experiments available through ChaosHub
- Reoccurring system health checks
- Automated error detection and resiliency scores
- Starting with Litmus can be difficult depending upon the user’s background
- Complicated administrative tasks require setting up service accounts and annotations for each namespace
- Permissions can be difficult to manage and track
ChaosBlade was designed as an open-source Chaos Engineering tool originally developed by Alibaba. It was created to ensure systems are fault-tolerant as a means of improving business operations. ChaosBlade operates by creating chaos attacks in different types of environments ranging from the cloud to containers.
The modular design of ChaosBlade makes it a versatile platform that’s able to employ a variety of experiments. It is ideal for testing resiliency at the code level by way of using application fault injections.
ChaosBlade has the ability to employ an array of attacks such as process killing, network packet loss, and disk usage. The tool’s experimental model can perform simple deployment, convenient execution, and rich experiments.
The prominent features of ChaosBlade include:
- Attack support at many levels: resource (CPU, memory, etc.), application (Java, C++, NodeJS, Golang, etc.), Kubernetes (Container, Pod, Node), and more.
- Helps enterprises remediate high-availability problems
- More than 200 experimental scenarios and over 3000 experimental parameters allowing users to closely manage experimental controls
- Automatically deploys experimental tools
Should I Use ChaosBlade?
The versatility of ChaosBlade makes it useful for employing a number of attacks. Its ability to use a variety of experimental tools makes it ideal for a plethora of use cases and scenarios. Many consider ChaosBlade to be an ideal tool for testing system resiliency and reliability.
- Supports a wide variety of attacks and experiment types
- Provides seamless automation support
- Fast and easy setup
- Cloud-native software supports Helm deployment management, Prometheus monitoring, etc.
- Documentation is lacking; learning curve is steep
- Lacks UI support and customization
- Limited safety and reporting capabilities
Integrate Chaos Engineering Tools with Harness
Did you know certain Chaos Engineering tools can easily be integrated with Harness? CD pipelines are a great place to experiment, so we created a tutorial on how to add Gremlin to your workflow and inject some failure! Stay tuned for further integrations. And as always – feel free to peruse our blog to gain more knowledge on Chaos Engineering (Here’s a great Chaos Engineering 101-level piece), CI/CD, Feature Flags, Cloud Cost Management, and beyond.