In the ever-evolving world of cloud computing, one term that has gained significant traction is 'Chaos Engineering as a Service'. This term, while complex, is a crucial component of modern cloud computing practices. As part of our comprehensive Cloud Computing Glossary, we delve into the intricate details of Chaos Engineering as a Service, breaking down its definition, history, use cases, and specific examples.
Chaos Engineering as a Service is a discipline in the field of software engineering that involves experimenting on a system in order to build confidence in the system's capability to withstand turbulent conditions in production. This is achieved by intentionally introducing faults to test the system's resilience. Now, let's explore this concept in more detail.
Definition of Chaos Engineering as a Service
Chaos Engineering as a Service is a systematic approach to identifying failures before they become outages. By 'breaking things on purpose', engineers can observe how their systems react, and then use this information to make improvements. This practice is often conducted in the cloud, hence the term 'as a Service'.
The 'as a Service' part of the term refers to the delivery of Chaos Engineering tools and practices in a way that is easy for engineers to consume, typically over the internet. This can be in the form of cloud-based tools or platforms that provide Chaos Engineering capabilities.
Chaos Engineering
Chaos Engineering is the discipline of experimenting on a distributed system in order to build confidence in the system's capability to withstand turbulent conditions in production. The goal is to reveal weaknesses before they manifest in system-wide, aberrant behaviours.
It involves the intentional introduction of failures into a system to see how it responds and to identify any weaknesses. These failures can be anything from server crashes to network latency, and the goal is to learn how to build more resilient systems.
As a Service
The term 'as a Service' is a key component of cloud computing. It refers to the provision of services over the internet, rather than via a direct connection to a server. This model allows users to access software, storage, and other services without the need for in-house infrastructure or hardware.
When applied to Chaos Engineering, 'as a Service' means that the tools and practices of Chaos Engineering are delivered over the internet. This allows engineers to use these tools without having to install or maintain them on their own systems, making the practice more accessible and scalable.
History of Chaos Engineering as a Service
The concept of Chaos Engineering originated at Netflix in 2010, with the creation of the Chaos Monkey tool. Chaos Monkey was designed to randomly terminate instances in Netflix's production environment to ensure that engineers implemented their services to be resilient to instance failures.
Chaos Engineering as a Service, however, is a more recent development. With the rise of cloud computing and the 'as a Service' model, companies have started to offer Chaos Engineering tools and practices over the internet. This has made the practice more accessible to a wider range of companies and engineers.
Chaos Monkey and the Birth of Chaos Engineering
Chaos Monkey was the first tool developed for Chaos Engineering. It was created by Netflix to test the resilience of their own systems by randomly terminating instances in their production environment. The goal was to ensure that their systems could withstand instance failures and continue to operate effectively.
The success of Chaos Monkey led to the creation of the Simian Army, a suite of tools developed by Netflix for testing the resilience of their systems. This suite included tools for introducing various types of failures, such as network latency and server crashes, and tools for monitoring the system's response.
The Rise of Chaos Engineering as a Service
With the rise of cloud computing and the 'as a Service' model, Chaos Engineering has become more accessible. Companies have started to offer Chaos Engineering tools and practices over the internet, allowing engineers to use them without having to install or maintain them on their own systems.
This has led to the growth of Chaos Engineering as a Service, with companies like Gremlin providing a fully-managed platform for Chaos Engineering. These platforms provide a range of tools and services for introducing failures into systems, monitoring the response, and making improvements.
Use Cases of Chaos Engineering as a Service
Chaos Engineering as a Service can be used in a variety of scenarios, from testing the resilience of microservices to preparing for disaster recovery. By introducing failures into a system, engineers can observe how the system responds and use this information to make improvements.
Some common use cases include testing the resilience of microservices, preparing for disaster recovery, and improving system observability. Let's explore these use cases in more detail.
Testing the Resilience of Microservices
Microservices are a common architectural style in cloud computing, where an application is structured as a collection of loosely coupled services. While this style can offer many benefits, it can also introduce new challenges in terms of resilience.
Chaos Engineering as a Service can be used to test the resilience of microservices by introducing failures into individual services and observing how the system as a whole responds. This can help engineers identify weaknesses in their microservices architecture and make improvements.
Preparing for Disaster Recovery
Disaster recovery is a critical aspect of any cloud computing strategy. It involves preparing for and recovering from a disaster that affects a company's data, applications, and IT infrastructure.
Chaos Engineering as a Service can be used to prepare for disaster recovery by simulating disasters and observing how the system responds. This can help companies identify weaknesses in their disaster recovery plans and make improvements.
Improving System Observability
Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. In cloud computing, observability often involves collecting and analyzing metrics, logs, and traces from a system.
Chaos Engineering as a Service can be used to improve system observability by introducing failures and observing how they affect the system's outputs. This can help engineers understand the system's behavior under different conditions and improve their ability to diagnose and fix problems.
Examples of Chaos Engineering as a Service
There are several companies that offer Chaos Engineering as a Service, including Gremlin, ChaosIQ, and ChaosNative. These companies provide platforms for introducing failures into systems, monitoring the response, and making improvements.
Let's take a closer look at these companies and how they implement Chaos Engineering as a Service.
Gremlin
Gremlin is a fully-managed platform for Chaos Engineering. It provides a range of tools for introducing failures into systems, including attacks on CPU, memory, disk, and network. Gremlin also provides a user-friendly interface for managing and monitoring these attacks.
One of the key features of Gremlin is its 'Scenarios' feature, which allows engineers to simulate real-world outages and observe how their systems respond. This can help engineers identify weaknesses in their systems and make improvements.
ChaosIQ
ChaosIQ is a platform for Chaos Engineering that focuses on making the practice more accessible. It provides a range of tools for introducing failures into systems, as well as a platform for managing and monitoring these experiments.
ChaosIQ also provides a 'Chaos Toolkit', which is an open-source project for running Chaos Engineering experiments. This toolkit includes a range of plugins for different cloud providers and technologies, making it easy for engineers to introduce failures into their specific environment.
ChaosNative
ChaosNative is a company that provides a platform for Chaos Engineering called LitmusChaos. LitmusChaos is an open-source project that provides a range of tools for introducing failures into Kubernetes environments.
One of the key features of LitmusChaos is its 'ChaosHub', which is a hub for sharing Chaos Engineering experiments. This allows engineers to share their experiments with the community and learn from others' experiences.
Conclusion
Chaos Engineering as a Service is a critical component of modern cloud computing practices. By 'breaking things on purpose', engineers can learn how their systems respond to failures and use this information to build more resilient systems.
With the rise of cloud computing and the 'as a Service' model, Chaos Engineering has become more accessible to a wider range of companies and engineers. Whether you're testing the resilience of microservices, preparing for disaster recovery, or improving system observability, Chaos Engineering as a Service can provide valuable insights and improvements.