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• Chaos engineering should be implemented and designed with software architecture
• Learning from maintainers and practitioners is important for understanding use cases and benefiting applications
• Proper communication is key for running chaos engineering in production with minimized blast radius
• Chaos Mesh is a growing open-source tool for managing chaos engineering experiments
• New features and community involvement are important for the growth of Chaos Mesh

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• Chaos engineering can be used to test the resilience of systems and identify vulnerabilities
• Litmus is a tool that can be used to implement chaos engineering in DevOps
• Chaos experiments can be constructed using APIs and injected into pipelines using Chaos IPs
• Chaos hubs can be used to share chaos experiments across teams
• Common security questions and challenges include controlling access to chaos experiments, isolating namespaces for chaos engineering, and managing privileges through service accounts
• Litmus 3.0 beta is focused on making chaos engineering easier for developers to use
• Joining the Litmus community can provide opportunities for feedback and contributions

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• Litmus Chaos is a tool for chaos engineering that focuses on making it more robust and lean
• The tool has monthly releases and has added new fault types
• Support for newer versions of Kubernetes and OpenShift has been added
• Support for randomization of fault inputs has been added
• The tool is being designed to enable developers to use it earlier in the development process

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• Chaos engineering involves deliberately causing production incidents to determine the impact on the environment.
• Defining success criteria is important to determine what success means for the test.
• Measuring steady state involves observing how the system behaves when everything is going well.
• Injecting failure is the actual chaos test itself.
• Observing outcomes involves seeing what happens during the chaos test.
• Restoring the system is necessary if required.
• Managed services in the cloud make traditional chaos engineering techniques difficult.
• Chaos engineering is essential for verifying the resiliency of cloud-native applications.
• Defining success criteria, measuring steady state, injecting failure, observing outcomes, and restoring the system are the five parts to running a chaos test.

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• Chaos Mesh is an open-source tool for chaos engineering in large-scale distributed systems
• The project aims to increase the probability of reproducing bugs by injecting failures into the system
• Features of the project include Azure chaos, multi-Kubernetes support, and improved usability
• Azure chaos allows users to run chaos workloads on top of the Azure cloud
• Multi-Kubernetes support enables users to run chaos experiments across multiple Kubernetes clusters using one central controller
• Improved usability includes a drag and drop feature for defining workflows

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• Modern computing systems have evolved beyond human ability to mentally model their behavior, leading to increased outages and incidents.
• Software complexity only increases and cannot be decreased, making it challenging for operators to manage.
• Chaos engineering is a proactive approach to fixing issues and navigating inherent complexity.
• Curviz is an open-source tool for Kubernetes security testing, targeting low-hanging fruit such as CIS benchmarks and network configurations.
• Experiments can be run to test configurations and validate changes before they cause issues in production.

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• Chaos Mesh provides a comprehensive data inspection mechanism and a simple yet powerful reporting system to improve availability
• Chaos Mesh plans to develop a new security component to program chaos experiments and provide a plugin to extend the tool's capabilities
• Chaos Mesh has a community of users who share their use cases and experiments through interactive tutorials, monthly meetings, and a GitHub repository

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• Litmus and Octeto are open-source tools that allow for the validation and verification of code resilience and application functionality on Kubernetes.
• Chaos engineering should be incorporated into the development workflow to improve application quality and resilience.
• Self-service portals and catalogs make it easy for developers to run chaos experiments and tests.
• Running chaos experiments on ephemeral dev environments on Kubernetes makes it easier to run tests and reuse experiments in staging and production.
• The more chaos tests are run, the less expensive and more normal they become in the development workflow.
• Using chaos engineering tools in all phases of development and with multiple components will improve application quality and resilience.

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• Chaos engineering involves injecting failures into an environment to test the resilience of services and prevent sub-optimal behavior.
• Cloud native chaos engineering is open source and community-collaborated.
• Observability is important for customizing chaos engineering to an organization's needs.
• Cloud native chaos engineering is becoming more democratic and involves a larger set of personas, including devops engineers and cloud native developers.
• Cloud native chaos engineering is important for maintaining resilience in complex dynamic deployment environments with many moving parts.