Cloud Computing
Chaos Engineering and Digital Resilience Testing
Turn Chaos Engineering and Digital Resilience Testing into controlled practice by examining experiment design and safeguards, learning remediation and governance, and completing a practical controlled chaos exercise.
Overview
Practical learning for workplace transfer.
Effective Chaos Engineering and Digital Resilience Testing requires technical choices to survive operational scrutiny. The course moves from resilience hypotheses and risk through learning remediation and governance, using peer review and scenario work to produce a feasible next-step plan.
Prerequisites
Relevant experience with Chaos Engineering and Digital Resilience Testing is useful; technical depth is adapted to the cohort.
Objectives
- Frame resilience hypotheses and risk for a defensible business decision.
- Diagnose experiment design and safeguards against technical and operational evidence.
- Select and justify an approach to failure injection and observability under realistic constraints.
- Establish ownership, controls, and measures for learning remediation and governance.
- Deliver the controlled chaos exercise output and defend it in a stakeholder review.
Target audience
- Cloud architects, engineers, and platform teams
- Infrastructure, resilience, security, and operations leaders
- Application owners and enterprise architects
- Technology sourcing and transformation teams responsible for Chaos Engineering and Digital Resilience Testing
Program outline
A clear structure for the learning journey.
Program outline
Outline points are grouped in one designed block instead of being treated as separate module cards.
Module 1: resilience hypotheses and risk
Establish acceptance criteria and evidence requirements before approving resilience hypotheses and risk.
Peer-review the proposed resilience hypotheses and risk approach for unintended effects and operational fit.
Resolve the scenario through a documented recommendation and escalation path.
Module 2: experiment design and safeguards
Establish acceptance criteria and evidence requirements before approving experiment design and safeguards.
Peer-review the proposed experiment design and safeguards approach for unintended effects and operational fit.
Resolve the scenario through a documented recommendation and escalation path.
Module 3: failure injection and observability
Establish acceptance criteria and evidence requirements before approving failure injection and observability.
Peer-review the proposed failure injection and observability approach for unintended effects and operational fit.
Resolve the scenario through a documented recommendation and escalation path.
Module 4: learning remediation and governance
Establish acceptance criteria and evidence requirements before approving learning remediation and governance.
Peer-review the proposed learning remediation and governance approach for unintended effects and operational fit.
Resolve the scenario through a documented recommendation and escalation path.
Module 5: controlled chaos exercise
Establish acceptance criteria and evidence requirements before approving controlled chaos exercise.
Peer-review the proposed controlled chaos exercise approach for unintended effects and operational fit.
Resolve the scenario through a documented recommendation and escalation path.
Materials provided
- Course workbook and specialist reference guide
- Applied case pack and decision worksheets
- Implementation checklist and action-plan canvas
- 4D Certificate of Completion
Training Options
Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.
Why choose 4D
The Chaos Engineering and Digital Resilience Testing cases are adapted to the client sector and conclude with a reviewable output, without claiming certification.
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