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Steps to Bootstrap a Chaos Experiment

The artifacts associated with a chaos-experiment are summarized below:

  • Submitted in the litmuschaos/litmus-python repository, under the experiments/chaos_category/experiment_name folder

    • Experiment business logic in python. May involve creating new or reusing an existing chaosLib
    • Experiment test deployment manifest that is used for verification purposes
    • Experiment RBAC (holds experiment-specific ServiceAccount, Role and RoleBinding)

    Example: pod delete experiment in litmus-python

  • Submitted in litmuschaos/chaos-charts repository, under the chaos_category folder

    • Experiment custom resource (CR) (holds experiment-specific chaos parameters & experiment entrypoint)
    • Experiment ChartServiceVersion (holds experiment metadata that will be rendered on charthub)
    • Experiment RBAC (holds experiment-specific ServiceAccount, Role and RoleBinding)
    • Experiment Engine (holds experiment-specific chaosengine)

    Example: pod delete experiment in chaos-charts

The generate_experiment.py script is a simple way to bootstrap your experiment, and helps create the aforementioned artifacts in the appropriate directory (i.e., as per the chaos_category) based on an attributes file provided as input by the chart-developer. The scaffolded files consist of placeholders which can then be filled as desired.

Steps to Generate Experiment Manifests

  • Clone the litmus-python repository & navigate to the contribute/developer-guide folder

    $ git clone https://github.com/litmuschaos/litmus-python.git
$ cd litmus-python/contribute/developer-guide

  • Populate the attributes.yaml with details of the chaos experiment (or chart). Use the attributes.yaml.sample as reference.

    As an example, let us consider an experiment to kill one of the replicas of a nginx deployment. The attributes.yaml can be constructed like this:

    $ cat attributes.yaml 

---
name: "sample_exec_chaos"
version: "0.1.0"
category: "sample_category"
repository: "https://github.com/litmuschaos/litmus-python/tree/master/sample_category/sample_exec_chaos"
community: "https://kubernetes.slack.com/messages/CNXNB0ZTN"
description: "it execs inside target pods to run the chaos inject commands, waits for the chaos duration and reverts the chaos"
keywords:
  - "pods"
  - "kubernetes"
  - "sample-category"
  - "exec"
platforms:
  - Minikube
scope: "Namespaced"
auxiliaryappcheck: false
permissions:
  - apigroups:
      - ""
      - "batch"
      - "apps"
      - "litmuschaos.io"
    resources:
      - "jobs"
      - "pods"
      - "pods/log"
      - "events"
      - "deployments"
      - "replicasets"
      - "pods/exec"
      - "chaosengines"
      - "chaosexperiments"
      - "chaosresults"
    verbs:
      - "create"
      - "list"
      - "get"
      - "patch"
      - "update"
      - "delete"
      - "deletecollection"
maturity: "alpha"
maintainers:
  - name: "oumkale"
    email: "[email protected]" 
provider:
  name: "ChaosNative"
minkubernetesversion: "1.12.0"
references:
  - name: Documentation
    url: "https://docs.litmuschaos.io/docs/getstarted/"

  • Run the following command to generate the necessary artefacts for submitting the sample_category chaos chart with sample_exec_chaos experiment.

    $ python3 generate_experiment.py -f=attributes.yaml -g=<generate-type>

    Note: Replace the -g=<generate-type> placeholder with the appropriate value based on the usecase:

    • experiment: Chaos experiment artifacts belonging to an existing OR new experiment.

    • chart: Just the chaos-chart metadata, i.e., chartserviceversion.yaml

      • Provide the type of chart in the -t=<type> flag. It supports the following values:
        • category: It creates the chart metadata for the category i.e chartserviceversion, package manifests
        • experiment: It creates the chart for the experiment i.e chartserviceversion, engine, rbac, experiment manifests
        • all: it creates both category and experiment charts (default type)

    • Provide the path of the attribute.yaml manifest in the -f flag.

    View the generated files in /experiments/<chaos_category> folder.

    $ cd /experiments

$ ls -ltr

total 8
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 16:44 __init__.py
drwxrwxr-x 3 oumkale oumkale 4096 Jul  7 16:44 generic/
drwxrwxr-x 3 oumkale oumkale 4096 Jul  7 16:47 sample_category/

$ ls -ltr sample_category/

total 4
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 16:50 __init__.py
drwxr-xr-x 5 oumkale oumkale 4096 July 7 16:51 sample_exec_chaos/

$ ls -ltr sample_category/sample_exec_chaos/

total 12
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 16:47 __init__.py
drwxrwxr-x 2 oumkale oumkale 4096 Jul  7 16:48 experiment/
drwxrwxr-x 2 oumkale oumkale 4096 Jul  7 16:49 charts/ 
drwxrwxr-x 2 oumkale oumkale 4096 Jul  7 16:50 test/ 

$ ls -ltr sample_category/sample_exec_chaos/experiment

total 8
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 18:43 __init__.py
-rw-rw-r-- 1 oumkale oumkale 6440 Jul  7 18:47 sample_exec_chaos.py

$ ls -ltr sample_category/charts

total 24
-rw-rw-r-- 1 oumkale oumkale  144 Jul  7 18:48 sample-category.package.yaml
-rw-rw-r-- 1 oumkale oumkale  848 Jul  7 18:48 sample-category.chartserviceversion.yaml
-rw-rw-r-- 1 oumkale oumkale  989 Jul  7 18:48 sample-exec-chaos.chartserviceversion.yaml
-rw-rw-r-- 1 oumkale oumkale 1540 Jul  7 18:48 experiment.yaml
-rw-rw-r-- 1 oumkale oumkale 1224 Jul  7 18:48 rbac.yaml
-rw-rw-r-- 1 oumkale oumkale  731 Jul  7 18:48 engine.yaml

$ ls -ltr sample-category/sample-exec-chaos/test

total 4
-rw-r--r-- 1 oumkale oumkale  1039 July 7 18:52 test.yaml

$ ls -ltr chaosLib
total 4
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 16:44 __init__.py
drwxrwxr-x 4 oumkale oumkale 4096 Jul  7 18:43 litmus

$ ls -ltr chaosLib/litmus
total 8
drwxrwxr-x 3 oumkale oumkale 4096 Jul  7 16:44 pod_delete
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 16:44 __init__.py
drwxrwxr-x 2 oumkale oumkale 4096 Jul  7 18:43 sample_exec_chaos

$ ls -ltr chaosLib/litmus/sample_exec_chaos
total 8
-rw-rw-r-- 1 oumkale oumkale    0 Jul  7 18:43 __init__.py
-rw-rw-r-- 1 oumkale oumkale 5828 Jul  7 18:47 sample_exec_chaos.py

  • Proceed with construction of business logic inside the sample_exec_chaos.py file, by making the appropriate modifications listed below to achieve the desired effect:

  • The chaosLib is created at chaosLib/litmus/sample_exec_chaos/lib/sample_exec_chaos.py path. It contains some pre-defined steps which runs the ChaosInject command (explicitly provided as an ENV var in the experiment CR). Which will induce chaos in the target application. It will wait for the given chaos duration and finally runs the ChaosKill command (also provided as an ENV var) for cleanup purposes. Update this chaosLib to achieve the desired effect based on the use-case or reuse the other existing chaosLib.

  • Create an experiment README explaining, briefly, the what, why & how of the experiment to aid users of this experiment.

Steps to Test Experiment

We can use Okteto to help us in performing the dev-tests for experiment created. Follow the steps provided below to setup okteto & test the experiment execution.

  • Install the Okteto CLI

    curl https://get.okteto.com -sSfL | sh

  • (Optional) Create a sample nginx deployment that can be used as the application under test (AUT).

    kubectl create deployment nginx --image=nginx

  • Setup the RBAC necessary for execution of this experiment by applying the generated rbac.yaml

    kubectl apply -f rbac.yaml

  • Modify the test/test.yaml with the desired values (app & chaos info) in the ENV and appropriate chaosServiceAccount along with any other dependencies, if applicable (configmaps, volumes etc.,) & create this deployment

    kubectl apply -f test/test.yml

  • Go to the root of this repository (litmuschaos/litmus-python) & launch the Okteto development environment in your workspace. This should take you to the bash prompt on the dev container into which the content of the litmus-python repo is loaded.

    • Note :
      • Add packages routes for all the files which are generated from sdk in setup.py before creating image. example :
      'chaosLib/litmus/sample_exec_chaos',
'chaosLib/litmus/sample_exec_chaos/lib',
'pkg/sample_category',
'pkg/sample_category/environment',
'pkg/sample_category/types',
'experiments/sample_category',
'experiments/sample_category/sample_exec_chaos',
'experiments/sample_category/sample_exec_chaos/experiment',
      • Add & operator at the end of chaos commands CHAOS_INJECT_COMMAND example: md5sum /dev/zero &. As we are running chaos commands as a background process in a separate thread.
      • Import main file it in bin/experiment/experiment.py and add case. example: line number 3 in experiment.py
      • Then go to root(litmus-python) and run python3 setup.py install
    root@test:~/okteto/litmus-python# okteto up 

Deployment litmus-python doesn't exist in namespace litmus. Do you want to create a new one? [y/n]: y
✓  Development container activated
✓  Files synchronized

The value of /proc/sys/fs/inotify/max_user_watches in your cluster nodes is too low.
This can affect file synchronization performance.
Visit https://okteto.com/docs/reference/known-issues/index.html for more information.
    Namespace: default
    Name:      litmus-experiment
    Forward:   2345 -> 2345
               8080 -> 8080

Welcome to your development container. Happy coding!

    This dev container inherits the env, serviceaccount & other properties specified on the test deployment & is now suitable for running the experiment.

  • Install dependencies

    • Run curl -L https://storage.googleapis.com/kubernetes-release/release/"v1.18.0"/bin/linux/"amd64"/kubectl -o /usr/local/bin/kubectl && chmod +x /usr/local/bin/kubectl
    • Run pip3 install -r requirements.txt
    • Run python3 setup.py install, run this command for every change in experiment code.

  • Execute the experiment against the sample app chosen & verify the steps via logs printed on the console.

    python3 bin/experiment/experiment.py -name=<experiment-name>

  • In parallel, observe the experiment execution via the changes to the pod/node state

    watch -n 1 kubectl get pods,nodes

  • If there are necessary changes to the code based on the run, make them via your favourite IDE. These changes are automatically reflected on the dev container. Re-run the experiment to confirm changes.

  • Once the experiment code is validated, stop/remove the development environment

    root@test:~/okteto/litmus-python# okteto down
✓  Development container deactivated
i  Run 'okteto push' to deploy your code changes to the cluster

  • (Optional) Once the experiment has been validated using the above step, it can also be tested against the standard Litmus chaos flow. This involves: The experiment created using the above steps, can be tested in the following manner:

  • Run the experiment.yml with the desired values in the ENV and appropriate chaosServiceAccount using a custom dev image instead of litmuschaos/litmus-python (say, oumkale/litmus-python) that packages the business logic.

    • Creating a custom image built with the code validated by the previous steps
    • Launching the Chaos-Operator
    • Modifying the ChaosExperiment manifest (experiment.yaml) with right defaults (env & other attributes, as applicable) & creating this CR on the cluster (pointing the .spec.definition.image to the custom one just built)
    • Modifying the ChaosEngine manifest (engine.yaml) with right app details, run properties & creating this CR to launch the chaos pods
    • Verifying the experiment status via ChaosResult

    Refer litmus docs for more details on performing each step in this procedure.

Steps to Include the Chaos Charts/Experiments into the ChartHub

  • Send a PR to the litmus-python repo with the modified experiment files, rbac, test deployment & README.
  • Send a PR to the chaos-charts repo with the modified experiment CR, experiment chartserviceversion, rbac, (category-level) chaos chart chartserviceversion & package.yaml (if applicable).