SLO generator
Project description
SLO Generator
slo-generator
is a tool to compute Service Level Objectives (SLOs), Error Budgets and Burn Rates, using policies written in JSON format, and export the computation results to available
exporters.
Description
slo-generator
will query metrics backend and compute the following metrics:
- Service Level Objective defined as
SLO (%) = GOOD_EVENTS / VALID_EVENTS
- Error Budget defined as
ERROR_BUDGET = 100 - SLO (%)
- Burn Rate (speed at which you're burning the available error budget)
Policies
The SLO policy (JSON) defines which metrics backend (e.g: Stackdriver), what metrics, and defines SLO targets are expected. An example is available here.
The Error Budget policy (JSON) defines the window to query, the alerting Burn Rate Threshold, and notification settings. An example is available here.
Metrics backends
slo-generator
currently supports the following metrics backends:
- Stackdriver Monitoring
Support for more backends is planned for the future (feel free to send a PR !):
- Prometheus
- Grafana
- Stackdriver Logging
- Datadog
Exporters
Exporters can be configured to send SLO Reports to a destination.
slo-generator
currently supports the following exporters:
- Cloud Pub/Sub for streaming export.
- Stackdriver Monitoring for exporting SLO metrics to Stackdriver Monitoring (e.g: Burn Rate metric, SLO/SLI metric).
- BigQuery for exporting SLO report to BigQuery for deep analytics.
The exporters configuration is put in the SLO JSON config. See an example in tests/fixtures/slo_linear.json.
Basic usage (local)
Requirements
- Python 3
- gcloud SDK installed
Installation
slo-generator
is published on PyPI. To install it, run:
pip install slo-generator
Write an SLO config file
See slo_linear.json
and slo_exponential.json
files in the tests/fixtures/
directory to write SLO definition files.
Write an Error Budget Policy file
See error_budget_policy.json
files in the tests/fixtures/
directory to write
Error Budget Policy files.
Run the slo-generator
slo-generator --slo-config=<SLO_CONFIG_FILE> --error-budget-policy=<ERROR_BUDGET_POLICY>
-
<SLO_CONFIG_FILE>
is the SLO config JSON file. -
<ERROR_BUDGET_POLICY>
is the Error Budget Policy JSON file.
Use slo-generator --help
to list all available arguments.
Usage in pipelines
Once the SLO measurement has been tested locally, it's a good idea to deploy a pipeline that will automatically compute SLO reports. This pipeline can be triggered on a schedule, or by specific events.
A few pipeline examples are given below.
Cloud Functions
slo-generator
is frequently used as part of an SLO Reporting Pipeline made of:
- A Cloud Scheduler triggering an event every X minutes.
- A PubSub topic, triggered by the Cloud Scheduler event.
- A Cloud Function, triggered by the PubSub topic, running
slo-generator
. - A PubSub topic to stream computation results.
Other components can be added to make results available to other destinations:
- A Cloud Function to archive SLO reports to BigQuery.
- A Cloud Function to export SLO and Burn Rate metrics (e.g: to Stackdriver Monitoring)
- A Stackdriver Monitoring Policy to alert on high budget Burn Rates.
Benefits:
-
Frequent SLO / Error Budget / Burn rate reporting (max 1 every minute) with Cloud Scheduler.
-
Real-time visualization by streaming results to DataStudio.
-
Historical analytics by analyzing SLO data in Bigquery.
-
Real-time alerting by setting up Stackdriver Monitoring alerts based on wanted SLOs.
The corresponding Terraform module to automate this setup can be found here.
Cloud Build
slo-generator
can also be triggered in a Cloud Build pipeline. This can be useful if we want to compute some SLOs as part of a release process (e.g: to calculate a metric on each git
commit or push)
To do so, you need to build an image for the slo-generator
and push it to Google Container Registry
in your project.
To build / push the image, run:
gcloud builds submit --config=cloudbuild.yaml . -s _PROJECT_NAME=<YOUR_PROJECT_NAME>
Once the image is built, you can call the Terraform generator using the following snippet in your cloudbuild.yaml
:
---
steps:
- name: gcr.io/${_PROJECT_NAME}/slo-generator
args: ['--slo-config', '${_SLO_CONFIG_FILE}', '--error-budget-policy', '${_ERROR_BUDGET_POLICY_FILE}']
Then, in another repo containing your SLO definitions, simply run the pipeline, substituting the needed variables:
gcloud builds submit . --config=cloudbuild.yaml --substitutions \
_SLO_CONFIG_FILE=<YOUR_SLO_CONFIG_FILE> \
_ERROR_BUDGET_POLICY_FILE=<_ERROR_BUDGET_POLICY_FILE> \
_WORKSPACE=<ENV>
If your repo is a Cloud Source Repository, you can also configure a trigger for Cloud Build, so that the pipeline is run automatically when a commit is made:
resource "google_cloudbuild_trigger" "dev-trigger" {
trigger_template {
branch_name = "dev"
repo_name = "my-repo"
}
substitutions = {
_SLO_CONFIG_FILE = "slo.json"
_ERROR_BUDGET_POLICY_FILE = "error_budget_policy.json"
_WORKSPACE = "dev"
}
filename = "cloudbuild.yaml"
}
resource "google_cloudbuild_trigger" "prod-trigger" {
trigger_template {
branch_name = "master"
repo_name = "my-repo"
}
substitutions = {
_SLO_CONFIG_FILE = "slo.json"
_ERROR_BUDGET_POLICY_FILE = "error_budget_policy.json"
}
filename = "cloudbuild.yaml"
}
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