slo-generator 1.3.0

SLO Generator

SLO Generator

slo-generator is a tool to compute and export Service Level Objectives (SLOs), Error Budgets and Burn Rates, using policies written in JSON or YAML format.

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 defined as BURN_RATE = ERROR_BUDGET / ERROR_BUDGET_TARGET

Local usage

Requirements

• Python 3

Installation

slo-generator is published on PyPI. To install it, run:

pip3 install slo-generator

Run the slo-generator

slo-generator -f <SLO_CONFIG_PATH> -b <ERROR_BUDGET_POLICY> --export

• <SLO_CONFIG_PATH> is the SLO config file or folder. If a folder path is passed, the SLO configs filenames should match the pattern slo_*.yaml to be loaded.

• <ERROR_BUDGET_POLICY> is the Error Budget Policy file.

• --export enables exporting data using the exporters defined in the SLO configuration file.

Use slo-generator --help to list all available arguments.

Notes:

• To enable debug logs, set the environment variable DEBUG to 1.
• To enable colorized output (local usage), set the environment variable COLORED_OUTPUT to 1.

Configuration

The slo-generator requires two configuration files to run, the SLO configuration file and the Error budget policy file.

SLO configuration

The SLO configuration (JSON or YAML) is composed of the following fields:

• SLO metadata:

  • slo_name: Name of this SLO.
  • slo_description: Description of this SLO.
  • slo_target: SLO target (between 0 and 1).
  • service_name: Name of the monitored service.
  • feature_name: Name of the monitored subsystem.

• SLI configuration:

  • backend: Specific documentation and examples are available for each supported backends:
    • Stackdriver Monitoring
    • Stackdriver Service Monitoring
    • Prometheus
    • ElasticSearch
    • Datadog
    • Dynatrace

• Exporter configuration:
  • exporters: A list of exporters to export results to. Specific documentation is available for each supported exporters:
    • Cloud Pub/Sub to stream SLO reports.
    • BigQuery to export SLO reports to BigQuery for historical analysis and DataStudio reporting.
    • Stackdriver Monitoring to export the error_budget_burn_rate metric to Stackdriver Monitoring.
    • Prometheus to export the error_budget_burn_rate metric to Prometheus.
    • Datadog to export the error_budget_burn_rate metric to Datadog.
    • Dynatrace to export the custom:error_budget_burn_rate metric to Dynatrace.

Note: you can use environment variables in your SLO configs by using ${} syntax to avoid having sensitive data in version control. Environment variables will be replaced at run time.

==> An example SLO configuration file is available here.

Error Budget policy

The Error Budget policy (JSON or YAML) is a list of multiple error budgets, each one composed of the following fields:

• window: Rolling time window for this error budget.
• alerting_burn_rate_threshold: Target burnrate threshold over which alerting is needed.
• urgent_notification: boolean whether violating this error budget should trigger a page.
• overburned_consequence_message: message to show when the error budget is above the target.
• achieved_consequence_message: message to show when the error budget is within the target.

==> An example Error Budget policy is available here.

More documentation

To go further with the SLO Generator, you can read:

• Build an SLO achievements report with BigQuery and DataStudio

• Deploy the SLO Generator on Google Cloud Functions (Terraform)

• Deploy the SLO Generator on Kubernetes (Alpha)

• Deploy the SLO Generator in a CloudBuild pipeline

• Contribute to the SLO Generator