Use it when you want to begin orchestration work without writing the first draft from scratch.
Data Contracts and SLA Management AI Prompt
Implement data contracts and SLA management for data products in this cloud platform. Data producers: {{producers}} Data consumers: {{consumers}} Current issues: {{issues}} (sch... Copy this prompt template, run it in your AI tool, and use related prompts to continue the workflow.
Implement data contracts and SLA management for data products in this cloud platform.
Data producers: {{producers}}
Data consumers: {{consumers}}
Current issues: {{issues}} (schema breaking changes, missed SLAs, undocumented changes)
1. What is a data contract:
A data contract is a formal agreement between a data producer (team that writes the data) and data consumers (teams that read it). It specifies:
- Schema: column names, types, and semantic meaning
- Quality: expected null rates, value distributions, referential integrity
- SLA: freshness (max hours since last update), availability (uptime %)
- Versioning: how schema changes are communicated and backward compatibility
2. Data contract specification (YAML):
apiVersion: v1
kind: DataContract
id: orders.v1
producer: payments-team
owner: payments-data@company.com
schema:
- name: order_id
type: bigint
nullable: false
unique: true
- name: amount_usd
type: numeric(10,2)
nullable: false
minimum: 0
sla:
freshness_hours: 2
availability_percent: 99.5
versioning:
current: 1.2.0
breaking_change_policy: 30-day notice required
3. Tooling:
- Data Contract CLI (open-source): validate data against contracts, publish to catalog
- Soda Core: run quality checks defined in contracts
- dbt + Elementary: enforce schema contracts via model contracts; test quality via tests
4. SLA monitoring:
- Freshness check: query MAX(updated_at) per table; alert if > SLA threshold
- Availability: monitor pipeline success rate; alert on consecutive failures
- Quality score: % of tests passing per data product; publish in the catalog
- SLA breach report: weekly report of SLA breaches per team, with trend
5. Governance process:
- Contract registration: new data products must register a contract before GA
- Breaking change process: 30-day notice + migration guide for all consumers
- Deprecation: deprecated products sunset after 90 days with active consumer notification
Return: data contract YAML schema, tooling recommendation, SLA monitoring implementation, and governance process.When to use this prompt
Use it when you want a more consistent structure for AI output across projects or datasets.
Use it when you want prompt-driven work to turn into a reusable notebook or repeatable workflow later.
Use it when you want a clear next step into adjacent prompts in Orchestration or the wider Cloud Data Engineer library.
What the AI should return
The AI should return a structured result that covers the main requested outputs, such as What is a data contract:, Schema: column names, types, and semantic meaning, Quality: expected null rates, value distributions, referential integrity. The final answer should stay clear, actionable, and easy to review inside a orchestration workflow for cloud data engineer work.
How to use this prompt
Open your data context
Load your dataset, notebook, or working environment so the AI can operate on the actual project context.
Copy the prompt text
Use the copy button above and paste the prompt into the AI assistant or prompt input area.
Review the output critically
Check whether the result matches your data, assumptions, and desired format before moving on.
Chain into the next prompt
Once you have the first result, continue deeper with related prompts in Orchestration.
Frequently asked questions
What does the Data Contracts and SLA Management prompt do?+
It gives you a structured orchestration starting point for cloud data engineer work and helps you move faster without starting from a blank page.
Who is this prompt for?+
It is designed for cloud data engineer workflows and marked as advanced, so it works well as a guided starting point for that level of experience.
What type of prompt is this?+
Data Contracts and SLA Management is a single prompt. You can copy it as-is, adapt it, or use it as one step inside a larger workflow.
Can I use this outside MLJAR Studio?+
Yes. The prompt text works in other AI tools too, but MLJAR Studio is the best fit when you want local execution, visible Python code, and reusable notebooks.
What should I open next?+
Natural next steps from here are Cloud Orchestration with Airflow, Infrastructure as Code for Data, Pipeline Observability and Monitoring.