An Introduction to Mistral Workflows in OpenStack

Mistral is OpenStack’s workflow automation service that simplifies cloud operations by turning manual tasks into automated workflows. Mistral works closely with other OpenStack services, which can help you manage your cloud more consistently and make better use of resources.

Here’s a quick look at what Mistral offers:

What It Does

• Defines Workflows: You write workflows using YAML, a straightforward syntax.
• Manages Tasks: It can automate many common cloud jobs, like creating virtual machines, setting up networks, or adjusting resources based on specific conditions.
• Tracks Progress: Mistral keeps an eye on how your workflows are running, helps deal with errors if they pop up, and logs what happened for later review.
• Connects with OpenStack: It can directly control compute, network, storage, and security parts of your OpenStack cloud.

Why It’s Useful

• Helps cut down on mistakes by making processes repeatable.
• Can assist in using resources more carefully, potentially reducing costs.
• Makes cloud management a bit simpler by giving you a central place to handle automated tasks.

Typical Uses

• Automatically setting up new resources (like firing up instances or configuring networks).
• Scheduling regular maintenance jobs.
• Changing the number of resources up or down based on current demand.

For anyone using OpenStack, Mistral can be a valuable tool for making cloud operations smoother and more dependable, plus less reliant on manual work.

Mistral’s Core Components and Functions

Mistral is built around a few key ideas to make automation work well.

Basic Parts

• Workflows: Think of these as the main plans or containers that hold all the individual steps (tasks) and define how they relate to each other.
• Tasks: These are the individual actions within a workflow, like creating a server or updating a security group.
• Transitions: These are the rules that guide how a workflow moves from one task to the next, often based on whether a task succeeded or failed.

Main Capabilities

• YAML for Workflow Definitions: You define workflows in YAML. This makes it fairly easy for administrators to write, read, and change automation sequences without needing deep programming knowledge.
• State Tracking: Mistral carefully records the state of everything happening in a workflow. This includes:
  • The status of each task (e.g., running, success, error).
  • The data passed into and out of tasks.
  • Information for error handling and points where a workflow can recover.
  • A history of executions for any audits.
• OpenStack Service Interaction: Mistral uses OpenStack’s standard APIs to communicate with other services. This allows your workflows to:
  • Manage virtual machines and other compute resources.
  • Adjust network settings.
  • Perform storage operations.
  • Work with security rules and groups.

How Workflows Run

Mistral follows a clear process to run automations reliably:

• Task Scheduling: Before a task runs, Mistral checks any dependencies on other tasks and any conditions that need to be met.
• Resource Handling: The engine makes sure the necessary OpenStack resources are available for a task.
• Progress Monitoring: As tasks run, their progress and state are constantly updated and logged.
• Error Management: If something goes wrong, Mistral detects it, and based on the workflow definition, can try to fix it or halt the process gracefully.

This structured way of working is important when you start designing your own YAML workflows.

Understanding Workflow Structure

Mistral workflows are all about YAML. This format lets you lay out each step of your automation clearly.

Setting Up a Workflow in YAML

Here’s a simple example of what a Mistral YAML file might look like:

version: '2.0'
workflow_name: sample_workflow
type: direct # or 'reverse'
input:
- parameter1
- parameter2
tasks:
task1:
action: std.echo
input:
output: "Starting workflow with {{ $.parameter1 }}"
publish:
my_message: "Workflow started"
on-success:
- task2

task2:
action: nova.servers_create
input:
name: "test-server-{{ $.parameter2 }}"
image: "your_image_id"
flavor: "your_flavor_id"
# ... other server parameters

Important Parts of a Workflow Definition:

• version: Specifies the Mistral DSL (Domain Specific Language) version, usually ‘2.0’.
• workflow_name: A unique name for your workflow.
• type: Defines how tasks in the workflow are structured. direct workflows have tasks that explicitly name their next steps. reverse workflows have tasks that list which tasks must complete before they can start.
• input: A list of parameters the workflow expects when it starts.
• tasks: This section contains the definitions for each task, including what action it performs and how it transitions to other tasks.

Task Types and Actions

Mistral provides different actions that tasks can perform to get things done in your cloud.

Standard Actions (from the ‘std’ action pack):

• std.echo: Useful for outputting messages, often for debugging.
• std.http: Lets you send HTTP/HTTPS requests to any web service.
• std.mistral_http: Similar to std.http, but specifically for making authenticated API calls to the Mistral API itself or other services using Mistral’s authentication.

OpenStack Actions (examples for common services):

• nova.servers_create: Creates a new compute instance (VM).
• neutron.create_network: Sets up a new network.
• glance.images_list: Lists available images.
• Many other actions are available for services like Cinder (storage), Heat (orchestration), Keystone (identity), etc.

Tasks can also handle mapping inputs and outputs, define what to do on errors, set up retry attempts, and check results.

Managing Your Workflows

Once workflows are written, you need to manage their execution and monitoring.

Controlling Execution: You can start workflows with specific inputs and keep an eye on them as they run. For instance, you might trigger a workflow like this (conceptually, often done via API call or CLI):

# This is a conceptual representation of an execution request
workflow_execution_request:
workflow_name: server_provision
input:
server_name: "production-1"
image_ref: "ubuntu-latest-image-uuid"
flavor_ref: "medium-flavor-uuid"

Starting Workflows (Triggers): Workflows can be kicked off in a few ways:

• Scheduled: Using cron-like expressions for regular intervals.
• Event-Based: Triggered by events from other OpenStack services (e.g., a new image upload in Glance) via services like Aodh or Ceilometer.
• Manual: Directly through an API call or the Mistral CLI.

Monitoring Capabilities: Mistral gives you ways to see what’s happening:

• Tracking executions in real-time.
• Viewing the state of individual tasks.
• Gathering metrics on performance.
• Accessing logs for troubleshooting if errors occur.

The Mistral engine keeps records of every execution. This helps administrators see how tasks are progressing, find and fix any slow spots or problems, use logs to figure out why something failed, and adjust workflows to make them run better over time.

Common Ways to Use Mistral

Mistral workflows are handy for taking care of routine cloud tasks, especially in OpenStack.

Examples of Standard Workflows

Mistral helps make repetitive OpenStack jobs consistent and dependable.

Automating Resource Setup:

• Launching virtual machines with specific configurations.
• Creating networks and applying security groups.
• Attaching and preparing storage volumes.
• Deploying and configuring load balancers.

Example: Maintenance Snapshot Workflow Snippet

This snippet shows tasks that might be part of a larger maintenance workflow to snapshot servers.

# Inside a larger workflow definition
tasks:
list_project_servers:
action: nova.servers_list
publish:
server_ids: "{{ task(list_project_servers).result.servers.select(s -> s.id).list() }}"
on-success:
- create_snapshots
create_snapshots:
# This would typically be a 'for-each' type construct or a sub-workflow
# to iterate over server_ids and create snapshots.
# For simplicity, imagine an action that can take a list.
action: nova.servers_action_create_image # Conceptual action for batch snapshots
input:
server_ids: "{{ $.server_ids }}"
snapshot_name_prefix: "auto_backup_"

(Note: Actual batch snapshot logic might involve looping or sub-workflows depending on the complexity and specific actions available.)

Example: Basic Scaling Logic Snippet

This conceptual snippet shows how you might check a metric and decide to scale.

# Inside a larger workflow definition
tasks:
get_cpu_load:
action: aodh.metric_aggregation_get # Or a similar Ceilometer/Aodh action
input:
metric: 'cpu_util'
# ... other parameters like resource_id, period
publish:
current_load: "{{ task(get_cpu_load).result.some_aggregated_value }}"
on-success:
- decide_to_scale
decide_to_scale:
# This task would use an expression or call another action (e.g., std.condition)
# to check if {{ $.current_load }} exceeds a threshold.
# Based on the outcome, it would transition to a 'scale_up_action' or finish.
action: std.noop # Placeholder for decision logic
on-success:
- condition: "{{ $.current_load > 75 }}"
tasks:
- scale_up_action # Name of the task that actually scales

Advantages of Using Workflows

Thierry Carrez, General Manager at the Open Infrastructure Foundation, has noted the value of OpenStack in providing flexible infrastructure. Mistral builds on this by automating the management of that infrastructure.

Here’s how automating with Mistral can help:

Other Useful Aspects:

• Running Tasks in Parallel: Mistral can run multiple tasks at the same time if they don’t depend on each other.
• Handling Errors: You can define how workflows react to and recover from failures.
• Managing Dependencies: Workflows can correctly order tasks that rely on others.
• Versioning Workflows: You can keep track of changes to workflows and roll back if needed.

Setting Up Mistral

Here’s a general guide to getting Mistral installed and configured. For detailed instructions, always refer to the official OpenStack documentation for your specific OpenStack release.

Installation Outline

Typically, you’ll need to:

1. Install Packages: Install mistral-api, mistral-engine, mistral-executor, and the python3-mistralclient on the appropriate controller or service nodes. Package names might vary slightly by Linux distribution.
2. Configure Database:
   • Create a database for Mistral (e.g., in MySQL/MariaDB).
   • Grant appropriate permissions to a ‘mistral’ user for this database.
   • Populate the database schema using Mistral’s tools (mistral-db-manage upgrade head).
3. Set Up Authentication with Keystone:
   • Create a ‘mistral’ user and assign it the ‘admin’ role in a service project (e.g., ‘service’ project).
   • Create the Mistral service entry and API endpoints (public, internal, admin) in Keystone.
4. Configure Mistral (mistral.conf): Update /etc/mistral/mistral.conf with your database connection details and Keystone authentication settings. Here’s an example snippet:

   [database]
   connection = mysql+pymysql://mistral:YOUR_DB_PASSWORD@controller_ip/mistral
   
   [keystone_authtoken]
   www_authenticate_uri = http://controller_ip:5000
   auth_url = http://controller_ip:5000
   memcached_servers = controller_ip:11211 # If using memcached
   auth_type = password
   project_domain_name = Default
   user_domain_name = Default
   project_name = service
   username = mistral
   password = YOUR_MISTRAL_USER_PASSWORD

5. Start Mistral Services: Start the mistral-api and mistral-engine services and ensure they are enabled to start on boot.

Once these steps are done and services are running, you should be able to create and run workflows.

Creating a Basic Workflow

Here’s an example of a simple workflow to deploy a new Nova instance:

version: '2.0'
deploy_basic_instance:
description: 'A simple workflow to deploy a new server.'
type: direct
input:
- instance_name: 'my-first-mistral-vm'
- flavor_id
- image_id
- network_id # The UUID of the network to connect to
tasks:
create_server:
action: nova.servers_create
input:
name: "{{ $.instance_name }}"
flavor: "{{ $.flavor_id }}"
image: "{{ $.image_id }}"
nics:
- net-id: "{{ $.network_id }}"
publish:
server_id: "{{ task(create_server).result.id }}"
server_status: "{{ task(create_server).result.status }}"
on-success:
- wait_for_server_active
on-error:
- report_failure # Another task you could define
wait_for_server_active:
action: nova.servers_get
input:
id: "{{ $.server_id }}"
retry:
delay: 10 # seconds
count: 30 # retry 30 times (5 minutes total)
on-success:
- condition: "{{ task(wait_for_server_active).result.status == 'ACTIVE' }}"
tasks:
- report_success # A task to indicate success
- condition: "{{ task(wait_for_server_active).result.status == 'ERROR' }}"
tasks:
- report_failure # A task to indicate failure
# Define report_success and report_failure tasks if needed, e.g., using std.echo
report_success:
action: std.echo
input:
output: "Server {{ $.server_id }} successfully created and is ACTIVE."
report_failure:
action: std.echo
input:
output: "Failed to create server or server went into ERROR state."

This workflow defines steps to create a server and then wait for it to become active. You would adapt the inputs and task details for your environment.

Tips for Setup and Use

Dealing With Errors:

Performance Thoughts:

• Organize Tasks: Group related operations logically. For very complex sequences, consider breaking them into smaller, linked workflows.
• Clean Up: Make sure workflows have paths to clean up resources if tasks fail midway, to avoid leaving orphaned resources.
• Monitoring: Check the Mistral logs (usually in /var/log/mistral/) for detailed information. mistral-engine.log and mistral-api.log are key. Configure log rotation to manage disk space.

Testing Your Workflows:

• Start with simple workflows to get a feel for how Mistral works and to catch issues early.
• Use the Mistral client’s validation command (mistral workflow-validate my_workflow.yaml) to check your YAML syntax and basic structure before uploading.
• Run workflows in a non-production environment first.
• Keep an eye on OpenStack service logs (Nova, Neutron, etc.) as your workflows interact with them.
• Review execution logs in Mistral (mistral execution-get <id>, mistral task-list <execution_id>) to understand what happened.

Wrapping Up – Mistral Workflows in OpenStack

Mistral helps manage complex sequences of tasks in OpenStack, making cloud administration more automated and consistent. By working with OpenStack’s core services, it allows organizations to get more from their infrastructure with less manual intervention. Many find Mistral useful for reducing hands-on work and making better use of cloud resources.

The Direction of Cloud Automation

Mistral continues to be an important part of OpenStack automation. Its development often focuses on:

• Smarter Resource Use: Better ways to schedule and manage how infrastructure is used.
• Cost Management: Helping to achieve savings by automating processes.
• Improved Operations: Making cloud management less of a burden.

Automation with tools like Mistral can lead to noticeable gains in efficiency and potential cost savings. Combined, Mistral and OpenStack give organizations a strong toolkit for managing their cloud infrastructure.

OpenMetal + Mistral

OpenMetal provides a platform for quickly deploying OpenStack-powered private clouds, which can simplify how you manage Mistral workflows. Our production-ready hosted private clouds can be launched super quickly (in under a minute), giving businesses a ready environment for their automation.

Using Mistral workflows on OpenMetal’s infrastructure can offer some practical benefits. Our fixed-cost approach to private clouds means that as your automation needs grow, your base infrastructure costs remain predictable.

Here are a just a few of the ways our infrastructure makes a great foundation for effective Mistral workflows:

These aspects can make it easier to get started with and scale your Mistral automations. Our engineering team can provide advice for setting up configurations, aiming for good automation performance without unexpected expenses. If you’re ready to get started exploring or building your Mistral workflows on OpenMetal, get in touch!