Deployments, when managed with Infrastructure as Code(IaC), face a fundamental challenge: they cannot be performed concurrently or in parallel due to Terraform state locks. These locks, while ensuring consistency by preventing simultaneous modifications to shared state, also create bottlenecks that slow down deployment processes. This article explores the technical challenges of managing parallel deployments with IaC, why splitting Terraform projects isn’t scalable (as detailed in our dedicated blog), and the innovations developed to address these challenges.
The Problem: Terraform Locks and Deployment Queues
Sequential Deployments
Terraform’s state locking mechanism ensures that only one operation can modify the infrastructure state at a time. While this guarantees consistency, it introduces significant delays:
State Locking: Terraform locks its remote state file (e.g., in AWS S3) during operations to prevent concurrent modifications.
Queue Formation: If multiple teams or services need to deploy updates, they must wait in a sequential queue for the lock to be released.
Impact on Productivity: Developers and operations teams face delays, reducing agility in high-frequency deployment environments.
Example Scenario
Team A updates Service X, locking the Terraform state.
Team B, needing to update Service Y, is blocked until Team A’s operation completes.
As the number of services grows, this sequential process increases deployment times exponentially.
Splitting Terraform into smaller projects is often proposed as a solution to avoid these queues. However, as detailed in Why a Unified Terraform Project is the Way to Seamless Operations, such approaches introduce their own challenges, including fragmented state management and complex dependency orchestration.
Facets' Technical Innovation: Breaking the Queue
Facets tackled this issue head-on by introducing Parallel Releases (Parallel Terraform applies), a feature that redefines how deployments interact with Terraform’s locking mechanism and shared infrastructure. This innovation allows multiple releases to occur concurrently without compromising consistency or safety.
Key Innovations in Parallel Releases
Remote State Plan Generation
How It Works: Deployment plans are generated directly from the remote state with the lock disabled. This ensures plans are accurate and consistent without locking the state.
Purpose: Avoids conflicts during plan generation while maintaining visibility into the current state.
Scoped Plan Validation
How It Works: Deployment plans are validated to ensure they only target specific services, such as those managed by Helm charts.
Purpose: Prevents unintended changes to shared infrastructure.
Fallback: If validation fails, deployments revert to using the locked remote state for added safety to ensure consistency.
Service-Specific Isolation
How It Works: Releases are isolated to individual services by running a Terraform-targeted operation. This ensures that changes are scoped specifically to the desired service without affecting shared infrastructure or unrelated services.
Purpose: Prevents resource conflicts and ensures parallel operations are safe and consistent.
Post-Release State Sync
How It Works: State syncing is deferred to scheduled maintenance windows, ensuring remote states are updated without relying on the local state.
Purpose: Decouples operational state changes from deployment-specific workflows.
Selective Locking
How It Works: Locks are retained only for shared infrastructure components—service-specific configurations bypass locks, enabling parallelism.
Purpose: Balances safety for critical resources with flexibility for service-level updates.
Helm Integration for Rollbacks
How It Works: Helm provides robust rollback mechanisms for service configurations.
Purpose: Enables quick recovery from failures without affecting other services or releases.
Benefits of Parallel Releases
Reduced Deployment Time:
Developers can deploy multiple services simultaneously, eliminating queues and accelerating the application of infrastructure changes.
Improved Scalability:
Teams can handle a growing number of microservices without introducing deployment bottlenecks.
Enhanced Reliability:
Helm’s rollback capabilities ensure safe and consistent deployments, even during failures.
Better Developer Experience:
By removing the need to wait for queued releases, developers can focus on delivering value rather than managing deployment conflicts.
Adopting Scoped Locking: Key Takeaways
Based on our learnings from addressing Terraform state lock bottlenecks and improving deployment workflows, here’s how teams can implement a similar strategy:
Modular Plan Generation Without Global Locks:
Generate deployment plans from the remote Terraform state with locks disabled. This prevents unnecessary contention and allows teams to proceed with plan generation concurrently.
Scoped Plan Validation:
Validate the Terraform plan to ensure it only targets the intended modules (e.g., services deployed as Helm charts) and does not affect shared infrastructure.
If validation fails, revert to using the locked remote state.
Local State for Apply Operations:
Always perform terraform apply using a local copy of the Terraform state whenever locks are disabled. This prevents race conditions during simultaneous updates.
State Syncing During Maintenance:
Defer syncing of the remote state until maintenance operations by running terraform refresh during scheduled intervals.
Terraform:
Retain locks only for shared infrastructure components while enabling module-specific updates to proceed independently.
Conclusion
Facets’ Parallel Releases demonstrate a cutting-edge solution to overcoming deployment bottlenecks caused by Terraform state locks and shared dependencies. Organizations can achieve faster, safer, and more scalable deployments by leveraging scoped operations, selective locking, and Helm integrations. For teams struggling with Terraform queues, these innovations offer a blueprint to unlock efficiency and agility in their workflows while maintaining the consistency Terraform is known for.
