As organizations continue to scale and adopt cloud-based solutions, identity and access management (IAM) becomes ever more important. Software as service (SaaS) tools are frequently deployed across an enterprise’s identity fabric to remediate emergent issues. In a modern setting, these IAM SaaS solutions have overtaken on-premise solutions as the cross-industry standard.
These platforms create workflows for access authorizations to downstream applications and other platforms. These systems process high volumes of data from identity stores, ensure secure user authentication, and manage lifecycles across distributed environments. However, handling high volumes of concurrent requests often creates threading constraints within these IAM solutions. Consequently, significant bottlenecks emerge, hampering efficiency and security.
Understanding and addressing these limitations is crucial for unlocking faster data flow and maintaining optimal performance. This is especially true in environments where high throughput and responsiveness are critical. This article explores how threading constraints manifest in popular IAM SaaS tools and provides strategies for optimizing performance.
Understanding Threading Constraints in IAM SaaS Solutions
Threading refers to the ability of a system or application to handle multiple tasks simultaneously by distributing them across several “threads” of execution. In IAM systems, threading is particularly important for a range of functions. These include processing authentication requests, managing tokens, synchronizing directories, and ensuring seamless data flows between identity sources, providers, and applications. However, threading limitations can lead to slowdowns, especially in high-traffic environments, as systems struggle to manage the concurrent requests efficiently. A real example: in a common identity governance and administration (IGA) platform, the identity attributes for 400,000 plus users were being aggregated from the active directory. This job would run more than 72 hours and never complete. The threading was found to be set to “1”. When optimization efforts set the threading to “6”, the job completed in under 16 hours.
Comparatively, in IGA systems, the Simeio team has started threading at a default value of 5. The team has seen this value increased to 15 or 16 based on needs. With “Client A,” the team did a 5, then a 12, then a 15 count for threads. Subsequently, the team saw performance increase drastically. Initially, pulling data from Microsoft Azure took 3 hours. However, after changing thread count to 15, the process took under 50 minutes.
Challenges that IAM SaaS Solutions must Solve
However, a lot can happen to a user’s identity lifecycle in 16 hours. Role or manager changes, employee status, requests for access – all these require workflow actions and reconciliations to/from downstream systems. In an access request for an in-scope Sarbanes-Oxley application (SOX), an approval by the wrong manager can lead to a control test failure. This occurs simply because of the reconciliation of the data (in this case a manager change) to the IGA tool. As a result, threading issues are not uncommon. However, robust IAM SaaS solutions can detect and address these issues in their entirety.
Common threading-related challenges in IAM systems include:
- Rate-limiting and throttling: Many IAM solution providers enforce rate limits to ensure fair use of resources, especially in multi-tenant environments. A properly implemented limiter avoids unnecessary restrictions on the number of concurrent threads handling authentication or API calls.
- Thread pool exhaustion: An IAM service can run out of available threads to process incoming requests. In this scenario, your IAM SaaS solution helps prevent slower response times or rejected requests.
- Synchronous versus asynchronous operations: Many IAM processes are handled synchronously, meaning that threads are held up until a task is completed. An IAM SaaS solution can help avoid delays in systems that rely heavily on real-time data processing.
Unlocking Faster Data Flow: Mitigation Strategies
While threading constraints can hinder IAM tool performance, several strategies can be employed to unlock faster data flow:
- Asynchronous Operations: Shift from synchronous to asynchronous operations wherever possible to prevent threads from being blocked by long-running tasks.
- Caching: Use caching for tokens and authentication data to reduce the number of real-time validation requests. This frees up threads for other operations.
- Horizontal Scaling: Deploy additional instances or nodes to handle high concurrency, distributing the load across multiple regions or availability zones.
- Rate-Limit Optimization: Review and optimize API usage patterns to stay within rate limits. Additionally, reduce the frequency of API calls during high-traffic periods.
- Thread Pool Tuning: Ensure thread pools are properly sized and optimized for handling the expected load, particularly during peak periods of concurrent authentication.
- Work with your solution integrator and tool vendor: Engage vendors before the solution tenants are deployed and configured. This ensures proper configuration and tuning in lower environments and production. Thus, enterprises ensure the expected data and lifecycle events are processed in a timely manner.
Conclusion
Threading constraints in IAM SaaS tools can significantly impact performance, particularly in high-traffic environments or during critical identity operations. By understanding these limitations and implementing best practices such as asynchronous processing, caching, and horizontal scaling, organizations can unlock faster data flow and maintain optimal performance. As IAM solutions continue to evolve, addressing threading constraints will remain an important factor in ensuring secure, scalable, and responsive identity management systems.
Reach out to Simeio now and learn how our team provide the best IAM SaaS Solutions on the market.
Written by Mike Bickford.
