Based on the provided knowledge sources, I can offer some insights into potential causes and debugging approaches for slow identity registration in Ory Kratos. The main reason for this issue is likely related to password hashing, specifically when using Argon2. According to the [Ory Kratos Debug Documentation](https://www.ory.sh/docs/kratos/debug/performance-out-of-memory-password-hashing-argon2), there are common errors that indicate your Argon2 parameters need adjustment: 1. Very slow login and registration requests, which might cause network timeouts. 2. Ory Kratos failing with a "fatal error: runtime: out of memory" message. 3. The host environment (Minikube, Docker, or Kubernetes) crashing or becoming unresponsive. To debug and resolve this issue, you can try the following steps: 1. Reduce the resources used by Argon2 or increase the resources available to Kratos. 2. Use the [Argon2 calibrate CLI](https://www.ory.sh/docs/kratos/cli/kratos-hashers-argon2-calibrate) to detect the best practice values for your server. It's important to note that the calibration should be done under the exact same conditions that the server runs at. The documentation also mentions that Ory Kratos comes with a CLI tool that automatically calibrates the Argon2 values, following best practices. You can read more about these best practices in their [blog post about choosing recommended Argon2 parameters for password hashing](https://www.ory.sh/choose-recommended-argon2-parameters-password-hashing/). By adjusting these parameters, you should be able to optimize the performance of identity registration in Ory Kratos.

I apologize for the confusion in my previous answer. Thank you for clarifying that you're using BCrypt instead of Argon2. Let's address your concern about slow identity registration with BCrypt in Ory Kratos. While BCrypt doesn't have the same performance issues as Argon2, it can still impact the speed of registration and login processes. Here are some insights based on the provided knowledge sources: 1. BCrypt Cost: Ory Kratos uses BCrypt to obfuscate secrets of OAuth 2.0 Clients. The performance depends on the BCrypt cost, which can be set using the environment variable

BCRYPT_COST

. According to the [Performance and benchmarks documentation](https://www.ory.sh/docs/ecosystem/benchmark), for their benchmarks, they've set

BCRYPT_COST=8

. 2. Character Limit: BCrypt has a maximum length of 72 bytes for passwords. As mentioned in the [BCrypt secret length troubleshooting guide](https://www.ory.sh/docs/troubleshooting/bcrypt-secret-length), "BCrypt hashed passwords and secrets have a 72 character limit. This is a limitation of the BCrypt algorithm and the Golang BCrypt library." While this doesn't directly cause slowness, it's an important factor to be aware of. 3. Debugging Approach: To debug the slow registration process, you might want to: - Check your

BCRYPT_COST

setting and consider lowering it if it's set too high. - Monitor your system resources during registration to see if there are any bottlenecks. - Use logging or profiling tools to identify where the slowdown is occurring in the registration process. 4. Configuration Check: Review your Kratos configuration to ensure there are no misconfigurations causing the slowdown. The [Kratos configuration documentation](https://www.ory.sh/docs/kratos/reference/configuration) might be helpful for this. If you're still experiencing significant slowdowns after checking these factors, it might be worth investigating other parts of your system or considering reaching out to the Ory community for more specific assistance, as the provided knowledge sources don't contain more detailed information about BCrypt-specific performance issues in Kratos.

According to the knowledge sources provided, for self-hosted Ory Kratos, the default password hashing algorithm is BCrypt, not Argon2. This information can be found in the [Ory Kratos password configuration documentation](https://www.ory.sh/docs/self-hosted/kratos/configuration/password), which states: "Per default, passwords are hashed using BCrypt." If you want to use Argon2id instead of BCrypt, you would need to explicitly configure it in your Kratos configuration file. The documentation provides an example of how to set up Argon2id:

yaml hashers:   argon2:     parallelism: 1     memory: 128MB     iterations: 3     salt_length: 16     key_length: 32

It's important to note that if you decide to switch to Argon2id, you should carefully consider the parameters to ensure a balance between security and performance. Ory provides a CLI tool to help calibrate these parameters for your specific environment, as mentioned in the [Argon2 password hashing parameters guide](https://www.ory.sh/docs/kratos/guides/setting-up-password-hashing-parameters).

Based on the information provided in the knowledge sources and your previous interactions, it seems that you've already explored the most common causes of slow registration related to password hashing. Since you've mentioned that subsequent calls are faster, there might be other factors at play. Unfortunately, the knowledge sources don't provide specific information about this particular scenario. However, I can suggest a few potential areas to investigate: 1. Cold Start: The first request might be slow due to a "cold start" phenomenon, where the system needs to initialize various components. This is not explicitly mentioned in the provided sources for Kratos, but it's a common issue in many systems. 2. Database Connections: The first request might be establishing database connections, which could cause a delay. Subsequent requests would reuse these connections, explaining the faster response times. 3. Caching: There might be some caching mechanism that's not warmed up on the first request but benefits subsequent requests. 4. External Service Calls: If your registration process involves calls to external services (e.g., for email verification), these might be slower on the first request. 5. JIT (Just-In-Time) Compilation: If you're running in an environment that uses JIT compilation, the first request might trigger this process, causing a delay. To further debug this issue, you might want to: 1. Use profiling tools to identify where exactly the slowdown is occurring during the first request. 2. Check your logs for any warnings or errors that might be causing delays. 3. Monitor system resources (CPU, memory, I/O) during the first and subsequent requests to see if there are any significant differences. If the issue persists, you might want to reach out to the Ory community or support channels with more detailed logs and profiling information, as the provided knowledge sources don't contain enough information to definitively identify the cause of this specific behavior.

To get more information about how Kratos is spending its time in fulfilling requests, you can utilize distributed tracing. Ory Kratos supports distributed tracing, which can provide valuable insights into the performance and behavior of your system. Here's what you can do: 1. Enable Distributed Tracing: According to the [Ory documentation on distributed tracing](https://www.ory.sh/docs/self-hosted/operations/tracing), you can configure Distributed Tracing (DT) in Kratos. This will allow you to obtain a visualization of the call paths that take place to process a request. The documentation states: "Configuring Distributed Tracing (DT) will enable you to obtain a visualization of the call paths that take place in order to process a request made to Ory. It's yet another tool that you can use to aid you in profiling, debugging and ultimately understanding your deployment of Ory better." 2. Use Tracing Tools: Once you've enabled distributed tracing, you can use tools compatible with the OpenTelemetry standard to visualize and analyze the traces. This will give you a detailed breakdown of how Kratos is spending its time during request processing. 3. Analyze Logs: While not as detailed as distributed tracing, analyzing Kratos logs can also provide valuable information. The log entries contain timestamps and details about various operations, which can help identify bottlenecks. For example, in the [log output provided in one of the issues](https://github.com/ory/kratos/issues/4161), you can see detailed timing information for each request:

time=2024-10-17T11:08:23Z level=info msg=completed handling request ... took:2.981164ms]

These log entries can help you identify which parts of the request handling process are taking the most time. 4. Use Profiling Tools: While not explicitly mentioned in the provided knowledge sources for Kratos, using Go's built-in profiling tools or third-party profilers can provide detailed information about CPU and memory usage, which can help identify performance bottlenecks. By implementing these methods, particularly distributed tracing, you should be able to get a much clearer picture of how Kratos is spending its time in fulfilling requests, allowing you to identify and address any performance issues more effectively.

Based on the knowledge sources provided, I can give you information about the configuration options for Kratos DSN (Data Source Name). The DSN is used to specify the database connection details for Ory Kratos. Ory Kratos supports several database options for data storage and persistence. Here are the main DSN configuration options: 1. In-memory (ephemeral): To use in-memory storage, set the DSN configuration key to "memory":

DSN=memory

This is useful for quick setups but remember that all data is ephemeral and will be removed when the service is stopped [Deployment Fundamentals and Requirements](https://www.ory.sh/docs/self-hosted/deployment). 2. SQLite: For SQLite, the DSN should be prefixed with "sqlite://". For example:

DSN=sqlite:///tmp/some-db.sqlite?_fk=true

Note that the

_fk=true

parameter is required for foreign keys to work [Deployment Fundamentals and Requirements](https://www.ory.sh/docs/self-hosted/deployment). 3. PostgreSQL: For PostgreSQL, the DSN should be prefixed with "postgres://". For example:

DSN=<postgres://user:password@host:123/database>

PostgreSQL supports additional parameters like

max_conns

,

max_idle_conns

,

max_conn_lifetime

,

sslmode

, etc. [Deployment Fundamentals and Requirements](https://www.ory.sh/docs/self-hosted/deployment). 4. MySQL: While not explicitly shown in the provided sources, MySQL is supported. The DSN format would be similar to PostgreSQL but with a "mysql://" prefix. 5. CockroachDB: For CockroachDB, the DSN should be prefixed with "cockroach://". For example:

DSN=<cockroach://user:password@host:123/database>

CockroachDB also supports additional parameters like

sslmode

,

application_name

, etc. [Deployment Fundamentals and Requirements](https://www.ory.sh/docs/self-hosted/deployment#cockroachdb). When setting up Kratos, you can specify the DSN in your configuration file or as an environment variable. For example, in a Docker setup, you might see something like this:

yaml environment:   - DSN=<postgres://kratos:secret@postgresd:5432/kratos?sslmode=disable&max_conns=20&max_idle_conns=4>

Remember to choose the appropriate DSN based on your database setup and requirements. Also, it's crucial to run SQL migrations when setting up or upgrading your database, which can be done using the

kratos migrate sql

command [Kratos migrate sql](https://www.ory.sh/docs/kratos/cli/kratos-migrate-sql).