Besu Logging: Reduce Verbosity For Clearer Chain Sync
Hey guys! Let's dive into a crucial discussion about improving the clarity of Besu's chain syncing logs. Currently, the logs are super noisy, making it tough to track the sync progress. We need to find ways to throttle the logging or adjust the logging levels so we can actually follow what's happening. Imagine trying to debug a complex issue when you're drowning in log messages – not fun, right? So, let's explore how we can make these logs more user-friendly and efficient.
Understanding the Current Logging Issue in Besu
Currently, Besu's chain syncing logging is producing a high volume of log messages, which can make it challenging to monitor and understand the synchronization process. The verbosity of these logs often obscures the critical information that developers and system administrators need to effectively track progress and troubleshoot issues. This section aims to break down the core problem with the current logging system and set the stage for potential solutions. To understand the issue, let's delve deeper into the kind of log messages that are generated. You'll see a lot of entries like these:
{"@timestamp":"2025-08-12T06:04:13,472","level":"INFO","thread":"EthScheduler-Services-41 (downloadSyncBodies)","class":"CompleteSyncBlocksTask","message":"Requesting bodies to complete 200 blocks, starting with 3491706.","throwable":""}
{"@timestamp":"2025-08-12T06:04:13,472","level":"INFO","thread":"EthScheduler-Services-41 (downloadSyncBodies)","class":"CompleteSyncBlocksTask","message":"Requesting bodies to complete 200 blocks, starting with 3491906.","throwable":""}
{"@timestamp":"2025-08-12T06:04:13,472","level":"INFO","thread":"EthScheduler-Services-41 (downloadSyncBodies)","class":"CompleteSyncBlocksTask","message":"Requesting bodies to complete 200 blocks, starting with 3492106.","throwable":""}
...
As you can see, there's a ton of similar messages flooding the logs, making it difficult to pick out the important stuff. These messages, while informative, are generated so frequently that they create a wall of text. This deluge makes it hard to spot any actual errors, warnings, or significant events during the syncing process. The problem is compounded when you're trying to diagnose issues in real-time. Sifting through this noise to find the root cause of a problem can be incredibly time-consuming and frustrating. Imagine you're dealing with a stalled sync or a network hiccup – you need clear, concise information to quickly identify and resolve the problem. With the current logging level, that's a tall order.
Moreover, the excessive logging has performance implications. Writing a large volume of log messages to disk consumes system resources, which can affect the overall performance of the Besu node. This is particularly critical in resource-constrained environments or during periods of heavy network activity. We need to strike a balance between providing enough information for debugging and minimizing the performance overhead of logging. Another key aspect is the readability and interpretability of the logs. While the JSON format is structured and machine-readable, it's not the most human-friendly format for quick scanning. When you're troubleshooting, you want to be able to glance at the logs and immediately grasp the situation. The current verbosity combined with the JSON format makes this challenging. In essence, the core issue is that the current logging level in Besu generates too much noise, hindering effective monitoring, troubleshooting, and potentially impacting performance. To enhance clarity and usability, we need to explore strategies to reduce this verbosity without losing critical information. This sets the stage for discussing potential solutions such as throttling, adjusting logging levels, and perhaps even introducing more sophisticated log aggregation and analysis tools. The goal is to make Besu's logs a valuable asset rather than a hindrance during chain synchronization.
Strategies to Reduce Logging Verbosity
So, what can we do about all this log noise? Let's explore some effective strategies to reduce the verbosity of chain syncing logs in Besu and make them more manageable. Our goal is to strike a balance between having enough information for debugging and avoiding an overwhelming flood of messages. There are primarily two approaches we can consider: throttling the logs and adjusting the logging levels. Each method has its own set of advantages and considerations, so let's break them down. First up, throttling. Throttling involves limiting the frequency of log messages, even if the underlying events are still occurring rapidly. This can be particularly useful for repetitive messages, like the "Requesting bodies to complete..." examples we saw earlier. Instead of logging every single request, we could throttle these messages to, say, once every few seconds or even minutes. This would drastically reduce the volume of logs without completely suppressing the information. There are several ways to implement throttling. One approach is to introduce a timer within the logging mechanism. The logger would record the timestamp of the last message and only emit a new message if a certain time interval has passed. Another approach is to use a counter. The logger would track the number of messages generated within a time window and only log a subset of them, perhaps one out of every N messages. The specific throttling strategy can be tailored to the type of log message. For example, we might choose a more aggressive throttling for informational messages and a less aggressive one for warnings or errors.
The second strategy is adjusting the logging levels. Most logging frameworks, including the one used by Besu, support different levels of logging, such as DEBUG, INFO, WARN, and ERROR. By default, Besu might be configured to log at the INFO level, which includes a lot of routine information. We could reduce the verbosity by increasing the logging level to WARN or ERROR. This would suppress the informational messages and only log warnings and errors, which are typically more critical for troubleshooting. However, adjusting the logging level is a bit of a blunt instrument. While it can significantly reduce verbosity, it also means we might miss some useful information. For instance, if we set the level to WARN, we won't see any INFO messages, even if they could help us understand the syncing process. Therefore, it's essential to carefully consider the trade-offs before changing the logging level. A more nuanced approach might involve adjusting the logging levels for specific components or classes within Besu. This would allow us to target the most verbose parts of the system without affecting other areas. For example, we could reduce the logging level for the CompleteSyncBlocksTask class, which generates a lot of the "Requesting bodies..." messages, while keeping the logging level for other components at INFO. In addition to throttling and adjusting logging levels, there are other techniques we could explore. One is to aggregate log messages. Instead of logging each individual event, we could collect them over a period of time and then log a summary message. For example, we could track the number of blocks requested and the number of blocks received within a minute and then log a single message with those statistics. This would reduce the log volume while still providing valuable information. Another technique is to use structured logging. Structured logging involves formatting log messages in a consistent, machine-readable format, such as JSON. This makes it easier to analyze the logs using automated tools and dashboards. While structured logging doesn't directly reduce verbosity, it can make the logs more manageable and useful, even at high volumes. By combining these strategies, we can significantly reduce the verbosity of Besu's chain syncing logs and make them more effective for monitoring and troubleshooting. The key is to experiment with different approaches and find the right balance for our specific needs.
Implementing Throttling in Besu: A Practical Approach
Okay, so we've talked about the theory behind throttling, but how do we actually implement throttling in Besu? Let's get practical and explore a step-by-step approach. Implementing throttling involves modifying Besu's codebase to limit the frequency of certain log messages. This typically involves identifying the most verbose log statements and adding logic to control how often they are emitted. The first step is to pinpoint the specific log messages that are causing the most noise. We already know that messages from the CompleteSyncBlocksTask class, like the "Requesting bodies to complete..." entries, are a major culprit. But it's worth doing a more thorough analysis to identify other potential sources of verbosity. We can use log analysis tools or even simple grep commands to search through the logs and count the occurrences of different message patterns. Once we've identified the target log statements, we need to decide on a throttling strategy. As mentioned earlier, we can use a timer-based approach or a counter-based approach. A timer-based approach is generally simpler to implement and is suitable for messages that don't need to be logged with perfect regularity. A counter-based approach is more precise but requires more careful handling to avoid missed messages. For our example, let's assume we're going to use a timer-based approach to throttle the "Requesting bodies..." messages. This means we'll keep track of the last time we logged the message and only log it again if a certain time interval has passed. The next step is to modify the Besu codebase. We'll need to find the CompleteSyncBlocksTask class and locate the log statements that generate the "Requesting bodies..." messages. Then, we'll add the throttling logic around these statements. Here's a simplified example of how we might implement this in Java (this is illustrative and might not be the exact code you'd use in Besu):
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.time.Instant;
import java.time.Duration;
public class CompleteSyncBlocksTask {
private static final Logger LOG = LoggerFactory.getLogger(CompleteSyncBlocksTask.class);
private static final Duration THROTTLE_INTERVAL = Duration.ofSeconds(5); // Log every 5 seconds
private Instant lastLogTime = Instant.MIN;
public void requestBodies(long startBlock, int count) {
Instant now = Instant.now();
if (Duration.between(lastLogTime, now).compareTo(THROTTLE_INTERVAL) >= 0) {
LOG.info("Requesting bodies to complete {} blocks, starting with {}.", count, startBlock);
lastLogTime = now;
}
}
}
In this example, we've added a THROTTLE_INTERVAL constant that specifies the minimum time between log messages (5 seconds in this case). We also have a lastLogTime variable that tracks the timestamp of the last log message. Before logging the message, we check if the time since the last log message is greater than or equal to the THROTTLE_INTERVAL. If it is, we log the message and update lastLogTime. If not, we skip the log message. This simple logic effectively throttles the "Requesting bodies..." messages, ensuring that they are logged no more than once every 5 seconds. Of course, this is a simplified example. In a real-world implementation, we'd need to consider things like thread safety, configuration options, and more sophisticated throttling strategies. We might also want to apply different throttling intervals to different types of log messages. Once we've implemented the throttling logic, it's crucial to test it thoroughly. We need to ensure that the throttling is working as expected and that we're not missing any critical log messages. We can do this by running Besu with the modified code and observing the logs. We should see a significant reduction in the number of "Requesting bodies..." messages, but we should still see them occasionally, especially during periods of heavy syncing activity. We should also monitor the overall behavior of Besu to ensure that the throttling hasn't introduced any performance issues or other unexpected side effects. In summary, implementing throttling in Besu involves identifying verbose log messages, choosing a throttling strategy, modifying the codebase, and testing the changes. By carefully applying these steps, we can significantly reduce log verbosity and make Besu's logs more manageable and useful.
Adjusting Logging Levels: A More Selective Approach
Alright, let's shift gears and talk about another strategy for taming those verbose logs: adjusting logging levels. This approach is all about being selective with the information we capture, filtering out the noise and focusing on what truly matters. As we touched on earlier, most logging frameworks, including the one Besu uses, support different logging levels. These levels typically include DEBUG, INFO, WARN, and ERROR, each representing a different level of severity or importance. The key idea behind adjusting logging levels is to set a threshold. We only capture messages at or above that level. For example, if we set the logging level to WARN, we'll only see warning and error messages, effectively suppressing informational and debug messages. This can drastically reduce the volume of logs, making it easier to spot critical issues. To understand how this works in practice, let's consider Besu's default logging configuration. By default, Besu likely logs at the INFO level. This means we see a lot of informational messages, like the "Requesting bodies..." entries, as well as warnings and errors. While these informational messages can be helpful for debugging, they often create a lot of noise, as we've discussed. To reduce this noise, we could increase the logging level to WARN. This would suppress the informational messages and only show us warnings and errors. This can be a quick and easy way to cut down on log verbosity, but it's important to understand the trade-offs. By raising the logging level, we might miss some valuable information. Informational messages can sometimes provide context or clues that help us diagnose problems. If we only see warnings and errors, we might not have the full picture. So, how do we strike the right balance? One approach is to adjust logging levels selectively for different components or classes within Besu. Instead of setting a single logging level for the entire system, we can configure different levels for specific parts of the code. This allows us to target the most verbose areas without affecting other parts. For example, we could set the logging level for the CompleteSyncBlocksTask class to WARN, while keeping the logging level for other components at INFO. This would suppress the "Requesting bodies..." messages while still capturing other informational messages that might be useful. To implement selective logging level adjustments, we typically need to modify Besu's logging configuration file. The exact format of this file depends on the logging framework being used, but it usually involves specifying logging levels for different loggers, which correspond to classes or packages in the codebase. Here's a hypothetical example of what a logging configuration file might look like:
log4j.rootLogger=INFO, console
log4j.logger.org.hyperledger.besu.sync.CompleteSyncBlocksTask=WARN
log4j.appender.console=org.apache.log4j.ConsoleAppender
log4j.appender.console.layout=org.apache.log4j.PatternLayout
log4j.appender.console.layout.ConversionPattern=%d{yyyy-MM-dd HH:mm:ss} %-5p %c{1}:%L - %m%n
In this example, we've set the root logger to INFO, but we've explicitly set the logger for org.hyperledger.besu.sync.CompleteSyncBlocksTask to WARN. This means that messages from that class will only be logged if they are warnings or errors. When adjusting logging levels, it's crucial to test the changes thoroughly. We need to ensure that we're still capturing the information we need to troubleshoot problems, while also reducing the noise. We can do this by running Besu with the modified logging configuration and observing the logs. We should see a reduction in the number of log messages, but we should also be able to spot any critical issues that arise. It's also a good idea to document the logging level adjustments we've made. This will help us understand why we made those changes and make it easier to revert them if necessary. Adjusting logging levels is a powerful tool for reducing log verbosity, but it requires careful consideration and testing. By selectively adjusting logging levels for different components, we can strike a balance between capturing the information we need and avoiding an overwhelming flood of messages. Remember, the goal is to make Besu's logs a valuable resource for monitoring and troubleshooting, not a source of frustration.
Combining Throttling and Logging Levels for Optimal Clarity
Okay, so we've explored throttling and adjusting logging levels as individual strategies. But what if we combine them? That's where things get really interesting! By combining throttling and logging levels, we can achieve an even more refined and effective approach to managing log verbosity in Besu. Think of it like this: adjusting logging levels is like setting a broad filter, while throttling is like fine-tuning the flow. We can use logging levels to filter out entire categories of messages (e.g., suppressing INFO messages), and then use throttling to control the frequency of specific messages within the remaining categories. For example, we might set the overall logging level to INFO, but then apply throttling to the "Requesting bodies..." messages, as we discussed earlier. This would allow us to capture most informational messages while preventing the "Requesting bodies..." messages from overwhelming the logs. The key to combining these strategies effectively is to think about the specific needs of our monitoring and troubleshooting efforts. What information is most critical? What messages are generating the most noise? How frequently do we need to see certain messages? By answering these questions, we can tailor our logging configuration to provide the optimal balance of information and clarity. Let's consider a practical scenario. Suppose we're running a Besu node in a production environment, and we want to monitor its syncing progress. We need to know if the node is keeping up with the network, and we want to be alerted if there are any issues. However, we don't want to be bombarded with log messages that don't directly indicate a problem. In this scenario, we might start by setting the overall logging level to INFO. This will ensure that we capture most informational messages, which can be helpful for understanding the node's behavior. However, we know that the "Requesting bodies..." messages are particularly verbose, so we'll apply throttling to those messages. We might configure the throttling to log these messages no more than once every 5 seconds, as we demonstrated earlier. In addition to throttling the "Requesting bodies..." messages, we might also consider adjusting the logging level for other specific components. For example, if we're particularly concerned about network connectivity issues, we might increase the logging level for the network-related classes to DEBUG. This would give us more detailed information about network events, which could help us diagnose problems. On the other hand, if we're not particularly interested in the details of transaction processing, we might decrease the logging level for the transaction-related classes to WARN. This would suppress most transaction-related messages, reducing the overall log volume. The specific logging configuration we choose will depend on our priorities and the characteristics of our environment. It's important to experiment with different settings and monitor the logs to ensure that we're capturing the information we need without being overwhelmed by noise. When combining throttling and logging levels, it's also crucial to document our configuration choices. We should clearly explain why we've chosen certain logging levels and throttling settings, and we should keep this documentation up-to-date as our needs evolve. This will help us and others understand our logging strategy and make informed decisions about future adjustments. In summary, combining throttling and logging levels is a powerful way to optimize Besu's logging configuration. By carefully selecting logging levels and applying throttling to specific messages, we can achieve a balance of information and clarity that meets our specific monitoring and troubleshooting needs. Remember, the goal is to make the logs a valuable tool for understanding and managing our Besu nodes, not a source of confusion and frustration. So, let's get those logs under control!
Next Steps and Community Collaboration
Alright, guys, we've covered a lot of ground on how to reduce the verbosity of chain syncing logging in Besu! We've looked at the problem, explored strategies like throttling and adjusting logging levels, and even discussed how to combine them for optimal clarity. So, what's next? The next step is to put these ideas into action and start making some real improvements to Besu's logging. This is where community collaboration comes in! We need to work together to identify the most effective solutions and implement them in a way that benefits everyone. One of the first things we can do is start experimenting with different logging configurations. Try out different logging levels and throttling settings in your own Besu deployments, and see what works best for you. Share your experiences and findings with the community. What settings did you use? What impact did they have on log verbosity and clarity? Did you encounter any unexpected side effects? The more we share our experiences, the better we can understand the trade-offs and identify the best practices. Another important step is to contribute to Besu's codebase. If you have the skills and the time, consider implementing some of the throttling or logging level adjustments we've discussed. You could start by submitting a pull request with a simple change, such as adding throttling to the "Requesting bodies..." messages. Or, you could tackle a more complex task, such as implementing a configurable logging level for different components. Any contribution, big or small, is valuable. To facilitate community collaboration, we can use various channels, such as the Hyperledger Besu Discord server, the GitHub issues and pull requests, and community calls. These channels provide opportunities to discuss ideas, ask questions, share code, and coordinate efforts. Let's use them effectively to move this initiative forward. In addition to code contributions, we can also contribute by providing feedback, reporting bugs, and suggesting improvements. If you encounter a logging-related issue in Besu, don't hesitate to report it. The more information we have about the problems, the better we can address them. And if you have ideas for how to improve Besu's logging, share them! Your suggestions could spark a valuable discussion and lead to a significant improvement. As we move forward, it's important to remember that reducing log verbosity is an ongoing process. We'll likely need to revisit our logging configuration periodically and make adjustments as our needs evolve. New features and improvements in Besu might introduce new logging patterns, and we'll need to adapt our strategies accordingly. So, let's make this a collaborative and iterative effort. By working together, we can make Besu's logs a valuable asset for everyone in the community. Let's make sure that our logs are clear, concise, and informative, so we can focus on building and running awesome decentralized applications!
