Collect Redis server logs
Ingest Redis server log output including startup messages, warnings, and runtime errors generated by standalone and clustered Redis instances.
Redis Operational Logs for Memory and Cluster Health
Track command execution, memory events, durability operations, and cluster synchronization in real time.
Challenges
Monitor Redis logs and operational events in production environments
Track persistence and snapshot events
Analyze Redis log entries related to RDB snapshots and AOF rewrites to understand persistence behavior and disk I/O impact.
Monitor replication and failover
Capture Redis replication logs to detect replica synchronization issues, role changes, and failover events in high-availability setups.
Detect memory pressure signals
Surface Redis log warnings related to maxmemory limits, eviction policies, and out-of-memory conditions before service degradation.
Observe key eviction and expiration
Inspect Redis log messages that indicate key eviction, expired keys processing, and cache behavior under load.
Analyze client connection issues
Identify Redis client connection errors, authentication failures, and timeout-related log entries affecting application access.
Correlate logs with runtime metrics
Link Redis log events with metrics such as memory usage, command throughput, and latency to investigate performance anomalies.
Support clustered Redis deployments
Aggregate logs from Redis Cluster nodes and sentinel-managed environments into a centralized operational view.
Command Execution and Keyspace Activity
- Track log generation across command execution, key access, and data operations to understand runtime behavior in Redis workloads.
- Correlate command logs with application requests and cache usage patterns to trace read and write activity.
- Identify failed commands, blocked operations, and abnormal key access affecting cache responsiveness.
- Detect disruptions in keyspace activity impacting application performance and data availability.
Memory Management and Persistence Signals
- Capture logs related to memory usage, eviction policies, and persistence operations such as RDB and AOF.
- Correlate memory pressure with eviction events, write failures, and cache saturation patterns.
- Identify recurring persistence failures caused by disk I/O constraints or configuration issues.
- Detect hidden risks affecting durability, data recovery, and cache stability.
Replication and Cluster Behavior
- Analyze replication logs, synchronization activity, and cluster communication events across Redis nodes.
- Correlate replication lag and failover behavior with workload spikes and infrastructure conditions.
- Identify recurring node synchronization failures and cluster instability affecting high availability.
- Detect operational disruptions impacting distributed cache reliability and scaling..
Security and Access Monitoring
- Track authentication attempts, unauthorized commands, and suspicious access patterns captured in Redis logs.
- Identify misuse patterns such as abnormal command frequency or unauthorized key modifications.
- Correlate Redis activity with application and network logs for incident investigation.
- Detect security risks and operational anomalies affecting Redis environments.
Why Atatus
Why choose Atatus for Redis logs monitoring?
01
Redis-native log insights
Atatus ingests and interprets Redis server logs including persistence events, replication changes, and runtime warnings.
02
Cache performance clarity
Atatus helps teams investigate evictions, cache misses, and latency spikes using log-driven signals.
03
High-availability visibility
Atatus surfaces replication and sentinel events to track failovers and cluster health.
04
Faster operational diagnosis
Atatus centralizes Redis logs across environments to speed up incident troubleshooting.
05
High-throughput ready
Atatus processes heavy Redis log volumes without impacting performance.
06
Modern deployment coverage
Atatus aggregates Redis logs across VMs, containers, and cloud Redis environments.
Teams
Unified Observability for Every Engineering Team
Atatus adapts to how engineering teams work across development, operations, and reliability.
Developers
Debug errors and slow paths with the full context of what happened.
Atatus for developersDevOps
Track deployments and see how each release affects stability.
Atatus for DevOpsRelease engineers
Watch latency and error rates to ship with less production risk.
Atatus for release engineers
FAQ
Frequently Asked Questions
Pricing, deployment, data and the agent. If something is missing, a person will answer it on a demo call.
Log monitoring in Atatus allows you to gain insights into the behavior of your Redis applications by collecting and analyzing log data. It helps identify issues, track performance, and troubleshoot errors, leading to improved application reliability and performance.
You can send Redis logs to Atatus by integrating the Atatus Agent with your Redis application. The Atatus Agent supports various logging libraries, such as Log4j, Winston, Bunyan and so on. By configuring the agent and updating your application's logging configuration, you can seamlessly send logs to Atatus.
Atatus supports multiple log levels, including INFO, DEBUG, WARN, and ERROR. You can configure your Redis application to log messages at different levels, allowing you to filter and analyze logs based on severity.
Yes, Atatus enables you to set up alerts based on specific log patterns or occurrences. By creating custom log-based metrics or using predefined log query filters, you can define alert conditions and receive notifications when certain log events match the specified criteria.
Yes, Atatus supports distributed tracing for Redis applications. By instrumenting your code with the Atatus tracing library, you can trace requests and transactions across distributed components, gaining insights into the entire application's performance.
Log data parsing prioritizes customer security by meticulously anonymizing Personally Identifiable Information (PII) data. Sensitive fields can be completely excluded during the parsing process, ensuring the privacy and compliance of customer information.
In Redis Logs Monitoring, log pipelines are customizable workflows that allow users to filter, parse, and fine-tune log data based on specific criteria.
Log pipelines can be customized by using diverse filters and defining custom parsing rules. Users have the flexibility to configure pipelines to meet their specific monitoring requirements, ensuring that log data is processed and organized according to their preferences.
Yes, log pipelines can be configured to filter log data based on various attributes such as log source, severity, timestamp, or any custom field. This customization allows users to focus on specific aspects of log data that are most relevant to their monitoring goals.
Saved Views in Redis Logs Monitoring enable you to create and save custom configurations for different troubleshooting scenarios. This feature simplifies collaboration, allows for quick context switching, and automates repetitive tasks, significantly improving overall efficiency.
If you exceed your log ingestion limits, we would contact you to discuss on stopping further processing new log data or upgrade your subscription.
You can choose to store logs in Atatus for a limited time (e.g., 7 days) or export them to external storage solutions like Amazon S3 for long-term retention.
To access historical log data beyond the retention period, you can rely on log data exports from Amazon S3, where you can push the logs into Atatus for further analysis.
Yes, Atatus provides users with the flexibility to customize log retention settings. Users can adjust retention periods based on their specific needs, aligning with compliance standards or internal data management policies.