Splunk APM offers comprehensive observability and troubleshooting capabilities for production environments. With full trace analysis and a no-trace-left-behind dashboard, it helps your team identify even the sneakiest anomalies.
The AI-driven analytics and directed troubleshooting feature allows for quick identification and resolution of issues by correlating system performance data. Splunk APM also supports OpenTelemetry, providing you with flexibility and avoiding vendor lock-in. Continuous code profiling enables the identification of service bottlenecks and resource optimization opportunities.
In addition, Splunk APM offers:
- Full-stack observability and efficient error detection and troubleshooting.
- Real-time ingestion, analysis, and storage of all data at any scale.
- NoSample™ trace ingestion so no anomaly goes undetected, and immediate feedback on releases is provided.
- Tag Spotlight event correlation with tag values, offering a centralized understanding of trace behavior.
- Grouping of end-to-end traces based on common services or tags to track business workflows.
- Smart dynamic alerting to set alerts based on thresholds, changes, or historical anomalies.
- Always On code profiling analyzes code-level performance to troubleshoot bottlenecks and optimize performance in both cloud-native and monolithic applications.
Application monitoring use cases with Splunk APM
Splunk recommends following the Prescriptive Adoption Motion: Application Monitoring. This guide walks you step-by-step through implementing a best-practice application performance monitoring program.
- Assessing the financial impact of eCommerce checkout errors
- How to use Splunk software to assess financial loss incurred from an outage, by looking for differences in payment trends around the time of the problem.
- Creating SLOs and tracking error budgets with SignalFlow
- How to use SignalFlow to better understand your service-level objective needs and performance.
- Optimizing performance in canary development environments with Splunk APM's custom MetricSets
- You can use use Splunk APM MetricSets to identify and respond to frequent microservice code releases, helping you to optimize your APM operations.
- Prescriptive Adoption Motion - Application Monitoring
- APM solves problems faster in monolith and microservice application architectures by detecting problems from deployments, troubleshooting the source of an issue, and optimizing service performance.
- Troubleshooting a service latency issue related to a database query
- How to troubleshoot latency issues with a service which may be the root cause of digital experience, service performance, or other SLI (Service Level Indicator) deviations.
- Troubleshooting code bottlenecks
- Identify and isolate code bottlenecks with Splunk software, allowing you to perform code profiling with minimal overhead.
- Troubleshooting database performance
- When monitoring the performance of a DB instance in Infrastructure Monitoring, you need to navigate to Splunk APM to determine what services are contributing to infrastructure high resource usage or a performance issue.
- Using OpenTelemetry annotations to lower MTTR
- Learn how to use annotations to associate your captured measurements to provide contextual information about your distributed workloads.