- Observability: other versions:
- Get started
- What is Elastic Observability?
- What’s new in 8.17
- Quickstart: Monitor hosts with Elastic Agent
- Quickstart: Monitor your Kubernetes cluster with Elastic Agent
- Quickstart: Monitor hosts with OpenTelemetry
- Quickstart: Unified Kubernetes Observability with Elastic Distributions of OpenTelemetry (EDOT)
- Quickstart: Collect data with AWS Firehose
- Add data from Splunk
- Applications and services
- Application performance monitoring (APM)
- Get started
- Learn about data types
- Collect application data
- View and analyze data
- Act on data
- Use APM securely
- Manage storage
- Configure APM Server
- Monitor APM Server
- APM APIs
- Troubleshooting
- Upgrade
- Release notes
- Known issues
- Synthetic monitoring
- Get started
- Scripting browser monitors
- Configure lightweight monitors
- Manage monitors
- Work with params and secrets
- Analyze monitor data
- Monitor resources on private networks
- Use the CLI
- Configure projects
- Multi-factor Authentication
- Configure Synthetics settings
- Grant users access to secured resources
- Manage data retention
- Use Synthetics with traffic filters
- Migrate from the Elastic Synthetics integration
- Scale and architect a deployment
- Synthetics support matrix
- Synthetics Encryption and Security
- Troubleshooting
- Real user monitoring
- Uptime monitoring (deprecated)
- Tutorial: Monitor a Java application
- Application performance monitoring (APM)
- CI/CD
- Cloud
- Infrastructure and hosts
- Logs
- Troubleshooting
- Incident management
- Data set quality
- Observability AI Assistant
- Reference
Dependencies
editDependencies
editAPM agents collect details about external calls made from instrumented services. Sometimes, these external calls resolve into a downstream service that’s instrumented — in these cases, you can utilize distributed tracing to drill down into problematic downstream services. Other times, though, it’s not possible to instrument a downstream dependency — like with a database or third-party service. Dependencies gives you a window into these uninstrumented, downstream dependencies.
Many application issues are caused by slow or unresponsive downstream dependencies. And because a single, slow dependency can significantly impact the end-user experience, it’s important to be able to quickly identify these problems and determine the root cause.
Select a dependency to see detailed latency, throughput, and failed transaction rate metrics.
When viewing a dependency, consider your pattern of usage with that dependency. If your usage pattern hasn’t increased or decreased, but the experience has been negatively effected — either with an increase in latency or errors, there’s likely a problem with the dependency that needs to be addressed.
If your usage pattern has changed, the dependency view can quickly show you whether that pattern change exists in all upstream services, or just a subset of your services. You might then start digging into traces coming from impacted services to determine why that pattern change has occurred.
Operations
editThis functionality is in beta and is subject to change. The design and code is less mature than official GA features and is being provided as-is with no warranties. Beta features are not subject to the support SLA of official GA features.
Dependency operations provides a granular breakdown of the operations/queries a dependency is executing.
Selecting an operation displays the operation’s impact and performance trends over time, via key metrics like latency, throughput, and failed transaction rate. In addition, the Trace sample timeline provides a visual drill-down into an end-to-end trace sample.
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