AVR (Analytics) Profile in BIG-IP LTM
The AVR (Analytics and Visibility Reporting) profile in BIG-IP LTM is used to monitor and analyze application traffic. It provides real-time visibility into traffic patterns, application performance, and user interactions. The AVR profile collects valuable metrics for assessing the health and efficiency of the application and helps in optimizing both server-side and client-side performance.
Traffic Sampling vs. Detailed Metrics
When Traffic Sampling is enabled in the AVR profile, it affects the availability of certain detailed metrics and features. Specifically, enabling traffic sampling means that instead of logging detailed information for every transaction, a sample of traffic is captured. This can reduce the performance overhead of continuously tracking detailed application metrics, but it also limits access to certain granular features.
When Traffic Sampling is Enabled:
The following options are NOT available:
Traffic Capturing Logging Type:
This option allows capturing detailed logs of traffic flows, which includes all interactions and transactions in the application. With traffic sampling enabled, capturing every transaction is bypassed, as the system only analyzes a subset of traffic.
User Sessions:
User session tracking is disabled. This feature monitors and tracks the number of sessions for users, their session durations, and activities. When traffic sampling is active, this level of detail is not captured.
Server Latency:
Server Latency refers to how long it takes for the BIG-IP system to receive data from the application server. When traffic sampling is enabled, this metric is not available, as sampling only collects partial traffic data and may not provide full insights into the latency experienced between the application server and the BIG-IP system.
Page Load Time:
Page Load Time tracks the amount of time it takes for an application user to receive a complete response from the application after making a request. When traffic sampling is enabled, this data point is unavailable, as sampling only provides partial insight into user interactions.
Overview of Key Metrics Impacted by Traffic Sampling:
Metric
Impact of Traffic Sampling Enabled
Traffic Capturing Logging
Not available. Traffic logs will only include sampled data, not the full set.
User Sessions
Not available. User session information is not tracked with traffic sampling.
Server Latency
Not available. Latency data between the application server and BIG-IP is omitted.
Page Load Time
Not available. Full user response time is not tracked when sampling is enabled.
Benefits of Traffic Sampling:
Reduced Overhead: Traffic sampling allows for less system resource consumption as only a portion of the traffic is captured and analyzed.
Faster Performance: Because not all traffic is logged and analyzed, enabling traffic sampling ensures that the BIG-IP system does not become overwhelmed with too much data, helping to maintain overall system performance.
Trade-offs of Traffic Sampling:
Reduced Granularity: You lose some of the detailed analytics such as session tracking, server latency, and page load time.
Potential Incomplete Data: With sampled traffic, you might miss specific interactions or transactions that could otherwise provide valuable insights into performance bottlenecks or issues.
Use Cases for Traffic Sampling:
Traffic sampling is most useful when:
Large Traffic Volumes: When dealing with massive amounts of traffic, enabling traffic sampling ensures that the system doesn't get bogged down by logging every single request, yet still provides useful insights based on a sample.
General Trends Analysis: Sampling is appropriate when you’re more interested in broad trends and overall traffic patterns rather than precise, transaction-level data.
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