Remote Analytics Agent Sizing

This page describes how to estimate the hardware requirements for a remote Analytics Agent deployment where a single Analytics Agent is aggregating transaction events from multiple application agents. This page describes transaction analytics only.

You should consider these two questions when sending analytics data to a remote Analytics Agent:

  • How many agents can report to one remote Analytics Agent?
  • What are the machine requirements for hosting the remote Analytics Agent?
Note: Do not extract the numbers on this page to size for Log Analytics because you must install the Analytics Agent on the local machine to capture Log Analytics.

Analytics Agent Sizing Based on Event Volume

Based on our testing, the volume of events being sent to the Analytics Agent is the limiting factor in determining how many agents can report to one remote Analytics Agent.

The tests were conducted on virtual hardware and programmatically generated workload. Real-world workloads may vary. To best estimate your hardware sizing requirements, carefully consider the traffic patterns in your application and test in a test environment that closely resembles your production application and user activity.

Calculate Analytics Event Volume

One business transaction can traverse many tiers. In each tier, one business transaction traverses one node. One node produces one request per business transaction when the transaction is synchronous. For async transactions, multiple events may be generated by a node for a single request. One request equals one analytics event. To calculate how many events a business transaction generates, you need to count the number of tiers/nodes that are sending data into the Analytics Agent.

You can estimate the number of events using the following formula:

One business transaction generates events at a rate = calls per minute times the number of tiers reporting analytics data for the business transaction.

In simple terms: #events for one business transaction = calls per minute times # of tiers.

Characteristics of the Amazon EC2 Instance Types

For complete information on Amazon EC2 instance types, see https://aws.amazon.com/ec2/instance-types/.

The testing was performed using c3.large, c3.xlarge, and c4.4xlarge.

Model vCPU Mem (GiB) SSD Storage  (GB)
c3.large 2 3.75 2 x 16
c3.xlarge 4 7.5 2 x 40
c4.4xlarge 16 30 EBS-Only

Test Results

Raw Data

Analytics Agent Host Machine Analytics Agent events/min Total CPU% JVM Heap(Mb)
c3.large 52313 17% 468
c3.large 54831 17% 470
c3.large 70746 24% 475
c3.large 74541 24% 477
c3.large 77344 23% 487
c3.large 97074 28% 512
c3.large 115999 36% 519
c3.large 139143 43% 526
c3.large 148782 47% 587
c3.large 204073 65% 527
c3.large 247543 80% 624
c3.large 249261 81% 637
c3.xlarge 196288 33% 518
c3.xlarge 254586 44% 727
c3.xlarge 302689 51% 497
c3.xlarge 336879 58% 913
c3.xlarge 372515 65% 1024
c3.xlarge 513598 91% 922
c3.xlarge 478954 78% 922
c3.xlarge 420000 69% 979
c3.xlarge 376034 61% 1024
c3.xlarge 318000 52% 1024
c3.xlarge 258000 43% 1024
c3.xlarge 198000 32% 1024
c3.xlarge 144000 22% 1024
c4.4xlarge 534900 17% 552
c4.4xlarge 604725 19% 841
c4.4xlarge 716141 23% 1024