How Production Traffic Replication Works

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Observe

Speedscale can observe traffic through a variety of means such as sidecars, Postman collections, or even on your local desktop. Data is sanitized for security, so no sensitive data is used.

Analyze

Speedscale then intelligently parameterizes key fields such as timestamps, unique IDs, and customer/order IDs in order to replace them with realtime values during traffic replay for flexible, no-code reuse. Tokenization can be customized. Collected traffic can be browsed, filtered and selected in the Traffic Viewer to auto-generate tests and mocks from.

Replay

These containerized “Snapshots” can then be replayed anywhere (even on your laptop with no kubernetes cluster), an unlimited number of times. A Snapshot is essentially a traffic generator, a collection of mocks, or both!  Traffic within snapshots can be multiplied, sped up or slowed down. Responses from the Mock pod can also be configured for 404’s, latency, and network black holes.

Installation Options

Speedscale’s Operator and Sidecars for listening can be installed via Helm, CRD, or annotations. We also have a CLI *speedctl* that can be installed and used to automate many install, record, and replay tasks.  We also have a variety of integrations.
Install Speedscale service

API Observability

Since Speedscale observes traffic, this data can be leveraged to debug new releases, perform root-cause analysis in staging environments and understand runtime API behavior. PII and sensitive data redaction included.

Real-time replacement of key fields and dates

Speedscale can automatically detect and mock your dependencies.

Service mocks are simulators that accept outbound requests from your app and mimic responses coming back from 3rd parties. 

Speedscale mocks contain PII-redacted, sanitized traffic so you don’t need to worry about sensitive data being used.

				
					"chaos": {
     "chaosPercent":25,
     "badStatusCodes": true,
     "intermittentResponses": true,
     "randomLatency": true,
     "randomHighLatencyMs": 5000
     }
				
			

Performance, regression and
chaos test without multiple tools

Traffic replay pods are ran locally in your clusters by a Kubernetes operator for traffic replay.

Test results are logged and sent to Speedscale for analysis and reporting. Pods are cleaned up afterward to return the cluster to the original state.

See How Speedscale Works

speedscale traffic viewer
Introduction When running tests in a CI/CD pipeline, relying on external APIs can introduce instability, slow down execution, a...
Developing APIs can often be a complex web of dependencies, external dependencies, and murky network traffic. In order to build...

How Production Traffic Replication Works

Observe

Speedscale can observe traffic through a variety of means such as sidecars, Postman collections, or even on your local desktop. Data is sanitized for security, so no sensitive data is used.

Analyze

Speedscale then intelligently parameterizes key fields such as timestamps, unique IDs, and customer/order IDs in order to replace them with realtime values during traffic replay for flexible, no-code reuse. Tokenization can be customized. Collected traffic can be browsed, filtered and selected in the Traffic Viewer to auto-generate tests and mocks from.

Replay

These containerized “Snapshots” can then be replayed anywhere (even on your laptop with no kubernetes cluster), an unlimited number of times. A Snapshot is essentially a traffic generator, a collection of mocks, or both!  Traffic within snapshots can be multiplied, sped up or slowed down. Responses from the Mock pod can also be configured for 404’s, latency, and network black holes.

Installation Options

Speedscale’s Operator and Sidecars for listening can be installed via Helm, CRD, or annotations. We also have a CLI *speedctl* that can be installed and used to automate many install, record, and replay tasks.  We also have a variety of integrations.
Install Speedscale service

API Observability

Since Speedscale observes traffic, this data can be leveraged to debug new releases, perform root-cause analysis in staging environments and understand runtime API behavior. PII and sensitive data redaction included.

Real-time replacement of key fields and dates

Speedscale can automatically detect and mock your dependencies.

Service mocks are simulators that accept outbound requests from your app and mimic responses coming back from 3rd parties. 

Speedscale mocks contain PII-redacted, sanitized traffic so you don’t need to worry about sensitive data being used.

				
					"chaos": {
     "chaosPercent":25,
     "badStatusCodes": true,
     "intermittentResponses": true,
     "randomLatency": true,
     "randomHighLatencyMs": 5000
     }
				
			

Performance, regression and
chaos test without multiple tools

Traffic replay pods are ran locally in your clusters by a Kubernetes operator for traffic replay. Test results are logged and sent to Speedscale for analysis and reporting. Pods are cleaned up afterward to return the cluster to the original state.

See How Speedscale Works

speedscale traffic viewer

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