Software Telemetry by Jamie Riedesel

Author:Jamie Riedesel [Jamie Riedesel]
Language: eng
Format: epub
Publisher: Manning Publications
Published: 2021-08-25T00:00:00+00:00

Figure 10.12 Two workflows for our Booking and Passenger Manifest department: one for accepting reservations and a second for checking in passengers to generate a flight manifest. This airline operates three regional clusters of web servers supporting reservations in North America, Europe, and Singapore. There is a gate computer at each airport gate loading passengers. The reservation servers and the gate computer talk to up to three APIs hosted on a central mainframe in Europe. The flight manifest is created as a batch job after all passengers are checked in. We will be looking at this production environment in later figures.

Figure 10.13 gives us the flow of logging data out of the Booking and Passenger Manifest department’s production servers and into the telemetry pipeline. A lot is going on here, so let’s step through it:

Events are emitted by the three production systems.

Globally located reservation web servers ship events by way of webhook to webhook receivers hosted in the Paris data center, using emitter/shipper functions in the backend application code. (See section 3.1.3 for an example of sending telemetry by way of HTTP POSTs.)

API servers running in LPARs on the Paris mainframe ship events directly into a Kafka-based stream on the logging_raw topic, also using emitter/shipper functions. (See section 3.1.2 for an example of sending telemetry into streams.)

The Create Flight Manifest batch job on the Paris mainframe emits job output into the mainframe system’s console.

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