Top keywords and use cases for your API, 50-60 chars


Traditionally, the data generated by applications and services is ingested into the Cisco Observability Platform in multiple ways. This is not the most efficient way to store data and correlate it. Therefore, Cisco Observability Platform introduces the Common Ingestion Service API to ingest the data in a single, efficient way.

AppDynamics uses OpenTelemetry as the data ingestion standard. OpenTelemetry is a set of APIs, SDKs, tooling, and integrations designed to create and manage telemetry data such as, traces, metrics, and logs.

Using the Common Ingestion Service API, AppDynamics and third-party agents can publish OpenTelemetry metric data to the common ingestion pipeline.

The Common Ingestion Service API is a collection of public REST endpoints. To begin using the API client, you need a valid JSON Web Token (JWT). To generate and use the token, see Cisco Observability Platform Authentication.

Use Cases

You want to ingest a variety of data from multiple data sources into Cisco Observability Platform to: 

  1. Monitor tool consolidation
    • Get the data from applications such as Splunk and ServiceNow into AppDynamics and use AppDynamics as a single pane of glass for monitoring, data visualization, and correlation. Some of the data that is ingested may not have any entities in AppDynamics.
    • Ingest all cloud data and use AppDynamics to monitor your multi-cloud infrastructures, such as Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP).
  2. Customize application data consolidation
    • Ingest data from different applications that Application Performance Monitoring (APM) does not monitor. You can send the cloud logs data into AppDynamics to visualize and query.
    • Ingest the data of your in-house tools into AppDynamics.
  3. Enrich data
    • Tag resources within AppDynamics and add data such as licensing info and chargeback organization.
    • Send data from thousands of tills with multiple containers into AppDynamics. You can aggregate the health data and filter that information based on stores, cities, countries, and geolocations.