Introduction

Using Cumulocity Streaming Analytics, you can add your own logic to your IoT solution for immediate processing of incoming data from devices or other data sources. This logic can, for example, alert applications of new incoming data, create new data based on the received data (such as sending an alarm when a threshold for a sensor is exceeded), or trigger operations on devices.

Typical real-time analytics use cases include:

  • Remote control: Turn a device off if its temperature rises over 40 degrees.
  • Validation: Discard negative meter readings or meter readings that are lower than the previous.
  • Derived data: Calculate the volume of sales transactions per vending machine per day.
  • Aggregation: Sum up the sales of vending machines for a customer per day.
  • Notifications: Send me an email if there is a power outage in one of my machines.
  • Compression: Store location updates of all cars only once every five minutes (but still send real-time data for the car that I am looking at to the user interface).

Cumulocity Streaming Analytics includes a built-in event processing engine that powers both Analytics Builder and custom EPL (Event Processing Language) apps. This engine, called the Apama correlator, runs automatically within the Cumulocity platform and does not require manual setup or management.

Streaming Analytics is available in both Cumulocity Core (cloud) and Cumulocity Edge (local installation), providing flexibility for different deployment needs.

Understanding processing modes in Streaming Analytics

When working with Streaming Analytics in Cumulocity, the availability and persistence of data depend on the processing mode chosen at ingestion. Refer to HTTP usage > Processing mode in the Cumulocity OpenAPI Specification and OPC UA > Sample payloads for more information.

This directly impacts what data you can access, analyze, and act upon in realtime.

PERSISTENT (default) and QUIESCENT modes:

Data is stored in the Cumulocity database and sent to the Streaming Analytics engine. This is the normal expectation where all data is persisted in the platform before Streaming Analytics processes it.

TRANSIENT and CEP modes:

Data is sent to the Streaming Analytics engine, but it is not stored in the database. This allows processing of data before it’s stored in the platform to reduce storage with aggregates or to do data conversion or cleaning tasks before it is stored in the database.

PERSISTENT and TRANSIENT modes also generate notifications to non-Streaming-Analytics subscribers to notifications, whereas CEP and QUIESCENT modes will only be sent to Streaming Analytics. The latter two modes are only applicable to measurements and events.

Prerequisites

Browsers

The Streaming Analytics application supports the same browsers as Cumulocity, with the following exception: browsers on smartphones and tablets are not supported.

Permissions

To use Analytics Builder, you must at least have the following permissions:

Permission type Permission level
CEP management ADMIN
Option management READ
Inventory READ

This is typically achieved by using a global role which has those permissions, and where the role has access to the Analytics Builder application. See Managing permissions for details.

To use EPL Apps, you only need the following permission:

Permission type Permission level
CEP management ADMIN

Home screen

To access the home screen of the Streaming Analytics application, click the Streaming Analytics icon in the application switcher.

Streaming Analytics home screen

The home screen of the Streaming Analytics application lets you navigate to the different pages of the application. These are Analytics Builder and EPL Apps. You can access these pages using the corresponding Open button on the home screen or by using the navigator on the left.

If you need more space for a page, you can hide the navigator. Click the small arrow at the very left of the top bar to toggle the display of the navigator.

The home screen also provides information on smart rules. You create and maintain them with the Cockpit application. See Smart rules for detailed information.

The home screen and navigator only show entries for the items that you are allowed to use, depending on the version of the Apama-ctrl microservice to which your tenant is subscribed. See also Microservice runtime and applications and Customizing the home screen of the Streaming Analytics application.

Analytics Builder

The Analytics Builder page of the Streaming Analytics application allows you to build analytic models that transform or analyze streaming data in order to generate new data or output events. The models are capable of processing data in real time.

The models interact with the devices and sensor measurements. Models can receive Measurement and Event objects from devices, which provide the inputs to calculations or pattern detection performed within a model. Models can create new Measurement objects which can represent derived values from sensors (for example, an average temperature) or the measurements can be used as an input to other analytic models (see Connections between models). Models can create new Operation objects which are sent to devices to control the devices (for example, to sound an alarm bell, display a message on a screen, or switch a device off). The models are also stored in the Cumulocity inventory, but can be uploaded or downloaded via the model manager.

You build the models in a graphical environment by combining pre-built blocks into models. The blocks in a model package up small bits of logic, and have a number of inputs, outputs and parameters. Each block implements a specific piece of functionality, such as receiving data from a sensor, performing a calculation, detecting a condition, or generating an output signal. You define the configuration of the blocks and connect the blocks using wires. You can edit the models, simulate deployment with historic data, or run them against live systems. See Analytics Builder for detailed information.

It is also possible to build custom blocks if none of the blocks delivered with Analytics Builder implement the logic required; see Creating your own blocks.

You can customize several aspects of Analytics Builder by setting various tenant options. See Configuration for detailed information.

EPL Apps

The EPL Apps page of the Streaming Analytics application allows you to write business logic in Apama’s Event Processing Language (Apama EPL) which gives more power and flexibility in a text-based programming language. This is an alternative if more complex logic is required or the logic does not fit into the pattern of an analytic model.

You can develop EPL apps (that is, single *.mon files) directly within Cumulocity, written in Apama EPL. You can also import existing *.mon files as EPL apps into Cumulocity. When you activate an EPL app from the Streaming Analytics application, you deploy it to Cumulocity. See EPL Apps for detailed information, including examples.

A quick way to get started is to explore the code of the EPL samples that can be accessed from the EPL editor. See Developing apps with the Streaming Analytics application for information on how to create an EPL app and access the samples. For a start, use one of the simpler samples with temperature measurements, such as “Create an alarm if a measurement exceeds a threshold value”. You can immediately see results using this sample. Add your own EPL code to the sample and try out your changes.

You use the Apama API for interacting with Cumulocity. For detailed information, see the com.apama.cumulocity package in the API Reference for EPL (ApamaDoc), which is part of the Apama documentation.

Microservice runtime and applications

Analytic models, EPL apps and smart rules are executed in an Apama-ctrl microservice. All microservices come with pre-configured resource limits (for example, CPU and memory). The resource usage of analytic models, EPL apps and smart rules depends on various factors such as application complexity, number of devices, etc. It is recommended that customers profile their applications to avoid out-of-memory issues.

To do this you need the following
Build analytic models Apama-ctrl microservice variant (for example, Apama-ctrl-starter) and Streaming Analytics application
Develop EPL apps Apama-ctrl microservice variant (for example, Apama-ctrl-250mc-1g) and Streaming Analytics application
Use smart rules Any Apama-ctrl microservice variant and Smartrule microservice (included in Cumulocity’s Standard tenant)

See also the following sections:

If your tenant is subscribed to the Apama-ctrl-starter microservice, then the following applies:

  • Limited number of at most 3 active analytic models. Custom blocks written with the Analytics Builder Block SDK cannot be used.
  • The EPL Apps page is not available in the Streaming Analytics application.
  • Smart rules are supported.

If your tenant is subscribed to the Apama-ctrl-250mc-1g microservice (or one of its larger variants), then the following applies:

  • Analytic models, EPL apps and smart rules are supported.
  • Custom blocks written with the Analytics Builder Block SDK can be used.

If your tenant is subscribed to the Apama-ctrl-mt-4c-16g microservice, then the following applies:

  • Multi-tenant support.
  • EPL apps are only enabled on the tenant that owns the microservice, but disabled on the subtenants.
  • Analytic models and smart rules are supported.

If your tenant is subscribed to the Apama-ctrl-smartrules or Apama-ctrl-smartrulesmt microservice, then the following applies:

  • Smart rules are supported.
  • The Analytics Builder and EPL Apps pages are not available in the Streaming Analytics application.

Contact product support to discuss adding more capabilities.