NRI Bitmovin Analytics Integration

This integration uses Bitmovin Analytics API to pull in the below metrics and push them into New Relic.

Supported Metrics:

1. max_concurrent_viewers
2. avg_rebuffer_percentage
3. cnt_play_attempts
4. cnt_video_start_failures
5. avg_video_startup_time_ms
6. avg_video_bitrate_mbps

Standalone

The Standalone environment runs the data pipelines as an independant service, either on-premises or cloud instances like AWS EC2. It can run on Linux, macOS, Windows, and any OS with support for GoLang.

Prerequisites

• Go 1.20 or later.

Build

Open a terminal, CD to cmd/standalone, and run:

$ go build

Configuring the Pipeline

The standalone environment requires a YAML file for pipeline configuration. The required keys are:

• interval: Integer. Time in seconds between requests(should be same as the schedule / cron).
• exporter: nrmetrics.
• bitmovin_api_key: String. Bitmovin API Key
• bitmovin_license_key: String. Bitmovin License Key.
• bitmovin_tenant_org: String. Bitmovin Tenant Org.
• nr_account_id: String.
• nr_api_key: String. Api key for writing.
• nr_endpoint: String. New Relic endpoint region. Either US or EU. Optional, default value is US.

Check config/example_config.yaml for a configuration example.

Running the Pipeline

Just run the following command from the build folder:

$ ./standalone path/to/config.yaml

To run the pipeline on system start, check your specific system init documentation.

Lambda

The Lambda environment runs the data pipeline in AWS Lambda instances. It's located in the lambda folder, and is divided into 3 binaries: lambda/receiver, lambda/processor and lambda/exporter.

Prerequisites

• An AWS account.
• AWS CLI tool.
• Go 1.20 or later.
• GNU Make.

Setting Up AWS

1. Create 3 lambdas for Receiver, Processor and Exporter. Runtime Go 1.x, arch x86_64, and handler names receiver, processor and exporter.
2. Create an SQS for ProcessorToExporter, type Standard, condition OnSuccess.
3. Open Receiver lambda config->permissions->execution role. Add another permission->create inline policy, add Lambda write permissions InvokeAsync and InvokeFunction.
4. Edit Receiver lambda config, add as a destination another lambda, the Processor, with async invocation.
5. Open Processor lambda config->permissions->execution role. Add another permission->create inline policy, add SQS write permissions.
6. Edit Processor lambda config, add as a destination the SQS ProcessorToExporter.
7. Open Exporter lambda config->permissions->execution role. Add another permission->create inline policy, add SQS read and write permissions.
8. Edit Exporter lambda config, add as a trigger the SQS ProcessorToExporter.

Note: when creating and configuring the SQS service and trigger, make sure to set the timing and batching options you will need. For example, a time interval of 5 minutes and batching of 50 events.

Build & Deploy

Open a terminal, CD to lambda, and run:

$ make recv=RECEIVER proc=PROCESSOR expt=EXPORTER

Where RECEIVER, PROCESSOR, and EXPORTER, are the AWS Lambda functions you just created in the previous step.

Configuring the Pipeline

A Lambda pipeline requieres some configuration keys to be set as environment variables. To set up environment variables, go to AWS console, Lambda->Functions, click your function, Configuration->Environment variables:

Environment Variables to be set on the Receiver function:

• interval: Integer. Time in seconds between requests(should be same as the schedule / cron).
• exporter: nrmetrics.
• bitmovin_api_key: String. Bitmovin API Key
• bitmovin_license_key: String. Bitmovin License Key.
• bitmovin_tenant_org: String. Bitmovin Tenant Org.

Environment Variables to be set on the Exporter function:

• nr_account_id: String. Account ID. Only requiered for nrevents and nrapi exporters.
• nr_api_key: String. Api key for writing.
• nr_endpoint: String. New Relic endpoint region. Either US or EU. Optional, default value is US.

Running the Pipeline

Finally, to start running the pipeline you will need an EventBridge rule. Add a trigger for the Receiver lambda, select EventBridge as the source, create new rule, schedule expression rate(1 minute) (or the time you desire).

Testing

Instead of running the pipeline with an EventBridge rule, you can just send async invocations to the Receiver lambda from the command line, using the following command:

$ aws lambda invoke-async --function-name RECEIVER --invoke-args INPUT.json

Where RECEIVER is the Receiver lambda name and INPUT.json is a file containing any JSON (the input event will be ignored by the receiver).

This will simulate a timer event and trigger the pipeline.