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Google Recommendations Metrics via Telegraf

Ship your Google Recommendations Metrics via Telegraf to your Logit.io Stack

Configure Telegraf to ship Google Recommendations metrics to your Logit.io stacks via Logstash.

Send Your DataMetricsGoogle CloudGoogle Recommendations Metrics via Telegraf Guide

Follow this step by step guide to get 'logs' from your system to Logit.io:

Step 1 - Set credentials in GCP

Google Recommendations AI is an advanced machine learning service offered by Google Cloud that helps businesses deliver personalized product recommendations to their customers. By leveraging machine learning algorithms and user behavior data, Recommendations AI generates accurate and relevant recommendations, enhancing the overall customer experience and driving higher engagement and conversion rates.

  • Begin by heading over to the 'Project Selector' and select the specific project from which you wish to send metrics.
  • Progress to the 'Service Account Details' screen. Here, assign a distinct name to your service account and opt for 'Create and Continue'.
  • In the 'Grant This Service Account Access to Project' screen, ensure the following roles: 'Compute Viewer', 'Monitoring Viewer', and 'Cloud Asset Viewer'.
  • Upon completion of the above, click 'Done'.
  • Now find and select your project in the 'Service Accounts for Project' list.
  • Move to the 'KEYS' section.
  • Navigate through Keys > Add Key > Create New Key, and specify 'JSON' as the key type.
  • Lastly, click on 'Create', and make sure to save your new key.

Now add the environment variable for the key

On the machine run:

export GOOGLE_APPLICATION_CREDENTIALS=<your-gcp-key>

Step 2 - Install Telegraf

This integration allows you to configure a Telegraf agent to send your metrics, in multiple formats, to Logit.io.

Telegraf is a flexible server agent equipped with plug-in support, useful for sending metrics and events from data sources like web servers, APIs, application logs, and cloud services.

To ship your metrics to Logit.io, we will integrate the relevant input and outputs.http plug-in into your Telegraf configuration file.

Choose the install for your operating system below to get started:

Windows

wget https://dl.influxdata.com/telegraf/releases/telegraf-1.19.2_windows_amd64.zip

Download and extract to: C:\Program Files\Logitio\telegraf\

Configuration file: C:\Program Files\Logitio\telegraf\

MacOS

brew install telegraf

Configuration file x86_64 Intel: /usr/local/etc/telegraf.conf Configuration file ARM (Apple Silicon): /opt/homebrew/etc/telegraf.conf

Ubuntu/Debian

wget -q https://repos.influxdata.com/influxdata-archive_compat.key
echo '393e8779c89ac8d958f81f942f9ad7fb82a25e133faddaf92e15b16e6ac9ce4c influxdata-archive_compat.key' | sha256sum -c && cat influxdata-archive_compat.key | gpg --dearmor | sudo tee /etc/apt/trusted.gpg.d/influxdata-archive_compat.gpg > /dev/null
echo 'deb [signed-by=/etc/apt/trusted.gpg.d/influxdata-archive_compat.gpg] https://repos.influxdata.com/debian stable main' | sudo tee /etc/apt/sources.list.d/influxdata.list

sudo apt-get update
sudo apt-get install telegraf

Configuration file: /etc/telegraf/telegraf.conf

RedHat and CentOS

cat <<EOF | sudo tee /etc/yum.repos.d/influxdata.repo
[influxdata]
name = InfluxData Repository - Stable
baseurl = https://repos.influxdata.com/stable/\$basearch/main
enabled = 1
gpgcheck = 1
gpgkey = https://repos.influxdata.com/influxdata-archive_compat.key
EOF

sudo yum install telegraf

Configuration file: /etc/telegraf/telegraf.conf

SLES & openSUSE

zypper ar -f obs://devel:languages:go/ go
zypper in telegraf

Configuration file: /etc/telegraf/telegraf.conf

FreeBSD/PC-BSD

sudo pkg install telegraf

Configuration file: /etc/telegraf/telegraf.conf

Read more about how to configure data scraping and configuration options for Telegraf

Step 3 - Configure the Telegraf input plugin

First you need to set up the input plug-in to enable Telegraf to scrape the GCP data from your hosts. This can be accomplished by incorporating the following code into your configuration file:

# Gather timeseries from Google Cloud Platform v3 monitoring API
[[inputs.stackdriver]]
  ## GCP Project
  project = "<your-project-name>"

  ## Include timeseries that start with the given metric type.
  metric_type_prefix_include = [
    "recommendationengine.googleapis.com",
  ]

  ## Most metrics are updated no more than once per minute; it is recommended
  ## to override the agent level interval with a value of 1m or greater.
  interval = "1m"
Read more about how to configure data scraping and configuration options for Stackdriver

Step 4 - Configure the output plugin

Once you have generated the configuration file, you need to set up the output plug-in to allow Telegraf to transmit your data to Logit.io in Prometheus format. This can be accomplished by incorporating the following code into your configuration file:

[[outputs.http]]
  
  url = "https://<your-metrics-username>:<your-metrics-password>@<your-metrics-stack-id>-vm.logit.io:0/api/v1/write"
  data_format = "prometheusremotewrite"

  [outputs.http.headers]
    Content-Type = "application/x-protobuf"
    Content-Encoding = "snappy"

Step 5 - Start Telegraf

Windows

telegraf.exe --service start

MacOS

telegraf --config telegraf.conf

Linux

sudo service telegraf start

for systemd installations

systemctl start telegraf

Step 6 - View your metrics

Data should now have been sent to your Stack.

View my data

If you don't see metrics take a look at How to diagnose no data in Stack below for how to diagnose common issues.

Step 7 - How to diagnose no data in Stack

If you don't see data appearing in your Stack after following the steps, visit the Help Centre guide for steps to diagnose no data appearing in your Stack or Chat to support now.

Step 8 - Telegraf Google Recommendations Platform metrics Overview

The integration of Telegraf with Google Recommendations AI allows businesses to monitor and analyze the performance of their recommendation systems in real-time. By collecting metrics on recommendation accuracy, click-through rates, conversion rates, and other relevant indicators, companies can gain insights into how effectively their recommendations are engaging customers and driving sales. This data is crucial for continuously refining recommendation algorithms, ensuring that the suggestions remain relevant and impactful.

However, the challenge lies in managing and interpreting the vast amounts of data generated by these systems. Logit.io offers a comprehensive solution, providing a robust platform for the efficient analysis and visualization of metrics from Telegraf and Google Recommendations AI.

With Logit.io, organizations can leverage advanced analytics to understand the performance of their recommendation systems better, identify areas for improvement, and make data-driven decisions to optimize their strategies. The platform's tools and insights help businesses to enhance customer satisfaction, drive revenue growth, and maintain a competitive edge in their markets.

For those utilizing Telegraf with Google Recommendations AI and seeking to improve their monitoring and analytics capabilities, Logit.io is here to assist. Our platform and dedicated support team provide the tools and guidance necessary to effectively manage your data and gain actionable insights.Elevate your data analysis and monitoring capabilities with the scalable integration of Google Recommendations and Logit.io. This powerful connection enables you to effortlessly transmit crucial data to Logit.io, unlocking real-time insights that empower you to make more informed decisions. Delve even further into the world of data-driven decision-making by exploring the benefits of Google Vertex AI metrics and unleash the potential of your machine learning models and leverage the insights they provide to achieve unparalleled results. Make the most of your Google logs by integrating with Logit.io's service for GCP logging.

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