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Compliance

Compliance

Use case

Guarantee regulatory compliance by forking every telemetry stream—no matter where the data is routed, filtered, or sampled—and persisting a full, unmodified copy into long-term cold or glacial storage for audit and retention needs.

Prerequisites

  1. Long-term storage backend (cold/glacial tiers)
  2. Fork/tee in pipeline
  3. Policy/config to duplicate all streams
  4. IAM & encryption keys

Choose your preferred self-guided experience

For the required MDAI cluster resources, clone the mdai-labs GitHub repo. This repo also contains the scripts resources needed for trying out the MyDecisive solutions.

Compliance flow

Overview

Let’s get started with the basics

To achieve control your Compliance pipelines, you’ll need to…

  1. Create a synthetic log stream that forwards data to your collector
  2. Create an OpenTelemetry collector to connect your data sources to destinations
  3. Create an MdaiHub to create dynamic control your data streams

Let’s get started with the basics

Step 1. Introduce OTel and MdaiHub into your cluster

Provision resources for your Compliance pipeline

Run the following command an you’ll deploy mock data, otel, and an MDAI Hub

mdai use-case compliance --version 0.8.6 --workflow basic

Validate dataflow with Grafana

If you haven’t yet logged into Grafana, the login is admin / mdai
kubectl port-forward -n mdai svc/mdai-grafana 3000:80

Navigate to the OTel Dataflow Dashboard

Grafana

You should see a consistent stream of data and a 1:1 ratio of logs received : logs exported

Step 2. use mdai recipe to statically achieve use case

Apply static routing

Update your collector to utilize static routing.

mdai use_case compliance --version 0.8.6 --workflow static

Validate dataflow with Grafana

You should see that your log stream no longer sends the 1:1 ratio and has decreased the amount exported.

Grafana

Step 3. Use MyDecisive to parameterize achieve use case

Coming soon…

Coming soon

Congrats 🎉

You’ve completed this recipe!

You’re one step closer to reducing your observability costs and owning your data.

Compliance flow

Overview

Let’s get started with the basics

To achieve control your Compliance pipelines, you’ll need to…

  1. Create a synthetic log stream that forwards data to your collector
  2. Create an OpenTelemetry collector to connect your data sources to destinations
  3. Create an MdaiHub to create dynamic control your data streams

Let’s get started with the basics

Step 1. Introduce OTel and MdaiHub into your cluster

Start generating data

Kick off your synthetic data generators. This will represent log streams from your services and/or infra in your existing ecosystem.

kubectl  apply -f ./mock-data/compliance.yaml -n mdai

Provision resources for your Compliance pipeline

Run the following commands and you’ll see these resources created.

kubectl  apply -f ./0.8.6/use_cases/compliance/basic/otel.yaml -n mdai

Validate dataflow with Grafana

If you haven’t yet logged into Grafana, the login is admin / mdai
kubectl port-forward -n mdai svc/mdai-grafana 3000:80

Navigate to the OTel Dataflow Dashboard

Grafana

You should see a consistent stream of data and a 1:1 ratio of logs received : logs exported

Step 2. use mdai recipe to statically achieve use case

Apply static routing

Update your collector to utilize static routing.

kubectl  apply -f ./0.8.6/use_cases/compliance/static/otel.yaml -n mdai

Validate dataflow with Grafana

You should see that your log stream no longer sends the 1:1 ratio and has decreased the amount exported.

Grafana

Step 3. Use MyDecisive to parameterize achieve use case

Coming soon…

Coming soon

Congrats 🎉

You’ve completed this recipe!

You’re one step closer to reducing your observability costs and owning your data.

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