What is Operational Analytics?

Operational analytics is a solution that gives you a view of the health of your system using several disparate data logs. Consider it like trips to your primary physician, dentist, and cardiologist to get a complete view of your health. All those different systems (doctors) combine their logs (findings) to show where problems may rest and how best to address them. The same concept drives operational analytics.

How does operational analytics work

Using operational analytics, you can review data in what’s known as Near Real-Time (NRT) as it enters your systems. This gives you immediate insights that can alert you to failures in your system before they escalate. Key Performance Indicators (KPIs) monitored during operational analytics are Mean Time to Detect (MTTD) and Mean Time to Respond (MTTR). MTTD is the time it takes from when a problem emerges to the time detection occurs. MTTR is the amount of time it takes to neutralize a threat or failure within your network environment. Having access to these business metrics allows you to make decisions that are in the best interest of your organization.

What are the benefits of operational analytics?

The main benefits of operational analytics are identifying problems quickly (MTTD), and fixing those problems (MTTR) just as quickly. By reducing MTTD and MTTR, you can minimize the cost of failures, preserve revenue, and protect against risks. You can also expect to see reductions in downtime, better capacity utilization, and reduced costs. The ability to scale is an important part of operational analytics. Scaling allows your organization to monitor more system components and protect your assets.

What are the challenges of operational analytics?

In order for operational analytics to work well, you need to integrate different tools like data warehouses, IoT, sensors, and more.. These integrations can lead to complex, costly solutions with steep learning curves. Depending upon the scope of their needs, some organizations may even look to build a dedicated department to manage this area.

Who uses operational analytics?

Your entire organization can benefit from operational analytics, but only a handful of staff typically use an operational analytics solution. Developers and operational engineers are the heaviest users.

How do you create an operational analytics strategy?

  1. Start by studying your use cases and identifying your top priorities.
  2. Determine what you’re trying to achieve and begin understanding which tools will be needed and the associated costs.
  3. Identify key metrics like MTTD and MTTD, including appropriate error thresholds.
  4. Determine which systems and data you’ll need to integrate to calculate your metrics.
  5. Create a data cleansing strategy. Data cleansing is a three-tier effort with the first step being determining who will be in charge of the actual cleansing process. Transformation cleansing comes next followed by the decision as to which tool you will deploy in order to get the most out of your data. 

What are AWS offerings for operational analytics?

AWS offers several solutions to help you manage your operational analytics efforts including the following:

How does operational analytics with AWS work?

How are other customers implementing operational analytics?

For customer stories on the benefits of operational analytics, check the case study repository. For example, a global marketplace for buying and selling vehicles approached AWS in 2022 looking to streamline their cloud infrastructure. Our solution reduced their response to support ticket wait time from 12 hours to 15 minutes.

AWS Operational Analytics next steps

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