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How DevOps Practitioners and SRE Teams Can Achieve Constant Change and Zero Downtime With Observability

By Adam Frank, VP of Product & Design at Moogsoft 

Today's DevOps practitioners and SRE teams face complex data coming from all ends of the business. In our digital-first business landscape, it's becoming more and more challenging to not only manage the data but understand how to analyze it in an effective way. To effectively do so, and make meaningful changes and decisions from this data, teams must pair artificial intelligence (AI) with observability. When teams leverage the two together, they are able to increase visibility and transparency, drive revenue growth, improve employee productivity and offer an overall better experience for customers.

Understanding observability

First and foremost, we must understand the definition of observability. Observability is the practice of emitting data to provide you insights and awareness, directly from your applications and services, as deep as the fundamental code level, whether it be through metrics, purpose-written log messages, or traces.

As data becomes more and more complex, DevOps practitioners and SRE teams can no longer rely only on traditional monitoring capabilities to achieve service assurance - they must apply observability techniques to identify the deeper causes of problems that arise and understand solutions to fix and avoid these same problems in the future. Leveraging observability, teams set themselves up for success as they have more visibility into valuable data and can make data-informed decisions to ensure the health of their systems and customer value.

Benefits of observability

When teams invest in observability with AI, they can quickly and accurately detect anomalies, automatically flag important information, understand services' normal behaviors and ensure the customer experience is manageable, automated and scalable. Without observability, legacy monitoring tools suffer from noise, expensive data lakes, manual diagnostics and little to no data context. When paired with AI, observability offers DevOps practitioners and SRE teams closed-loop, autonomous, actionable, and high-context insight that fix critical incidents before they become outages. Essentially, observability uncovers invisible data not immediately available to DevOps practitioners and SRE teams to guide better decision making.

The impact of observability on the DevOps culture

Once DevOps embraces observability, it's likely they'll see an immediate improvement across the board that enhances the traditional DevOps CALMS framework: culture, automation, lean, measurement and sharing. With observability, the DevOps culture improves because teams have more visibility, transparency and trust, and conversations are data-informed rather than opinion-driven. Additionally, teams have more actionable insights to properly measure progress and improvements and have a shared platform for collaborative analysis, allowing them to meet goals quickly and efficiently.

What's next?

Ready to get started with observability and AI? There are three important steps to consider as you plan your first project:

  1. Pick target apps and services: Identify one or two applications and services that will be the testbed for your observability with AI proof of concept of data gathering, analytics and monitoring.
  2. Observe the initial results: Once you are able to analyze your data and determine normal operating behaviors, observe your results and understand what's normal versus anomalous operating behavior.
  3. Share your experiences: Inform stakeholders of the results of the POC by sharing examples of how incident resolutions prevented outages and improved the overall customer experience. As a result, you show the value of observability with AI as it relates to overarching business goals.

Observability strengthened by AI is the key to improving overall visibility, reliability and agility. Teams spend more time developing solutions and less time operating for constant change and zero downtime - allowing them to embrace constant change through focused development and assuring reliability for the customer experience.

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About the Author

adam frank 

Adam Frank is a product and technology leader with more than 15 years of AI and IT Operations experience. His imagination and passion for creating Observability and AI solutions are helping DevOps and SREs around the world. As Moogsoft's VP of Product & Design, he's focused on delivering products and strategies that help businesses to digitally transform, carry out organizational change, and attain continuous service assurance.

Published Wednesday, October 07, 2020 7:37 AM by David Marshall
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