How Integrations Lead to Easier, Quicker and Better Decision-Making
Richard Whitehead | June 24, 2021

Integrations are turning AIOps into the modern hub for service assurance.

Integrations are turning AIOps into the modern hub for service assurance.

Whether from a monitoring tool such as Datadog, a collaboration tool such as Slack, an automation tool such as Chef or a ticketing tool such as ServiceNow or JIRA, AIOps seamlessly integrates data from all of your IT sources. A robust AIOps solution with integrations can help your DevOps and SRE teams better know where to begin fix problems, resolving incidents before they affect services and reducing downtime.

Here are four ways how integrations within your AIOps solution leads to easier, quicker and better decision-making:

Integrations track all of your operational data

The key to resolving incidents before they affect business services is to ensure that data from all of your IT sources is integrated under your AIOps solution.

Effective solutions receive, analyze and manage monitoring and observability data from any system or device using either standard integrations or simple application programming interfaces for DIY integrations and workflows. Integrations allow your DevOps and SRE teams to cover all of the bases without feeling like they’re running in circles.

Integrations should easily connect all of your monitoring and observability data, tools and systems for incorporating data streams of any size. AIOps also should leverage the data to understand what’s relevant and what’s not in order to reduce noise and surface only the issues your teams need to take action on.

The AIOps algorithms also effectively correlate results by discovering patterns and relationships in the data.

The goal is finding and fixing problems faster, and the heart of the matter is identifying the root cause. Integrations are a critical component for determining root cause quickly and efficiently.

The beauty of synchronization

Synchronizing integrated data flows and workflow processes ensures that the right information is automatically delivered to the right people. Alerts are pre-correlated with context and insight so AIOps can determine which alerts matter and which alerts don’t.

Synchronization also helps teams collaborate with peers, including the integration of DevOps and SRE team feedback from previous incidents related to new incidents. This historical context helps.

And bidirectional integration of automated ticketing, notification and collaboration systems helps keep everyone further in sync.

Enriched data helps automate workflows

AIOps simplifies where and how to begin fixing issues by automatically enriching data with additional information. Probable root cause context and intelligence, for example, can trigger automation workflows. Authoritative visual information, such as asset topology maps and incident timelines, helps DevOps and SRE teams know where to begin fixing a problem.

With modern tools, in particular those found in modern DevOps tool chains, developers and operators are leveraging tags and dimensions to label data. This metadata is capitalized on by AIOps capabilities such as natural language processing (NLP)  for correlation and routing.  In cases where tags are not available, AIOps algorithms can perform feature extraction to generate the tags, and machine learning with NLP performs auto-classification.

Algorithms analyze internal data and data integrated from third-party tools to assist in effective analytics and decision making.

One view to see it all

AIOps can best investigate issues, reduce downtime and ensure service availability when complete visibility and context are provided by a unified view. AIOps lets your DevOps and SRE teams view everything in one place, where it’s easier to see monitoring, observability and change data and get those pesky trouble tickets under control.

Integrations in a robust AIOps platform makes the most of all of your existing tools. AIOps monitors all of the incoming data, synchronizes data and workflow processes, automates tasks by enriching data and presents a unified, context-rich source of information. As the desire for increased automation moves teams away from the “single pane of glass” ideal, AIOps becomes the hub, or clearinghouse, allowing them to resolve issues faster and avoid downtime.

Moogsoft is the AI-driven observability leader that provides intelligent monitoring solutions for smart DevOps. Moogsoft delivers the most advanced cloud-native, self-service platform for software engineers, developers and operators to instantly see everything, know what’s wrong and fix things faster.

About the author

mm

Richard Whitehead

As Moogsoft's Chief Evangelist, Richard brings a keen sense of what is required to build transformational solutions. A former CTO and Technology VP, Richard brought new technologies to market, and was responsible for strategy, partnerships and product research. Richard served on Splunk’s Technology Advisory Board through their Series A, providing product and market guidance. He served on the Advisory Boards of RedSeal and Meriton Networks, was a charter member of the TMF NGOSS architecture committee, chaired a DMTF Working Group, and recently co-chaired the ONUG Monitoring & Observability Working Group. Richard holds three patents, and is considered dangerous with JavaScript.

All Posts by Richard Whitehead

Moogsoft Resources

September 14, 2021

Reducing Pages with Alertmanager and Moogsoft

September 8, 2021

AIOps: Time to Sit Up, Observe and Listen

August 31, 2021

Monthly Moo Update | September 2021

August 23, 2021

Chapter Twelve: In Which Dinesh Starts an AI Community of Practice

Loading...