Central AIOps capabilities
The future of IT Operations
Modern organizations cannot function properly during IT outages or issues, and IT has advanced significantly to provide critical services for the always-on demands of today’s world. Outages and incidents are a major challenge for IT Operations teams, especially with the complex and ever-changing IT stacks that support modern applications.
Fortunately, AIOps is finally providing some assistance.
How AIOps works
Ingest events from multiple sources, vendors and technology domains
Many point tools integrate AI in order to add intelligence to the data within their own purview. But true AIOps platforms must be able to easily ingest data from multiple sources, vendors and technology domains, ideally using a combination of out-of-the-box connectors and flexible APIs.
Data types can vary, but you should prioritize ingestion of alerts (for actionable triggers) as well as change and topology data (for root cause analysis).
Because outages must (ideally) be caught in real time, your system must be able to process the ingested data streams in real time, normalizing and enriching this data with operational context as soon as it’s collected.
Discover and assemble unified topology of IT assets
In today’s complex and dynamic IT stacks, app and service topologies are not only fragmented across several systems (orchestration, configuration management, CMDBs and others), they’re also constantly changing. Understanding the relationships between IT assets, applications and services has never been more complex. So your AIOps platform must be able to dip into the sources of topology in modern environments and stitch together a real-time, up-to-date topology model.
This model makes it easy to understand the dependencies and connections between different servers, network devices, cloud-based resources and other IT assets. When there’s an outage, IT Operations teams can then identify the root cause more easily and shorten downtime.
Correlation of all alerts and events
Your AIOps system must be able to correlate all of your alerts and events (which, for the typical enterprise, can easily be tens or hundreds of thousands of daily alerts) against your unified topology model. With event correlation, all the alerts related to a single outage are grouped together—or correlated—into a single incident. Since a single outage commonly triggers dozens or even hundreds of alerts across a dozen or more tools, your IT Operations teams can focus on troubleshooting one incident instead of wasting time on 60 seemingly different yet related events.
Event correlation can reduce events by as much as 95%. This means that your IT Operations teams are no longer drowning in data or chasing false positives—or simply ignoring the valuable alerts generated by expensive observability and monitoring tools.
Recognition of incidents in real time
Your AIOps solution should recognize incidents in real time before they escalate into crippling outages and continually learn and refine its correlation logic in order to detect future incidents more efficiently. The ability to define and then refine correlation logic enables better outcomes because the system internalizes your organization’s knowledge to identify and process incidents more efficiently. When your AIOps platform is exposed to new tools or datasets used across your organization, it should be able to recognize patterns in the data and recommend newer, more efficient correlation logic.
It must also be able to infuse business context into the incidents that it detects, so your teams can recognize and appropriately handle incidents with different levels of business severity and priority. Furthermore, correlation logic should improve by learning from users’ interactions and actions taken on the incidents within the platform.
Automated remediation steps
IT Operations teams spend valuable time on various manual tasks that delay remediation. Not only do they often waste minutes during the incident triage phase, but when incidents require further investigation, they can spend valuable minutes sharing information with ticketing, service desk and on-call notification or paging systems. Your AIOps system must give you the ability to automate these actions so you can meaningfully reduce your mean time to resolve (MTTR).
For recurring issues that have a vetted set of remediation actions, your solution should allow you to invoke automation systems (such as Ansible, StackStorm, Rundeck and others) to execute those actions. You must have the flexibility to integrate with the automation system of your choice—whether it’s a commercial offering, an open-source project or a homegrown solution.
About BigPanda’s AIOps platform
BigPanda keeps digital services running with AIOps that transforms IT data into incident insights and actions.
BigPanda can ingest alerts from any monitoring source your organization uses—now and in the future—and enrich them with topology data that provides valuable contextual information. This drives remarkably effective event correlation that allows IT Operations teams to recognize important incidents as they develop in real time, often before they are reported by users. BigPanda also ingests and correlates change data, allowing responders to easily identify suspicious changes in the environment that cause incidents. Finally, BigPanda accelerates remediation and reduces MTTR by automating key incident management steps, from creating tickets to running runbook automations.