December 1, 2021
Driving Unified Visibility Within Modern Digital Environments
Written by: François Cattoen
Operational monitoring can be like looking down the wrong end of a telescope. There’s no clear picture of the horizon. Everything is blurred, indistinct, and difficult to trace. If you’re relying on traditional, domain-centric monitoring, you’re faced with a similar problem: you can see the performance of individual elements, but you don’t have any visibility into the broader picture.
Diverse datasets generated and stored in isolated monitoring solutions — which could be open-source, packaged, or homegrown custom developments — challenge many organizations. Teams are forced to hunt for monitoring data in multiple disconnected operational silos. That process absorbs precious time, resources, and money.
The difficulties of operational monitoring are set to get worse too. Today’s digital environments are predominantly distributed and hybrid, highly reliant upon networks, and increasingly made up of multiple clouds. Gartner estimates that 85% of enterprises will have a cloud-first principle by 2025. Environments are becoming more complex – and harder to observe – by the day.
This complexity is expanding exponentially, driven by increased adoption of cloud-native services, microservices, Software Defined Everything (SDx), and more. With the increasingly widespread use of microservices and cloud-native architectures, the management of applications, infrastructures, and networks is starting to converge.
Observability versus monitoring
To gain the visibility required to meet critical imperatives, IT operations teams need observability rather than monitoring. Monitoring is about detecting the heartbeat of individual components, whereas observability is about understanding how business services are behaving and how they are related.
The volume, variety, and velocity of data produced by modern digital systems all make it a challenge to switch from monitoring to observability. Given the massive data volumes being generated, individuals relying on manual analysis can’t possibly keep up and be on top of it all, let alone mine maximum intelligence from it. Artificial Intelligence (AI) and Machine Learning (ML) have become critical capabilities to help correlate cross-domain data and provide valuable insight.
Delivering observability at scale
AIOps platforms such as DX Operational Intelligence provide end-to-end observability and advanced analytics that deliver key insights for efficiently managing complex environments.
DX Operational Intelligence unifies visibility across existing monitoring tools, consolidating data into visual, cross-domain dashboards. Mobile-to-mainframe and app-to-network, the platform connects all environments while also integrating with third-party tools to deliver new levels of visibility across the entire digital delivery chain.
You can now move to proactive management, minimizing the “war rooms” and finger-pointing associated with tool sprawl. DX Operational Intelligence provides a single platform that works for every user, from the C-level to the level-one operator.
Rather than having disparate teams working with different systems and pulling data into spreadsheets or slides, everyone can go to a single resource. When working on data from the same platform, different users can still gain intuitive views around the aspects they care about, while keeping an eye on the big picture from a service delivery standpoint.
The latest revision of RESTMon — the ingestion and consolidation component part of DX Operational Intelligence — enables even greater performance and availability by introducing health dashboards and self-monitoring probes. It also includes new out-of-the-box integrations with third-party tools such as Zabbix, Netcool, Google Cloud, and many others.
Now is the time for action. As organizations gain maturity in AIOps adoption, Gartner envisages the market bridging operational silos by shifting to domain-agnostic platforms. This change means ingesting increasingly diverse datasets and heavily relying on integrations with many different tools to aggregate monitoring data.
Visit our AIOps page and the new release presentation at Broadcom’s Enterprise Software Academy to discover how modern AIOps solutions can help your organization create end-to-end visibility and observability at scale.
François Cattoen
François is a Product Manager for Broadcom's DX Operational Intelligence, which leverages big data, analytics and machine learning to provide insight in the entire IT stack and enable autonomous remediation. He works closely with customers to validate existing and upcoming high value capabilities, as well as with...
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