Curious about AIOps these days? You’re not alone. AIOps (Artificial Intelligence for IT Operations) is all about analyzing and automating your IT operations using artificial intelligence and machine learning algorithms. These operations include end-to-end workflows that bring monitoring, analytics, incident management, and automation systems together with a common goal of optimizing and automating operational tasks. Just like an autonomous vehicle, an AIOps system will learn and understand the complex dependencies within your infrastructure, spanning from network to the clouds, to help you prevent problems before they occur and enable a self-driving digital business.
At LogicMonitor, we are on a mission to create the most comprehensive, extensible, and intelligent insights platform in the world. And, we are going to achieve this not only through LM Intelligence™ , our existing AIOps functionality, but also by acquiring other jaw-dropping complementary products such as Unomaly’s.
The first step in automated troubleshooting is building context between all the infrastructure dependencies inside a unified platform like LogicMonitor. Context brings together insights that answer the key questions of what, where and why:
Context is important for automated troubleshooting – What, Where, Why
Similar to how a doctor treats a patient by first checking his or her metrics (i.e. blood-pressure, weight, heart rate, and oxygen level) and then ordering a blood report for a more detailed analysis, LogicMonitor first understands the normal behavior of your infrastructure through metrics, dependencies, and sophisticated AI/ML algorithms. With the addition of Unomaly, LogicMonitor will now be able to help you diagnose the root cause even faster than before.
Our vision for expanding our LM Intelligence™ AIOps platform with Unomaly is multi-fold as listed below in the primary use cases for this technology:
Gain contextual observability from infrastructure down to specific log events
LogicMonitor collects metrics for everything within an organization’s infrastructure and turns them into actionable insights to help with troubleshooting and optimization processes such as capacity management. In a typical complex infrastructure, all application and infrastructure components generate observable information (metrics and logs) that include hidden signals depicting their current and future health. The challenge is that with cloud and new innovative technologies, sorting through the increasing variety and volume of data, at speed is nearly impossible. Now with Unomaly, we will be able to automatically collect and correlate relevant metrics with log events, no matter if infrastructure is in the cloud or on-prem, and present them to you for contextual troubleshooting.
Pre-empt business problems with powerful ML-algorithms that surface issues
Logs provide facts about activity taking place within infrastructure, applications, and cloud components in real time. But today, logs are analyzed reactively for root cause analysis only when there is already an outage. Unomaly, however, provides patented ML-algorithms that learn patterns in log file data to automatically surface and alert on unexpected log events, specific parameters that are out of the ordinary, or suspicious repetitive entries. This will enhance our existing AIOps Early Warning System (EWS) by ensuring that IT teams get proactive insight into the root cause of issues before they become a business problem.
“Before working with Unomaly, we waited for incidents to happen before accessing our log data. Now we find problems as they occur. In many cases we have been able to fix problems before they affect our users.”
– John Ström, IT at Vasakronan, one of the largest real estate companies in Sweden
Detect issues caused by frequent releases and continuous delivery processes
In order to be successful and stay competitive today’s digital businesses must meet rising user experience expectations through the frequent delivery of new applications or features (web, mobile or IoT based). However, frequent releases equal changes to production environments — and changes can mean disruption if not discovered in time. Adding Unomaly to the LogicMonitor platform means that symptoms caused by change are automatically identified by metrics and specific log anomalies will be presented in context. The result is DevOps teams will get the visibility and insight they need to confidently monitor changes for a smooth continuous delivery process.
If observability is about context then AIOps is about contextual intelligence, and we are well on our way to an insights platform that includes AIOps features such as Early Warning System, LM Service Insight, Topology, and Anomaly Visualization. Unomaly aligns perfectly with this vision. We were impressed by the sheer simplicity of the Unomaly experience in generating insights from such complex and disparate log sources. Together, we are moving forward with the common vision of building the best contextually intelligent platform in the world so that our customers can prevent problems instead of reacting to them.
This year, you will see some amazing new experiences delivered through this integration. Watch this space!
To learn more about our combined future plans, please get in touch with your LogicMonitor Customer Success Manager.
Tej has been building enterprise software products for more than 20 years. He has led Engineering, Product Management, User Experience, and Data Science teams several times in his career in industry-leading organizations like Microsoft, VMWare, Cisco, and AppDynamics. Tej has consistently delivered highly successful products like Rational Rose, VMware Labs, Microsoft Azure Machine Learning, PowerBI, and AppDynamics that have fundamentally transformed people's productivity in respective domains. His latest milestone was architecting Cisco's $3.7 billion acquisition of AppDynamics from ground zero and enhancing the AppDynamics platform by infusing large-scale AI/Machine Learning capabilities for automated complex root cause analysis. Tej brings the right balance of business and deep technical expertise to the team to drive strategy and execution at LogicMonitor. His fundamental mission is to build autonomous infrastructure. In his spare time, Tej reads technical and philosophical texts, as well as plays music on Santoor and Harmonium.
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