Artificial Intelligence is set to disrupt every industry vertical. While scenarios like self-driving cars and cancer diagnosis instantly get our attention, more common areas such as IT operations and DevOps are also impacted by AI.
One of the core aspects of DevOps is monitoring and logging. It is common for IT administrators and system operations managers to collect and aggregate logs in a central location. Typically, these logs are used for audit trail, and to perform root cause analysis and remediation. This process is manual where network and application specialists search for a needle in a haystack to detect an anomaly or an unusual pattern in the available system logs. In most of the cases, this analysis takes place after the fact causing significant downtime and disruption to the business.
By bringing Machine Learning to log analysis, the systems become smart by becoming proactive. The algorithms applied to the logs detect anomalies and unusual patterns much before the end users experiencing it.
Sensing the opportunity in algorithmic log management, a few startups have built viable business models in the space of Security Information and Event Management (SIEM).
Here are a few startups that deliver AI-driven log management and analysis
Based in Israel, Anodot
was founded in 2014 by David Drai, Ira Cohen, and Shay Lang. The company is an early mover in bringing ML to log management. Anodot claims that it analyzed over 5.2 billion data points per day within six months of the launch. Delivered as a SaaS platform, Anodot can ingest data from a variety of sources including clickstreams, sensors, CRMs, server logs and application logs.
is not exactly a startup but a veteran in the space of Application Performance Management (APM). Split from Compuware in 2014, Dynatrace created a niche for itself in the application monitoring and log management segment. The platform integrates with traditional application platforms, DevOps tools, cloud infrastructure, and databases.
is another startup focused on log management from Israel. This Tel Aviv-based company built the platform based on the popular technology stack powered by Elastic Search, Log Stash, and Kibana often called as the ELK stack. Logz.io also has an AI-powered continuous delivery system that integrates with AWS, Azure, and Google Cloud Platform.
This San Francisco-based startup was founded in 2015 by Gabby Menachem, an entrepreneur with expertise in data and analytics. Loom Systems
claims to deliver an advanced AI-powered analytics platform to predict and prevent problems in the digital business. The platform can deal with digitized information in structured, unstructured, non-standard or uncommonly structured text format.
is an Algorithmic IT operations platform that uses unsupervised machine learning to deal with the deluge of data. This San Francisco-based startup was founded by Phil Tee and Mike Silvey, who built Netcool, an IT systems management and service assurance product that was acquired by IBM. MoogSoft's platform is available for deployment in the cloud as well as on-premises data center. The company boasts of impressive clientele that includes the likes of Intuit, GoDaddy and T-Mobile.
, the San Jose-based startup was found in 2014 by JF Huard, ex-CTO of Netuitive, Inc. Like most of its competitors, it promises to deliver artificial intelligence powered analytics and observability for TechOps and DevOps. It integrates with mainstream monitoring systems, log aggregation engines and Big Data platforms. Perspica recently added a root cause analysis feature to its SaaS platform.
Machine Learning and Artificial Intelligence will become an integral part of infrastructure management. Servers and applications will turn intelligent through self-monitoring and self-healing. This will usher a new phase in systems management and DevOps.