Say hello to a new AIOps platform: Wave of the future or just another drop in the ocean?
Are self-healing applications on our horizon? CA Technologies’ new AIOps platform hopes to bring us closer to the future of intelligent automation. What are the grand plans for AIOps and is it a potential reality or just another buzzword?
Artificial Intelligence for IT Operations, also known as AIOps, gains momentum as our machine learning capabilities and algorithims become more complex. On October 16, 2018 CA Technologies revealed a new AIOps platform that will help teams automate tasks intelligently. The goal is self-healing applications.
In an interview with us in April 2018, CMO of FixStream (an AIOps platform which helps correlate, visualize, and predict issues across hybrid stacks) Enzo Signore had some ideas to share about how AI is transforming IT operations. He clarified that AIOps does not intend to eliminate existing operations, but it will continue to optimize them to maximum efficiency and agility. “Machine learning is transforming IT since it can correlate millions of disparate data points across the entire IT stack, detect patterns and predict issues much faster and with a much higher degree of accuracy than traditional tools can”, Signore stated.
Their official definition is:
AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.
DevOps broke down silos between Devs and Ops; AIOps hopes to augment the human developer with the power of artificial intelligence.
The benefits of big data in IT are becoming apparent and some industries are banking on its successful future. (One thing of note, getting started with AIOps doesn’t come cheap. Gartner provides a market guide listed at 1,295.00 USD for 9 pages.)
As self-driving cars become a reality, are we also going to see self-driving apps?
In their press release, CA AIOps lists some of their capabilities for the new platform. Some of the highlights include:
- Comprehensive Contextual Operational Intelligence. CA Digital Experience Insights ingests structured and unstructured data from IT performance monitoring tools spanning mainframe to the cloud and any third-party source into a single, resilient data lake. Supported coverage includes metric, alarm, log, topology, text and API data.
- Proactive Closed Loop Remediation. CA Digital Experience Insights combined with Automic Service Orchestration offers predictive analytics to help solve complex IT problems like performance and capacity. Configuration issues can be detected proactively (before they impact users) and remediated automatically.
Vendor-agnostic Integrations. Customers can more quickly and easily stream metric, event, log and topology data to and from any third-party monitoring, management, analytics, and visualization tools, including Splunk, IBM, Elastic, ServiceNow, Dynatrace, AppDynamics, SolarWinds, Puppet, Chef, Tableau and more.
- Pre-packaged Algorithms and CA Integrations. Built-in machine-learning-driven algorithms, dashboards, and integrations speed time to value for customers. The CA AIOps platform also integrates with a wide variety of CA solutions.
- Powerful open source-based engine. Built on top of CA Jarvis, a powerful analytics engine that leverages open technologies such as Elasticsearch, Apache Kafka®, and Apache Spark™, the solution scales and allows teams to more easily integrate with third-party business or IT data sources to further enrich the data set.
Augmenting human developer intelligence with machine learning would mean for smarter root-cause analytics, better issue predictions, and noise reduction. Potentially, developers could prevent service disruptions and identify potential bottlenecks.
Right now, CA Technologies lists some of their big name customers as: Us Bank, KPN, LinkedIn, and Barclays.
All bark, no bite?
Let’s slow down for a moment and ditch the rose colored glasses. If you are raising your eyebrows at AIOps, you aren’t alone.
An article by Michael Cote for The Register discusses some of the alarm bells that the idea sets off. It is worth a read and a serious consideration for those interested in the topic.
For now, playing it safe and skeptically seems to be a good option. The idea is an interesting one. But for right now it is still too new and rough to make a definitive statement on. We just don’t have enough data to agree with Gartner’s (extremely generous) assessment that “by 2023, AIOps platforms will become the prime tool for analysis of monitoring data“.
Meanwhile, we will keep our radar receptive to the idea.
As always, we want to hear from you, the reader. Is AIOps just the latest buzzword in IT or does it have some industry-changing potential? Will it save teams precious time and help resolve issues, or it just a dream?