The Need for Intelligence
In today’s age of mass digital transformation, it’s not always the strongest, or largest businesses that survive and thrive. It’s often the ones who can adapt the quickest to the change in markets.
If you were running a bricks-and-mortar only store pre-COVID, when lock-down hit, you needed to either adopt technology very quickly, or risk obsolescence. It didn’t matter if you were large and established or not. Not even your most loyal customers could wait for you, they had to go elsewhere.
This is happening in every industry and even goes beyond COVID. Agility and speed are imperative in today’s global market.
Since businesses are so heavily focused on technology and digital transformation, there is a surge in the number of applications being developed every year. This means more data being created than ever, more novel technologies being used, more infrastructure being consumed, and more cloud services leveraged.
But now, there’s almost too much to handle, way beyond what humans can deal with anyway. This leads to more data retention requirements, because humans can’t work in real time and so we must store data for retrospective analysis when there’s a problem.
Developers have dramatically increased their output and are often developing new different ways of working, such as the adoption of DevOps methodologies. But even this seemingly positive innovation leads to more code creation, more quickly, producing more and more data.
This means I.T. Operations MUST move faster too, ensuring they do not become the bottleneck to innovation.
By moving to an AIOps platform (and leveraging technologies such as vRealize), you can start to apply intelligence to your platforms, aggregate the vast amount of data you have, apply analytics with machine learning to get to the root cause of failure faster, integrate with your existing IT service management processes to ensure you stay in sync with your business and with embedded automation capabilities you can remediate issues quickly.
These benefits make AIOps an essential consideration for any digital transformation project.
Covering this full spectrum, you can observe, engage and act on your technology intelligently and quickly, for quick wins, and tangible long-term success.
Observe, Engage, Act
The concept of AIOps, at its core is to provide intelligence for the vast amount of data you have, and then bring this intelligence into a platform, to make use of.
AIOps provides a structure that takes three very common components of traditional I.T. Operations and combines them, for many benefits. The major benefit being that its currently the fastest way to resolve issues in your I.T. environment. Operations will also be able to work much faster, be more proactive and make better decisions.
Let’s break down the three components.
Monitoring has been around almost since the first I.T. system was released into production; we need a way to check how things are looking and be ready to engage and act when they do. The goal of continued observation across the IT estate, is to provide a stable platform, by identifying issues before the make any serious impact.
This observational pillar of AIOPs is focused on applying machine learning to your vast array of logs, metrics and topology data across all your data centers, clouds and endpoints. Think of it as adding context to the data all these technologies provide. This allows you to visualize and query real-time and historical data through Dashboards and API Calls. Using machine learning (ML) we can quickly detect any anomalies, find correlation across environments & contextualize issues for faster remediation.
With AIOps, this is all done in real time. Impossible to do manually.
Engage (Service Management)
Traditional Service Management in I.T. covers the full spectrum of designing, creating, delivering, supporting and managing the entire lifecycle of any IT services.
An AIOps platform needs to integrate with the I.T. service management model in your business to ensure that any incidents, dependencies and changes made across the environments are synced with your current (and future) service management tool sets. This way you can be sure that your platform doesn’t become its own island of complexity, requiring further time and effort.
In modern I.T. environments, the engagement pillar of AIOps can become part of the rest of the business in many ways, for example, in a ChatOps implementation where you’re integrating communication into the overall I.T. Operations workflow too, you’ll need dashboards, logs and contextual views which can be quickly shared among teams, to act even quicker across large enterprises.
Once you’ve got all this intelligence implemented across your I.T. estate, you need to be able to act just as quickly. If you were to raise a ticket for all these issues the incredible ML technology has found, you might need to wait another week before each issue I resolved. Automation becomes important to answering the question “What do we do with all of these alerts?!”
This pillar focuses on the automated remediation of issues, continual automated tuning of the underlying technology, and can kick off custom scripts or run-books to resolve issues based on certain triggers or scenarios.
Often, we see automation leveraged heavily in the provisioning of I.T. services, but less often for IT Operations tasks, until now.
vRealize has been around in some shape or another since the early days of VMware, vRealize Operations has always been there to monitor and observe vSphere, growing in value-add through the advent of virtualization, cloud, and now artificial intelligence.
In the following blog posts of this series, we will get into the detail and talk you through how to leverage vRealize Operations, Log Insight and AI cloud in the context of AIOps, to improve your mean time to resolution (MTTR), increase innovation and provide even more control and predictability over your platforms.
The technologies we will focus on throughout this blog series are as follows:
vRealize Log Insight
Manage massive amounts of data and gain operational visibility and rapid troubleshooting across physical, virtual and cloud environments with vRealize Log Insight.
vRealize Operations enables self-driving IT Operations Management across private, hybrid and multi-cloud environments with a unified operations platform that delivers continuous performance, capacity, and cost optimization, intelligent remediation and integrated compliance through AI/ML and predictive analytics.
vRealize AI Cloud
vRealize AI Cloud is an artificial intelligence and machine learning solution used to continuously optimize infrastructure operations and configure KPIs of dynamic modern apps.
These technologies provide some major benefits as you will see throughout this series. By breaking down each technology in the coming articles, we will show the intelligence built into the software, how to integrate it into your existing service management models and we will highlight opportunities to use automation for dramatically improving the uptime of your I.T. services.
Check back soon for Part 2, where we will be talking about leveraging vRealize Log Insight for AIOps!