Deploying software to support the work of an enterprise is an increasingly complex job that’s often referred to as ‘devops.’ When enterprise teams started using artificial intelligence (AI) algorithms to more efficiently and collaboratively run these operations, end users coined the term AIOps for these tasks.
The volume of data that IT systems generate nowadays is overwhelming, and without intelligent monitoring and analysis tools, it can result in missed opportunities, alerts, and expensive downtime. However, with the advent of Machine Learning and Big Data, a new category of IT operations tool has emerged called AIOps.
Artificial intelligence for IT operations (AIOps) is an umbrella term for the use of big data analytics, machine learning (ML) and other artificial intelligence (AI) technologies to automate the identification and resolution of common IT issues. The systems, services and applications in a large enterprise produce immense volumes of log and performance data.
The Prometheus and Grafana combination is rapidly becoming ubiquitous in the world of IT monitoring. There are many good reasons for this. They are free open source toolkits, so easy to get hold of and try out and so there is a lot of crowd sourced help available online to getting started, and this even includes documentation from the developers of middleware such as IBM MQ and RabbitMQ.
There are a few key differences between distributed tracing and OpenTelemetry. One is that OpenTelemetry offers a more unified approach to instrumentation, while distributed tracing takes a more granular approach. This means that OpenTelemetry can be less time-consuming to set up, but it doesn’t necessarily offer as much visibility into your system as distributed tracing does.
Introduction
In this era, machine learning is important. Machine learning helps in business Management operations and understanding customer behaviors. It also helps in the development of new products.
Every leading company is shifting towards machine learning.
This is a follow up to my previous post which you can find here - Intelligent Machine Monitoring.
Machine Learning isn’t perfect
When we think of computers, we typically think in terms of exactness.
Nastel XRay 1.5 release builds on industry analyst acclaim for leading AIOps & transaction observability vendor.
PLAINVIEW, NY, UNITED STATES, August 19, 2022 /EINPresswire.com/ -- Nastel Technologies, the leader in integration infrastructure management (i2M) solutions, announced today significant enhancements to its versatile AIOps and Transaction Observability solution, including machine learning for integration management, and visualization of business flows and IoT locations.