Published December 16, 2022
Observability is a term that has gained a lot of traction in recent years, particularly in the realm of software engineering and DevOps. At its core, observability refers to the ability to gain insight into the internal workings of a system by observing its external outputs.
Published December 15, 2022
Observability tools have traditionally focused on capturing and analyzing log data to improve application performance monitoring and security.
Data observability turns the focus back on the data to improve data quality, tune data infrastructure and identify problems in data engineering pipelines and processes.
Published December 1, 2022
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.
Published November 29, 2022
As we settle into the time of year when we reflect on what we’re thankful for, we tend to focus on important basics such as health, family and friends. But on a professional level, IT operations (ITOps) practitioners are thankful to avoid disastrous outages that can cause confusion, frustration, lost revenue and damaged reputations.
Published November 15, 2022
One of the building blocks of messaging is, you guessed it, messages! But there are different kinds of messages: Commands and Events. So, what’s the difference? Well, they have very distinct purposes, usage, naming, ownership, and more!
The purpose of commands is the intent to invoke behavior.
Published November 14, 2022
Do you want to use Kafka? Or do you need a message broker and queues? While they can seem similar, they have different purposes. I’m going to explain the differences, so you don’t try to brute force patterns and concepts in Kafka that are better used with a message broker.
Published November 8, 2022
Many people wonder what the difference is between monitoring vs. observability. While monitoring is simply watching a system, observability means truly understanding a system’s state. DevOps teams leverage observability to debug their applications or troubleshoot the root cause of system issues.
Published November 7, 2022
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.
Published November 3, 2022
Published November 2, 2022
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.
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