- If you're tasked with cloud operations or CloudOps,
I highly recommend not to focus on the tools and technology
at the expense of focusing on the processes.
It's my recommendation that you understand the tools
but don't look at them as your guide
to CloudOps excellence.
It's the people and processes
that are ultimate keys for success.
So having set the priority level for tools
in the big picture of cloud operations,
let's talk about them to help you gain
a basic understanding of the tools.
The ability to set up redundant systems is only part
of the CloudOps battle.
The real action is found in the cloud's ability
to place these systems behind a layer of management software
that can manage the machine instances
to work around updates and failures.
There are three flavors of these tools.
First, cloud managing platforms or CMP tools that allow you
to manage cloud services, provisioning and deprovisioning
machines and services and providing the ability
to automate continuous operations since you can place
a layer of automation around cloud-based machine instances
and cloud services.
System failures can typically be worked around automatically
therefore most common problems such as
storage system failures, network device failures,
et cetera, can usually be self healed
without users even realizing that there was a problem.
Also when software is updated automatic processes
that are typically linked with automated DevOps processes
are able to test, stage and deploy software updates
without any interruption in application services.
Second is AIOps which is short for
artificially intelligent IT operations.
It refers to multi-layer technology platforms
that automate and enhance IT operations
through analytics and machine learning.
AIOps represents both an evolution and a revolution
IT operations management.
It's an evolution in that traditional management
and monitoring tools were AI enabled and thus they became
AIOps by simply adding features.
These tools are typically sold by traditional enterprise
infrastructure management companies that have been around
for years, many of which are name brands.
While the use of AI by each of the AIOps players
differ substantially, there are a few core AI services
that most tools share.
Third, are metrics and monitoring system tools
on private and public cloud that are more data-driven.
The idea with these systems is that we can proactively
spot issues when they arise
in operations of cloud-based systems.
These tools constantly gather data that's reflective
of current state and health of the system.
Then fire off automated procedures based upon that data
to correct issues as they become problems
or before they become problems.