We can definitely say that cloud computing is not just a trend anymore. Yes, there’s no denying it: businesses today are either moving to the cloud or seriously looking into it.

The cloud, along with other technology trends such as virtualization, makes it possible to create large, highly automated pools of computing resources that can be scaled up or down based on traffic demands, quickly reprovisioned for new purposes, and even maneuver around many types of applications. failures, providing optimized self-service user access. Cloud environments have much less in terms of: less hardware by typically running a multitude of virtual machines per host, fewer support resources, and less room for error as users are directly exposed to cloud services.

However, from a management perspective, cloud environments create many new challenges compared to the traditional data center. Cloud environments have more of everything: more users, more changes, and most of all, more data.

And for many businesses, cloud management is an afterthought, which means keeping cloud-based applications at accustomed performance levels is an elusive undertaking.

So, by applying tools that combine detailed analysis of the mass of configuration data with relevant classification, IT operations can extract actionable insights, insights, and visibility to manage the cloud intelligently.

Challenge of working in the cloud

While the cloud has eliminated many challenges in managing the environment, particularly in the area of ​​deployment, it has also created new ones. For example, in the area of ​​change monitoring and configuration management, many assume that monitoring applications in a cloud is only slightly different from monitoring traditional internal enterprise applications. That assumption is far from the truth, due to the new features that the cloud brings.

New Cloud Conditions

What are some of the new features that make management more challenging?

abstraction

Instead of having servers, software, applications, and storage dedicated to specific tasks, all of that is abstracted from the users and even the IT administrator.

Elasticity

One of the most powerful capabilities of the cloud is the automatic scaling up and down of computing resources.

Automatic provisioning/deprovisioning

The cloud automatically adds and removes available machines in the system, dynamically reconfiguring a cloud.

Dynamic server creation

Additional virtual servers required to support operations can be automatically created and provisioned

IP can be different

Each of the multiple dynamically assigned and deallocated servers can support the same service and will get a new IP when spun off.

Tons of less important changes

Rapid change and impermanence can quickly lead to processing overload

Administration

Successfully managing any business system requires checks and balances, the volume of cloud automation changes makes constant analysis and comparison against expected results a challenge.

A new generation of tools

The new generation of IT management tools must be able to aggregate dynamic information from multiple cloud providers and translate this data into actionable metrics. These tools need to integrate seamlessly with dynamic resource management and automated deployment, capable of recognizing and supporting the traditional software stack and underlying cloud and virtual infrastructure.

The new generation of tools needs to face and overcome the dynamic nature of the cloud by:

Identification of new instances

When a new server instance is spun off, you want to start monitoring and managing this instance as soon as it is activated.

Support reductions and decommissioning

Recognize instance downscaling and decommissioning as expected events rather than system failures.

Connection to instances

Automatically adjust your monitoring scope to address evolving instance content

Identify the instance type

Correlate your observations with the type of the instances. As the amount of information generated by the tools could be significant, the ability to aggregate data based on instance type could be essential to make monitoring manageable.

Leaving IT operations unprepared

The dynamic nature of cloud platforms generates significant amounts of events and data with high frequency. While it may appear that everything is working and there are no issues, this essentially leaves IT operations unprepared for a slowdown or incident. Despite the automated state of the cloud, IT still needs to be able to take a proactive approach and react quickly when the service is impacted.

For example, with autoscaling, the hardest part is maintaining all configuration management and lifecycle management while making sure new servers go into production successfully. With a large volume of events occurring, Operations Console receives monitoring information about many events and does not distinguish why the events occur. Therefore, you need to know the context of these events. Do you have a heavy workload and servers are provisioned automatically, or is there a bug creating new instances and slowing down performance?

Managing Management Tools is Different in the Cloud

Cloud management tools play an essential role in the automated delivery of high-quality IT services. So you don’t want managing these tools to become another legacy-style management challenge that gets in the way of the cloud’s sought-after efficiencies. You don’t want to waste the benefits of your cloud transition on deploying and managing cloud management tools. These tools should hide the complexity of monitoring and managing the cloud environment, providing simple configuration, minimal administration overhead, maximum stability, and an easy means of delivering information to users.

Next-generation tools must take on unique qualities of the cloud

The new generation of management tools needs to face and overcome the dynamic nature of the cloud. Where traditional tools dump endless amounts of data on the operations specialist, assuming he’ll be able to process it, this won’t work in the cloud.

Cloud-based operations mean that IT operations must address the integrated management of increasingly disparate IT assets and resources, as well as maintain greater visibility and control over those assets. Currently available tools can analyze performance, availability, configuration, etc., but do not connect monitoring results to related assets, such as connecting CPU performance to a Puppet manifest that configures the server.

To effectively manage infrastructure, system management tools must correlate collected monitoring information with deployment assets to understand the context of changes. This should extend to all types of assets: traditional physical IT assets, virtualized IT environments, elastic cloud environments, and provide visibility in an easily accessible way.

Cloud management tools must introduce zero overhead and not hinder cloud efficiency. Operations should stay lean and not have to spend IT staff time and attention to keep track of changes created through cloud elasticity, including and excluding new and deleted server instances. IT needs management tools that can drill down through activity on the fly to quickly identify performance and availability issues, automatically detect changes, and adjust to continue supporting managed environments.

IT analytics for cloud management

The increasing amount of information generated by cloud operations makes it impossible to manage IT environments without intelligent automated analytics. Massive volumes of data can provide IT organizations with deep insight into complex pattern phenomena, which can be extremely helpful to IT operations when trying to improve performance and availability. Such analytics will drive more sophisticated processes such as comparing environment states, validating versions, and scanning the vast data repository of configuration information to make cloud operations information actionable and identify critical issues.