What is cloud management? Everything you need to know

Controlling resources and services provided by public, private or hybrid clouds is called cloud management. An IT professional can control those dynamic and scalable computing environments with a well-designed cloud management strategy.

Cloud management can also help organizations achieve three other objectives:

• When IT professionals access cloud resources, create new ones, monitor usage and costs, and adjust resource allocations, they are practicing self-service.
• With workflow automation, operations teams can manage cloud instances without human intervention.
• User experiences and workloads can be tracked through cloud analysis.

Any cloud management strategy will fail without a competent IT staff. In addition to possessing knowledge of the proper tools and best practices, they must also stay focused on the business's cloud management goals.

Why is cloud management important?

When companies adhere to tried-and-true cloud optimization practices, they're more likely to improve cloud computing performance, reliability, cost containment, and environmental sustainability.

Cloud management can be handled in a number of ways, and they are best implemented together. IT shops can navigate vendor pricing models with cost-monitoring tools. Using performance optimization tools and implementing architectures that are based on proven methodologies allows applications to run more efficiently. Environmentally sustainable architectural strategies lower energy consumption through many of these tools and strategies. Cloud management decisions must ultimately be made based on individual corporate priorities and objectives, as there is no one-size-fits-all solution.

Cloud management goals and characteristics

Cloud sprawl is arguably the biggest challenge to cloud management, which is exactly what it sounds like: IT staff lose track of cloud resources, which then multiply unchecked throughout an organization. An IT shop needs governance policies and role-based access controls in place to prevent cloud sprawl and security threats.

Create a cloud migration strategy that incorporates proper documentation and ensures that only necessary data and workloads are transferred to the cloud. Consider multi-cloud management, user self-service portals and other forms of provisioning and orchestration.

To monitor both internal and external cloud services, cloud management platforms provide a unified view of all cloud resources. All individuals involved in the lifecycle of an application can benefit from management platform tools. Resources can be managed with regular audits. Lastly, consider third-party tools to fine-tune enterprise usage, performance, cost and benefits.

Identify metrics that will help you identify trends and provide guidance on what you want to measure and track over time. Enterprises should choose the data points that matter most to their business from the multitude of potential data points available. Consider the following:

• An application's health can be gauged by the utilization of its compute instance's volume and performance (processor, memory, disk, etc.).
• Consumption of storage is related to compute instances.
• Load-balancing services handle incoming network traffic.
• Database instances store and analyze data.
• Cache instances store frequently accessed data in memory in order to avoid having to use slower storage media, such as disks.
• The purpose of functions, also known as serverless computing services, is to provision workloads without purchasing or supplying compute instances. The cloud provider runs the service that loads, executes, and unloads the function when trigger parameters are met.

Security management

Major public cloud vendors continue to invest in their services and improve cloud security, such as their ability to fend off distributed denial-of-service attacks. According to some experts, cloud attacks today are less destructive than on-premises attacks because cloud attacks are typically limited to a single misconfigured service, whereas a local attack could ruin an entire infrastructure.

Despite this, IT shops must remain vigilant to protect themselves. Google, Amazon Web Services, and Microsoft, among others, do not fully take responsibility for cloud data security. To protect their data, cloud users have a shared responsibility. Configuration management, automated security updates on SaaS, and improved logging and access management are among the best practices for cloud security. Standard configurations of the cloud are easier to secure because they are more common today.

To keep an enterprise's environment secure, companies can use security dashboards and trend analysis tools. Cloud versions offer greater flexibility than traditional tools. An enterprise can, for example, access a service provider's online dashboard and gain insight into an online attack quickly.

Cloud security challenges

Although security technologies have improved and service providers have girded their networks, cloud security breaches and incidents continue to occur. Network hosts and web apps can be attacked as fast as they can be fortified. Security audits and reports should be kept up to date for cloud administrators. Use caution when implementing new technologies, such as AI and machine learning, which use many data sources and therefore widen the range of possible attacks.

Cost management

Unmanaged cloud computing costs can spiral out of control. There are many short-term and long-term cost optimization strategies for cloud configurations that can keep budgets in check.

Choose an appropriate provider first. An application can be hosted on VMs, containerized, or in a serverless computing environment. Each has its own management complexity and cost. Finding the right balance between enterprise needs and cost is crucial. Here are some things to consider:

• Analyze your application's redundancy needs. Cloud redundancy can be achieved by distributing workloads over multiple data centers in a region. There is little redundancy in this strategy, which is low-cost. There is also the option to mirror workloads across more than one region, but this offers more redundancy at a higher cost.
• Select the appropriate size and scale for your installation. It is possible to identify a more economical VM instance for the workload you wish to run with the help of tools. Reservations cost less than on-demand VMs, but they must be booked in advance. Preemptible instances are cheap, but there is a risk of interruption by the cloud service provider, so they aren't suited for consistent workloads that require uptime. Typically, autoscaling is integrated into a vendor's overall framework and can increase or decrease resources based on demand.
• Keep data movement to a minimum. Cloud service providers charge for data movement. Select a cloud service that meets your needs. Moving data can also increase security risks.
• Use third-party tools. A third-party cost-management tool may offer better management, monitoring, and security than a cloud platform's native services. They can also be used across multiple clouds.
• Take advantage of advanced technologies. Cloud management can be challenging, even when you do everything right. Artificial intelligence and machine learning, according to some experts, can significantly reduce cloud costs. Cloud vendors already offer tools that scan cloud workloads, detect anomalies quickly, and alert administrators about issues that may affect cloud invoices.

Cost management challenges

Detailed information about cloud costs may not be readily available. In order to calculate the total cost for a single service such as backup snapshots, a customer might search across regions, accounts, and many attached cloud services.

As a result of the COVID-19 pandemic and related economic factors, enterprises moved more workloads to the cloud, underscoring the need for cost optimization practices.

Machine learning and AI tools complement rather than replace human actions. Software can identify additional information that staff may miss, but people must collaborate when analyzing cloud cost strategies and make decisions based on resources and experience. IT and business staff should be aware of how cloud usage affects the bottom line.\

Governance and compliance

Recent years have seen cloud vendors grapple with regulations that govern how they can use personal data. In particular, the General Data Protection Regulation (GDPR) of the European Union and the California Consumer Privacy Act (CCPA) came into force. Although cloud providers have offered different responses to these regulations, their services generally comply with data transparency regulations.

It is more challenging for cloud providers to help customers ensure compliance while using these platforms. Resource portals are available from Amazon, Google, Microsoft, and others to guide customers through the compliance process.

Cloud governance and compliance challenges

make IT professionals' lives difficult in the current regulatory environment. Globally, data protection teams are overwhelmed by the sheer number of requests that increase their workload, particularly with regard to GDPR. There is also a need to combat the false notion that adherence to standards makes one secure -- adherence to standards does not stop phishing attacks or other breaches of the cloud. Improve your organization's compliance with regulations and rules with a cloud governance framework.

Cloud automation

Cloud automation, also called orchestration, reduces the repetitive, manual work involved in managing cloud workloads. In general, the idea is to boost operational efficiency, accelerate application deployment, and reduce human error that can cause applications to fail. In order to accomplish this, IT pros need orchestration or automation tools.

From on-premises tools that target private clouds to hosted services from the big cloud service providers, from Microsoft Azure Automation to AWS Systems Manager, software is available to automate different aspects of cloud computing.

Cloud automation challenges

In most cases, automation saves enterprises time and money, but one challenge is that users may feel it will make them unemployed. Automation usually supplements a job and frees up the cloud pro to do other tasks.

Cloud provisioning

It refers to how a customer procures and orchestrates the use of a cloud provider's resources and services, from compute instances and VMs to storage volumes and other capabilities, such as data analytics and machine learning.

It is important to right-size instances and virtual machines for appropriate scalability during the development phase. Optimizing cloud capacity parameters not only ensures workloads run efficiently, but it can also prevent a lot of wasted money. Determine what an application needs to run properly, and eliminate anything unnecessary. Cloud providers offer tools and templates to help further optimize resource deployments.

Cloud provisioning models differ in the resources they offer and how they are delivered and paid for.

• Advised provisioning. An agreement is signed between the customer and the cloud provider outlining the resources and services that will be provided. A flat fee or a monthly charge is applied to the customer's account.
  
• Provisioning dynamically. Typically, cloud resources are scaled up to accommodate spikes in usage and scaled down to meet decreasing demands. Billing is based on usage.
• Users can provision resources themselves. Through a web interface or cloud brokerage portal, the customer purchases resources from the cloud provider. Those resources are immediately available for use, sometimes within minutes.

Although a self-service brokerage will not completely eliminate administrative tasks, it will shift some of the burden away from the IT service desk. IT Ops teams still must maintain the portal.

Cloud provisioning challenges

The classic challenge here is to optimize the allocation of resources and services, while balancing various factors, such as performance, cost, and security -- and the priorities for those factors may change. There are many cloud services that are reliant on or dependent upon other services. Users should be aware of these dependencies to avoid being surprised by unexpected usage and costs. Security and policy enforcement are other challenges with provisioning.

Cloud monitoring

Monitoring the cloud involves measuring the conditions of a workload and various quantifiable parameters that pertain to overall cloud operations. Results are monitored with specific, granular data, but this data is often devoid of context.

Cloud observability is similar to cloud monitoring in that it helps assess the health of cloud infrastructure. Observability is less about metrics than what can be learned from a workload based on its external characteristics. The two aspects of cloud observability are methodology and operating state. Methodology emphasizes specifics like metrics, tracing, and log analysis. Tracking and event relationships are integral to operating state, which is a part of DevOps.

Cloud monitoring challenges

Maintaining modern and distributed application designs is one of the biggest challenges for IT teams. Monitoring strategies must adapt as applications change. Monitoring cloud applications is a complex process. As different types of applications need monitoring in different ways, the tools that an organization currently uses may no longer be adequate.

Performance management

is about maximizing the performance of an application. There is no single architecture that will guarantee peak performance for all applications, but there are some ways to boost cloud performance across the board:

• correctly sizing instances. Start by choosing the right resources for a workload.
  
• Use autoscaling. In public cloud computing, instances can be added and deleted on demand due to their dynamic nature. Rules are applied to track when workloads exceed or decline from a given threshold, and resources are readjusted as a result.
• Cached. Application performance can be slowed by accessing storage. Cache data allows applications to execute tasks much faster than they would if they had to access data from regular storage.
• The key features and functions of an application are built in modular services in a microservices architecture. If you break down an application into a number of programs that are deployed, operated and scaled separately, you will be more responsive than if the application is monolithic.
• Use event-driven architectures. Event-driven architectures can be implemented on cloud services, such as AWS Lambda, Azure Functions and Google Cloud Functions. The cloud platform hosts code for specific software behaviors and functions. When it is triggered by an event, it operates. Once completed, it no longer consumes cloud resources.

Load balancing is another way IT shops can optimize cloud application performance, since it distributes network traffic so that each instance performs at peak performance. The load balancer used to be a local appliance in the data center. A typical application today is one that lives on a server and is provided as a network service.

Cloud management strategies

Cloud management strategies are not only successful when tools and automation are used effectively, but also when competent IT staff is in place. In order to assimilate to a cloud culture and understand the business's goals, IT and business teams must collaborate naturally.

As well as testing cloud application performance, monitoring cloud computing metrics, making critical infrastructure decisions, addressing vulnerabilities and updating business rules that guide cloud management, IT teams must also maintain cloud infrastructure. In addition, organizations must rethink their change management policies for the cloud, where resource consumption can be much faster and more distributed than in an on-premises environment.

Organizations lacking qualified IT staff can seek help from third parties. Budget threshold alerts can be sent by third-party apps to finance and line-of-business stakeholders, so they can track their cloud spending. Many cloud brokerages offer service catalogs and financial management tools. During the phase when apps go into production, cloud spending should be scrutinized.

It is important that cloud management training extends beyond IT to other departments, from supply chain to accounting. Cloud training, such as certifications through CompTIA Cloud Essentials and AWS Cloud Practitioner, can benefit personnel. If traditional certification programs are too expensive, consider online programs such as LinkedIn Learning, A Cloud Guru, Linux Academy, etc.

Tools and platforms for cloud management

An enterprise-wide cloud management platform can help deploy, manage, and monitor all cloud resources as cloud computing becomes more prevalent. Enterprise IT must understand what it wants to monitor before evaluating cloud management platforms to meet those needs -- whether it's individual tools that solve a single problem, such as network performance or traffic analysis, or a comprehensive suite that covers all aspects of IT operations. Many of these decisions will be made based on tools from cloud providers, such as security tools from cloud platform vendors or from third-party providers.

Most comprehensive cloud management products cover the following five categories: automation and orchestration for applications and individual VMs; security, such as identity management, data protection, and encryption; policy governance and compliance, including audits and service level agreements; performance monitoring; and cost management.

Many multi-cloud management vendors offer a range of tools, each with strengths and weaknesses. Some of the more prominent ones are VMware, CloudBolt Software, Snow Software (which acquired Embotics), Morpheus Data, Scalr and Flexera. Also in this mix are traditional IT service management vendors, such as BMC Software, CA Technologies, Micro Focus and ServiceNow, which typically serve big companies with ITSM governance processes.

Those who use a single public cloud might want to stick with the tools provided by that provider since these tools are designed to complement those native management platforms. Google Cloud Operations (formerly Stackdriver) monitors Google Cloud as well as applications and virtual machines running on AWS Elastic Compute Cloud. Data and resources from the Azure cloud are collected and analyzed by Microsoft Azure Monitor. Amazon CloudWatch is available to AWS customers. There are also options such as Oracle Cloud Infrastructure's Application Performance Monitoring service and Cisco CloudCenter, as well as tools such as Datadog for cloud analytics and monitoring, and New Relic for monitoring web applications. For enterprises comfortable working with open source tools, there are also plenty of open source cloud monitoring options.

Private cloud management tools

Typically, enterprises use their own tools for managing private clouds. A private cloud does not offer the unlimited elasticity of a public cloud service built on a massive infrastructure. To ensure that no single app consumes too many resources within the company, the IT team must ensure it has adequate, available resources and manage environments carefully.

Platform-specific management software such as Turbonomic Operations Manager (now owned by IBM) or Snow Commander can be used in-house. Private cloud management tools are also available with sophisticated software frameworks to manage hybrid cloud deployments, such as Microsoft System Center Virtual Machine Manager for Hyper-V, VMware vCloud Suite, and Citrix Cloud.