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Centralized Log Management for Optimizing Cloud Costs

January 20, 2021

Centralized Log Management offers the visibility you need to optimize your cloud usage to keep infrastructure costs down. 

Cloud-first infrastructures are the future of modern business operations. As organizations like Google and Twitter announce long-term plans for enabling a remote workforce, maintaining a competitive business model includes scaled cloud services adoption. While the cloud offers scalability that can save money with pay-as-you-need services, managing the costs is challenging. Many organizations use more services than estimated, which undermines the original reason for choosing the cloud service.

How is cloud pricing calculated?

Cloud services providers base their pricing models on the type and amount of services consumed, including the number of virtual machines, memory used, storage, and time spent in the environment. If you plan to use workloads regularly, a long term commitment makes sense. Meanwhile, for compute-intensive workloads, you may want to use a pay-as-you-go plan to reduce costs. 

Additionally, you may also want to consider direct and operational costs, such as:

  • Physical servers
  • Software licenses
  • Maintenance contracts
  • Warranties
  • Supplies
  • Labor for maintenance
  • Facilities for housing hardware
  • Internet connectivity
  • Network bandwidth
  • Storage
  • Backup
  • Database capacity

Finally, most organizations now use a multi-cloud strategy to maximize different providers’ strengths and minimize their weaknesses. With so many variables included in the cost calculation, many organizations struggle to estimate cloud costs effectively and often turn to cloud cost optimization to drive better results. 

What is cloud cost optimization?

Cloud cost optimization is the process of standardizing business processes that provide governance over compute and storage resources by identifying inefficient usages, then consolidating or eliminating underutilized and idle resources.

For example, a developer spins up a workload for a specific purpose but leaves it running after completing the project. The organization is charged for this resource even though it no longer uses it. Purposeful cloud resource use reduces overall costs for a better return on investment. However, getting visibility into resource use can be difficult. Monitoring this usage will allow you to know sooner rather than later when you need to turn down systems. This knowledge equals saving costs.

Why organizations struggle with cloud cost optimization

While every cloud services provider offers tools to help companies optimize their cloud costs, the interconnected nature of these ecosystems often means that one action can create a domino effect across the infrastructure. In multi-cloud infrastructures, visibility becomes a problem since vendor-supplied dashboards may not integrate. Siloed information leaves you trying to compare divergent data, often creating gaps in your monitoring. 

Additionally, organizations often struggle to align service use with financial impact. According to Flexera 2020 State of the Cloud Report, optimizing existing cloud spending was the top initiative for the fourth year in a row. Specific data points include:

  • 82%: enterprises struggle managing cloud spend
  • 79%: enterprises struggle with governance 
  • 30%: self-estimated spend waste
  • 35%: average actual spend waste
  • 51%: organizations reporting that they shut down workloads after hours
  • 49%: organizations reporting that they rightsize instances

Increased use of cloud services leads to increased problems with cost optimization. The more services an organization uses, the less visibility into its use it has. The cloud offers flexibility, efficiency, and strategic value only when organizations can manage the costs effectively. 

Centralized log management and cloud optimization

Centralized log management provides visibility into cloud computing processes, which helps you identify what you can optimize. Since all actions taking place within your infrastructure generate a record, you can leverage a centralized log management solution to uncover inefficient processes, misconfigurations, or underutilized resources. When aggregated and correlated appropriately, event logs provide detailed information and offer insight into additional cost reduction areas. 

Identify Underutilized Resources

Underutilized resources drive up cloud costs because your organization pays for their existence, not how often you use them. Some examples of event log data that can help optimize your cloud costs include: 

  • CPU usage: Many organizations review CPU usage to detect processes that reduce performance. However, using historical log data, you can also gain visibility into processes with low CPU usage. Because you pay for instances by the hour, reducing low usage resources can reduce costs. 
  • RAM usage: While CPU usage measures processing, measuring RAM usage needed to load applications will help define how much is required. This metric enables you to optimize your server memory spend. If your monitoring proves that you regularly use only a fraction of the memory you need, you may be able to reduce costs. 
  • Load balancers: Cloud service providers often charge for any configured load balancers, even those with limited use. Load balancer logs can provide visibility into how efficiently you manage your resources and offer insight into where you can reduce costs. 
  • Virtual machine removed: When trying to reduce pay-as-you-go costs, you need visibility into the number of VMs removed from your cloud to determine whether your team is efficiently using your compute capacity. 
  • VM access logs: You can view access logs to learn how often users access your VMs and eliminate underutilized ones. 

Monitor Autoscaling and Rightsizing

Autoscaling and rightsizing often enable you to optimize your cloud costs. However, they only work when you monitor the metrics to ensure that you have established the right parameters. Since these capabilities work to maintain performance, not monitoring them can lead to increased costs associated with Spot Instance use. 

  • Disk read/write: Setting alerts for disk read/write metrics can let you know when you need to launch new instances to monitor disk IOPS and track instance termination to ensure that they are terminated appropriately. 
  • API call logs: Cloud services charge API calls per object, not by the amount of data transmitted. Monitoring API call logs can give insight into areas where you can use batch objects to reduce costs. 
  • Firewall logs: Autoscaling reviews incoming network traffic to determine whether a resource needs additional resources. Firewall logs can help show underutilized areas, giving visibility to places where you can optimize your cloud usage and costs. 

Using Graylog’s Centralized Log Management for Cloud Cost Optimization

Centralized log management is a key component for cloud cost optimization. Graylog is a leading centralized log management solution built to open standards for capturing, storing, and enabling real-time analysis of terabytes of machine data. Thousands of IT professionals rely on Graylog’s scalability, comprehensive access to complete cloud and om premise data, and exceptional user experience to solve security, compliance, operational, and DevOps issues every day. Purpose-built for modern log analytics, Graylog removes complexity from data exploration, compliance audits, and threat hunting so you can quickly and easily find meaning in data and take action faster.


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