Cloud optimization is the process of selecting and allocating the appropriate resources to a workload or application. Efficiency is achieved when workload performance, compliance, and cost are correctly and continuously balanced against the best-fit infrastructure in real time.
Every application’s and workload’s infrastructure requirements are distinct, and these requirements change over time. Traditionally, baseline performance is achieved by using domain knowledge when selecting resources for a workload, but all workloads that have been manually matched to cloud resources can benefit from and be further optimized using machine intelligence.
Apps with their ongoing needs dynamically matched to the optimal cloud supply perform better, require fewer resources to manage and less supporting infrastructure on-premises and in the cloud, and provide the best value for cloud dollars spent.
Why Organizations are Concerned about Cloud Optimization
Cloud optimization is a deliverable for IT Operations teams that are in charge of resource allocation, such as CloudOps or DevOps, depending on the organization.
These highly skilled individuals are frequently caught between the requirements of Finance departments, which want to control cloud spend, and application owners, who never want to hear that their apps’ resources are being reduced.
For modern organizations to succeed, IT Operations must maintain control over these stakeholders. Cloud optimization enables CloudOps to maximise cloud value-for-spend (assuring Finance Analysts and the CFO) while also delivering top-tier app performance and reporting (making application owners and their end users happy).
Purchasing services that do not match application requirements exposes businesses to risk and unnecessary cloud spending—results that cannot be tolerated.
Things to optimize
For most businesses, cost reduction is the most important factor in cloud optimization. One significant disadvantage of cloud computing is that it is very easy to overspend by allocating more resources to your workloads than you would on-premises.
The complexity of cloud pricing models exacerbates the problem. Cloud service providers frequently use pricing menus that charge different rates for the same services in different regions or at different times.
The cost monitoring tools provided by the cloud provider can assist in resolving this issue (i.e., Cost Optimization Monitor for AWS and Cost Alerts for Azure). These tools can help you better understand your spending and alert you when you go overboard.
Cloud providers, on the other hand, do not intervene to prevent users from overspending on their platforms. They do not offer tools for working in hybrid or multi-cloud environments. As a result, cloud cost-cutting strategies typically include a variety of tools and methods, such as third-party services for multi-cloud architectures, rather than native, vendor-specific offerings.
Optimizing cloud performance entails ensuring that your services and applications run quickly and smoothly.
Cloud performance, like cost, is a complex subject that is affected by numerous factors. The design of the cloud architecture is an important factor to consider. A cloud architecture that requires frequent data transmission between different regions or separate clouds, for example, may suffer from poor performance as a result of network latency and bottlenecks.
The type of cloud service you select may also have an impact on performance. For certain workloads, VM resource allocation may be more constrained—serverless features may outperform standard VMs.
Even if the code isn’t explicitly cloud-specific, the underlying efficiency can have a big impact on cloud performance. Before deployment, you should test the performance of all application code on a regular basis.
A cloud-based workload can become unavailable if the hosting cloud fails. Workloads can become unreliable due to inherent issues. It is critical to mitigate these risks in order to maximise the dependability of your cloud applications.
Redundancy is a solid strategy for ensuring dependability. A company will deploy multiple instances of a single workload across multiple regions within a cloud or in separate clouds. However, because this type of protection is frequently costly, it is critical to balance the redundancy strategy with cost optimization goals for the best overall results.
Third-party solutions that ensure enterprise-level SLAs across multiple clouds can also be used to supplement these strategies.
Working in the cloud can make it difficult to accurately identify security vulnerabilities and put in place the necessary security measures to mitigate them. This challenge can be met by achieving centralised visibility and utilizing tools that provide actionable security insights.
Choose a tool with dedicated security measures that can address the most common, severe threats your cloud systems are likely to face. Ascertain that the technology offers both preventive and reactive measures:
Pre-event awareness entails assessing risks and putting in place the necessary safeguards before events occur. Container visibility, VPNs, and virtual machine (VM) encryption are all important pre-event safeguards.
Post-event awareness entails implementing measures that aid in the effective and timely identification and response to security events. DevSecOps practices, security risk mitigation tools, and compliance automation are examples of common post-even techniques.
Why is cloud optimization important?
Many organisations experience cloud overspending by allocating more resources to a workload than is necessary. Including cloud optimization practices in your cloud infrastructure and organisation can reap numerous benefits, including the following:
- Cloud Efficiency: Efficiency is achieved when workload performance, compliance, and cost are constantly balanced against the best-fit infrastructure in real-time. Implementing cloud optimization practices will reduce cloud resource waste to the greatest extent possible, thereby improving the performance of your cloud environment.
- Cost Savings: Although cloud optimization can take many forms, cost optimization is the most important aspect for many businesses. Costs are reduced as a byproduct of reducing waste in the cloud.
- Greater Visibility: Analytics are used in cloud optimization practices to provide visibility into your cloud environment so that data-driven decisions can be made. Implementing optimization tools also improves cost visibility, giving your organization a better understanding of its cloud spending.
- Increased Productivity: After implementing a cloud optimization strategy, IT teams will spend less time trying to solve problems because an optimized environment prevents problems from occurring.
- Organizational Innovation and Efficiency: Implementing cloud optimization frequently results in a cultural shift within organizations, such as improved decision-making and team collaboration.
Cloud Cost Optimization Strategies
Consider the following strategies for optimal long-term performance:
It is critical to reduce the costs of existing systems without requiring design changes, such as waste removal and proper repositioning. Right-sizing evaluates the amount of money paid on unused capacity by analyzing resource usage vs. capacity. This is typically a service-based study that looks at specific aspects of a specific service.
Teams with individual finances must keep track of their Cloud Budget and expenditure. Cost Centers can be assigned to their own account, making reporting easier. If an organisation employs multiple application teams with varying budgets, each team should be able to allocate costs to the appropriate team.
This would ensure that there is a standardised method for verifying ownership of Cloud resources. When resource naming standards fail, extra properties are frequently used as resource labels. Consider resource labels in the cloud to be barcode-based labels.
Find cost-effective ways to quickly replace existing system components. Cloud-native ideas seek to capitalize on every economic advantage gained by leveraging cloud-specific capabilities. Automatic scaling is one example.
All servers used to build the pool are purchased in advance and are still being paid for. The great cloud-native benefit is that you are only charged for server activity on collections. Cloud auto-scale means that the paid capacity does not significantly exceed the system’s usage.
To achieve your business goals, you must reduce time-to-market and accelerate innovation. As a result, you must have a cloud strategy in place to support your long-term business objectives. Cloud computing can help you reduce time to market and accelerate innovation.