Proven Strategies For Reducing Your AWS Cloud Bill

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Proven Strategies For Reducing Your AWS Cloud Bill

Optimizing costs on AWS is a crucial part of running a cost-effective cloud infrastructure. With tighter budgets and limited resources, it is essential to be strategic in how you spend your resources on AWS. By understanding optimization strategies, you can reduce operational costs while maintaining performance standards.

In this article, we will first dive into understanding the main drivers of cost and then go over very effective cost optimization techniques that have proven to provide huge cost savings on AWS

Three Main Drivers Of Cost

When using Amazon Web Services (AWS), there are several key cost drivers that will impact the overall expenses for a particular service or application. The three main drivers of cost on AWS are Compute, Storage and Outbound Data Transfer.

Compute

Compute costs can be broken down into EC2 costs, which refer to the compute resources used to run applications in the cloud, as well as Lambda charges, which are billed based on the number of requests for code execution and duration of each request. Additionally, Amazon ECS (Elastic Container Service) provides container services and is also charged by the amount of resources used including EC2 Fargate.

Storage

Storage costs typically include EBS (Elastic Block Storage) volumes, Glacier storage for long-term archiving purposes, S3 (Simple Storage Service) buckets used to store data objects in the cloud and RDS Database instances with their associated provisioned storage and retained backup snapshots

Outbound Data Transfers

Outbound Data Transfer refers to data sent from AWS- hosted services to external networks or systems outside the AWS environment. This includes both direct uploads from customers’ applications running on AWS as well as downloads initiated by customers’ end users. Charges for outbound data transfers depend on bandwidth allocation and usage pattern over a given month/year period.?Outbound data transfers also include cross-region replication/transfers within AWS environments

Additional Cost Drivers

In addition to these three main drivers of cost on AWS, there are other components that can add additional expense to an organization's monthly bill. These include load balancing services such as Elastic Load Balancing (ELB); API gateway fees; content delivery fees; managed solution fees (for example EKS); backup fees; monitoring services fees such as CloudWatch; support packages fees such as Business Support or Enterprise Support plans; SSL certificate fees etc… It is important for businesses using cloud infrastructure solutions like AWS to make sure they understand all associated charges when selecting a particular service option or package in order to avoid any potential surprises at the end of the billing cycle.

Optimizing Compute Costs

Optimizing compute costs on AWS is an important part of ensuring that businesses get the most value for their resources. Following are the most effective approaches to getting significant cost savings on compute on AWS

Reserved Instances (RIs)

RIs offer businesses a significant discount compared to on-demand instances, as they are paid for upfront at a fixed hourly rate over the duration of the reservation period. This allows businesses to save money in the long run and ensure that they are always getting maximum performance from their instance.

Savings Plans

Another way to optimize compute costs on AWS is by using Savings Plans. These plans allow customers to commit to a certain amount of computing power usage and pay for it at a discounted rate. Customers can set up their own custom plans or choose from pre-defined Amazon EC2 Savings Plans or Compute Savings Plans, depending on their need. Both plans offer customers substantial savings compared to what they would pay if they used On-Demand rates instead.

EC2 Spot Instances

In addition, customers can also get significant discounts with EC2 Spot Instances, which provide unused Amazon EC2 capacity at significantly reduced prices compared to On-Demand and Reserved Instances. When demand falls below expected levels, Amazon makes these spare instances available to customers at deep discounts, allowing them to take full advantage of lower prices while still enjoying reliable performance from their instances.

Additional Techniques

Finally, customers can also optimize compute costs through Auto Scaling and using other cost-saving features such as Trusted Advisor and AWS Cost Explorer.

With Auto Scaling, companies can automatically add or remove instances according to changes in demand without having to manually scale up or down their instance count and instead rely on the system's intelligent handling mechanism.

Trusted Advisor helps identify areas where businesses could be saving additional costs on services like storage and databases while AWS Cost Explorer provides detailed insights into how much an organization is spending each month so that more informed decisions can be made when it comes time to adjust budgets accordingly.

Optimizing storage

Optimizing storage costs on AWS can be accomplished through a number of strategies. One of the most effective ways to reduce storage costs on AWS is to use Reserved Capacity. The concept is similar to EC2 Reserved Instances discussed above i.e get discounted pricing on specific services in exchange for a commitment to use that service for a predefined period of time (1 or 3 years).

Reserved Capacity For DynamoDB

To optimize DynamoDB costs, you can leverage reserved capacity. Reserved capacity allows you to pay for a reserve of read and write throughput that is guaranteed to be available whenever needed, which eliminates the need to pay for additional capacity on an as-needed basis. In addition, reserved capacity also comes with significant discounts over on-demand pricing.

Reserved Nodes For ElastiCache

To optimize ElastiCache storage costs, use Reserved Nodes, which allow you to reserve compute resources ahead of time and receive discounts based on the size of the reservation term and number of nodes purchased. This reduces costs compared to On-Demand or Spot pricing models while still allowing you access to resources as needed when demand increases or decreases; similar concept as Reserved Capacity for DynamoDB and Reserved Instances for EC2

Reserved Instances For RDS

For RDS significant price discounts can be achieved via Reserved Instances (RI). Just like RIs for EC2 instances, these provide a discount from On Demand prices by committing to use specific instances for a 1 or 3 year period

Reserved Nodes For Redshift

To optimize Redshift storage costs Reserved Nodes can be purchased that offer similar benefits as RI on RDS; customers purchase hardware upfront at discounted prices that are applied throughout their usage duration as long as they remain committed users.

Additionally, Redshift also offers “Concurrency Scaling” which dynamically adjusts nodes used based on workloads and queries – allowing customers more flexibility in managing their cluster size and maximizing cost savings when demand drops back down again.

Storage Classes For S3

To save costs for S3, Storage Classes should be used in conjunction with Life Cycle Policies. These features allow customers to store data at different levels of performance based on their needs. The?Standard?Storage Class is accessed frequently but does not offer reduced prices when storing large amounts of data. The S3?Infrequent Access?Storage Class offers reduced pricing when storing large amounts of data that is accessed less frequently than the Standard Storage Class. Finally, the?Glacier?Storage Class provides extremely low-cost storage for archiving data that is rarely accessed but must be retained long-term. Through the use of the S3 Life Cycle Policies customers can automatically move data from Standard and Infrequent Access classes into Glacier as it ages saving them money in the process.

Optimizing Data Transfer Costs

Optimizing data transfer costs on AWS can be done in a number of ways but first, it’s important to understand what factors influence data transfer costs on AWS:

1. There are no costs incurred on inbound data transferred to AWS. Costs are incurred for outbound data transfer from AWS
2. Data transferred between two different Availability Zones in the same region is free of charge.
3. Data transferred between regions is charged according to the amount of data transferred.

In addition to paying attention to the above, there are a few other best practices that can be employed when looking to optimize data transfer costs on AWS:

1. Route your traffic within AWS instead of over the internet by utilizing VPC endpoints. VPC gateway endpoints enable seamless communication with Amazon S3 and Amazon DynamoDB without incurring any data transfer fees within the same region. For certain AWS services, VPC interface endpoints are an option, but be aware that this option incurs an hourly service fee and data transfer fees.
2. Consider using direct connect services instead of public internet access whenever possible – this will reduce both latency time and cost per Gigabyte transferred.
3. Use multiple Availability Zones within a single region as well as leveraging replication strategies across regions in order to minimize inter-region traffic while increasing redundancy and reliability across distributed applications.
4. Certain types of transfers could be optimized by leveraging CloudFront Edge locations for content delivery networks (CDNs). This allows for reduction in reduce latency times and enhance end-user experience by caching static assets closer to end users geographically; in turn driving down the overall cost for serving those assets due to fewer round trips having to be made through regional gateways.
5. Similarly, for faster access times to objects stored within S3 buckets, S3 Transfer Acceleration could be enabled; it leverages CloudFront Edge Locations for faster downloads via shorter routes.

Article originally posted at: https://12tech.io/12tech-blog/proven-strategies-for-reducing-your-aws-cloud-bill