AWS Cloud Cost Saving process and Challenges.
If you are spending 4 digit dollars on every month, then this information is more relevant. Any complex application stack which has Data tier, App Tier, Content tier, Network & Load Balancer Tier and Monitoring Tier.
Let’s go through the quick questions .
a. Does the app is being developed through Multi Cloud (Hybrid) approach ?
Formulate the basic checklist questions
- How does the app/product stack was being deployed ?
- How does the traffic routing through DNS, LB & App flow?
- How does the monitoring is being configured ?
- Peak & offpeak hours ?
- Devops pipeline and Continuous provisioning model?
- Security checkpoints & tools ?
- Disaster Recover mechanism ?
- Backup’s duration ?
Formulate the cost associated to it
b. Does it require 100% instance availability ? Day time & Night time also ?
Choose the right sizing of EC2 instance and what it requires for the app.
Steady state: The load remains constant over time, making forecasting simple. Consider using Reserved Instances. • Variable, but predictable: The load changes on a predictable schedule. Consider using
Auto Scaling. • Dev/test/production: Development, testing, and production environments can usually be turned of outside of work hours.
Temporary: Temporary workloads that have fexible start times and can be interrupted are good candidates for Spot Instances.
c. Does the stack requires to run specific zone ? Can it be run on the lower cost zones ?
- AUTOMATING TIMEBASED ELASTICITY
- Amazon EC2 Scheduler & Amazon EC2 API tools –>Programmatically terminates the instances.
- AWS Lambda –> Threshold based events to trigger the start/stop instances
- AWS DataPipeline –> Manage through AWS CLI commands for scheduling.
- Amazon CloudWatch –> stops the unused or underutilized EC2 instances
# AUTOMATING VOLUMEBASED ELASTICITY
- Auto Scaling: This is a straight forward. Automatically increases the
number of Amazon EC2 instances during demand spikes Application
- Auto Scaling: Automatically scales resources for other AWS services
- Amazon ECS: Can scale services automatically in response to
- CloudWatch alarms. Amazon EC2 Spot Fleets: Launches or terminate
instances according to scaling policies.
-Amazon EMR clusters (Elastic MapReduce): Scales out and scales in core and task nodes in a
cluster.
-AppStream 2.0 fleets: Adjusts the size of a fleet
automatically based on utilization metrics, and optimizes the number
of running instances to match demand.
-Amazon DynamoDB: Dynamically
adjusts provisioned throughput capacity in response to actual traffic
patterns.
OnDemand - Reserved - Spot instances
| On-Demand |
Reserved |
Spot Instances |
| $5,000/mo |
$3,000/mo ($2,000/mo) |
$1,000/mo ($4,000/mo) |
| $60,000/mo |
$36,000/mo ($24,000/mo) |
$12,000/mo ($48,000/mo) |
Storage optimization
- S3 - Redefine the purge policies & Retention policies , migrate to the cheaper tier.
- EBS -(Elastic block storage) –>Resize the snapshot and remove the unwanted snapshots
Change the culture:
- Make use of tagging feature for every resource for better understanding in elastic search and also the cost explorer
- Not everytime the low cost model is successful. Tradeoffs between speed-to-market and upfront cost optimization are consciously chosen.
- Costs are clearly allocated using linked accounts and tags.
AWS is going very aggressively , frequent reviews on every quarter will help on cost optimization and correct way of doing with AWS.