Amazon EC2 Auto Scaling

Validating forecast accuracy has never been faster – now with Amazon EC2 Auto Scaling.

Carrying out successful projects with Amazon EC2 Auto Scaling is common in our developments. Because it allows us to maintain application availability and automatically add or remove EC2 instances according to conditions you define. But we are also seeing a continuous improvement in the capabilities of the predictive and auto-scaling tools we use. And is that since last week we can do that Amazon EC2 Auto Scaling goes back 14 days to generate capacity forecasts for the past dates, enabling you to see how predictive scaling would have scaled your Auto Scaling group.

Now when Cloud Levante’ team create a new predictive scaling policy, we can quickly validate forecast accuracy. 

This allows our clients to quickly decide if the predictive scaling policy is accurate for your applications by comparing the demand and capacity forecasts against the actuals immediately after you create a predictive scaling policy. Previously, you would have had to wait at least a few days after creating the policy to build up sufficient forecast history for the same comparison to determine the forecast accuracy. Adding Amazon EC2 Auto Scaling to your of our customers’ applications architecture is one way to maximize the benefits of the AWS Cloud.

With Amazon EC2 Auto Scaling we can help companys meet application demand by automatically adding or removing EC2 instances to an Auto Scaling group according to the conditions you define. Besides to offering dynamic scaling policies that react to changes in demand. Auto Scaling allows us offer predictive scaling policies that can proactively change the size of our customers’ Auto Scaling group in advance of predictable demand spikes. This help us maintain high application availability and responsiveness.

When we use Amazon EC2 Auto Scaling, customer applications benefit greatly. 

At Cloud Levante we develop projects where predictive scaling can observe recurring peaks in certain months, weeks, days or even hours. Thus, we can predictively scale the application before the increase in traffic occurs so that we do not have to overprovision your Auto Scaling group and prevent the platform from crashing due to excessive load.

Amazon EC2 Auto Scaling detect when an instance is unhealthy, terminate it, and launch an instance to replace it achieving better fault tolerance. Companies have at their disposal Multiple Availability Zones. So that if one Availability Zone becomes unavailable, we can launch instances in another one to compensate. We ensure that the application always has the right amount of capacity to handle the current traffic demand. With all this there is improved cost management. Since by increasing and reducing capacity as needed our customers pay only for the instances they use, they save money by launching instances when they are needed and terminating them when they aren’t.

DESIGN AND DEPLOY AUTO SCALING PLATFORM

 

Pipeline design to deploy new App versions.

Integration with external Data platforms.

Machine Learning dev environment.

Database Migration to Cloud.

Networking platform.

DESIGN AND DEPLOY KUBERNETES PLATFORM

 

Prometheus and Grafana monitoring system.

Defined pipeline to deploy services.

Microservice High Availability.

Platform metric system.

Health control panel.

DEPLOY AUTOMATIC SYSTEM VERTICAL SCALING

 

Ecommerce Migration.

Improve platform capacity.

Load optimisation when traffic increases.

Flexibility: scale up or down as needed.

Performance and Cost Savings.

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