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Amazon Auto Scaling Latency

By Paul Carley posted Mon February 27, 2023 02:37 PM

  

Amazon Auto Scaling is a service that automatically adjusts the number of Amazon Elastic Compute Cloud (EC2) instances in a specified group based on certain conditions, such as the average network latency of the instances. This helps to ensure that the instances can handle the incoming traffic and provide the required level of performance for your application. 

There are various factors that can impact the latency of Amazon Auto Scaling, including the scaling policies you have defined, the size of your instance group, and the time it takes for new instances to launch. In general, Amazon Auto Scaling is designed to respond quickly to changes in demand, so the latency is typically low. However, in some cases, there may be a delay between the time the demand for resources changes and the time the instances are scaled.

If the latency is high, it could indicate that there are not enough instances to handle the incoming traffic, this is where auto scaling will automatically add more instances to the group to help alleviate this.

To minimize latency and ensure that your application always has the resources it needs, it is important to carefully plan your scaling policies and monitor the performance of your instance group. Additionally, you may want to consider using Amazon EC2 Auto Scaling, which automatically adjusts the number of EC2 instances in a group based on demand, rather than Amazon auto scaling, which requires manual scaling policies to be defined.

Fixing Amazon Auto Scaling latency can involve several steps, including:

  1. Monitor performance: Use Amazon CloudWatch to monitor the performance of your Auto Scaling group and identify any potential latency issues.
  2. Analyze Latency Causes: Analyze the root cause of the latency, such as network congestion, disk I/O, CPU utilization, and memory usage.
  3. Update Launch Configuration: Update the Launch Configuration for your Auto Scaling group to use larger instance types with more CPU, memory, and storage if necessary.
  4. Use Placement Groups: Use Placement Groups to ensure that the instances in your Auto Scaling group are in the same Availability Zone and network for low network latency.
  5. Tune your application: Optimize your application code to reduce response time and improve performance.
  6. Use Load Balancers: Use Elastic Load Balancers to distribute traffic evenly across multiple instances and help reduce latency.
  7. Enable Auto Scaling: Enable Auto Scaling based on demand and set appropriate scaling policies to ensure that your Auto Scaling group has the resources it needs to meet performance demands.

These are some steps that you can follow to fix Amazon Auto Scaling latency, however, the specific solution will depend on the specific root cause of the latency. And while Amazon auto scaling can leverage many of these tools, it still requires analysis and actions from IT admins to correct the issue. This can result in many man hours properly monitoring and designing your deployment to ensure proper performance. And often admins will overprovision cloud resources to ensure they have enough, leading to wasteful cloud spending and going over cloud budgets. What if there was a way to incorporate automation to ensure your applications are always performing properly with the right number of resources and budgets are kept in line?

Free Offer: Try the IBM Turbonomic Sandbox, no configuration required!

Using IBM Turbonomic to ensure application performance continually

As organizations continue to move to the cloud and develop a hybrid approach, IT is realizing the complexity that comes with moving to hybrid cloud. Migrating applications to the cloud, monitoring their performance, and responding instantly to a performance issue can be a difficult task even for the highly trained, experienced IT personnel.

To avoid disruption, IT may overprovision resource allocations, making estimates that are often costly and don’t always pay off. This leads to higher consumption costs and still doesn’t assure application performance or timely response when problems occur. 

IBM Turbonomic is a software platform that uses AI-driven automation to manage the performance and capacity of applications running on physical, virtual, and cloud infrastructures. It helps to ensure application performance by continuously monitoring the resources being consumed by the applications and dynamically adjusting the allocation of those resources in real-time based on defined policies. 

Turbonomic dashboard

IBM Turbonomic software uses an application-driven, top-down approach to “stitch” your resources, such as memory, CPU, and storage, together. It’s much more than visibility and monitoring; the IBM Turbonomic platform continuously considers how each entity, such as a VM or container, works with and impacts every layer, bridging silos for increased collaboration. IBM Turbonomic helps to ensure that applications are always performing at their best, even during periods of high demand or unexpected spikes in resource usage.

Here how Turbonomic ensures application performance:

  1. Resource monitoring: Turbonomic collects real-time performance and resource utilization data from various sources, including virtual machines, storage devices, networks, and applications.
  2. AI-driven analysis: The collected data is analyzed using algorithms to determine the most efficient allocation of resources for each application.
  3. Dynamic resource allocation: Based on the analysis, Turbonomic makes real-time adjustments to the allocation of resources, such as CPU, memory, storage, and network bandwidth, to ensure that each application has the resources it needs to perform optimally.
  4. Policy enforcement: Turbonomic enforces policies defined by administrators to ensure that applications are always given the necessary resources, while also considering constraints such as budget and compliance requirements.

Ask yourself how important your applications to your business are today and consider a new way of managing your business-critical applications to assure performance with a trusted AIOps solution. Try IBM Turbonomic today and ensure your critical applications always perform in the cloud and in the data center.

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