In today’s fast-paced digital world, latency is a critical factor in ensuring the smooth functioning of applications, particularly those in sectors like financial services where real-time data processing is a must. In a hybrid cloud environment, where on-premises resources and public cloud services coexist, reducing latency becomes even more crucial. Latency issues in such environments can hinder the performance of applications, degrade user experiences, and even lead to financial losses, especially in industries like finance.
Let’s take a look at some of the ways you can reduce latency in a hybrid cloud environment, and some of the tools AWS offers to bring the cloud closer to on-premises systems.
The Importance of Low Latency in a Hybrid Cloud Environment
Latency, the delay before a transfer of data begins following an instruction for its transfer, is a critical factor for applications that require real-time processing. For hybrid cloud environments, where workloads are split between on-premises data centers and the cloud, latency can be influenced by several factors, including network performance, distance between resources, and data transfer rates.
Applications that require low latency include real-time trading platforms, fraud detection systems, risk analytics, and other financial services that rely on instant data processing. These systems must operate without noticeable delay to make decisions based on live data, and any latency can cause significant issues in these scenarios.
AWS Services to Reduce Latency in Hybrid Cloud Environments
Amazon Web Services (AWS) provides a wide range of services and tools designed to optimize the performance of hybrid cloud environments. These tools help minimize latency by bringing cloud resources closer to on-premises data centers, ensuring faster communication. Here are three examples.
1. AWS Local Zones
AWS Local Zones extend AWS services closer to end users by placing AWS compute, storage, and other resources in metropolitan areas. These local zones can bring services like EC2 instances and EBS volumes closer to on-premises infrastructure, significantly reducing latency. For hybrid cloud environments, AWS Local Zones provide a solution to reduce the time it takes to access cloud services from on-premises systems.
For a financial services company operating in New York City, the closest AWS region is US-EAST-1, located hundreds of miles away in Virginia, but AWS also offers a Local Zone as part of this region, and that’s in the New York City area. The financial services company could use this Local Zone to ensure that real-time applications like market data feeds or risk analytics systems experience minimal delay. By processing data closer to the source, these applications can deliver faster insights, enabling quicker decision-making.
2. Amazon CloudFront
Amazon CloudFront is a Content Delivery Network (CDN) that can help reduce latency for applications that need to deliver content to end users quickly, regardless of their geographical location. By caching content at edge locations near users, CloudFront ensures that data is served with low latency.
For hybrid cloud environments, CloudFront can cache content from both on-premises and cloud-based sources. Financial applications that require the delivery of market data, stock prices, or real-time analytics to a wide audience can benefit from CloudFront’s low-latency delivery system. For example, an online stock trading platform could use CloudFront to ensure real-time price updates are delivered without delay to users, enhancing the trading experience.
3. AWS Global Accelerator
AWS Global Accelerator optimizes the routing of traffic between users and applications deployed in different regions. By leveraging the AWS global network infrastructure, it ensures that traffic takes the fastest and most reliable path, minimizing latency and improving application performance.
For hybrid cloud applications that span both on-premises and AWS regions, Global Accelerator can significantly reduce latency. Financial institutions that require real-time access to market data and other resources can use this service to ensure that their users experience minimal lag when accessing critical information.
Service Based Approaches in a Hybrid Environment
The previous three examples I shared are general offerings from AWS. These can be utilized in a wide variety of applications. But there are also specific service based offerings that can also help reduce latency in a hybrid environment. Here is one of them.
Kafka Mirror maker
MirrorMaker is a tool for replicating and streaming data between Kafka clusters. If you’re running a Kafka cluster on-prem, and another cluster in Amazon Managed Streaming for Apache Kafka (MSK) in the cloud, MirrorMaker can be used to keep the two platforms in-sync with enhanced efficiency, scalability, and fault tolerance. Not only does this allow you to process messages across both of your clusters for hybrid efficiency, it also provides resiliency in case of a failure in one or the other.
Use Cases of Low-Latency Applications in Financial Services
In the financial services industry, applications that rely on real-time data and decision-making cannot afford to have latency affect their performance. Below are some key financial services applications that require low latency:
1. Algorithmic Trading Platforms
Algorithmic trading platforms, used by hedge funds, investment banks, and other financial institutions, rely on real-time data to execute high-frequency trades. These platforms need to respond to market changes within milliseconds, and even a small delay can result in significant losses. For these platforms, minimizing latency is crucial.
By using AWS services like Direct Connect, Local Zones, and Global Accelerator, financial institutions can ensure that their algorithmic trading systems operate with minimal delay, even when using hybrid cloud architectures.
2. Fraud Detection Systems
Fraud detection systems analyze transactions in real-time to identify potentially fraudulent activities. These systems use machine learning models to assess risk, often relying on data from both on-premises and cloud-based sources. Therefore any delay in processing can result in false positives or, worse, missed fraudulent transactions.
In order to reduce latency for fraud detection, financial institutions can leverage AWS services like Local Zones for fast access to cloud resources, ensuring that data from both on-premises and cloud-based sources is processed with minimal delay.
3. Risk Management Systems
Risk management systems often need to process large volumes of data in real time to assess market risks and other potential threats. In financial markets, delays in calculating risk factors can expose firms to significant financial losses. Reducing latency in these systems is essential to ensure quick and accurate risk assessments.
With AWS Snowcone or Snowball devices, financial institutions can transfer large datasets quickly to the cloud for analysis, while services like CloudFront and AWS Global Accelerator can improve access to global risk data sources, ensuring real-time insights.
4. High-Volume Transaction Systems
Payment gateways, banking systems, and trading platforms that handle high volumes of transactions need low-latency systems to ensure swift transaction processing. Any delay in processing could lead to transaction failures or delays, disrupting customer experiences and creating financial and reputational risks.
By utilizing low-latency solutions, these high-volume transaction systems can ensure quick and reliable transaction processing, both on-premises and in the cloud.
Latency is King
In a hybrid cloud environment, reducing latency is a vital aspect of ensuring the smooth performance of mission-critical applications, especially in industries like financial services. AWS offers a variety of tools and services—such as Local Zones, CloudFront, Global Accelerator and MirrorMaker—that help bring cloud resources closer to on-premises systems, ensuring faster data transfer, real-time processing, and minimal delays.
By adopting these AWS solutions, financial institutions can improve the performance of their hybrid systems, enabling them to stay competitive in an increasingly fast-paced market.