Blogs / Cloud Consulting
How to Reduce Latency When Connecting to a Public Cloud?
By
Sibin Vincent
Posted: September 18, 2024
• 6 Minutes
Cloud computing has quite dramatically redefined the way modern organizations access and utilize IT resources. Gone are the days of struggling for storage space, computing power, and expensive software purchases. By leveraging public cloud services, you can easily provision computing power, storage, and software applications on-demand without any upfront investments in hardware and infrastructure. This highly scalable and flexible model enables you to be more agile and cost-effective, providing a competitive edge in today’s digital landscape.
Despite their numerous benefits, public cloud applications that power your organization sometimes end up delivering a subpar user experience. And one of the major reasons behind it is network latency. When latency levels increase, the application or the website takes too much time to load and respond. This negatively affects the end-user experience.
As far as cloud-based applications are concerned, it is important to keep network latency as low as possible. But to do that, you must first understand what latency is and what causes it. This blog post is intended to give you a full breakdown of the concept of latency while sharing some strategies to reduce the latency when connecting to the public cloud. Let’s begin by looking at what latency is.
What is Latency in Cloud Computing?
Latency can be defined as the time it takes for data to travel from the source to the destination. In cloud computing terms, it refers to the time taken for data to travel from the user’s device to the cloud service provider’s data center, as well as the time taken to process and respond to requests within the cloud infrastructure. High latency results in major performance issues and a negative user experience.
Latency is typically measured as ‘round-trip-time (RTT)’, which is the time it takes for a data packet to travel from the user’s device to the cloud service provider’s data center and back. It can occur due to various factors such as physical distance between the user device and data center, network congestion, inefficiencies in routing, limitations in the cloud service provider’s network infrastructure, etc.
Here are some of the major problems that arise due to high latency in cloud-based applications:
- Poor Application Performance: Web applications and mobile apps often require frequent data transfers or real-time updates. When latency is high, these applications slow down drastically, leading to negative user experiences.
- High Loading Time: When latency is high, web pages, videos, and other media and non-media content hosted in the cloud take a long time to load. This results in users becoming frustrated and even abandoning the application altogether.
- Performance Glitches in Real-Time Applications: Cloud applications that involve real-time data exchange (video conferencing, online gaming, trading, etc.) are severely impacted by high latency, becoming virtually unusable.
- Productivity Loss: If you are relying on cloud tools for improving productivity and collaboration, high latency can be a major headache for you as it will lead to delays in data synchronization, file transfers, and communication.
Now that we have a brief understanding of the concept of latency, let’s analyze the factors that contribute to high latency in the public cloud.
Factors Contributing to High Latency in Public Clouds
- Increased Distance to Data Center: One main factor that contributes to high latency is the distance data packets must travel between the user and the cloud provider’s data center. The greater the distance, the more time it takes for requests and responses to travel, resulting in higher latency.
- Network Congestion: Data packets rely on the public internet to travel between users’ systems and the cloud provider’s infrastructure. There are times when the public internet experiences network congestion and bandwidth constraints, especially during peak usage hours and huge file transfers. This can lead to packet loss, retransmissions, and enhanced queuing delays, contributing to high latency.
- Complex Network Architectures: The network architecture has a huge influence on latency. When the design is complex, it may increase the number of hops or intermediate devices between the user and the cloud service. With each hop, the system experiences processing and routing delays, adding up to the overall latency.
- Misconfigurations in Cloud Infrastructure: Often overlooked, the cloud provider’s infrastructure configuration is an important factor that contributes to high latency. Service providers must ensure that their computing resources (virtual machines, containers, etc.) are fine-tuned and optimized to scale flexibly without compromising on performance. Failure to do so will result in queuing, processing delays, and increased latency for end-users.
- Additional Overhead Due to Security Mechanisms: All major cloud service providers come with advanced security mechanisms. Security measures like firewalls, encryption, authentication protocols, etc., introduce added processing overhead and latency as your data must be inspected, encrypted, decrypted, and validated before processing.
These are some of the most common reasons for high latency when connecting to the public cloud. It is important to evaluate them and take corrective measures to minimize latency and ensure optimal performance. The following section outlines some of the techniques you can employ to reduce latency.
Strategies for Reducing Latency When Connecting to Public Clouds
- Cache Locally: Caching locally eliminates the need for repeated data transfers from the cloud. If you can implement caching mechanisms at the edge of the network, it will allow the applications to fetch the content from local caches instead of pulling it from cloud data centers situated at a distant location. Cached information can include everything from API requests or responses to computationally intensive calculations, image files, database query results, and much more.
- Make Use of Content Delivery Networks (CDNs): A CDN can help you overcome the challenges of high latency effectively. CDNs are a network of servers that are distributed geographically. They cache and compress mirror versions of your content, which are then stored in multiple data centers. When an end-user requests content, the CDN simply delivers it from the closest server, reducing the RTT. Additionally, CDNs have route optimization and load balancing capabilities to ensure data takes the fastest route possible and eliminate any network bottlenecks.
- Implement Edge Computing: Edge computing brings data and processing power closer to the end-user. By using small-scale data centers, known as points of presence (PoP), situated at strategic locations closer to the end-user, edge computing can minimize latency to a great extent. This method of processing and analyzing data at the edge, near the end-user, enables real-time data analysis and optimized resource usage. Edge computing is extremely beneficial in industries like transportation and manufacturing, where a large amount of real-time data is generated from IoT devices and sensors. By analyzing this data at the edge, you can gain valuable insights into equipment performance, thereby identifying potential issues before they become major problems.
- Optimize Your Network Configuration: Network configuration has a huge influence on latency. By properly configuring the network infrastructure with load-balancing mechanisms, firewall rules, and routing protocols, you can minimize latency and improve application performance. Load balancing enables the system to distribute traffic across multiple servers, reducing bottlenecks, while firewall rules and routing protocols eliminate unnecessary hops to ensure efficient data paths.
- Optimizing Application Codes: Inefficient coding practices like excessive data transfers, synchronous communication patterns, and unoptimized algorithms can often lead to high latency levels.
- Code Profiling: Code profiling is the process of analyzing an application’s code to identify performance bottlenecks, resource utilization, and areas for improvement. This process includes collecting and analyzing runtime data (execution times, memory usage, and CPU utilization) to pinpoint the parts of the code consuming most resources or causing performance-related issues.
- Data Serialization: Data serialization involves converting data structures into a format that is suitable for transmission over the network. Inefficient serialization techniques can result in larger data payloads and increased data transfer time. By using serialization methods like binary formats or compressing data packets, you can reduce the amount of data that needs to be transferred.
- Asynchronous Programming: Synchronous communication patterns can often result in a prolonged waiting time, as it requires the client to wait for a response from the server before proceeding. On the other hand, asynchronous programming techniques (event-driven architectures, non-blocking I/O, and reactive programming) allow applications to continue processing even while waiting for responses, which minimizes overall latency.
- Minimizing Chattiness: “Chattiness” is the excessive back-and-forth communication between an application and cloud services. You must design APIs and establish communication patterns that reduce the number of round trips, thereby minimizing the impact of latency on overall performance.
- Leverage Serverless Architectures & Microservices: One of the most efficient strategies to minimize latency is to redesign the applications to be cloud-native and make use of its serverless architecture and microservices design. This way, it enables you to take advantage of cloud-intrinsic features, such as auto-scaling, distributed caching, and much more, reducing latency eventually.
- Extending SD-WAN to Your Public Cloud: Software-Defined Wide Area Networks (SD-WANs) come with efficient routing capabilities for dynamically selecting the most optimal network paths by analyzing various factors like latency, bandwidth, and congestion. By extending these capabilities to your public cloud environment, you can make sure that the traffic is routed over to the most effective paths.
Here are some of the common techniques for application code optimization:
Conclusion
According to the latest data, 70% of users will abandon your app if it takes too long to load. Similarly, 53% of site visitors will leave your site if it takes more than 3 seconds to load. These numbers indicate the crucial role latency has in influencing user experience. With the dependency on the public cloud increasing, it is important to achieve low latency when it comes to cloud-based applications.
In this blog post, we have outlined some of the key strategies that you can employ for reducing latency when connecting to a public cloud. If you are interested in a more detailed discussion, reach out to our experts at www.gsoftcomm.net/contact-us/.
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