The first rule of thought leadership in advanced computing is: don’t abuse the term edge. During my series of blogs on the subject, I have defined the edge, Explanation of edge computing, and discussed the economics of advanced computing. There have also been a few articles in which I have discussed how confusing it can all be for people to understand. In an effort to tie it all together, I wanted to highlight use cases where customers are using Akamai’s edge platform to solve real-world issues.

Here are four simple use cases where customers have faced challenges with cloud platforms and cloud computing.

You are here: Speed ​​up geolocation by 99%

Personalization is an important part of a modern user experience. Displaying local inventory and offers is a table issue, and yet not always easy to do. Geolocation allows a popular automotive market to tailor inventory and information. It displays prices, ratings and reviews based on market value, as well as sales information.

As simple as it may sound, retrieving this data requires many calls to the web application. When a user accesses the app, a geolocation microservice allows the app to filter what it displays. The challenge was that these calls added latency. The geolocation microservice slowed page loading to between 500 milliseconds and 2 seconds. Moving the microservice to Akamai EdgeWorkers saved 99% of round trip time. The microservice now returns geolocation data in 20 milliseconds.

EdgeWorkers injects geolocation data via a cookie at the edge. It works by adding regional data in the header of the request. This results in two savings. First, by removing the first round trip to retrieve the geolocation data. Then by eliminating a separate request to retrieve additional information for the region. This makes the application more efficient. Fewer calls to the cloud improve response times and lower cloud costs. Check it out cookie-based example. You can also do something similar with a geolocation service call.

Are you looking for me: improve personalization

Search engine optimization is a dark art. It is generally misunderstood and maligned. A North American sporting goods retailer struggled to balance SEO and performance. It had two goals: to increase the value of search engines and to reduce cloud infrastructure costs.

Like most B2C businesses, the company attracts and retains customers through personalization. It runs marketing campaigns with custom URLs containing UTM codes for tracking and analysis. You may have noticed strings like “? utm_source = blog & utm_medium = email & utm_campaign = member”If you followed a link from a promotional email. These URL codes are great for marketers, but not for cache performance. To enable marketing, each URL must be separate. To optimize cache performance, URLs should be consistent. To keep users engaged, pages need to load quickly.

To resolve this issue, the customer wrote a JavaScript function to improve matches. The function checks the cache key, ignoring UTM codes. To illustrate, a URL like “www.retailer.com/offers/promo_page?utm_source=blog&utm_medium=email&utm_campaign=member“Correspond to”www.retailer.com/offers/promo_page.“It improves cache hit rates. The function then adds the UTM codes to maintain the analysis of user behavior. You can read more about this use case in this blog post.

A people-based marketing platform did something similar. Promotional emails from this company include many contextual attributes to deliver personalized content. The marketing platform architecture uses different microservices that live on different cloud provider platforms. Email attributes determine where to route requests and what content to return. By moving this logic to Akamai EdgeWorkers, URLs are now decoded and routed from the edge. This improves user responsiveness and eliminates additional requests at the origin.

Privacy please: comply with regulations

GDPR, CCPA, APPI, and other user privacy laws have focused on compliance efforts. Businesses around the world have stepped up their compliance efforts to avoid sanctions. A global media measurement and analysis company needed to manage user content. The first order of business was tracking user consent data from its publishers.

The company used the Interactive Advertising Bureau (IAB) Transparency and Consent Framework (TCF 2.0), an industry standard for sending and verifying user consent. He designed a microservice to track user consent for activity tracking. Akamai EdgeWorkers enabled the company to create this as a native edge microservice. When the user consents to tracking, state tracking cookies are added to the session. This allows the business to personalize the user experience. If the user does not agree, the cookie is deleted and the user has a more general experience. To learn more, read this blog post, where you can also find links to the source code.

I have been around the world: at what time is my connection?

Anyone who has stolen has had this problem. You know your scheduled flight time. You download the airline app to receive notifications. You check the flight tracks and the airport website to verify. When you arrive at the airport, you check the flight and gate information on the screens. And once you’re at the door, you watch the updates on the kiosk. More often than not, the information does not match.

Airlines face many challenges when sending and synchronizing critical data. Inconsistent internet and network speeds make real-time data coordination a real problem. Conflicting information on flight status disrupts passengers and increases demand for customer service resources. More accurate and timely information distribution increases customer satisfaction and lowers costs.

A global airline has contacted Akamai to help resolve this issue. He realized that standard web apps couldn’t overcome the challenge of syncing data – there are too many apps to sync. Additionally, web applications stay up to date by requesting information on a calendar (or in response to an event). For example, have you ever played with your phone’s email client configurations? There is a setting for retrieval or forward message delivery. Shoot asks the app on your phone to request updates from the mail server. Push asks the mail server to send you information. You configure push or pull synchronization depending on how often you expect to receive new messages. The problem with flight information is the number of apps. The mobile app, airport screens, websites and boarding kiosks shoot at different intervals. Flight delays will therefore appear differently for each application.

The airline in question used Akamai Edge Cloud to synchronize the global flight information. Edge Cloud uses Message Queuing Telemetry Transport (MQTT), compared to HTTP type web applications. With MQTT, we enable publisher-subscriber communication. This offers three main advantages:

1. Messages are smaller and delivered faster and more reliably.
2. The information is more secure because it is only sent to known subscribers.
3. Each device that displays flight information receives it at the same time.

Edge Cloud provides automated and reliable real-time message delivery and notification. To find out more, read this Blog post on Edge Cloud.

If you’re looking for more code examples, we’ve released a variety of use cases in a GitHub repository that you can engage with today.

*** This is a syndicated Security Bloggers Network blog from the Akamai Blog written by Ari Weil. Read the original post at: http://feedproxy.google.com/~r/TheAkamaiBlog/~3/MlcflLduI94/can-edge-computing-exist-without-the-edge-part-4-emerging-edge -computing- use-cases.html