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Over 20 years ago, Cambridge, Massachusetts-based Akamai Technologies set out to solve some of the toughest challenges of making the World Wide Web a platform that could serve billions of humans around the world. To embody this mission, the company eventually rolled out the Akamai platform in 1999, which was edge computing in its earliest form (content delivery network or CDN), even before the advent of virtualization, and remains one of the most critical infrastructures for security and performance, underpinning the web as we know it today.
The success of the web was possible, in large part, due to the CDNs. Because the internet wasn’t originally designed to handle the demands of massive amounts of data, live high-definition video, flash sales and large downloads, CDNs were built to make the internet work better. They help to securely deliver media at scale and enable all of the connected experiences that are part of daily life for most of us today.
Businesses — from small and medium content providers to the world’s large corporations — use content delivery networks to provide a seamless web experience to their customers. But with the advent of the cloud, things are changing.
Moving from the edge to the cloud
Today, nearly 90% of enterprise software is provided either as software-as-a-service (SaaS) or platform-as-a-service (PaaS) running in the cloud. Akamai predicts that in the next few years, enterprise software will be served from the edge, with the cloud used primarily for batch processing. They believe that there are three aspects driving this change:
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- Serve apps and API nearer to users
- Move compute closer to data source
- Implement rules to protect and control data
However, they believe that the cloud is very much like the Web before the advent of CDN; meaning it is often slow and breaks easily. Just as the web needed a CDN, the cloud needs a secure and performant edge-computing infrastructure, along with a global data network (GDN) for real-time delivery of apps, APIs and data-driven digital web services.
To fulfill its vision of a new, better cloud, Akamai recently announced a strategic equity investment, go-to-market partnership, and product integrations with Macrometa Corporation, a GDN and edge-computing cloud. In conjunction with Akamai’s equity investment in Macrometa, Andy Champagne, CTO of Akamai Labs, will join the Macrometa board as a nonvoting board observer. This investment spearheads a deep technology and multiyear product collaboration to provide an ubiquitous edge-cloud platform built for enterprise.
“This partnership and technical integration greatly simplifies the amount of work and effort that goes into building applications and deploying them on the edge. And it brings a certain level of elegance and velocity that allows faster time-to-market and a more modern experience of building these types of apps,” said Chetan Venkatesh, founder and CEO at Macrometa in a statement.
Understanding global data networks
Macrometa created the GDN — which is a hyper-distributed edge cloud (with a CDN-like topology) available across 175 edge locations around the world. It features a global data mesh to connect, ingest, store, serve and process data. With this architecture, developers can turn data into APIs, edge-computing functions and containers for performing stateful computing at hyper-proximity to data producers and consumers.
“We also set out to solve emerging challenges with data regulation and legal frameworks for data sovereignty with our built-in, in-region Data Protection. The end result: a developer platform that is uniquely built to solve the problems of real-time data and operational analytics in a way that the cloud just can’t,” said Venkatesh.
The platform helps cloud developers build an entirely new generation of advanced distributed microservices, and other types of cloud backend services. It enables cloud developers to run closer to things like mobile phones, web browsers, smart appliances, connected cars, and their users in edge regions (or PoPs — short for point of presence) around the world in major metropolitan regions, within 50 milliseconds of access to more than 90% of internet-connected humans and their devices.
“By moving cloud-hosted web services and cloud-native data and apps to the edge we fix the slow part of the cloud problem. And by making these cloud data and apps run in dozens — if not hundreds — of regions around the world simultaneously, Macrometa fixes the ‘breaks easily’ part of the cloud problem,” Venkatesh told VentureBeat. “If you are thinking how this is possible, it is because if one edge or region goes down, another edge or region takes its place instantly. This kind of fault tolerance is something that is incredibly hard to design and architect, and expensive to implement on the cloud.”
The Macrometa and Akamai partnership involves technology and product integrations, as well as a preferred go-to-market via which Akamai will offer Macrometa products to its worldwide sales force, partner channels and enterprise customers. Macrometa and Akamai say they have integrated the Akamai EdgeWorkers technology directly into Macrometa’s GDN console, API and SDK. This means that developers can build a full end-to-end cloud app or API in Macrometa and, with the click of a button, deploy it in minutes to thousands of Akamai edge locations around the world.
Developers can bring their Akamai credentials and store them on Macrometa. They can build their apps using Macrometa’s global data mesh features such as the poly model key value, document and graph database, edge computing features (query workers and stream workers), and global data protection features (vaults and tokens).
Once the application is ready to be deployed in Macrometa, a generate EdgeWorker button enables the compiling of the application into a native Akamai EdgeWorker that then is automatically configured and deployed securely on Akamai’s edge network as EdgeWorkers that expose API endpoints to mobile phones, web browsers, smart TVs, connected cars, etc.
Perks of a single multicloud/polycloud platform
Macrometa and Akamai have created deep technology, platform and product-level integrations to make it possible for developers to use Macrometa’s GDN as a primary devops environment for building hyper-distributed cloud applications.
“Today, developers must wrangle a very complex set of disparate tools and programming frameworks to build simple applications at the edge,” said Venkatesh. “The ability to build sophisticated apps that use real-time data is very limited because programming the edge requires many hacks and kludges to extend the cloud to the edge. To successfully devops on the edge requires an edge-native approach, and that’s what the integrations between Macrometa and Akamai provide.”
Network and infrastructure integration
Macrometa is now available on all Linode regions by default and directly sits on top of Akamai’s worldwide network backbone. In addition, Macrometa is also co-located with Akamai edge PoPs in more than a hundred regions around the world. This means that developers can now build and deploy apps on Akamai and Linode directly with Macrometa in all Linode and Akamai edge regions.
Technology and product integration
Apps built with Macrometa can run on all the major cloud providers such as AWS, GCP and Azure, as well as middle-of-the-network cloud providers like Akamai’s Linode and the CDN edge as Akamai EdgeWorkers. In 2023, Macrometa will enable these apps to also run directly on 5G telecom wireless networks.
Though customers are building many different industry-specific apps and solutions on Macrometa and Akamai EdgeWorkers, the joint solution is aimed to address problems in four specific areas:
SaaS, web services and developer tools
As per Venkatesh, SaaS customers are using the joint solution to serve cloud-native SaaS offerings to customers spread around the world and seeing speed increases and latency improvements of between 25 to 100 times for their offerings. This translates into better product stickiness, less user churn and, in the case of freemium models, better conversion rates from free to paying customers.
“Many customers are building new real-time data-powered web services that use operational analytics to serve highly personalized content by combining the edge with AI to make more relevant recommendations or real-time offers,” he said. Developer-focused tool providers are using the joint solution to augment their existing cloud-based devops platforms with differentiated features that leverage the edge to make devops faster.
Enterprise apps and operational data analytics
Enterprise customers use the joint solution to improve the performance of streaming data pipelines and real-time data analytics on operational data such as log processing, network and application performance monitoring and management. Enterprise customers can quickly connect data in disparate systems in different parts of the world and put APIs on the data. They are using this solution to solve data residency and sovereignty issues by vaulting and tokenizing data securely in geofenced data vaults for compliance.
Streaming media, gaming, and interactive digital services
Video-streaming customers use the joint solution to move cloud-based streaming platforms to the edge to provide a better user experience in interactive services on smart TVs, as well as web and mobile video-streaming apps. By relocating authentication, content-catalog rendering, personalization and recommendations of content to watch, and intelligent search using graphs to connect search terms across more dimensions than simple keywords; it all makes for a more powerful and fun video-streaming experience.
Gaming companies use the joint solution to move game servers closer to players and consoles to make gaming smoother and more enjoyable. Game developers use the joint solution for smart features like player matching, leaderboards, multiplayer game lobbies, anticheating and more.
Retail and etail omnichannel ecommerce
Traditional retailers, Venkatesh says, struggle to compete online with Amazon’s juggernaut and are looking to make their ecommerce platforms more powerful by using data and the edge to make shopping easier and more pleasant. Fulfillment from a local store is a powerful enabler of better gross margins and customer satisfaction because items purchased can be delivered from a nearby store instead of an out-of-state fulfillment center at lower cost, with shorter wait time. But, to do this requires the joint solution to connect and stream data from local stores and fulfillment centers to online ecommerce platforms.
“Our collaboration will extend into several areas in the future, including the use of AI- and ML-powered apps with EdgeWorkers, and low-code developer tools for making edge-application development available to noncloud developers,” said Venkatesh.
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