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In 2010, as I sat watching the FIFA World Cup with friends and family, an octopus named Paul was the topic of discussion. Paul had gained worldwide attention as an animal oracle due to its amazingly accurate predictions of the results of multiple soccer matches. I was captivated too.

The intersection with Macrometa started to happen when I thought about distributed systems, especially a 

. There are all these parallels between a good distributed system design, and the biology of an octopus: a good distributed system has a shared nothing architecture. It is highly reliable due to built-in redundancies hence no single point of failure, similar to the physiology of an octopus, which has multiple hearts and multiple brains.

Macrometa’s decentralized architecture has no single point of failure.

What's even more fascinating is that the octopus’ brain is distributed across its entire body, giving it the ability to articulate each arm independently. So, you can imagine if an octopus was a musician, it would simultaneously be able to play diametrically opposite instruments with its arms, as each one has its own brain, or dedicated processing units. This boggled my mind.

All of that processing capacity gives the octopus even more superpowers, such as camouflage. Octopus camouflage is not only limited to color blending, it can also replicate the texture of its surroundings in the most beautiful and creative ways, while also using these changes to communicate. The engineering of these uniquely intelligent cephalopods is vastly different from anything else on earth.

Just like the octopus, Macrometa’s converged multi model data platform is unique and powerful, and it delivers users superhero-like ability to develop amazing things in a fraction of the time it would take going the traditional routes. 

Our architecture is so fundamentally different from anything else that has ever been built to handle data in the cloud.

Just like the world deserved a better way to choose world cup winners, the world deserves a better way to build for the cloud. Start building your impossible application and let Macrometa be the brains in its appendages.

The Octopus And Macrometa

My professional life during the pandemic has been interesting (to say the least). Reflecting on life these past two years, I’ve realized I’ve had some amazing experiences and accomplishments: I’ve been through an acquisition, led some systems integrations, and managed a team during hyper growth. So why did I begin getting the feeling that something was missing? After some much needed introspection, I realized I was missing the joy of learning and doing something new every day.

That's why I am so excited to join Macrometa as its first Program Manager! I am also looking forward to supporting Macrometa as it grows to become the fourth cloud titan.


The largest factor for me was the culture - the people and the 

 they embody. Having experienced what an amazing, kind, and supportive work culture feels like, versus one that is overly demanding and unenjoyable, I knew I had to find the right culture fit to be happy. I could find meaningful work where I learn new things, but if the culture wasn’t right, I knew I wouldn’t be happy. 

Not only are they incredibly smart, they also truly embody the core values – Honest, Humble, Heart. The culture they create is one of trust, one of learning, and one of compassion. This is so important to me because culture lays the groundwork for how successful a company can be. I see that same culture when I meet someone new in the company.

The next important factor for me was the ability to learn and grow. Startups tend to move at the speed of light which means I also get to grow at that pace. While I don’t see myself becoming a full-time developer, I can already say I have learned a ton and I am only on Day 10. I get to learn technology and grow with the support of an amazing team.

Lastly, it’s always been important to me to be in a role where I believe in the company, the mission, and the vision. 

 is at the core of our technological future because it brings data closer to the location where it’s needed. It has such a wide range of applications from streaming services to telemedicine to autonomous vehicles. But more so, the company’s mission to “make every developer a hero” is what spoke to me. Our product will make globally-distributed app development and deployment simple and instant. I want to be a part of making that happen and leading us into the future.

I am beyond thrilled to join Macrometa on this journey!

Why Roma Shah Joined Macrometa

The themes around 5G in recent months have focused on how the reduced latency, high reliability, increased connectivity, and large bandwidth provided by 5G will disrupt industries. But the promise of 5G is only part of the story. The real value of a technology is not its attributes but what that technology actually delivers to people. There's a reason why internet infrastructure companies don't have the same market capitalization as FAANG companies.

When I read about a 5G use case claiming to disrupt the status quo, three questions come to mind:

 For some use cases, 50ms-100ms improvements in latency isn't going to matter much.

Can you do the same thing with existing wifi or cloud infrastructure?

 You can deliver many use cases from the cloud without sacrificing needs or user experience.

 Some critical use cases would be better off to just do data storage and processing on the device itself.

My experience is that many use cases lose their relevance to 5G once you start asking questions. So which use cases actually make sense for 5G?

Use cases dealing with Computer Vision (CV) and 5G-enabled cameras are an intriguing candidate. CV is a field of study that uses 

 techniques to help computers “see” and develop context around digital media like photographs and videos. Many use cases like quality control, change or object detection, etc., fall into this category. This category's suitability to 5G makes sense to me because

CV use cases are often real-time in nature and will immensely benefit from reduced latency.

CV use cases produce a lot of data (video streams), but 90% of it is noise. It's poor economics to send all that noisy data to the cloud, assuming one has the capacity to transmit.

Moving data and compute to a 5G edge will reduce the cost and improve the battery/longevity of the device.

 and stadiums are multi-faceted. On one hand, 5G reduces fan frustration because it can handle more users, and the extra bandwidth allows fans to receive or send large amounts of data with very low latency. In addition to reducing frustration, 5G can even heighten fan experiences with features like augmented reality. Additionally, use cases dealing with large crowds for other events and conferences make sense to me because

Stadiums and sporting events bring thousands of people and devices into a relatively small area. Providing ideal connectivity and bandwidth over 4G or wifi to provide rich experiences just isn't possible.

Real-time crowd management is another significant factor in this category (estimating queue wait times, tailored updates, social distance monitoring, crowd analytics, etc.)

Use cases dealing with mobility like public transportation and drones are another excellent candidate. 

 have become invaluable assets for end-users, enterprises, and governments, and much of this technology is helpful for companies testing autonomous aerial transportation as well. They make sense because

Public transportation involves both mobility (i.e., increased connectivity) and large crowds. Providing continuous connectivity and a large bandwidth to meet a crowd's needs is not something you can do over the cloud or wifi.

Drones involve both mobility and a lot of noisy data. Providing continuous connectivity and processing of noisy data at the 5G edge makes sense and is cheap. Also, 5G edge will enable drones to share computing resources (i.e., device offload), reducing their cost and increasing their stay in the air longer.

 are just as much about generating data and optimized workflows as they are about making things. Use cases dealing with smart manufacturing, factories, and construction are good use case candidates for 5G because

Smart manufacturing, factories & construction involve many devices/robots doing real-time monitoring, learning, and actuating in a small space. A lot of the generated data is noise. So it does not make sense to send to the cloud. A better alternative is to pool the resources and process this data at the edge. That will reduce the cost of the devices & improve their longevity.

I am not fully sure about this category's applicability to 5G, though, i.e., one can also achieve the above benefits by utilizing Wi-Fi. 5G provides more security out of the box and network slicing compared to Wi-Fi. So that could be the reason to use 5G.

 is empowering game developers to create new digital experiences. A 5G use case for gaming makes sense because

Improved bandwidth and lower latency creates a better multiplayer experience or enhanced cloud gaming delivery.

5G's high reliability means games can go uninterrupted, regardless of where the player is in the mobile network.

As a small thought experiment, think about a photograph you have seen or liked recently. Chances are it is a color photograph.

When Kodak introduced a 35mm camera in 1934, no one called photos "black and white" photos. 

. When color photos were introduced, only then did people start differentiating between the essence and attributes of a photograph. Suddenly photographs were either color or black and white. Over time, black and white photos became a unique case, and color photographs became the standard.

To me, 5G NSA or SA today is a lot like photographs in 1934. If you dig deeper into the use cases above, 

 is the common thread. These use cases are either about

Volume & velocity of data (i.e., bandwidth) or

Mobility of data source (i.e., mobility) or

Reliable data access (i.e., reliability) or

Time to process & actuate on data (i.e., latency).

 to process an event or request and take action. The context could be about the

The environment in which the event/request and processing happens or

Relationships between itself & its peers or

Connections between its past and present or

Configurations & Constraints around processing the event/request etc.

Current cloud native data platforms can't meet all of the needs of 5G. These use cases, to reach full potential, need 

 decentralized data platforms to bring much needed color.

Please feel free to share your perspectives. What other 5G use cases are showing promise?

Building applications the edge native way

Telecom providers need to be more than just data pipe providers

The Top 5 Use Cases For 5G

Gaming has the potential to be a killer application for 5G. But it must bring something new to the industry.

We have to look beyond reusing the technology created before the mobile broadband era. That must not be the extent of our ambition.

We must empower developers to create the next-gen experiences of the 5G era. We can provide a 5G cloud, one that is both 5G native and 

. Developers need a platform that can not only reduce lag beyond human perception but also process game data in real-time.

5G is empowering game developers to create new digital experiences.

Do you remember when you fell in love with video games? I remember when it was for me. I had plugged the new network adapter card into my Sony PlayStation 2. Connected it to my 600K Cable Broadband Modem (fastest connection in the UK at the time). I then fired up SOCOM US Navy Seals + Headset :) and joined my first 8v8 multiplayer battle. A few games later I received an invitation to join a faction called the Disposable Heroes. In no time, I was playing competitive organized events and leagues and my world was never the same again.

What amazing formula connectivity and gameplay make. Much greater than the sum of their parts. The original product marketing for the PS2 Network adapter card was as follows:

“The World at your fingertips. Tackle, shoot, frag, and outwit anyone, anywhere, anytime. With the Network Adaptor for PlayStation 2, just about anything is possible. Start your own rivalry across the nation with trash-talking opponents you’ve never met. Experience the best in live competition. No two games are ever alike”

SOCOM for PlayStationPowerful messaging (at least to me back in 2003). After my experience with SOCOM, I didn’t play another game for quite some time. I became addicted to online play. With every new game, I would check to see if it had those three little words written on the cover: “with network play”.

That promise of playing anyone, anywhere, and anytime was a bit of a stretch. I wasn’t going to be able to carry my PS2 around with me to play it “anywhere”, and “anytime” was usually when I finished work. As a side observation, the first version of SOCOM actually supported LAN parties. The precursor, or at least an unknowing nod to the future of Esports events? No latency, or lag issues, no unfair advantages. Skill vs Skill. V.cool.

The developers of SOCOM had a vision for the experience they wanted to bring to console gamers. They nailed it.

5G gaming “The World at your fingertips...”

When I contemplate 5G and gaming, I think back to SOCOM. That promise of a game “with network play” that would open up new worlds and experiences. Game developers in 2021 should see 5G with that same sense of vision and opportunity. Just like developers did in 2003 for the PlayStation 2 network adapter card. An enabler of new experiences.

I want my daughter to have that same “wow” moment provided that I had. But in truth, I want it for me too. :) “The World at your fingertips”

 combined have such great potential. But we need to get it in the hands of developers in a meaningful way. We don’t even need to wait for 5G Standalone – Non-Stand Alone with edge computing is a great start. Improved bandwidth and lower latency are attributes that provide a better quality of service (QoS), which translates into a better multiplayer experience or enhanced cloud gaming delivery. But how do they provide that “wow” moment to the gamer? Something they have never experienced before. What is the compelling event or new experience that is being enabled or introduced?

5G is not enough for next-gen gaming on its own. 5G gaming platforms must reduce lag beyond human perception. And they have to do this 

 limiting the player pool. In fact, they need to expand the proximity limits of who can play. Developers need a platform capable of processing more game events in a single “tick”. Data processed closer to gamers that enables game developers to create new and richer experiences. Derived from insights generated from gameplay events in real-time. 

The 5G era of gaming needs to be much more than lower latency play. 5G should be the standard all future mobile gaming platforms have to beat.

Current games are supported by simple client-server-based architectures. 5G will have to support a polyglot approach to gaming traffic protocols and provide a transport layer that transforms game architectures into an event-driven architecture.

This will enable game developers to add new capabilities to the game in an agile manner, while also reducing complexity and operational costs.

A 5G database must enable game developers to leverage historical and real-time context. This data will allow developers to incorporate rich insights, personalization, recommendations, and intelligence into the games they create.

 will introduce rich leaderboards and player statistics, as well as identify patterns and trends in real-time from their game worlds.

5G will support serverless functions and containerized game logic. Artificial Intelligence to enhance the gaming experience, for example, there will be more sophisticated systems for identifying cheaters and identifying player abuse and checking the gameplay in real-time. Developers have the ability to take action in real-time on the game world mechanics.

Imagine more customized matchmaking systems based on real-time data and 

 that reduce queue times. Developers will understand a player’s real-time mobility within the mobile network and make sure they have the best experience.

With data and imagination, anything is possible.

I love this visualization because it shows the market history from 2020 all the way back to 1972. In 2020, consoles generated $33B, PC $40B, and Mobile $85B. The types of games that launched between 2018 and 2020 are quite telling. They are mostly free-to-play, or freemium. They are battle royale and massively multiplayer. They are on mobile devices. They are also moving beyond traditional gameplay and offering new in-game-world experiences.

This is why I say I hope for more from 5G and 5G for game developers. I hope that 

 take a leading role in building on next-gen gaming technology. I hope they enable cross-over and extension into other industries and experiences. 

Online Esports. Interactive gaming. eCommerce. Anti-cheat and abuse-detection. Streaming. Vast multiplayer worlds, and augmented realities. Experiences that can be accessed from anywhere across the 5G network. Powered by the real ability to access, process, and act on 

. And it's all within our reach. Who knows, they might even be able to build their own metaverse.

I believe that 5G has the potential to enable that “wow” moment for mobile gaming. Just like the network adapter card was for my PlayStation 2. “The World at your fingertips”

And yes the vertical axis should be inverted, well it depends actually ;-)

 if you'd like to talk more about 5G. Maybe we can take a call whilst playing some CoD :) (I just started Naraka Bladepoint, so maybe on there).

How 5G Gaming Will Change the Industry

2021 will be a memorable year for so many personal and professional reasons. It marks the end of many journeys as it marks the beginning of new ones. There are moments in life when you stop, look back, reflect on the past and double down on what comes next. I found myself in this moment and being at the right place at the right time as I crossed paths with Macrometa.

Could I find another opportunity to match or top my 11 year journey with Gazzang? I began writing its very first lines of code on nights and weekends, and saw it through Series A and the acquisition by Cloudera. I watched it become a unicorn IPO and growth north of $800 million in ARR. I was happy with my journey as VP of Engineering and CISO to CIO. But, like getting off a rollercoaster, I felt I needed to do it all over again.

I had heard all these great about Macrometa – but I was a bit skeptical. As a security person, you have to be skeptical about pretty much everything. As I talked to the founders, saw the technology, and learned more about their early customers and successes, that skepticism quickly faded away. As I dug deeper, I continued to be amazed and started to see that Macrometa was at the beginning of something big.

After 30 years of building software and solutions across different operating systems, coding languages, databases, user interfaces, APIs, data centers, clouds and containers, you name it, I have seen many technologies come and go. The ones that endured are the ones that were embraced by developers, easy to use and maintain, stable, and trustworthy. In Macrometa’s 

 (GDN), I see all the right ingredients for developers to quickly, securely, and seamlessly create the technology that will drive a new world. A world that does not believe in barriers, that is globally-distributed, that processes information in milliseconds, where —living on the edge— takes on a whole new meaning.

I am thrilled to join Macrometa as CISO/CDO/CIO and will work tirelessly to win the trust of our customers, providing a secure and safe place to process their most sensitive and critical data. I will also keep confidentiality and privacy at the forefront of all data analytics, data engineering, and data science that will continuously improve the Macrometa platform. I will also be helping Macrometa grow and mature to its full potential. As a Macrometan, I will be a colleague, friend, and voice for diversity and inclusion.

While I have been part of several startups in my career, I have never been as excited as I am for Macrometa. The feeling is hard to describe, being part of a team with so much energy where everyone is bringing the best of all their previous experiences and coming together to build something big and new.

The future ahead is ripe for new technology breakthroughs in space, renewable energy, telemedicine, technology, and quality of life. I am so excited to see how Macrometa can become an important contributor to these breakthroughs.

Thank you Macrometa for this opportunity.

Why Eddie Garcia Joined Macrometa

I’ve been involved in some great edge-related activities over the past few years. Some of these activities have been focused on Infrastructure as a Service (IaaS) or orchestrating workloads around a distributed cloud. While IaaS and workload orchestration are important parts of an edge cloud solution, where does the platform for developers fit into all of this?

In my last blog post, I said that building applications for the edge will require a different set of tools. The edge (and the 

 in the most extreme sense) is about real-time performance and an improved experience for humans and machines. It’s this concept of service immediacy that goes beyond industries.

Even though there are many applications and technologies residing in the centralized clouds, they don’t always translate into workloads that make sense at the edge. The main reason a traditional 

 is because it doesn’t face the same barriers as distributed architectures. Even if they technically can run at the edge, that doesn’t mean that they’re optimized for the edge. 

, especially mobile network operators with 5G, are transforming their business in two main ways. The first way is technical, i.e. network transformation and evolving from the traditional physical network functions approach to network deployment to a virtualized approach (VNFs and now CNFs). The second way is monetization, i.e. business transformation and how they monetize that network asset and capabilities to attain a return on their investment.

Telcos are essentially becoming edge technology services with the goal being to offer their unique value proposition in the form of network-centric edge cloud services.

Telcos that focus their edge cloud services on 

 and service immediacy are going to be more successful and fit into the technical and business requirements of modern distributed systems.

What application developers need for the edge

Rather than simply hosting application workloads created by others to run at the edge, 5G mobile network operators can become enablers of solutions. But first, they’ll need to address the needs of enterprise application developers at the edge. Telco edge cloud providers need to consider three main concerns: Performance, developer velocity, and costs. 

, low latency real-time insight, and actuation. Developer velocity isn’t just about the speed of development or deployment, it’s about the rate of developer adoption as well. The costs also have to be worth the investment – does the platform’s cost result in tangible performance and increased developer velocity?


To meet the demands of enterprise applications and the developers that create them, network operators need to support a polyglot approach to enterprise architecture primitives. Imagine a platform that embraces an edge native approach to application development. Developers can leverage 

 computing to maximize the dynamic, mobile (migratory) nature of deployed software services at the network edge. 

How Macrometa overcomes obstacles of the edge

The edge is born from the principle that data has gravity. Basically, the existence and mass the data has, in itself, attracts processes and workloads to it. Like any large body that has gravity, other objects are attracted to it and sit (and therefore operate) in its orbit.

At Macrometa, we have built an edge cloud platform that embraces the principle that data has gravity. For example, if insights need to be generated in real-time, our platform enables a distributed approach to application design that brings workloads, 

, and application logic to where the data actually is. The mechanisms required to intercept, capture, process, and manipulate data have everything they need.

Telcos and mobile network operators that work with Macromenta are able to deploy an application that is natively low latency, built for high-velocity data ingestion, manipulation, and actuation. Data replication, query, processing, and insights can be performed and generated across the operator’s footprint with near-instantaneous synchronization, or even globally (off-net) within ms.

 is built around persistent streams and real-time stream processing via our Stream Worker technology. Our Stream Workers allow developers and Telco enterprise customers to define sources and sinks, tables, processors, and javascript functions. Stream Workers are extremely powerful in real-time event execution in an 

 / ELT architecture. Stream workers give the developer the power to collect, shape, analyze and act on application in-flight data and data at rest.

The platform also provides a stateful container runtime that is distributed across a network topology with both compute and FaaS capability.

Hopefully I’ve managed to explain what we have in our platform, its features, and how our Telco customers are using it to offer real-time edge cloud services. It’s pretty exciting stuff.

We (Macrometa) have telco customers today who are right in the middle of this transformation and using the Macrometa platform to build their edge cloud services while addressing complex use cases like connected vehicles, 

 you can find tons of demos and tutorials, from simple “hello-world” type applications to more complex ones like 

. We also have all the documentation you need to get started to familiarize yourself with our platform and build your own global edge applications today.

How To Build Applications The Edge Native Way

Today, we have many hyper-scale, distributed data platforms that can handle big data workloads with elasticity and simplicity. This simplicity comes from the fact these workloads run within a single data center in a single, centralized region. As long as those resources needed to scale are available within that same data center, everything scales as it should. But we’re entering a new age of data decentralization enabled by powerful next-gen devices, 5G networks, advances in 

, AI/ML, and the current geopolitical trends for regulating sensitive data.

This new world requires a new cloud –one that is distributed rather than centralized. The problem is that cloud native approaches that worked well in our centralized architectures 

 in this new paradigm of dispersion and decentralization. 

Edge cloud needs an edge native approach that is designed to meet the challenges of the edge, built for distributed architectures, and optimized for decentralization.‍

The centralized approach doesn’t work because it doesn’t face the same barriers as distributed architectures. Unlike single region architectures, decentralized architectures need to deal with these five following challenges:

Large network latencies with 100s of milliseconds

For any data platform architecture to be truly edge native, it has to effectively address these five primary challenges of edge.

Cloud native and the network latency and unreliability problem

Current cloud native data platforms are primarily 

 systems. This means that they rely heavily on data center class networks (i.e., very low 

 and high reliability) for their throughput, performance, and availability. The primary reason is the need for 

Consensus is the task of getting all nodes in a group to agree on some specific values based on each node’s votes. For example, in election algorithms, the goal of consensus is to pick a leader. With distributed transactions, the goal of consensus is to get an agreement on whether to commit or not. In short, any algorithm that relies on multiple processes or nodes maintaining a common state relies on consensus. 

While consensus algorithms solve many distributed systems problems, these algorithms are 

. Coordination creates three primary penalties for distributed systems:

Increased Latency (due to stalled execution)

 seconds to execute, the maximum throughput of the concurrent transactions operating on the same data items is 

. If a data platform is within a single availability zone or a single data center, this is not usually a problem. The network delays are slight (i.e., hundreds of microseconds or low single-digit milliseconds), permitting from a few 100s to a few 1000s of concurrent transactions per second.

However, if the data platform is spread across multiple regions/PoPs, the penalties will dramatically increase. The read & write delays are lower bound by the network latencies, which run into 100s of milliseconds. This leads to a rise in request latencies and a reduction in throughput. 

For example, if you have an eight-region cluster, the 

 across those eight regions, bringing down the system’s throughput to 2-3 concurrent transactions per second. This is assuming the network is reliable. If the network is not reliable, then the system degrades to unavailability. Neither of these are practical solutions.

Everyone talks about the data tsunami that is on the horizon (or already here, depending on who we talk to). Then the focus switches to how to optimize the read path for costs & performance? how to analyze data effectively? Or how to serve the ml models? These are certainly valid issues.

A big omission is that first we need to write the data, and that’s at least 50% of the data tsunami problem. This is an area where current distributed data platforms underperform. 

For example, let’s take a sample eCommerce store. This reference architecture from AWS Blueprints shows a fairly standard model for an eCommerce store. The blue text is my annotations.

aws-samples/aws-bookstore-demo-app (github.com)

Like most enterprise apps, the store requires:

A DynamoDB /document store for its users, items, and order information.

A search store to provide search capability for users.

A graph store to record its user activity and items for recommendations.

An API gateway and lambdas to wire all these together.

While this architecture will technically work, it still presents a few problems::

You have to store the same data in multiple formats in multiple stores. In essence, your writes are amplified as they fan out across various stores.

You give up on consistency & transaction semantics across these multiple stores. You will also have to spend a lot of time and money to address the pain from these problems.

Your developers will spend 80% of their time learning & writing extra glue code to integrate these stores, while spending only 20% on business logic that actually moves the needle.

In short, you have expensive writes, loss of developer velocity, and solution complexity.

It’s estimated that IoT devices will generate 

 by 2025. In the current cloud native system, all this data needs to be transferred to centralized cloud locations for processing. That increases not only the data transmission costs but the data write costs as well. In addition to being costly, the latencies involved with this approach make it difficult to take advantage of data in real-time, let alone react in a timely manner for recommenders, predictions, alerts, or something else.

One option is to optimize the data for transfer by compressing it through some intelligent means to reduce the data transfer costs. But that ends up just trading one problem for another with the increase in processing costs. The rest of the problems still remain.

In reality, over 90% of the data is noise, depending on the use case. A better approach is to just process data at the location near the data source and only transfer the signals. There are some solutions that provide this capability at the edge, but the problem is that they are mostly stateless solutions.

 solutions require and benefit tremendously from the state (aka context) around the data event that is being processed. But maintaining state at the edge requires a data platform that can run in 10s and 100s of locations around the world. In essence, one needs an edge native data platform to provide state.

Cloud native and complex service orchestration

Think of the last time you worked on a distributed system paired with another region for active-active or active-passive replication. This could be a hybrid cloud or a multicloud solution. I don’t need to tell the complexities inherent in this, the multidimensional expertise required from the engineers, and the efforts involved – those are all pain points we know too well. Not to mention the deployments, upgrades, and monitoring. You have to account for so many factors as part of the development of your service using these cloud models. Now multiply these factors by 10x or 20x to account for the 10s, if not 100s, of PoPs required for the edge.

 (CDN) have perfected the art of providing a Single System Image (SSI) addressing these challenges for website developers. We need similar SSI capabilities for backend developers working with data and streaming platforms dealing with dynamic data. 

Macrometa GDN provides a Single System Image (SSI) of the platform to the developer while running in 10s and 100s of PoPs just like CDNs provide an SSI of their network for a website developer.

To summarize, we don’t use a hammer to chop wood! Hammers are a perfectly useful tool, but if we need to solve the challenges at the edge, we need an edge native approach.

 and I discussed edge native in late 2015, it was a far-fetched idea with its fair share of skeptics. We benefited from those who provided constructive feedback and ignored those who were bound to the status quo. It is nice to see the industry trending towards the edge these last few years. The five challenges of the edge mentioned in this post guide all the fundamental principles for stateful edge computing. 

Building technically complex data platforms like Macrometa isn’t easy, but I believe there will be more data platform providers in the future who will address these principles natively in their architecture. Similarly, consumers will want these capabilities from their data platform providers as they learn the hard way that the cloud of today is ill-equipped for the edge of tomorrow.

, including our Globally Distributed Multi-Model Database and Real-Time Stream Processing. If you want to see Macrometa in action, 

How to build applications the edge native way

The Great Shift - Edge computing & faster data processing

Cloud Native Is Not Edge Native

“No one can whistle a symphony. It takes a whole orchestra to play it." – Halford E Luccock

 for the first time in July of last year (2020) at the 

 near the Giants stadium in San Francisco. It was during the peak of the pandemic lockdown, and the streets of this great city were empty of the usual excitement and energy that fills it. 

But Chris, Blake, and Zain’s energy and enthusiasm more than made up for the unusual stillness of that day. We spent three or more hours together sitting outside the cafe while I listened intently to Chris and Blake share the many life lessons of being an early-stage investor. Lessons of great disappointments from missed opportunities, poor execution, and bad luck, along with lessons of courage, accomplishment, and winning against great adversity and all odds. As I sat there enthralled, it hit me like an eighteen-wheeler truck - Chris, Zain, and 

 embodied everything that I believed were the most important characteristics of a great investor. They were kind, humble, tenacious, and utterly optimistic people who shared my belief that building a great business with amazing people was one of the most sacred, noble, and rewarding endeavors one could attempt. 

they invested a small check into Macrometa

 in the fall of 2020. And with that, we got the opportunity to start collaborating closely with Chris, Zain, and the Pelion team. They taught me many things in a very short amount of time - like how to race cars and make them drift and how to think big, not just with my head but with my heart. 
Today, we are incredibly proud and excited to share that Macrometa has just raised a $20M Series A round led by Chris, Zain, and the Pelion team with full support and participation from our amazing investors 

. This brings our total raised to ~$30M, with $28.5M of that raised during the pandemic in just under 12 months. This Series A funding comes on the back of skyrocketing interest and adoption of our serverless edge data platform by enterprise customers, triple-digit ARR growth, and game-changing 

Macrometa’s mission is to make every developer a hero by making it trivial to build stateful, real-time, low latency, globally distributed, edge, and multi-cloud apps that run simultaneously across 100s of edge or cloud regions. To do this, we are investing the proceeds from this round into engineering the most powerful, globally-distributed, stateful serverless edge platform, on a deeply capillated edge computing network connecting 175 global POPs, all wrapped together in a developer experience second to none.

This is a big and bold mission. It's not for the faint of heart, and it's the stuff that takes courage, tenacity, and audacious levels of leadership, optimism, and hope. If our mission makes your heartbeat a little faster with excitement, or if it speaks directly to your aspirations, 

, and let's get to know each other. We have incredibly smart, humble, and fun people like my co-founder and CTO 

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