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3 questions to ask before adopting microservice architecture
As a product manager, I’m a true believer that you can solve any problem with the right product and process, even one as gnarly as the multiheaded hydra that is microservice overhead.
Working for Vertex Ventures US this summer was my chance to put this to the test. After interviewing 30+ industry experts from a diverse set of companies — Facebook, Fannie Mae, Confluent, Salesforce and more — and hosting a webinar with the co-founders of PagerDuty, LaunchDarkly and OpsLevel, we were able to answer three main questions:
- How do teams adopt microservices?
- What are the main challenges organizations face?
- Which strategies, processes and tools do companies use to overcome these challenges?
How do teams adopt microservices?
Out of dozens of companies we spoke with, only two had not yet started their journey to microservices, but both were actively considering it. Industry trends mirror this as well. In an O’Reilly survey of 1500+ respondents, more than 75% had started to adopt microservices.
It’s rare for companies to start building with microservices from the ground up. Of the companies we spoke with, only one had done so. Some startups, such as LaunchDarkly, plan to build their infrastructure using microservices, but turned to a monolith once they realized the high cost of overhead.
“We were spending more time effectively building and operating a system for distributed systems versus actually building our own services so we pulled back hard,” said John Kodumal, CTO and co-founder of LaunchDarkly.
“As an example, the things we were trying to do in mesosphere, they were impossible,” he said. “We couldn’t do any logging. Zero downtime deploys were impossible. There were so many bugs in the infrastructure and we were spending so much time debugging the basic things that we weren’t building our own service.”
As a result, it’s more common for companies to start with a monolith and move to microservices to scale their infrastructure with their organization. Once a company reaches ~30 developers, most begin decentralizing control by moving to a microservice architecture.
Teams may take different routes to arrive at a microservice architecture, but they tend to face a common set of challenges once they get there.
Large companies with established monoliths are keen to move to microservices, but costs are high and the transition can take years. Atlassian’s platform infrastructure is in microservices, but legacy monoliths in Jira and Confluence persist despite ongoing decomposition efforts. Large companies often get stuck in this transition. However, a combination of strong, top-down strategy combined with bottoms-up dev team support can help companies, such as Freddie Mac, make substantial progress.
Some startups, like Instacart, first shifted to a modular monolith that allows the code to reside in a single repository while beginning the process of distributing ownership of discrete code functions to relevant teams. This enables them to mitigate the overhead associated with a microservice architecture by balancing the visibility of having a centralized repository and release pipeline with the flexibility of discrete ownership over portions of the codebase.
What challenges do teams face?
Teams may take different routes to arrive at a microservice architecture, but they tend to face a common set of challenges once they get there. John Laban, CEO and co-founder of OpsLevel, which helps teams build and manage microservices told us that “with a distributed or microservices based architecture your teams benefit from being able to move independently from each other, but there are some gotchas to look out for.”
Indeed, the linked O’Reilly chart shows how the top 10 challenges organizations face when adopting microservices are shared by 25%+ of respondents. While we discussed some of the adoption blockers above, feedback from our interviews highlighted issues around managing complexity.
The lack of a coherent definition for a service can cause teams to generate unnecessary overhead by creating too many similar services or spreading related services across different groups. One company we spoke with went down the path of decomposing their monolith and took it too far. Their service definitions were too narrow, and by the time decomposition was complete, they were left with 4,000+ microservices to manage. They then had to backtrack and consolidate down to a more manageable number.
Defining too many services creates unnecessary organizational and technical silos while increasing complexity and overhead. Logging and monitoring must be present on each service, but with ownership spread across different teams, a lack of standardized tooling can create observability headaches. It’s challenging for teams to get a single-pane-of-glass view with too many different interacting systems and services that span the entire architecture.
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Microsoft launches Azure Purview, its new data governance service
As businesses gather, store and analyze an ever-increasing amount of data, tools for helping them discover, catalog, track and manage how that data is shared are also becoming increasingly important. With Azure Purview, Microsoft is launching a new data governance service into public preview today that brings together all of these capabilities in a new data catalog with discovery and data governance features.
As Rohan Kumar, Microsoft’s corporate VP for Azure Data, told me, this has become a major pain point for enterprises. While they may be very excited about getting started with data-heavy technologies like predictive analytics, those companies’ data and privacy-focused executives are very concerned to make sure that the way the data is used is compliant or that the company has received the right permissions to use its customers’ data, for example.
In addition, companies also want to make sure that they can trust their data and know who has access to it and who made changes to it.
“[Purview] is a unified data governance platform which automates the discovery of data, cataloging of data, mapping of data, lineage tracking — with the intention of giving our customers a very good understanding of the breadth of the data estate that exists to begin with, and also to ensure that all these regulations that are there for compliance, like GDPR, CCPA, etc, are managed across an entire data estate in ways which enable you to make sure that they don’t violate any regulation,” Kumar explained.
At the core of Purview is its catalog that can pull in data from the usual suspects, like Azure’s various data and storage services, but also third-party data stores, including Amazon’s S3 storage service and on-premises SQL Server. Over time, the company will add support for more data sources.
Kumar described this process as a “multi-semester investment,” so the capabilities the company is rolling out today are only a small part of what’s on the overall road map already. With this first release today, the focus is on mapping a company’s data estate.
Image Credits: Microsoft
“Next [on the road map] is more of the governance policies,” Kumar said. “Imagine if you want to set things like ‘if there’s any PII data across any of my data stores, only this group of users has access to it.’ Today, setting up something like that is extremely complex and most likely you’ll get it wrong. That’ll be as simple as setting a policy inside of Purview.”
In addition to launching Purview, the Azure team also today launched into general availability Azure Synapse, Microsoft’s next-generation data warehousing and analytics service. The idea behind Synapse is to give enterprises — and their engineers and data scientists — a single platform that brings together data integration, warehousing and big data analytics.
“With Synapse, we have this one product that gives a completely no-code experience for data engineers, as an example, to build out these [data] pipelines and collaborate very seamlessly with the data scientists who are building out machine learning models, or the business analysts who build out reports for things like Power BI.”
Among Microsoft’s marquee customers for the service, which Kumar described as one of the fastest-growing Azure services right now, are FedEx, Walgreens, Myntra and P&G.
“The insights we gain from continuous analysis help us optimize our network,” said Sriram Krishnasamy, senior vice president, strategic programs at FedEx Services. “So as FedEx moves critical high-value shipments across the globe, we can often predict whether that delivery will be disrupted by weather or traffic and remediate that disruption by routing the delivery from another location.”
Image Credits: Microsoft
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With Hyperforce, Salesforce lets you move your data to any public cloud
For much of its existence, Salesforce was a cloud service on its own with its own cloud resources available for its customers, but as the company and cloud computing in general has evolved, Salesforce has moved some of its workloads to other clouds like AWS, Azure and Google. Now, it wants to allow customers to do the same.
To help facilitate that, the company announced Hyperforce today at its Dreamforce customer conference, a new architecture designed from the ground up to help customers deliver workloads to the public cloud of choice.
The idea behind Hyperforce is to enable customers to take all of the data in what Salesforce calls Customer 360 — that’s the company’s detailed view of the customer across channels, Salesforce products and even other systems outside the Salesforce family — and be able to store that in whichever public cloud you want in whatever region you happen to operate. For now, they are in India and Germany, but there are plans to add support for 10 additional countries over the next year.
Company president and COO Bret Taylor introduced the new approach. “We call this new capability Hyperforce. Simply put, we’ve been working to enable us to deliver Salesforce on public cloud infrastructure all around the world,” Taylor said.
Holger Mueller, an analyst at Constellation Research, says the underlying architecture running the Salesforce system is long overdue for an overhaul. At over 20 years old, it’s been around a long time now, but Mueller says that it’s about more than modernizing. “The pandemic requires SaaS vendors to move their offerings from their own data centers to [public cloud] data centers, so they can offer both architectural and commercial elasticity to their customers,” he said.
Mueller added that by bringing Salesforce data into the public cloud, besides the obvious data sovereignty issues it solves, it brings all of the advantages of using public cloud resources.
“Salesforce can now offer both architectural and commercial elasticity to their customers. Commercial elasticity matters a lot to CIOs and CTOs these days because when your business slows down, you pay less, and when your business accelerates, then you can afford to pay more,” he said. He says that Salesforce is bringing an early generation SaaS product and pulling it into the modern age, something that is imperative at this point in the company’s evolution.
But while moving forward, Taylor was careful to point out that they rebuilt the system in such a way as to be fully backward compatible, so you don’t have to throw out all of the applications and investment you’ve made over the years, something that most companies couldn’t afford to do.”For you developers out there, This is the most remarkable thing. It is 100% backward compatible, your apps will work with no changes and you can benefit from all of this automatically,” he said.
The company will be rolling out Hyperforce over the next year and beyond as it opens in more regions.
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Fylamynt raises $6.5M for its cloud workflow automation platform
Fylamynt, a new service that helps businesses automate their cloud workflows, today announced both the official launch of its platform as well as a $6.5 million seed round. The funding round was led by Google’s AI-focused Gradient Ventures fund. Mango Capital and Point72 Ventures also participated.
At first glance, the idea behind Fylamynt may sound familiar. Workflow automation has become a pretty competitive space, after all, and the service helps developers connect their various cloud tools to create repeatable workflows. We’re not talking about your standard IFTTT- or Zapier -like integrations between SaaS products, though. The focus of Fylamynt is squarely on building infrastructure workflows. While that may sound familiar, too, with tools like Ansible and Terraform automating a lot of that already, Fylamynt sits on top of those and integrates with them.
Image Credits: Fylamynt
“Some time ago, we used to do Bash and scripting — and then [ … ] came Chef and Puppet in 2006, 2007. SaltStack, as well. Then Terraform and Ansible,” Fylamynt co-founder and CEO Pradeep Padala told me. “They have all done an extremely good job of making it easier to simplify infrastructure operations so you don’t have to write low-level code. You can write a slightly higher-level language. We are not replacing that. What we are doing is connecting that code.”
So if you have a Terraform template, an Ansible playbook and maybe a Python script, you can now use Fylamynt to connect those. In the end, Fylamynt becomes the orchestration engine to run all of your infrastructure code — and then allows you to connect all of that to the likes of DataDog, Splunk, PagerDuty Slack and ServiceNow.
Image Credits: Fylamynt
The service currently connects to Terraform, Ansible, Datadog, Jira, Slack, Instance, CloudWatch, CloudFormation and your Kubernetes clusters. The company notes that some of the standard use cases for its service are automated remediation, governance and compliance, as well as cost and performance management.
The company is already working with a number of design partners, including Snowflake.
Fylamynt CEO Padala has quite a bit of experience in the infrastructure space. He co-founded ContainerX, an early container-management platform, which later sold to Cisco. Before starting ContainerX, he was at VMWare and DOCOMO Labs. His co-founders, VP of Engineering Xiaoyun Zhu and CTO David Lee, also have deep expertise in building out cloud infrastructure and operating it.
“If you look at any company — any company building a product — let’s say a SaaS product, and they want to run their operations, infrastructure operations very efficiently,” Padala said. “But there are always challenges. You need a lot of people, it takes time. So what is the bottleneck? If you ask that question and dig deeper, you’ll find that there is one bottleneck for automation: that’s code. Someone has to write code to automate. Everything revolves around that.”
Fylamynt aims to take the effort out of that by allowing developers to either write Python and JSON to automate their workflows (think “infrastructure as code” but for workflows) or to use Fylamynt’s visual no-code drag-and-drop tool. As Padala noted, this gives developers a lot of flexibility in how they want to use the service. If you never want to see the Fylamynt UI, you can go about your merry coding ways, but chances are the UI will allow you to get everything done as well.
One area the team is currently focusing on — and will use the new funding for — is building out its analytics capabilities that can help developers debug their workflows. The service already provides log and audit trails, but the plan is to expand its AI capabilities to also recommend the right workflows based on the alerts you are getting.
“The eventual goal is to help people automate any service and connect any code. That’s the holy grail. And AI is an enabler in that,” Padala said.
Gradient Ventures partner Muzzammil “MZ” Zaveri echoed this. “Fylamynt is at the intersection of applied AI and workflow automation,” he said. “We’re excited to support the Fylamynt team in this uniquely positioned product with a deep bench of integrations and a nonprescriptive builder approach. The vision of automating every part of a cloud workflow is just the beginning.”
The team, which now includes about 20 employees, plans to use the new round of funding, which closed in September, to focus on its R&D, build out its product and expand its go-to-market team. On the product side, that specifically means building more connectors.
The company offers both a free plan as well as enterprise pricing and its platform is now generally available.
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Jitsu nabs $2M seed to build open-source data integration platform
Jitsu, a graduate of the Y Combinator Summer 2020 cohort, is developing an open-source data integration platform that helps developers send data to a data warehouse. Today, the startup announced a $2 million seed investment.
Costanoa Ventures led the round with participation from Y Combintaor, The House Fund and SignalFire.
In addition to the open-source version of the software, the company has developed a hosted version that companies can pay to use, which shares the same name as the company. Peter Wysinski, Jitsu’s co-founder and CEO, says a good way to think about his company is an open-source Segment, the customer data integration company that was recently sold to Twilio for $3.2 billion.
But, he says, it goes beyond what Segment provides by allowing you to move all kinds of data, whether customer data, connected device data or other types. “If you look at the space in general, companies want more granularity. So let’s say for example, a couple years ago you wanted to sync just your transactions from QuickBooks to your data warehouse, now you want to capture every single sale at the point of sale. What Jitsu lets you do is capture essentially all of those events, all of those streams, and send them to your data warehouse,” Wysinski explained.
Among the data warehouses it currently supports are Amazon Redshift, Google BigQuery, PostGres and Snowflake.
The founders built the open-source project called EventNative to help solve problems they themselves were having moving data around at their previous jobs. After putting the open-source version on GitHub a few months ago, they quickly attained 1,000 stars, proving that they had delivered something that solved a common problem for data teams. They then built the hosted version, Jitsu, which went live a couple of weeks ago.
For now, the company is just the two co-founders, Wysinski and CTO Vladimir Klimontovich and couple of contract engineers, but they intend to do some preliminary hiring over the next year to grow the company, most likely adding engineers. As they begin to build out the startup, Wysinski says that being open source will help drive diversity and inclusion in their hiring.
“The goal is essentially to go after that open-source community and hire people from anywhere because engineers aren’t just […] one color or one race, they’re everywhere, and being open source, and especially being in a remote world, makes it so, so much simpler [to build a diverse workforce], and a lot of companies I feel are going down that road,” he said.
He says along that line, the plan is to be a fully remote company, even after the pandemic ends, as they hire from anywhere. The goal is to have quarterly offsite meetings to check in with employees, but do the majority of the work remotely.
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YC-backed BuildBuddy raises $3.15M to help developers build software more quickly
BuildBuddy, whose software helps developers compile and test code quickly using a blend of open-source technology and proprietary tools, announced a funding round today worth $3.15 million.
The company was part of the Winter 2020 Y Combinator batch, which saw its traditional demo day in March turned into an all-virtual affair. The startups from the cohort then had to raise capital as the public markets crashed around them and fear overtook the startup investing world.
BuildBuddy’s funding round makes it clear that choppy market conditions and a move away from in-person demos did not fully dampen investor interest in YC’s March batch of startups, though it’s far too soon to tell if the group will perform as well as others, given how long it takes for startup winners to mature into exits.
Let’s talk code
BuildBuddy has foundations in how Google builds software. To get under the skin of what it does, I got ahold of co-founder Siggi Simonarson, who worked at the Mountain View-based search giant for a little over a half decade.
During that time he became accustomed to building software in the Google style, namely using its internal tool called Blaze to compile his code. It’s core to how developers at Google work, Simonarson told TechCrunch. “You write some code,” he added, “you run Blaze build; you write some code, you run Blaze test.”
What sets Blaze apart from other developer tools is that “opposed to your traditional language-specific build tools,” Simonarson said, it’s code agnostic, so you can use it to “build across [any] programming language.”
Google open-sourced the core of Blaze, which was named Bazel, an anagram of the original name.
So what does BuildBuddy do? In product terms, it’s building the pieces of Blaze that Google engineers have access to inside the company, for other developers using Bazel in their own work. In business terms, BuildBuddy wants to offer its service to individual developers for free, and charge companies that use its product.
Simonarson and his co-founder Tyler Williams started small, building a “results UI” tool that they shared with a Bazel user group. The members of that group picked up the tool, rapidly bringing it inside a number of sizable companies.
This origin story underlines something that BuildBuddy has that early-stage startups often lack, namely demonstrable enterprise market appetite. Lots of big companies use Bazel to help create software, and BuildBuddy found its way into a few of them early in its life.
Simply building a useful tool for a popular open-source project is no guarantee of success, however. Happily for BuildBuddy, early users helped it set direction for its product development, meaning that over the summer the startup added the features that its current users most wanted.
Simonarson explained that after BuildBuddy was initially used by external developers, they demanded additional tools, like authentication. In the words of the co-founder, the response from the startup was “great!” The same went for a request for dashboarding, and other features.
Even better for the YC graduate, some of the features requested were the sort that it intends to charge for. That brings us back to money and the round itself.
Money
BuildBuddy closed its round in May. But like with most venture capital tales, it’s not a simple story.
According to Simonarson, his startup started raising the round during one of those awful early-COVID days when the stock market dropped by double-digit percentage points in a single trading session.
BuildBuddy’s goal was to raise $1.5 million. Simonarson was worried at the time, telling TechCrunch that it was his first time fundraising, and that he wasn’t sure if his startup was going to “raise anything at all” in that climate.
But the nascent company secured its first $100,000 check. And then a $300,000 check, over time managing to fill out its round.
So what happened that got the company from $1.5 million to just over $3 million? The investor that put in $300,000 wanted to put in another $2 million. The company talked them down to $1.5 million at a higher cap (BuildBuddy raised its round using a SAFE), and the deal was done at those terms.
The startup initially didn’t want to raise the extra cash, but Simonarson told TechCrunch that at the time it was not clear where the fundraising environment was heading; BuildBuddy raised back when startup layoffs were a leading story, and a return to high-cadence VC rounds was months away.
So BuildBuddy wound up securing $3.15 million to support a current headcount of four. It intends to hire, naturally, lower its comically long runway and keep building out its Bazel-focused service.
Picking a few names from the investor spreadsheet that BuildBuddy sent over — points for completeness to the startup — Y Combinator, Addition, Scribble and Village Global, among others put capital into the round.
Dev tools are hot at the moment. Given that, as soon as BuildBuddy’s ARR starts to get moving, I expect we’ll hear from them again.
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Databand raises $14.5M led by Accel for its data pipeline observability tools
DevOps continues to get a lot of attention as a wave of companies develop more sophisticated tools to help developers manage increasingly complex architectures and workloads. In the latest development, Databand — an AI-based observability platform for data pipelines, specifically to detect when something is going wrong with a datasource when an engineer is using a disparate set of data management tools — has closed a round of $14.5 million.
Josh Benamram, the CEO who co-founded the company with Victor Shafran and Evgeny Shulman, said that Databand plans include more hiring; to continue adding customers for its existing product; to expand the library of tools that it’s providing to users to cover an ever-increasing landscape of DevOps software, where it is a big supporter of open-source resources; as well as to invest in the next steps of its own commercial product. That will include more remediation once problems are identified: that is, in addition to identifying issues, engineers will be able to start automatically fixing them, too.
The Series A is being led by Accel with participation from Blumberg Capital, Lerer Hippeau, Ubiquity Ventures, Differential Ventures and Bessemer Venture Partners. Blumberg led the company’s seed round in 2018. It has now raised around $18.5 million and is not disclosing valuation.
The problem that Databand is solving is one that is getting more urgent and problematic by the day (as evidenced by this exponential yearly rise in zettabytes of data globally). And as data workloads continue to grow in size and use, they continue to become ever more complex.
On top of that, today there are a wide range of applications and platforms that a typical organization will use to manage source material, storage, usage and so on. That means when there are glitches in any one data source, it can be a challenge to identify where and what the issue can be. Doing so manually can be time-consuming, if not impossible.
“Our users were in a constant battle with ETL (extract transform load) logic,” said Benamram, who spoke to me from New York (the company is based both there and in Tel Aviv, and also has developers and operations in Kiev). “Users didn’t know how to organize their tools and systems to produce reliable data products.”
It is really hard to focus attention on failures, he said, when engineers are balancing analytics dashboards, how machine models are performing, and other demands on their time; and that’s before considering when and if a data supplier might have changed an API at some point, which might also throw the data source completely off.
And if you’ve ever been on the receiving end of that data, you know how frustrating (and perhaps more seriously, disastrous) bad data can be. Benamram said that it’s not uncommon for engineers to completely miss anomalies and for them to only have been brought to their attention by “CEO’s looking at their dashboards and suddenly thinking something is off.” Not a great scenario.
Databand’s approach is to use big data to better handle big data: it crunches various pieces of information, including pipeline metadata like logs, runtime info and data profiles, along with information from Airflow, Spark, Snowflake and other sources, and puts the resulting data into a single platform, to give engineers a single view of what’s happening and better see where bottlenecks or anomalies are appearing, and why.
There are a number of other companies building data observability tools — Splunk perhaps is one of the most obvious, but also smaller players like Thundra and Rivery. These companies might step further into the area that Databand has identified and is fixing, but for now Databand’s focus specifically on identifying and helping engineers fix anomalies has given it a strong profile and position.
Accel partner Seth Pierrepont said that Databand came to the VC’s attention in perhaps the best way it could: Accel needed a solution like it for its own internal work.
“Data pipeline observability is a challenge that our internal data team at Accel was struggling with. Even at our relatively small scale, we were having issues with the reliability of our data outputs on a weekly basis, and our team found Databand as a solution,” he said. “As companies in all industries seek to become more data driven, Databand delivers an essential product that ensures the reliable delivery of high-quality data for businesses. Josh, Victor and Evgeny have a wealth of experience in this area, and we’ve been impressed with their thoughtful and open approach to helping data engineers better manage their data pipelines with Databand.”
The company is also used by data teams from large Fortune 500 enterprises to smaller startups.
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Can artificial intelligence give elephants a winning edge?
Images of elephants roaming the African plains are imprinted on all of our minds and something easily recognized as a symbol of Africa. But the future of elephants today is uncertain. An elephant is currently being killed by poachers every 15 minutes, and humans, who love watching them so much, have declared war on their species. Most people are not poachers, ivory collectors or intentionally harming wildlife, but silence or indifference to the battle at hand is as deadly.
You can choose to read this article, feel bad for a moment and then move on to your next email and start your day.
Or, perhaps you will pause and think: Our opportunities to help save wildlife, especially elephants, are right in front of us and grow every day. And some of these opportunities are rooted in machine learning (ML) and the magical outcome we fondly call AI.
Image Credits: Jes Lefcourt (opens in a new window)
Open-source developers are giving elephants a neural edge
Six months ago, amid a COVID-infused world, Hackster.io, a large open-source community owned by Avnet, and Smart Parks, a Dutch-based organization focused on wildlife conservation, reached out to tech industry leaders, including Microsoft, u-blox and Taoglas, Nordic Semiconductors, Western Digital and Edge Impulse with an idea to fund the R&D, manufacturing and shipping of 10 of the most advanced elephant tracking collars ever built.
These modern tracking collars are designed to deploy advanced machine-learning (ML) algorithms with the most extended battery life ever delivered for similar devices and a networking range more expansive than ever seen before. To make this vision even more audacious, they called to fully open-source and freely share the outcome of this effort via OpenCollar.io, a conservation organization championing open-source tracking collar hardware and software for environmental and wildlife monitoring projects.
Our opportunities to help save wildlife — especially elephants — are right in front of us and grow every day.
The tracker, ElephantEdge, would be built by specialist engineering firm Irnas, with the Hackster community coming together to make fully deployable ML models by Edge Impulse and telemetry dashboards by Avnet that will run the newly built hardware. Such an ambitious project was never attempted before, and many doubted that such a collaborative and innovative project could be pulled off.
Creating the world’s best elephant-tracking device
Only they pulled it off. Brilliantly. The new ElephantEdge tracker is considered the most advanced of its kind, with eight years of battery life and hundreds of miles worth of LoRaWAN networking repeaters range, running TinyML models that will provide park rangers with a better understanding of elephant acoustics, motion, location, environmental anomalies and more. The tracker can communicate with an array of sensors, connected by LoRaWAN technology to park rangers’ phones and laptops.
This gives rangers a more accurate image and location to track than earlier systems that captured and reported on pictures of all wildlife, which ran down the trackers’ battery life. The advanced ML software that runs on these trackers is built explicitly for elephants and developed by the Hackster.io community in a public design challenge.
“Elephants are the gardeners of the ecosystems as their roaming in itself creates space for other species to thrive. Our ElephantEdge project brings in people from all over the world to create the best technology vital for the survival of these gentle giants. Every day they are threatened by habitat destruction and poaching. This innovation and partnerships allow us to gain more insight into their behavior so we can improve protection,” said Smart Parks co-founder Tim van Dam.
Image Credits: Jes Lefcourt (opens in a new window)
Open-source, community-powered, conservation-AI at work
With hardware built by Irnas and Smart Parks, the community was busy building the algorithms to make it sing. Software developer and data scientist Swapnil Verma and Mausam Jain in the U.K. and Japan created Elephant AI. Using Edge Impulse, the team developed two ML models that will tap the tracker’s onboard sensors and provide critical information for park rangers.
The first community-led project, called Human Presence Detection, will alert park rangers of poaching risk using audio sampling to detect human presence in areas where humans are not supposed to be. This algorithm uses audio sensors to record sound and sight while sending it over the LoRaWAN network directly to a ranger’s phone to create an immediate alert.
The second model they named “Elephant Activity Monitoring.” It detects general elephant activity, taking time-series input from the tracker’s accelerometer to spot and make sense of running, sleeping and grazing to provide conservation specialists with the critical information they need to protect the elephants.
Another brilliant community development came from the other side of the world. Sara Olsson, a Swedish software engineer who has a passion for the national world, created a TinyML and IoT monitoring dashboard to help park rangers with conservation efforts.
With little resources and support, Sara built a full telemetry dashboard combined with ML algorithms to monitor camera traps and watering holes, while reducing network traffic by processing data on the collar and considerably saving battery life. To validate her hypothesis, she used 1,155 data models and 311 tests!
Sara Olsson’s TinyML and IoT monitoring dashboard. Image Credits: Sara Olsson
She completed her work in the Edge Impulse studio, creating the models and testing them with camera traps streams from Africam using an OpenMV camera from her home’s comfort.
Image Credits: Sara Olsson (opens in a new window)
Technology for good works, but human behavior must change
Project ElephantEdge is an example of how commercial and public interest can converge and result in a collaborative sustainability effort to advance wildlife conservation efforts. The new collar can generate critical data and equip park rangers with better data to make urgent life-saving decisions about protecting their territories. By the end of 2021, at least ten elephants will be sporting the new collars in selected parks across Africa, in partnership with the World Wildlife Fund and Vulcan’s EarthRanger, unleashing a new wave of conservation, learning and defending.
Naturally, this is great, the technology works, and it’s helping elephants like never before. But in reality, the root cause of the problem runs much more profound. Humans must change their relationship to the natural world for proper elephant habitat and population revival to occur.
“The threat to elephants is greater than it’s ever been,” said Richard Leakey, a leading palaeoanthropologist and conservationist scholar. The main argument for allowing trophy or ivory hunting is that it raises money for conservation and local communities. However, a recent report revealed that only 3% of Africa’s hunting revenue trickles down to communities in hunting areas. Animals don’t need to die to make money for the communities you live around.
With great technology, collaboration and a commitment to address the underlying cultural conditions and the ivory trade that leads to most elephant deaths, there’s a real chance to save these singular creatures.
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Will Zoom Apps be the next hot startup platform?
When Zoom announced Zapps last month — the name has since been wisely changed to Zoom Apps — VC Twitter immediately began speculating that Zoom could make the leap from successful video conferencing service to becoming a launching pad for startup innovation. It certainly caught the attention of former TechCrunch writer and current investor at Signal Fire Josh Constine, who tweeted that “Zoom’s new ‘Zapps’ app platform will crush or king-make lots of startups.”
As Zoom usage exploded during the pandemic and it became a key tool for business and education, the idea of using a video conferencing platform to build a set of adjacent tooling makes a lot of sense. While the pandemic will come to an end, we have learned enough about remote work that the need for tools like Zoom will remain long after we get the all-clear to return to schools and offices.
We are already seeing promising startups like Mmhmm, Docket and ClassEdu built with Zoom in mind, and these companies are garnering investor attention. In fact, some investors believe Zoom could be the next great startup ecosystem.
Moving beyond video conferencing
Salesforce paved the way for Zoom more than a decade ago when it opened up its platform to developers and later launched the AppExchange as a distribution channel. Both were revolutionary ideas at the time. Today we are seeing Zoom building on that.
Jim Scheinman, founding managing partner at Maven Ventures and an early Zoom investor (who is credited with naming the company) says he always saw the service as potentially a platform play. “I’ve been saying publicly, before anyone realized it, that Zoom is the next great open platform on which to build billion-dollar businesses,” Scheinman told me.
He says he talked with Zoom leadership about opening up the platform to external developers several years ago before the IPO. It wasn’t really a priority at that point, but COVID-19 pushed the idea to the forefront. “Post-IPO and COVID, with the massive growth of Zoom on both the enterprise and consumer side, it became very clear that an app marketplace is now a critical growth area for Zoom, which creates a huge opportunity for nascent startups to scale,” he said.
Jason Green, founder and managing director at Emergence Capital (another early investor in Zoom and Salesforce) agreed: “Zoom believes that adding capabilities to the core Zoom platform to make it more functional for specific use cases is an opportunity to build an ecosystem of partners similar to what Salesforce did with AppExchange in the past.”
Building the platform
Before a platform can succeed with developers, it requires a critical mass of users, a bar that Zoom has clearly passed. It also needs a set of developer tools to connect to the various services on the platform. Then the substantial user base acts as a ready market for the startup. Finally, it requires a way to distribute those creations in a marketplace.
Zoom has been working on the developer components and brought in industry veteran Ross Mayfield, who has been part of two collaboration startups in his career, to run the developer program. He says that the Zoom Apps development toolset has been designed with flexibility to allow developers to build applications the way that they want.
For starters, Zoom has created WebViews, a way to embed functionality into an application like Zoom. To build WebViews in Zoom, the company created a JS Kit, which in combination with existing Zoom APIs enables developers to build functionality inside the Zoom experience. “So we’re giving developers a lot of flexibility in what experience they create with WebViews plus using our very rich set of API’s that are part of the existing platform and creating some new API’s to create the experience,” he said.
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Grouparoo snares $3M seed to build open source customer data integration framework
Creating a great customer experience requires a lot of data from a variety of sources, and pulling that disparate data together has captured the attention of companies and big and small from Salesforce and Adobe to Segment and Klaviyo. Today, Grouparoo, a new startup from three industry vets is the next company up with an open source framework designed to make it easier for developers to access and make use of customer data.
The company announced a $3 million seed investment led by Eniac Ventures and Fuel Capital with participation from Hack VC, Liquid2, SCM Advisors and several unnamed angel investors.
Grouparoo CEO and co-founder Brian Leonard says that his company has created this open source customer data framework based on his own experience and difficulty getting customer data into the various tools he has been using since he was technical founder at TaskRabbit in 2008.
“We’re an open source data framework that helps companies easily sync their customer data from their database or warehouse to all of the SaaS tools where they need it. [After you] install it, you teach it about your customers, like what properties are important in each of those profiles. And then it allows you to segment them into the groups that matter,” Leonard explained.
This could be something like high earners in San Francisco along with names and addresses. Grouparoo can grab this data and transfer it to a marketing tool like Marketo or Zendesk and these tools could then learn who your VIP customers are.
For now the company is just the three founders Leonard, CTO Evan Tahler and COO Andy Jih, and while he wasn’t ready to commit to how many people he might hire in the next 12 months, he sees it being less than 10. At this early stage, the three co-founders have already been considering how to build a diverse and inclusive company, something he helped contribute to while he was at TaskRabbit.
“So, coming from [what we built at TaskRabbit] and starting something new, it’s important to all three of us to start [building a diverse company] from the beginning, and especially combined with this notion that we’re building something open source. We’ve been talking a lot about being open about our culture and what’s important to us,” he said.
TaskRabbit also comes into play in their investment where Fuel GP Leah Solivan was also founder of TaskRabbit. “Grouparoo is solving a real and acute issue that companies grapple with as they scale — giving every member of the team access to the data they need to drive revenue, acquire customers and improve real-time decision making. Brian, Andy and Evan have developed an elegant solution to an issue we experienced firsthand at TaskRabbit,” she said.
For now the company is taking an open source approach to build a community around the tool. It is still pre-revenue, but the plan is to find a way to build something commercial on top of the open source tooling. They are considering an open core license where they can add features or support or offer the tool as a service. Leonard says that is something they intend to work out in 2021.
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