Oct
26
2020
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Freshworks (re-)launches its CRM service

Freshworks, the customer and employee engagement company that offers a range of products, from call center and customer support software to HR tools and marketing automation services, today announced the launch of its newest product: Freshworks CRM. The new service, which the company built on top of its new Freshworks Neo platform, is meant to give sales and marketing teams all of the tools they need to get a better view of their customers — with a bit of machine learning thrown in for better predictions.

Freshworks CRM is essentially a rebrand of the company’s Freshsales service, combined with the company’s capabilities of its Freshmarketer marketing automation tool.

“Freshworks CRM unites Freshsales and Freshmarketer capabilities into one solution, which leverages an embedded customer data platform for an unprecedented and 360-degree view of the customer throughout their entire journey,” a company spokesperson told me.

The promise here is that this improved CRM solution is able to provide teams with a more complete view of their (potential) customers thanks to the unified view — and aggregated data — that the company’s Neo platform provides.

The company argues that the majority of CRM users quickly become disillusioned with their CRM service of choice — and the reason for that is because the data is poor. That’s where Freshworks thinks it can make a difference.

Freshworks CRM delivers upon the original promise of CRM: a single solution that combines AI-driven data, insights and intelligence and puts the customer front and center of business goals,” said Prakash Ramamurthy, the company’s chief product officer. “We built Freshworks CRM to harness the power of data and create immediate value, challenging legacy CRM solutions that have failed sales teams with clunky interfaces and incomplete data.”

The idea here is to provide teams with all of their marketing and sales data in a single dashboard and provide AI-assisted insights to them to help drive their decision making, which in turn should lead to a better customer experience — and more sales. The service offers predictive lead scoring and qualification, based on a host of signals users can customize to their needs, as well as Slack and Teams integrations, built-in telephony with call recording to reach out to prospects and more. A lot of these features were already available in Freshsales, too.

“The challenge for online education is the ‘completion rate’. To increase this, we need to understand the ‘Why’ aspect for a student to attend a course and design ‘What’ & ‘How’ to meet the personalized needs of our students so they can achieve their individual goals,” said Mamnoon Hadi Khan, the chief analytics officer at Shaw Academy. “With Freshworks CRM, Shaw Academy can track the entire student customer journey to better engage with them through our dedicated Student Success Managers and leverage AI to personalize their learning experience — meeting their objectives.”

Pricing for Freshworks CRM starts at $29 per user/month and goes up to $125 per user/month for the full enterprise plan with more advanced features.

Oct
26
2020
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DataFleets keeps private data useful and useful data private with federated learning and $4.5M seed

As you may already know, there’s a lot of data out there, and some of it could actually be pretty useful. But privacy and security considerations often put strict limitations on how it can be used or analyzed. DataFleets promises a new approach by which databases can be safely accessed and analyzed without the possibility of privacy breaches or abuse — and has raised a $4.5 million seed round to scale it up.

To work with data, you need to have access to it. If you’re a bank, that means transactions and accounts; if you’re a retailer, that means inventories and supply chains, and so on. There are lots of insights and actionable patterns buried in all that data, and it’s the job of data scientists and their ilk to draw them out.

But what if you can’t access the data? After all, there are many industries where it is not advised or even illegal to do so, such as in healthcare. You can’t exactly take a whole hospital’s medical records, give them to a data analysis firm, and say “sift through that and tell me if there’s anything good.” These, like many other data sets, are too private or sensitive to allow anyone unfettered access. The slightest mistake — let alone abuse — could have serious repercussions.

In recent years a few technologies have emerged that allow for something better, though: analyzing data without ever actually exposing it. It sounds impossible, but there are computational techniques for allowing data to be manipulated without the user ever actually having access to any of it. The most widely used one is called homomorphic encryption, which unfortunately produces an enormous, orders-of-magnitude reduction in efficiency — and big data is all about efficiency.

This is where DataFleets steps in. It hasn’t reinvented homomorphic encryption, but has sort of sidestepped it. It uses an approach called federated learning, where instead of bringing the data to the model, they bring the model to the data.

DataFleets integrates with both sides of a secure gap between a private database and people who want to access that data, acting as a trusted agent to shuttle information between them without ever disclosing a single byte of actual raw data.

Illustration showing how a model can be created without exposing data.

Image Credits: DataFleets

Here’s an example. Say a pharmaceutical company wants to develop a machine-learning model that looks at a patient’s history and predicts whether they’ll have side effects with a new drug. A medical research facility’s private database of patient data is the perfect thing to train it. But access is highly restricted.

The pharma company’s analyst creates a machine-learning training program and drops it into DataFleets, which contracts with both them and the facility. DataFleets translates the model to its own proprietary runtime and distributes it to the servers where the medical data resides; within that sandboxed environment, it grows into a strapping young ML agent, which when finished is translated back into the analyst’s preferred format or platform. The analyst never sees the actual data, but has all the benefits of it.

Screenshot of the DataFleets interface. Look, it’s the applications that are meant to be exciting. Image Credits: DataFleets

It’s simple enough, right? DataFleets acts as a sort of trusted messenger between the platforms, undertaking the analysis on behalf of others and never retaining or transferring any sensitive data.

Plenty of folks are looking into federated learning; the hard part is building out the infrastructure for a wide-ranging enterprise-level service. You need to cover a huge amount of use cases and accept an enormous variety of languages, platforms and techniques, and of course do it all totally securely.

“We pride ourselves on enterprise readiness, with policy management, identity-access management, and our pending SOC 2 certification,” said DataFleets COO and co-founder Nick Elledge. “You can build anything on top of DataFleets and plug in your own tools, which banks and hospitals will tell you was not true of prior privacy software.”

But once federated learning is set up, all of a sudden the benefits are enormous. For instance, one of the big issues today in combating COVID-19 is that hospitals, health authorities, and other organizations around the world are having difficulty, despite their willingness, in securely sharing data relating to the virus.

Everyone wants to share, but who sends whom what, where is it kept, and under whose authority and liability? With old methods, it’s a confusing mess. With homomorphic encryption it’s useful but slow. With federated learning, theoretically, it’s as easy as toggling someone’s access.

Because the data never leaves its “home,” this approach is essentially anonymous and thus highly compliant with regulations like HIPAA and GDPR, another big advantage. Elledge notes: “We’re being used by leading healthcare institutions who recognize that HIPAA doesn’t give them enough protection when they are making a data set available for third parties.”

Of course there are less noble, but no less viable, examples in other industries: Wireless carriers could make subscriber metadata available without selling out individuals; banks could sell consumer data without violating anyone in particular’s privacy; bulky datasets like video can sit where they are instead of being duplicated and maintained at great expense.

The company’s $4.5 million seed round is seemingly evidence of confidence from a variety of investors (as summarized by Elledge): AME Cloud Ventures (Jerry Yang of Yahoo) and Morado Ventures, Lightspeed Venture Partners, Peterson Ventures, Mark Cuban, LG, Marty Chavez (president of the board of overseers of Harvard), Stanford-StartX fund, and three unicorn founders (Rappi, Quora and Lucid).

With only 11 full-time employees DataFleets appears to be doing a lot with very little, and the seed round should enable rapid scaling and maturation of its flagship product. “We’ve had to turn away or postpone new customer demand to focus on our work with our lighthouse customers,” Elledge said. They’ll be hiring engineers in the U.S. and Europe to help launch the planned self-service product next year.

“We’re moving from a data ownership to a data access economy, where information can be useful without transferring ownership,” said Elledge. If his company’s bet is on target, federated learning is likely to be a big part of that going forward.

Oct
26
2020
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The No-Code Generation is arriving

In the distant past, there was a proverbial “digital divide” that bifurcated workers into those who knew how to use computers and those who didn’t.[1] Young Gen Xers and their later millennial companions grew up with Power Macs and Wintel boxes, and that experience made them native users on how to make these technologies do productive work. Older generations were going to be wiped out by younger workers who were more adaptable to the needs of the modern digital economy, upending our routine notion that professional experience equals value.

Of course, that was just a narrative. Facility with using computers was determined by the ability to turn it on and log in, a bar so low that it can be shocking to the modern reader to think that a “divide” existed at all. Software engineering, computer science and statistics remained quite unpopular compared to other academic programs, even in universities, let alone in primary through secondary schools. Most Gen Xers and millennials never learned to code, or frankly, even to make a pivot table or calculate basic statistical averages.

There’s a sociological change underway though, and it’s going to make the first divide look quaint in hindsight.

Over the past two or so years, we have seen the rise of a whole class of software that has been broadly (and quite inaccurately) dubbed “no-code platforms.” These tools are designed to make it much easier for users to harness the power of computing in their daily work. That could be everything from calculating the most successful digital ad campaigns given some sort of objective function, or perhaps integrating a computer vision library into a workflow that calculates the number of people entering or exiting a building.

The success and notoriety of these tools comes from the feeling that they grant superpowers to their users. Projects that once took a team of engineers some hours to build can now be stitched together in a couple of clicks through a user interface. That’s why young startups like Retool can raise at nearly a $1 billion valuation and Airtable at $2.6 billion, while others like Bildr, Shogun, Bubble, Stacker and dozens more are getting traction among users.

Of course, no-code tools often require code, or at least, the sort of deductive logic that is intrinsic to coding. You have to know how to design a pivot table, or understand what machine learning capability is and what it might be useful for. You have to think in terms of data, and about inputs, transformations and outputs.

The key here is that no-code tools aren’t successful just because they are easier to use — they are successful because they are connecting with a new generation that understands precisely the sort of logic required by these platforms to function. Today’s students don’t just see their computers and mobile devices as consumption screens and have the ability to turn them on. They are widely using them as tools of self-expression, research and analysis.

Take the popularity of platforms like Roblox and Minecraft. Easily derided as just a generation’s obsession with gaming, both platforms teach kids how to build entire worlds using their devices. Even better, as kids push the frontiers of the toolsets offered by these games, they are inspired to build their own tools. There has been a proliferation of guides and online communities to teach kids how to build their own games and plugins for these platforms (Lua has never been so popular).

These aren’t tiny changes; 150 million play Roblox games across 40 million user-created experiences, and the platform has nearly 350,000 developers. Minecraft for its part has more than 130 million active users. These are generation-defining experiences for young people today.

That excitement to harness computers is also showing up in educational data. Advanced Placement tests for computer science have grown from around 20,000 in 2010 to more than 70,000 this year according to the College Board, which administers the high school proficiency exams. That’s the largest increase among all of the organization’s dozens of tests. Meanwhile at top universities, computer science has emerged as the top or among the top majors, pulling in hundreds of new students per campus per year.

The specialized, almost arcane knowledge of data analysis and engineering is being widely democratized for this new generation, and that’s precisely where a new digital divide is emerging.

In business today, it’s not enough to just open a spreadsheet and make some casual observations anymore. Today’s new workers know how to dive into systems, pipe different programs together using no-code platforms and answer problems with much more comprehensive — and real-time — answers.

It’s honestly striking to see the difference. Whereas just a few years ago, a store manager might (and strong emphasis on might) put their sales data into Excel and then let it linger there for the occasional perusal, this new generation is prepared to connect multiple online tools to build an online storefront (through no-code tools like Shopify or Squarespace), calculate basic LTV scores using a no-code data platform and prioritize their best customers with marketing outreach through basic email delivery services. And it’s all reproducible, as it is in technology and code and not produced by hand.

There are two important points here. First is to note the degree of fluency these new workers have for these technologies, and just how many members of this generation seem prepared to use them. They just don’t have the fear to try new programs, and they know they can always use search engines to find answers to problems they are having.

Second, the productivity difference between basic computer literacy and a bit more advanced expertise is profound. Even basic but accurate data analysis on a business can raise performance substantially compared to gut instinct and expired spreadsheets.

This second digital divide is only going to get more intense. Consider students today in school, who are forced by circumstance to use digital technologies in order to get their education. How many more students are going to become even more capable of using these technologies? How much more adept are they going to be at remote work? While the current educational environment is a travesty and deeply unequal, the upshot is that ever more students are going to be forced to become deeply fluent in computers.[2]

Progress in many ways is about raising the bar. This generation is raising the bar on how data is used in the workplace, in business and in entrepreneurship. They are better than ever at bringing together various individual services and cohering them into effective experiences for their customers, readers and users. The No-Code Generation has the potential to finally fill that missing productivity gap in the global economy, making our lives better, while saving time for everyone.

[1] Probably worth pointing out that the other “digital divide” at the time was describing households that had internet access and households that did not. That’s a divide that unfortunately still plagues America and many other rich, industrialized countries.

[2] Important to note that access to computing is still an issue for many students and represents one of the most easily fixable inequalities today in America. Providing equal access to computing should be an absolute imperative.

Oct
26
2020
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SAP shares fall sharply after COVID-19 cuts revenue, profit forecast at software giant

SAP announced its Q3 earnings yesterday, with its aggregate results down across the board. And after missing earnings expectations, the company also revised its 2021 outlook down. The combined bad news spooked investors, crashing its shares by more than 20% in pre-market trading, and the stock wasn’t showing any signs of improving in early trading.

The German software giant has lost tens of billions of dollars in market cap as a result.

The overall report was gloomy, with total revenues falling 4% to €6.54 billion, cloud and software revenue down 2% and operating profit down 12%. The only bright spot was its pure-cloud category, which grew 11%, to €1.98 billion.

SAP’s revenue result was around €310 million under expectations, though its per-share profit beat both adjusted and non-adjusted expectations.

While SAP’s big revenue miss might have been enough to send investors racing for the exits, its revised forecast doubled concerns. Even though the company said that its customers are accelerating their move to the cloud during the pandemic — something that TechCrunch has been tracking for some time now — SAP also said the pandemic is slowing sales and large projects.

Constellation Research analyst Holger Mueller says this is resulting in an unexpected revenue slow-down.

“What has happened at SAP is a cloud revenue delay as customers know that SAP is only investing into cloud products, and they have to migrate to those in the future. The news is that SAP customers are not migrating to the cloud during a pandemic,” Mueller told TechCrunch.

In a sign of the times, SAP spent a portion of its earnings results talking about 2025 results, a maneuver that failed to allay investor concerns that the pandemic was dramatically impacting SAP’s business today and in the coming year.

For 2020, SAP made the following cuts to its forecasts:

  • €8.0 – 8.2 billion non-IFRS cloud revenue at constant currencies (previously €8.3 – 8.7 billion)
  • €23.1 – 23.6 billion non-IFRS cloud and software revenue at constant currencies (previously €23.4 – 24.0 billion)
  • €27.2 – 27.8 billion non-IFRS total revenue at constant currencies (previously €27.8 – 28.5 billion)
  • €8.1 – 8.5 billion non-IFRS operating profit at constant currencies (previously €8.1 – 8.7 billion)

So, €300 million to €500 million in cloud revenue is now gone, along with €300 million to €400 million in cloud and software revenue, and €600 to €700 million in total revenue. That cut profit expectations by up to €200 million.

The company, however, is trying to put a happy face on the future projections, believing that as the impact of COVID begins to diminish, existing customers will eventually shift to the cloud and that will drive significant new revenues over the longer term. The trade-off is short-term pain for the next year or two.

“Over the next two years, we expect to see muted growth of revenue accompanied by a flat to slightly lower operating profit. After 2022 momentum will pick up considerably though. Initial headwinds of the accelerated cloud transition will start to turn into tailwinds for revenue and profit. […] That translates to accelerated revenue growth and double digit operating profit growth from 2023 onwards,” SAP CFO Luka Mucic said in a call with analysts this morning.

The question now becomes can they meet these projections, and if the longer-term approach during a pandemic will placate investors. As of this morning, they weren’t looking happy about it.

Oct
26
2020
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Dropbox begins shift to high-efficiency Western Digital Shingled Magnetic Recording disks

Last year, Dropbox talked about making a shift to Shingled Magnetic Recording, or SMR disks for short, because of the efficiency they can give a high-volume storage platform like theirs. Today, Western Digital announced that Dropbox was one of the first companies to qualify their Ultrastar® DC HC650 20TB host-managed SMR hard disks.

Dropbox’s modern infrastructure story goes back to 2017, when it decided to shift most of its business from being hosted on AWS to building their own infrastructure. As they moved through the process of making that transition in the following years, they were looking for new storage technology ideas to help drive down the cost of running their own massive storage system.

As principal engineer James Cowling told TechCrunch last year, one of the ideas that emerged was using SMR:

What emerged was SMR, which has high storage density and a lower price point. Moving to SMR gave Dropbox the ability to do more with less, increasing efficiency and lowering overall costs — an essential step for a company trying to do this on its own. “It required expertise obviously, but it was also exciting to bring a lot of efficiencies in terms of cost and storage efficiency, while pulling down boundaries between software and hardware,” Cowling said.

As it turns out, Dropbox VP of engineering Andrew Fong says that the company has been working with Western Digital for a number of years and the new SMR technology is the latest step in that partnership.

Western Digital says these drives deliver this cost savings through increased storage density and lower power requirements. “When considering exabyte-scale needs, and associated capital and operating cost of the data center, the long-term value in terms of lower cost-per-TB, higher density, low power and high reliability can help benefit the bottom line,” the company said in a statement.

Time will tell if these disks deliver as promised, but they certainly show a lot of potential for a high-volume user like Dropbox.

Oct
25
2020
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Talking Drupal #267 – Nubay

Today we talk with the founder of Nubay a non-profit that is empowering other non-profits with Drupal. There is a narrative that Drupal 8 is for enterprise customers. Nubay is an example of how enterprise functionality benefits websites of all sizes.

www.talkingdrupal.com/267

Topics

  • Stephen – CSPAN
  • John – Soap
  • Nic – Ring Fit
  • Dave – Hoel in one
  • What is Nubay and history
  • What does non-profit mean for Nubay
  • Services the Nubay provides
  • Volunteers

Hosts

Stephen Cross – www.stephencross.com @stephencross

John Picozzi – www.oomphinc.com @johnpicozzi

Nic Laflin – www.nLighteneddevelopment.com @nicxvan

Guest

Dave Tarrant   https://www.nubay.org

 

Oct
22
2020
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Extra Crunch Partner Perk: Get 6 months free of Zendesk Support and Sales CRM

We’re excited to announce an update to the Extra Crunch Partner Perk from Zendesk. Starting today, annual and two-year Extra Crunch members that are new to Zendesk, and meet their startup qualifications, can now receive six months of free access to Zendesk’s Sales CRM, in addition to Zendesk Support Suite, Zendesk Explore and Zendesk Sunshine.

Here is an overview of the program.

Zendesk is a service-first CRM company with support, sales and customer engagement products designed to improve customer relationships. This offer is only available for startups that are new to Zendesk, have fewer than 100 employees and are funded but have not raised beyond a Series B.

The Zendesk Partner Perk from Extra Crunch is inclusive of subscription fees, free for six months, after which you will be responsible for payment. Any downgrades to your Zendesk subscription will result in the forfeiture of the promotion, so please check with Zendesk first regarding any changes (startups@zendesk.com). Some add-ons such as Zendesk Talk and Zendesk Sell minutes are not included. Complete details of what’s included can be found here.

Oct
22
2020
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Using Volume Snapshot/Clone in Kubernetes

Volume snapshot and clone Kubernetes

Volume snapshot and clone KubernetesOne of the most exciting storage-related features in Kubernetes is Volume snapshot and clone. It allows you to take a snapshot of data volume and later to clone into a new volume, which opens a variety of possibilities like instant backups or testing upgrades. This feature also brings Kubernetes deployments close to cloud providers, which allow you to get volume snapshots with one click.

Word of caution: for the database, it still might be required to apply fsfreeze and FLUSH TABLES WITH READ LOCK or

LOCK BINLOG FOR BACKUP

.

It is much easier in MySQL 8 now, because as with atomic DDL, MySQL 8 should provide crash-safe consistent snapshots without additional locking.

Let’s review how we can use this feature with Google Cloud Kubernetes Engine and Percona Kubernetes Operator for XtraDB Cluster.

First, the snapshot feature is still beta, so it is not available by default. You need to use GKE version 1.14 or later and you need to have the following enabled in your GKE: https://cloud.google.com/kubernetes-engine/docs/how-to/persistent-volumes/gce-pd-csi-driver#enabling_on_a_new_cluster.

It is done by enabling “Compute Engine persistent disk CSI Driver“.

Now we need to create a Cluster using storageClassName: standard-rwo for PersistentVolumeClaims. So the relevant part in the resource definition looks like this:

persistentVolumeClaim:
        storageClassName: standard-rwo
        accessModes: [ "ReadWriteOnce" ]
        resources:
          requests:
            storage: 11Gi

Let’s assume we have cluster1 running:

NAME                                               READY   STATUS    RESTARTS   AGE
cluster1-haproxy-0                                 2/2     Running   0          49m
cluster1-haproxy-1                                 2/2     Running   0          48m
cluster1-haproxy-2                                 2/2     Running   0          48m
cluster1-pxc-0                                     1/1     Running   0          50m
cluster1-pxc-1                                     1/1     Running   0          48m
cluster1-pxc-2                                     1/1     Running   0          47m
percona-xtradb-cluster-operator-79d786dcfb-btkw2   1/1     Running   0          5h34m

And we want to clone a cluster into a new cluster, provisioning with the same dataset. Of course, it can be done using backup into a new volume, but snapshot and clone allow for achieving this much easier. There are still some additional required steps, I will list them as a Cheat Sheet.

1. Create VolumeSnapshotClass (I am not sure why this one is not present by default)

apiVersion: snapshot.storage.k8s.io/v1beta1
kind: VolumeSnapshotClass
metadata:
        name: onesc
driver: pd.csi.storage.gke.io
deletionPolicy: Delete

2. Create snapshot

apiVersion: snapshot.storage.k8s.io/v1beta1
kind: VolumeSnapshot
metadata:
  name: snapshot-for-newcluster
spec:
  volumeSnapshotClassName: onesc
  source:
    persistentVolumeClaimName: datadir-cluster1-pxc-0

3. Clone into a new volume

Here I should note that we need to use the following as volume name convention used by Percona XtraDB Cluster Operator, it is:

datadir-<CLUSTERNAME>-pxc-0

Where CLUSTERNAME is the name used when we create clusters. So now we can clone snapshot into a volume:

datadir-newcluster-pxc-0

Where newcluster is the name of the new cluster.

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: datadir-newcluster-pxc-0
spec:
  dataSource:
    name: snapshot-for-newcluster
    kind: VolumeSnapshot
    apiGroup: snapshot.storage.k8s.io
  storageClassName: standard-rwo
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 11Gi

Important: the volume spec in storageClassName and accessModes and storage size should match the original volume.

After volume claim created, now we can start newcluster, however, there is still a caveat; we need to use:

forceUnsafeBootstrap: true

Because otherwise, Percona XtraDB Cluster will think the data from the snapshot was not after clean shutdown (which is true) and will refuse to start.

There is still some limitation to this approach, which you may find inconvenient: the volume can be cloned in only the same namespace, so it can’t be easily transferred from the PRODUCTION namespace into the QA namespace.

Though it still can be done but will require some extra steps and admin Kubernetes privileges, I will show how in the following blog posts.

Oct
22
2020
--

Customer experience and digital transformation concepts are merging during the pandemic

Customer experience and digital transformation are two terms we’ve been hearing about for years, but have often remained nebulous in many organizations — something to aspire to perhaps, but not take completely seriously. Yet the pandemic has been a forcing event for both concepts, thrusting the ideas front and center.

Suddenly startups that help with either of these concepts are seeing rising demand, even in a year with an overall difficult economic climate. If you are fortunate enough to be helping companies digitize a process or improve how customers interact with companies, you may be seeing increased interest from customers and potential acquirers (and this was true even before this year). A case in point is Twilio acquiring Segment for $3.2 billion recently to help build data-fueled applications to interact with customers.

Even though building a positive customer experience has never been completely about digital, at a time where it’s difficult to interact with customers in person, the digital side of it has taken new urgency. As COVID-19 took hold this year, businesses, large and small, suddenly realized the only way to connect to their customers was digitally. At that point, digital transformation became customer experience’s buddy when other ways of contacting one another have been severely limited.

Pandemic brings changes

Just about every startup founder I talk to these days, along with bigger, more established companies, talk about how the pandemic has pushed companies to digitally transform much faster than they would have without COVID.

Brent Leary, founder at CRM Essentials, says that the pandemic has certainly expedited the need to bring these two big ideas together and created opportunities as that happens. “The coronavirus, as terrible as it has been in so many ways to so many people, has created opportunities for companies to build direct-to-consumer (D2C) digital pipelines that can make them stronger companies despite the current hardships,” Leary told TechCrunch.

The cloud plays a big role in the digital transformation process, and for the last decade, we have seen companies make a slow but steady shift to the cloud. When you have a situation like we’ve had with the coronavirus, it speeds everything up. As it turns out, being in the cloud helps you move faster because you don’t have to worry about all of the overhead of running a business critical application as the SaaS vendors take care of all that for you.

Oct
22
2020
--

Harness delivers enterprise continuous integration on heels of Drone.io acquisition

In August, Harness made its first acquisition when it bought open source continuous integration startup Drone.io. The company didn’t waste any time building on that purchase, announcing a new enterprise continuous integration tool today to go alongside the open source project Drone has been building.

The Harness software development platform consists of various modules and the latest one helps with continuous integration, which is the build and test process that happens before developers start deploying their code changes.

As Brad Rydzewski, co-founder at Drone.io, explained it at the time of the acquisition:

“Drone is a continuous integration software. It helps developers to continuously build, test and deploy their code. The project was started in 2012, and it was the first cloud-native, container-native continuous integration solution on the market, and we open sourced it.”

Bansal indicated at the time of the acquisition that he wanted to build on that open source project and provide an enterprise commercial version, while continuing to support the open source project.

“This is really the first product in the industry that is bringing AI and machine learning into optimizing the build and test process,” Bansal said. That intelligence layer is what separates it from the open source version of the software, and the idea is to use machine learning to speed up the building and testing process.

The company is also announcing a new module around managing feature flags. These are elements developers leave in the code to limit the roll out of software, allowing them to see how the update is performing before rolling it out to the user base at large. The problem is these as these flags proliferate, they become difficult to manage, and the new module is designed to help developers understand and control the flags that exist in their code.

Bansal says his goal for the company has been to put the kind of automated software delivery pipeline that’s in place at the world’s largest tech companies within reach of every developer.

“[Our goal] is that every company in the world can have the same level of software delivery sophistication as a Google or Amazon or Facebook,” Bansal said.

Bansal founded AppDynamics, a company he sold to Cisco in 2017 for $3.7 billion. He launched Harness later that same year. The company has raised almost $80 million on a valuation of $500 million, according to Pitchbook data.

Bansal also started the venture capital firm Unusual Ventures in 2018 and as though he doesn’t have enough to do, he launched his third startup Traceable, a security company, in July.

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