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WordPress.com launches new P2 to take on internal communication tools

WordPress.com, a division of Automattic, is launching a new product called P2. And this time, it’s all about improving internal communications for private groups. As a remote company, Automattic has been using P2 internally for years to communicate asynchronously. It’s a place to share long-form posts, a repository to keep onboarding documents and other important ever-green documents.

P2 is built on top of WordPress . You can view it as a sort of WordPress for teams that is heavily customized around the concept of sharing ideas with other team members. Companies now rely on multiple internal communication tools. P2 can replace some of them but doesn’t want to reinvent the wheel altogether.

For instance, P2 isn’t a Slack competitor. You can’t use it for real-time chat. But P2 can be used to share important announcements — the kind of announcements that you can find on an intranet portal.

Image Credits: WordPress.com

You can also use it for long-term projects and create your own P2 for your team in particular. In that case, P2 competes more directly with Workplace by Facebook or Yammer. In order to make it more useful for asynchronous communications, P2 has some features that make it more useful than a simple WordPress blog.

For instance, you can @-mention your coworkers to send them a notification and follow posts to receive updates. You can also create checklists, embed PDF documents, stick important posts at the top of the homepage and stay on top of what happened while you were gone. There are dedicated menus to view new posts, new comments and mentions you’ve received.

While you can theoretically access the classic WordPress back-end, you can write new posts, edit existing posts and write comments without ever leaving P2. The company uses the new block editor that lets you add headings, lists, video embeds and media in a visual way. It works a bit like Squarespace’s editor or Notion, and it makes a ton of sense to leverage the new editor right next to content you’re viewing, commenting on, etc.

For content that always remains relevant, you can create documents, which are pages without a specific publishing date and without comments. These documents are sorted in their own category and can be easily shared across a company. You can use documents for internal policies, guides or important contact information. Many companies rely on Google Docs and shared folders in Google Drive for this kind of documents. P2 could potentially replace those shared folders and become the main information repository.

By default, P2 sites are private but you can make them public in case you want to share updates on your product with clients or use P2 for public events.

If you’re familiar with the WordPress ecosystem, you might already know a WordPress theme called P2. The new P2 announced today is a new product that takes that idea to the next level. Automattic has been iterating on the concept and using it widely with its 1,300 employees across 912 internal P2 sites.

WordPress.com is going to offer hosted P2 instances. Anybody can create a P2 for free and invite other people. Eventually, WordPress.com plans to offer paid subscriptions for advanced features. In other words, P2 is going to be a software-as-a-service product. But there will be a self-hostable, open source version in the future as well.

I played around with a few P2 instances, and the overall impression is that the complexity of WordPress remains hidden by default, which is a good thing. It’s a clean and focused product that would work particularly well in that spot between company-wide emails and announcements getting lost in Slack.

Image Credits: WordPress.com

Microsoft launches Open Service Mesh

Microsoft today announced the launch of a new open-source service mesh based on the Envoy proxy. The Open Service Mesh is meant to be a reference implementation of the Service Mesh Interface (SMI) spec, a standard interface for service meshes on Kubernetes that has the backing of most of the players in this ecosystem.

The company plans to donate Open Service Mesh to the Cloud Native Computing Foundation (CNCF) to ensure that it is community-led and has open governance.

“SMI is really resonating with folks and so we really thought that there was room in the ecosystem for a reference implementation of SMI where the mesh technology was first and foremost implementing those SMI APIs and making it the best possible SMI experience for customers,” Microsoft partner program manager (and CNCF board member) Gabe Monroy told me.

Image Credits: Microsoft

He also added that, because SMI provides the lowest common denominator API design, Open Service Mesh gives users the ability to “bail out” to raw Envoy if they need some more advanced features. This “no cliffs” design, Monroy noted, is core to the philosophy behind Open Service Mesh.

As for its feature set, SMI handles all of the standard service mesh features you’d expect, including securing communications between services using mTLS, managing access control policies, service monitoring and more.

Image Credits: Microsoft

There are plenty of other service mesh technologies in the market today, though. So why would Microsoft launch this?

“What our customers have been telling us is that solutions that are out there today, Istio being a good example, are extremely complex,” he said. “It’s not just me saying this. We see the data in the AKS support queue of customers who are trying to use this stuff — and they’re struggling right here. This is just hard technology to use, hard technology to build at scale. And so the solutions that were out there all had something that wasn’t quite right and we really felt like something lighter weight and something with more of an SMI focus was what was going to hit the sweet spot for the customers that are dabbling in this technology today.”

Monroy also noted that Open Service Mesh can sit alongside other solutions like Linkerd, for example.

A lot of pundits expected Google to also donate its Istio service mesh to the CNCF. That move didn’t materialize. “It’s funny. A lot of people are very focused on the governance aspect of this,” he said. “I think when people over-focus on that, you lose sight of how are customers doing with this technology. And the truth is that customers are not having a great time with Istio in the wild today. I think even folks who are deep in that community will acknowledge that and that’s really the reason why we’re not interested in contributing to that ecosystem at the moment.”

Datafold is solving the chaos of data engineering

It seemed so simple. A small schema issue in a database was wrecking a feature in the app, increasing latency and degrading the user experience. The resident data engineer pops in a fix to amend the schema, and everything seems fine — for now. Unbeknownst to them, that small fix completely clobbered all the dashboards used by the company’s leadership. Finance is down, ops is pissed, and the CEO — well, they don’t even know whether the company is online.

For data engineers, it’s not just a recurring nightmare — it’s a day-to-day reality. A decade plus into that whole “data is the new oil” claptrap, and we’re still managing data piecemeal and without proper systems and controls. Data lakes have become data oceans and data warehouses have become … well, whatever the massive version of a warehouse is called (a waremansion I guess). Data engineers bridge the gap between the messy world of real life and the precise nature of code, and they need much better tools to do their jobs.

As TechCrunch’s unofficial data engineer, I’ve personally struggled with many of these same problems. And so that’s what drew me into Datafold.

Datafold is a brand-new platform for managing the quality assurance of data. Much in the way that a software platform has QA and continuous integration tools to ensure that code functions as expected, Datafold integrates across data sources to ensure that changes in the schema of one table doesn’t knock out functionality somewhere else.

Founder Gleb Mezhanskiy knows these problems firsthand. He’s informed from his time at Lyft, where he was a data scientist and data engineer, and later transformed into a product manager “focused on the productivity of data professionals.” The idea was that as Lyft expanded, it needed much better pipelines and tooling around its data to remain competitive with Uber and others in its space.

His lessons from Lyft inform Datafold’s current focus. Mezhanskiy explained that the platform sits in the connections between all data sources and their outlets. There are two challenges to solve here. First, “data is changing, every day you get new data, and the shape of it can be very different either for business reasons or because your data sources can be broken.” And second, “the old code that is used by companies to transform this data is also changing very rapidly because companies are building new products, they are refactoring their features … a lot of errors can happen.”

In equation form: messy reality + chaos in data engineering = unhappy data end users.

With Datafold, changes made by data engineers in their extractions and transformations can be compared for unintentional changes. For instance, maybe a function that formerly returned an integer now returns a text string, an accidental mistake introduced by the engineer. Rather than wait until BI tools flop and a bunch of alerts come in from managers, Datafold will indicate that there is likely some sort of problem, and identify what happened.

The key efficiency here is that Datafold aggregates changes in datasets — even datasets with billions of entries — into summaries so that data engineers can understand even subtle flaws. The goal is that even if an error transpires in 0.1% of cases, Datafold will be able to identify that issue and also bring a summary of it to the data engineer for response.

Datafold is entering a market that is, quite frankly, as chaotic as the data being processed. It sits in the key middle layer of the data stack — it’s not the data lake or data warehouse for storing data, and it isn’t the end user BI tools like a Looker, Tableau or many others. Instead, it’s part of a number of tools available for data engineers to manage and monitor their data flows to ensure consistency and quality.

The startup is targeting companies with at least 20 people on their data team — that’s the sweet spot where a data team has enough scale and resources that they are going to be concerned with data quality.

Today Datafold is three people, and will be debuting officially at YC’s Demo Day later this month. Its ultimate dream is a world where data engineers never again have to get an overnight page to fix a data quality issue. If you’ve been there, you know precisely why such a product is valuable.