Personal blog of Yzmir Ramirez

The digital transformation currently sweeping society has likely reached your favorite local restaurant.

Since 2013, Boston-based Toast has offered bars and eateries a software platform that lets them manage orders, payments and deliveries.

Over the last year, its customers have processed more than $38 billion in gross payment volume, so Alex Wilhelm analyzed the company’s S-1 for The Exchange with great interest.

“Toast was last valued at just under $5 billion when it last raised, per Crunchbase data,” he writes. “And folks are saying that it could be worth $20 billion in its debut. Does that square with the numbers?”

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Airbnb, DoorDash and Coinbase each debuted at past Y Combinator Demo Days; as of this writing, they employ a combined 10,000 people.

Today and tomorrow, TechCrunch reporters will cover the proceedings at YC’s Summer 20201 Demo Day. In addition to writing up founder pitches, they’ll also rank their favorites.

Even remotely, I can feel a palpable sense of excitement radiating from our team — anything can happen at YC Demo Day, so sign up for Extra Crunch to follow the action.

Thanks very much for reading; I hope you have an excellent week.

Walter Thompson
Senior Editor, TechCrunch
@yourprotagonist

How Amazon EC2 grew from a notion into a foundational element of cloud computing

In August 2006, AWS activated its EC2 cloud-based virtual computer, a milestone in the cloud infrastructure giant’s development.

“You really can’t overstate what Amazon was able to accomplish,” writes enterprise reporter Ron Miller.

In the 15 years since, EC2 has enabled clients of any size to test and run their own applications on AWS’ virtual machines.

To learn more about a fundamental technological shift that “would help fuel a whole generation of startups,” Ron interviewed EC2 VP Dave Brown, who built and led the Amazon EC2 Frontend team.

3 ways to become a better manager in the work-from-home era

Most managers agree that OKRs foster transparency and accountability, but running a team effectively has different challenges when workers are attending all-hands meetings from their kitchen tables.

Instead of just discussing key metrics before board meetings or performance reviews, make them part of the day-to-day culture, recommends Jeremy Epstein, Gtmhub’s CMO.

“Strengthen your team by creating authentic workplace transparency using numbers as a universal language and providing meaning behind your team’s work.”

The pre-pitch: 7 ways to build relationships with VCs

Many founders must overcome a few emotional hurdles before they’re comfortable pitching a potential investor face-to-face.

To alleviate that pressure, Unicorn Capital founder Evan Fisher recommends that entrepreneurs use pre-pitch meetings to build and strengthen relationships before asking for a check:

“This is the ‘we actually aren’t looking for money; we just want to be friends for now’ pitch that gets you on an investor’s radar so that when it’s time to raise your next round, they’ll be far more likely to answer the phone because they actually know who you are.”

Pre-pitches are good for more than curing the jitters: These conversations help founders get a better sense of how VCs think and sometimes lead to serendipitous outcomes.

“Investors are opportunists by necessity,” says Fisher, “so if they like the cut of your business’s jib, you never know — the FOMO might start kicking hard.”

Lessons from COVID: Flexible funding is a must for alternative lenders

FischerJordan’s Deeba Goyal and Archita Bhandari break down the pandemic’s impact on alternative lenders, specifically what they had to do to survive the crisis, taking a look at smaller lenders including Credibly, Kabbage, Kapitus and BlueVine.

“Only those who were able to find a way through the complexities of their existing capital sources were able to maintain their performance, and the rest were left to perish or find new funding avenues,” they write.

Inside Freshworks’ IPO filing

Customer engagement software company Freshworks’ S-1 filing depicts a company that’s experiencing accelerating revenue growth, “a great sign for the health of its business,” reports Alex Wilhelm in this morning’s The Exchange.

“Most companies see their growth rates decline as they scale, as larger denominators make growth in percentage terms more difficult.”

Studying the company’s SEC filing, he found that “Freshworks isn’t a company where we need to cut it lots of slack, as we might with an adjusted EBITDA number. It is going public ready for Big Kid metrics.”

Databricks this morning confirmed earlier reports that it was raising new capital at a higher valuation. The data- and AI-focused company has secured a $1.6 billion round at a $38 billion valuation, it said. Bloomberg first reported last week that Databricks was pursuing new capital at that price.

The Series H was led by Counterpoint Global, a Morgan Stanley fund. Other new investors included Baillie Gifford, UC Investments and ClearBridge. A grip of prior investors also kicked in cash to the round.

The new funding brings Databricks’ total private funding raised to $3.5 billion. Notably, its latest raise comes just seven months after the late-stage startup raised $1 billion on a $28 billion valuation. Its new valuation represents paper value creation in excess of $1 billion per month.

The company, which makes open source and commercial products for processing structured and unstructured data in one location, views its market as a new technology category. Databricks calls the technology a data “lakehouse,” a mashup of data lake and data warehouse.

Databricks CEO and co-founder Ali Ghodsi believes that its new capital will help his company secure market leadership.

For context, since the 1980s, large companies have stored massive amounts of structured data in data warehouses. More recently, companies like Snowflake and Databricks have provided a similar solution for unstructured data called a data lake.

In Ghodsi’s view, combining structured and unstructured data in a single place with the ability for customers to execute data science and business-intelligence work without moving the underlying data is a critical change in the larger data market.

“[Data lakehouses are] a new category, and we think there’s going to be lots of vendors in this data category. So it’s a land grab. We want to quickly race to build it and complete the picture,” he said in an interview with TechCrunch.

Ghodsi also pointed out that he is going up against well-capitalized competitors and that he wants the funds to compete hard with them.

“And you know, it’s not like we’re up against some tiny startups that are getting seed funding to build this. It’s all kinds of [large, established] vendors,” he said. That includes Snowflake, Amazon, Google and others who want to secure a piece of the new market category that Databricks sees emerging.

The company’s performance indicates that it’s onto something.

Growth

Databricks has reached the $600 million annual recurring revenue (ARR) milestone, it disclosed as part of its funding announcement. It closed 2020 at $425 million ARR, to better illustrate how quickly it is growing at scale.

Per the company, its new ARR figure represents 75% growth, measured on a year-over-year basis.

That’s quick for a company of its size; per the Bessemer Cloud Index, top-quartile public software companies are growing at around 44% year over year. Those companies are worth around 22x their forward revenues.

At its new valuation, Databricks is worth 63x its current ARR. So Databricks isn’t cheap, but at its current pace should be able to grow to a size that makes its most recent private valuation easily tenable when it does go public, provided that it doesn’t set a new, higher bar for its future performance by raising again before going public.

Ghodsi declined to share timing around a possible IPO, and it isn’t clear whether the company will pursue a traditional IPO or if it will continue to raise private funds so that it can direct list when it chooses to float. Regardless, Databricks is now sufficiently valuable that it can only exit to one of a handful of mega-cap technology giants or go public.

Why hasn’t the company gone public? Ghodsi is enjoying a rare position in the startup market: He has access to unlimited capital. Databricks had to open another $100 million in its latest round, which was originally set to close at just $1.5 billion. It doesn’t lack for investor interest, allowing its CEO to bring aboard the sort of shareholder he wants for his company’s post-IPO life — while enjoying limited dilution.

This also enables him to hire aggressively, possibly buy some smaller companies to fill in holes in Databricks’ product roadmap, and grow outside of the glare of Wall Street expectations from a position of capital advantage. It’s the startup equivalent of having one’s cake and eating it too.

But staying private longer isn’t without risks. If the larger market for software companies was rapidly devalued, Databricks could find itself too expensive to go public at its final private valuation. However, given the long bull market that we’ve seen in recent years for software shares, and the confidence Ghodsi has in his potential market, that doesn’t seem likely.

There’s still much about Databricks’ financial position that we don’t yet know — its gross margin profile, for example. TechCrunch is also incredibly curious what all its fundraising and ensuing spending have done to near-term Databricks operating cash flow results, as well as how long its gross-margin adjusted CAC payback has evolved since the onset of COVID-19. If we ever get an S-1, we might find out.

For now, winsome private markets are giving Ghodsi and crew space to operate an effectively public company without the annoyances that come with actually being public. Want the same thing for your company? Easy: Just reach $600 million ARR while growing 75% year over year.

Percona Monitoring and Management (PMM) has dashboards that cover a lot of ground, yet PMM Superpowers come from the fact you do not need to stick to dashboards that are included with the product! You also can easily install additional dashboards provided by the Community, as well as implement your own.

In this blog post, we will cover some of the additional dashboards which I find particularly helpful.

Node Processes Dashboard

Get insights into the processes on the system to better understand resource usage by your database server vs other stuff on the system.   Unexpected resource hog processes are a quite common cause of downtime and performance issues.  More information in the Understanding Processes on your Linux Host blog post.

MySQL Memory Usage Details

Ever wondered where MySQL memory usage comes from? This dashboard can shed a light on this dark place, showing the top global memory consumers as well as what users and client hosts contribute to memory usage.  More details in the Understanding MySQL Memory Usage with Performance Schema blog post.

MySQL Query Performance Troubleshooting

Want to understand which queries are responsible for CPU, Disk, Memory, or Network Usage and get some other advanced MySQL Query Troubleshooting tools? Check out this dashboard.  Read more about it in the  MySQL Query Performance Troubleshooting blog post.

RED Method for MySQL Dashboard

Want to apply the RED (Rate-Errors-Duration)  method to MySQL?  Check out this dashboard, and check out RED Method for MySQL Performance Analyses for more details.

OK, so let’s say you’re convinced and want to get those dashboards into your PMM install but manual installation does not excite you.  Here is how you can use custom dashboard provisioning  to install all of them:

curl -LJOs https://github.com/Percona-Lab/pmm-dashboards/raw/main/misc/import-dashboard-grafana-cloud.sh --output import-dashboard-grafana-cloud.sh
curl -LJOs https://github.com/Percona-Lab/pmm-dashboards/raw/main/misc/cleanup-dash.py --output cleanup-dash.py

chmod a+x import-dashboard-grafana-cloud.sh
chmod a+x cleanup-dash.py

./import-dashboard-grafana-cloud.sh -s <PMM_SERVER_IP> -u admin:<ADMIN_PASSWORD> -f Custom -d 13266 -d 12630 -d 12470 -d 14239

Note:  Node Processes and MySQL Memory Usage Details dashboards also require additional configuration on the client-side. Check out the blog posts mentioned for specifics.

Enjoy!

Percona Monitoring and Management is a best-of-breed open source database monitoring solution. It helps you reduce complexity, optimize performance, and improve the security of your business-critical database environments, no matter where they are located or deployed.

Download Percona Monitoring and Management Today

Software billing startup Octane announced Tuesday that it raised $2 million on a post-money valuation of $10 million to advance its pay-as-you-go billing software.

Akash Khanolkar and his co-founders met a decade ago at Carnegie Mellon University and since then went off in different directions. In Khanolkar’s case, he ran a cloud consulting business and saw how fast companies like Datadog and Snowflake were coming to market and dealing with Amazon Web Services.

He found that the commonality in all of those fast-growing companies was billing software using a pay-as-you-go business model versus the traditional flat-rate plans, Khanolkar told TechCrunch.

However, he explained that monitoring consumption means that billing becomes complicated: companies now have to track how customers are using the software per second in order to bill correctly each month.

Seeing the shift toward consumption-based billing, the co-founders came back together in June 2020 to create Octane, a metered billing system that helps vendors create a plan, monitor usage and charge in a similar way to Snowflake and AWS, Khanolkar said.

“We are API-driven, and you as a vendor will send us usage data, and on our end, we store it and then do real-time aggregations so at the end of the month, you can accordingly bill customers,” Khanolkar said. “We have seen contention between engineering and product. Engineers are there to create core plans, so we built a no-code experience for product teams to be able to create new price plans and then perform changes, like adding coupons.”

Within the global cloud billing market, which is expected to reach $6.5 billion by 2025, there are a set of Octane competitors, like Chargebee and Zuora, that Khanolkar said are tackling the subscription management side and succeeding in the past several years. Now there is a usage and consumption-based world coming and a whole new set of software businesses, like Octane, coming in to succeed there.

The new round of funding was led by Basis Set Ventures and included Dropbox co-founder Arash Ferdowsi, Github CTO Jason Warner, Fortress CTO Assunta Gaglione, Scale AI CRO Chetan Chaudhary, former Twilio executive Evan Cummack, Esteban Reyes, Abstraction Capital and Script Capital.

“With the rise of product-led growth and usage-based pricing models, usage-based billing is a critical and foundational piece of infrastructure that has been simply missing,” said Chang Xu, partner at Basis Set Ventures, via email. “At the same time, it’s something that every department cares about as it’s your revenue. Many later-stage companies we talk to that have built this in-house talk about the ongoing maintenance costs and wishes that there is a vendor they can outsource it to.”

We are super impressed with the Octane team with their dedication to building a best-in-class and robust usage-based billing solution. They’ve validated this opportunity by talking to lots of engineering teams so they can solve for all the edge cases, which is important in something as mission critical as billing. We are convinced that Octane will become an inevitable part of the tech infrastructure.”

The new funding will go primarily toward hiring engineers, as well as product, marketing and sales staff. Octane currently has seven employees, and Khanolkar expects to be around 10 by the end of the year.

The company is working with a large range of companies, primarily focused on infrastructure and the depth gauge industries. Octane is also seeing some unique use cases emerge, like a construction company using the usage meter to track the hours an employee works and companies in electric charging using the meter for those purposes.

“We didn’t envision construction guys using it, but in theory, it could be used by any company that tracks time — even legal,” Khanolkar added.

He declined to speak about the company’s revenue, but did say it now had two to three years of runway.

Up next, the company plans to roll out new features like price experimentation based on usage to help customers better make decisions on how to price their software, another problem Khanolkar sees happening. It will build ways that customers can try different plans against usage data to validate which one works the best.

“We are still in the early innings of consumption-based models, but we see more end users opting to go with an enterprise that wants to let them try out the software and then pay as they go,” he added.

Walnut raised $15 million in Series A funding, led by Eight Roads Ventures, to continue developing its sales experience platform.

Founders Yoav Vilner and Danni Friedland started the company in July 2020. Vilner told TechCrunch that while at a previous company, he was building a category called technology marketing in Israel. He realized that company sales people often ran into problems when it was time to demonstrate their product — the product would break, or they would have to ask another department to open something or add a feature, none of which happened instantaneously, Vilner added.

He and Friedland’s answer to that problem is a no-code platform for teams to create customized product demonstrations quickly, be able to integrate them into their sales and marketing processes and then generate insights from the demos.

“We let the sales and marketing teams replicate the SaaS product in our cloud environment, which is disconnected from the back end,” Vilner explained. “They can create a storyline to fit their customer and the demonstration, and then following the demo, sales leaders can get insight on what was good or bad. It encourages the sharing of knowledge and what story worked best for which kind of company.”

The company’s latest round gives it $21 million raised to date, and follows a $6 million seed round that included NFX, A Capital, Liquid2 Ventures and Graph Ventures, Vilner said.

Walnut serves over 60 business-to-business clients, including Adobe, NetApp, Varonis and People AI. In addition to Tel Aviv, the company has offices in New York and London.

Vilner intends to use the new funding to grow the team across the U.S, Europe and Israel and continue developing its technology and platform, including tools to embed demos into a website for product-led growth. He also expects to double the team of 25 over the next year.

Eyal Rabinovich, an investor at Eight Roads Ventures, said his brother is a Walnut customer, and the company fits with one of the firm’s theses around broad vertically integrated brands in SaaS and deep technology.

Rabinovich was tracking the sales enablement space for a while and said many companies claim to provide something unique, but it is usually workflow and processes. In Walnut’s case, it is solving something at the core of sales.

“They make everything measurable, and the ‘holy grail’ is conversion, and even just 1% conversion could mean millions of dollars,” he added. “Every company we spoke to wanted to use this product. Customers were telling us they closed the sales cycle within two weeks.”

 

This blog was originally published in August of 2021 and updated in November of 2023.

Following the series of blogs written with the intention to describe basic operations matching Docker and open source databases, in this article, I will demonstrate how to proceed with installing MongoDB with Docker.

The first one, written by Peter Zaitsev, was Installing MySQL with Docker.

Before proceeding, it is important to double warn by quoting Peter’s article:

“The following instructions are designed to get a test instance running quickly and easily; you do not want to use these for production deployments”. 

Also, a full description of Docker is not the objective of this article, though I assume prior knowledge of Docker, and also you that already have it installed and configured to move on.

Docker quickly deploys standalone MongoDB containers. If you are looking for fast deployments of both replica sets and shards, I suggest looking at the mlaunch tool.

Peter mentioned, in his article, how MySQL has two different “official” repositories, and with MongoDB, it’s the same: MongoDB has one repository maintained by MongoDB and another maintained by Docker. I wrote this article based on the Docker-maintained repository.

What are MongoDB Docker Containers?

Docker containers are small, executable, standalone packages that come with all the components—code, runtime, libraries, and system tools—necessary to run a piece of software. They provide a reliable and effective method for developing, deploying, and executing applications in a range of settings, from development to production.

When discussing MongoDB containers, we are talking about a Docker container holding MongoDB together with its particular version, customizations, and dependencies. Whether it is a production server, a test environment, or a developer’s workstation, this encapsulation makes it easier to deploy MongoDB instances in a variety of scenarios, making it more portable and scalable.

Installing the Latest Version of MongoDB

The following snippet is one example of how to initiate a container of the latest MongoDB version from the Docker repository. 

docker run --name mongodb_dockerhub 
                -e MONGO_INITDB_ROOT_USERNAME=admin 
                -e MONGO_INITDB_ROOT_PASSWORD=secret 
                -d mongo:latest

Now, if you want to check the container status right after creating it:

docker ps

CONTAINER ID        IMAGE COMMAND                  CREATED STATUS PORTS               NAMES
fdef23c0f32a        mongo:latest "docker-entrypoint..."   4 seconds ago Up 4 seconds 27017/tcp           mongodb_dockerhub

Connecting to MongoDB Server Docker Container

Having the container installed up and running, you will notice that no extra step or dependency installation was previously required, apart from the docker binaries. Now, it is time to access the container MongoDB shell and issue a basic command like “show dbs”. 

docker exec -it mongodb_dockerhub mongo -u admin -p secret
MongoDB shell version v4.2.5
connecting to: mongodb://127.0.0.1:27017/?compressors=disabled&gssapiServiceName=mongodb
Implicit session: session { "id" : UUID("89c3fb4a-a8ed-4724-8363-09d65024e458") }
MongoDB server version: 4.2.5
Welcome to the MongoDB shell.

> show dbs
admin   0.000GB
config  0.000GB
local   0.000GB

> exit
bye

It is also possible to connect to the containerized MongoDB using a host mongo shell. On the docker ps output, the container id has a field that informs its port mapping, and then it is a simple connection using that port.

In the below example, we connected to the mongodb_dockerhub36. It’s up and running locally on port 27017  but mapped to the host 27018 port:

docker ps

CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS              PORTS                      NAMES
60ffc759fab9        mongo:3.6           "docker-entrypoint..."   20 seconds ago      Up 19 seconds       0.0.0.0:27018->27017/tcp   mongodb_dockerhub36

Hence, the mongo shell connection string will be executed against the external IP and port 27018

mongo admin -u admin --host 172.16.0.10 --port 27018 -psecret

Managing MongoDB Server in Docker Container

The following commands will demonstrate basic management operations when managing a MongoDB container. 

• Starting the container and checking the Status

docker start mongodb_dockerhub

docker ps

CONTAINER ID        IMAGE COMMAND                  CREATED STATUS PORTS               NAMES
fdef23c0f32a        mongo:latest "docker-entrypoint..."   47 minutes ago Up 2 seconds 27017/tcp           mongodb_dockerhub

• Stopping the container and checking the Status

docker stop mongodb_dockerhub

docker ps

CONTAINER ID        IMAGE COMMAND

• Taking a look at the MongoDB log entries

docker logs mongodb_dockerhub
...
about to fork child process, waiting until server is ready for connections.
forked process: 25
2020-04-10T14:04:49.808+0000 I  CONTROL [main] ***** SERVER RESTARTED *****
2020-04-10T14:04:49.812+0000 I  CONTROL [main] Automatically disabling TLS 1.0, to f
...

Passing Command Line Options to MongoDB Server in Docker Container

It is also possible to define the instance’s parameters when launching the MongoDB container. In the example below, I will show how to set the WiredTiger cache.

docker run --name mongodb_dockerhub 
                -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=secret 
                -d mongo:latest --wiredTigerCacheSizeGB 1.0

Running Different MongoDB Server Versions in Docker

Another possibility is getting two MongoDB containers running in parallel but under different versions. The below snippet will describe how to build that scenario

• Launching a 4.0 container

docker run --name mongodb_dockerhub40 
 -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=secret 
 -d mongo:4.0

• Launching a 3.6 container

docker run --name mongodb_dockerhub36 
 -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=secret 
 -d mongo:3.6

• Checking the container’s status

docker ps

CONTAINER ID        IMAGE COMMAND                  CREATED STATUS PORTS               NAMES
e9f480497f2d        mongo:3.6 "docker-entrypoint..."   32 seconds ago Up 32 seconds 27017/tcp           mongodb_dockerhub36
3a799f8a907c        mongo:4.0 "docker-entrypoint..."   41 seconds ago Up 41 seconds 27017/tcp           mongodb_dockerhub40

If for some reason you need both containers running simultaneously and access them externally, then use different port mappings. In the below example, both MongoDB’s containers are deployed on the local 27017 port, nevertheless, I am setting different external port maps for each one.

• MongoDB 4.0 mapping the port 27017

docker run --name mongodb_dockerhub40 
 -p 27017:27017 
 -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=secret 
 -d mongo:4.0

• MongoDB 3.6 mapping the port 27018

docker run --name mongodb_dockerhub36 
 -p 27018:27017 
 -e MONGO_INITDB_ROOT_USERNAME=admin -e MONGO_INITDB_ROOT_PASSWORD=secret 
 -d mongo:3.6

• Checking both Container’s status

docker ps

CONTAINER ID        IMAGE COMMAND                  CREATED STATUS PORTS                      NAMES
78a79e5606ae        mongo:4.0 "docker-entrypoint..."   3 seconds ago Up 2 seconds 0.0.0.0:27017->27017/tcp   mongodb_dockerhub40
60ffc759fab9        mongo:3.6 "docker-entrypoint..."   20 seconds ago Up 19 seconds 0.0.0.0:27018->27017/tcp   mongodb_dockerhub36

There are a lot of extra details on Docker’s MongoDB Hub page and you will find more options to use on your MongoDB Docker deployment. Enjoy it!

Advantages of Using Docker for MongoDB

MongoDB Docker containers offer a more efficient, consistent, and scalable way to run MongoDB instances, and they offer several advantages over typical MongoDB installations in the following ways:

Isolation and portability: Because MongoDB containers have their own file system, libraries, and network configurations, they are isolated from the host system. Because of this isolation, the MongoDB instance is guaranteed to operate consistently no matter what host system is used. In conventional setups, achieving this degree of isolation is difficult.

Uniformity throughout environments: MongoDB instances are housed in a uniform environment thanks to MongoDB containers. This consistency minimizes the “it works on my machine” issue by guaranteeing that what functions on a developer’s laptop will act similarly in a staging or production environment.

Dependency management: MongoDB containers bundle all required dependencies, removing the possibility of conflicts with the host system’s other programs or libraries. Managing and resolving dependencies in a typical MongoDB installation can be difficult and error-prone.

Scalability and resource management: MongoDB containers and other containers are very scalable. Multiple MongoDB containers can be quickly spun up to divide workloads, establish replica sets, and sharded clusters. A conventional MongoDB installation’s scaling can be more difficult.

Easy to use: Setting up MongoDB containers is a simple procedure, as you can specify the desired state of your MongoDB containers using Docker Compose or Kubernetes, and then let the orchestration tools take care of the deployment.

Troubleshooting and Common Issues for MongoDB Docker Installation

Although deploying MongoDB in a Docker container has many advantages, there are occasionally typical challenges. Here, we’ll explore some of these issues and provide troubleshooting guidance.

MongoDB container fails to start: If your MongoDB container doesn’t start, check that the Docker command you are using to launch it is correct. Verify image names, ports, and environment variables one more time and examine container logs.

Connection issues: Make sure your application is connecting to the correct hostname and port if you are experiencing issues with MongoDB connections in Docker. Verify network settings to ensure appropriate communication, as well as the accuracy of the credentials before utilizing authentication.

Data persistence: By configuring data persistence, you can prevent data loss in the case that a MongoDB container is stopped or removed. Use Docker volumes or host bind mounts to safeguard data.

Resource allocation: Optimize the performance of MongoDB containers by modifying resource distribution. Adjust Docker’s CPU and RAM limits to improve slow performance.

And if you are in need of some assistance from fellow MongoDB users, there are lots of resources and communities you can participate in:

• Look through the MongoDB community forums for advice, solutions, and group problem-solving with experienced users.
• The Docker community forum is a good place to find answers on containerization-related issues and is a vital resource for assistance with Docker-related difficulties.
• Look through the issues section of the MongoDB GitHub repository to find and discuss any MongoDB Docker image problems.
• The Percona Community Forum is where users, developers, and database professionals gather to discuss and share information about database management solutions.

Best Practices for Managing MongoDB Containers

Maintaining your database system’s scalability, security, and performance requires effective MongoDB container administration. In order to optimize your MongoDB deployment, it’s essential that you adhere to best practices in a number of vital areas.

Security considerations: Securing your MongoDB containers is a top priority. To protect your data, put authentication and access control systems in place. Strong security features are provided by MongoDB, including authentication, encryption, and role-based access control (RBAC). Set parameters to prevent unwanted access and safeguard private data, and to protect yourself against known vulnerabilities, keep your MongoDB container images and software updated with the newest security updates.

Container orchestration options: To handle MongoDB containers at scale, think about utilizing container orchestration systems like Docker Swarm or Kubernetes. These solutions provide high availability and resource optimization while making deployment, scaling, and load balancing simpler. Container orchestration is especially helpful when dealing with a large number of containers, as it automates routine tasks to maintain system integrity.

Regular maintenance and updates: To keep your MongoDB containers operating properly, make sure you regularly update the underlying container image as well as the database software because performance enhancements, security patches, and bug fixes are frequently included in updates. Monitoring your containers for indications of resource limitations or performance problems is another aspect of routine maintenance, and to make sure your MongoDB containers can effectively manage a range of workloads, set up warnings and automated scaling.

Run MongoDB Your Way Percona

Percona offers source-available, enterprise-grade software and services to run MongoDB at peak performance, on any infrastructure. No licensing fees, expensive support contracts, or vendor lock-in.

 

Learn more about Percona for MongoDB

 

FAQs

Is it advisable to deploy MongoDB within a Docker container?

In some cases, it can be advisable to use a Docker container to deploy MongoDB, especially if you are running it on-premises. Docker containers are a good option for MongoDB installations because of their benefits, which include isolation, portability, and scalability. Before making a choice, it is crucial to consider the requirements and the particular use case into account.

Can I run multiple MongoDB containers on the same host using Docker?

Yes, you can use Docker to run multiple MongoDB containers on the same host. You can create numerous isolated MongoDB instances for different applications or workloads because each container runs independently.

As artificial intelligence continues to weave its way into more enterprise applications, a startup that has built a platform to help businesses, especially non-tech organizations, build more customized AI decision-making tools for themselves has picked up some significant growth funding. Peak AI, a startup out of Manchester, England, that has built a “decision intelligence” platform, has raised $75 million, money that it will be using to continue building out its platform, expand into new markets and hire some 200 new people in the coming quarters.

The Series C is bringing a very big name investor on board. It is being led by SoftBank Vision Fund 2, with previous backers Oxx, MMC Ventures, Praetura Ventures and Arete also participating. That group participated in Peak’s Series B of $21 million, which only closed in February of this year. The company has now raised $119 million; it is not disclosing its valuation.

(This latest funding round was rumored last week, although it was not confirmed at the time and the total amount was not accurate.)

Richard Potter, Peak’s CEO, said the rapid follow-on in funding was based on inbound interest, in part because of how the company has been doing.

Peak’s so-called Decision Intelligence platform is used by retailers, brands, manufacturers and others to help monitor stock levels and build personalized customer experiences, as well as other processes that can stand to have some degree of automation to work more efficiently, but also require sophistication to be able to measure different factors against each other to provide more intelligent insights. Its current customer list includes the likes of Nike, Pepsico, KFC, Molson Coors, Marshalls, Asos and Speedy, and in the last 12 months revenues have more than doubled.

The opportunity that Peak is addressing goes a little like this: AI has become a cornerstone of many of the most advanced IT applications and business processes of our time, but if you are an organization — and specifically one not built around technology — your access to AI and how you might use it will come by way of applications built by others, not necessarily tailored to you, and the costs of building more tailored solutions can often be prohibitively high. Peak claims that those using its tools have seen revenues on average rise 5%, return on ad spend double, supply chain costs reduce by 5% and inventory holdings (a big cost for companies) reduce by 12%.

Peak’s platform, I should point out, is not exactly a “no-code” approach to solving that problem — not yet at least: It’s aimed at data scientists and engineers at those organizations so that they can easily identify different processes in their operations where they might benefit from AI tools, and to build those out with relatively little heavy lifting.

There have also been different market factors that have played a role. COVID-19, for example, and the boost that we have seen both in increasing “digital transformation” in businesses and making e-commerce processes more efficient to cater to rising consumer demand and more strained supply chains have all led to businesses being more open and keen to invest in more tools to improve their automation intelligently.

This, combined with Peak AI’s growing revenues, is part of what interested SoftBank. The investor has been long on AI for a while; but it also has been building out a section of its investment portfolio to provide strategic services to the kinds of businesses in which it invests.

Those include e-commerce and other consumer-facing businesses, which make up one of the main segments of Peak’s customer base.

Notably, one of its recent investments specifically in that space was made earlier this year, also in Manchester, when it took a $730 million stake (with potentially $1.6 billion more down the line) in The Hut Group, which builds software for and runs D2C businesses.

“In Peak we have a partner with a shared vision that the future enterprise will run on a centralized AI software platform capable of optimizing entire value chains,” Max Ohrstrand, senior investor for SoftBank Investment Advisers, said in a statement. “To realize this a new breed of platform is needed and we’re hugely impressed with what Richard and the excellent team have built at Peak. We’re delighted to be supporting them on their way to becoming the category-defining, global leader in Decision Intelligence.”

It’s not clear that SoftBank’s two Manchester interests will be working together, but it’s an interesting synergy if they do, and most of all highlights one of the firm’s areas of interest.

Longer term, it will be interesting to see how and if Peak evolves to extend its platform to a wider set of users at the organizations that are already its customers.

Potter said he believes that “those with technical predispositions” will be the most likely users of its products in the near and medium term. You might assume that would cut out, for example, marketing managers, although the general trend in a lot of software tools has precisely been to build versions of the same tools used by data scientists for these less technical people to engage in the process of building what it is that they want to use.

“I do think it’s important to democratize the ability to stream data pipelines, and to be able to optimize those to work in applications,” Potter added.

Independent restaurants don’t typically have the luxury to create their own online food ordering and delivery capabilities or negotiate for lower rates from legacy ordering platforms like the large restaurant chains do.

Here’s where Owner.com comes in. The Palo Alto-based company provides a free online ordering, delivery and marketing platform for independent restaurants that puts them on similar playing fields with the big guys. And unlike the legacy food delivery services, Owner.com restaurants own their customer data and can automate marketing campaigns.

Adam Guild is the company’s 21-year-old co-founder and CEO, a high school dropout and a Thiel Fellow, who originally started by assisting his mother’s dog grooming business that was having difficulties attracting customers. After stepping in with some online marketing methods, her business grew, and is now looking to expand into multiple locations. Guild then wanted to work with a bigger group of people and stumbled across restaurants while helping some clients create online landing pages.

With consumer demand shifting to primarily online ordering and delivery over the past 18 months, online ordering revenue is expected to double from $248 billion in 2020 to $449 billion by 2025. Ordering platforms like Doordash, Uber Eats and Grubhub control 80% of orders and typically charge between 20% and 30% per order to restaurants and additional fees to consumers.

In contrast, Owner.com is free for restaurants and charges customers a 5% convenience fee when they order from the website. Guild explained that larger restaurant chains have the buying power to negotiate lower rates, while independent restaurants do not. With the inability to keep up, some 110,000 restaurants in the U.S. closed in 2020.

Guild initially bootstrapped his company, working with large restaurant chains, like P.F. Chang’s, drive in-store orders. Then the global pandemic hit. He ended up losing all of his revenue and had to let all of his employees go but one. To add to his bad luck, he was then rejected from Y Combinator and other accelerator programs.

“For the first three days, I was depressed,” Guild told TechCrunch. “I had spent two years building a company and now it was dead. In the same way we were disrupted, I began to think there was no better position to be in than a scrappy startup. I didn’t know what the next business would look like, so I started cold-calling restaurant owners, asking how I can be helpful and what type of technology they were looking for. Many of them told me that online ordering sucked, but if they didn’t solve it soon, they would go out of business.”

One pivot and a year later with co-founder Dean Bloembergen, Owner.com closed on $10.7 million in seed funding led by SaaStr Fund, with participation from Redpoint Ventures and Day One Ventures, as well as a group of individual investors including Naval Ravikant, CNBC’s The Profit host Marcus Lemonis, The Kitchen Restaurant Group’s Kimbal Musk, DoNotPay founder Joshua Browder, Figma founder Dylan Field, The Chainsmokers and independent restaurant owners and customers of Owner.com.

Jason Lemkin, founder of SaaStr Fund, said restaurant SaaS was a space in which his firm was interested in investing, but thought it was a bit boring — there were already quite a few vendors in the space, like Toast and Grubhub, and most were just technology solutions. However, when he heard that Owner.com was a break-out company from the monotony, he said he had to take a look.

“The ability to own the customer relationship is that ultimate differentiation,” Lemkin said. “Their ultimate goal is to provide a robust technology platform to increase margins, have people order more and come back often.”

Meanwhile, Guild intends to use the new funding to continue product development and add new features like landing pages, the ability to make reservations and native apps for white-label service.

Since the launch last year, the company has reached a seven-figure run-rate and over 105% monthly revenue retention across over 700 restaurant locations, Guild said. To date, Owner.com has transacted over $18 million and helped its restaurant customers avoid paying $3 million to online order platform fees annually.

“It’s all about empowering the 40% of the restaurant industry that is run by people who started off in entry-level positions, and over the years, worked their way up to own the ‘American Dream,’ ” he added.

 

Today we are talking about Media with Adam Globus-Hoenich and Sean Blommaert.

www.talkingdrupal.com/309

Topics

• John – Stung by a bee
• Chad – Obedience training
• Adam – Vacation in Canada – new tattoo idea
• Sean – New tattoos
• Nic – Cousin’s game
• Current state of media
• Biggest advantage of media
• Common use cases
• Editing experience improvements
• Biggest common mistake
• Media library
• Scoping
• Change since being in core
• Momentum recently
• Standard Profile
• Performance concerns

Resources

https://en.wikipedia.org/wiki/Great_Molasses_Flood Lily’s command list: https://docs.google.com/document/d/1HzdUMDOdj54Fy9snE6fsA0i0Py4DJZu7Np45… http://riskylab.com/warbits/ Media add on Modules https://www.drupal.org/project/entity_reference_override https://www.drupal.org/project/focal_point https://www.drupal.org/project/entity_media_usage Patchzilla https://www.drupal.org/node/2831274

Guests

Sean Blommaert – @seanBlommaert

Adam Globus-Hoenich – @PhenaProxima

Hosts

Nic Laflin – www.nLighteneddevelopment.com @nicxvan

John Picozzi – www.epam.com @johnpicozzi

Chad Hester – www.chadkhester.com @chadkhester

For more than a year now, Zoom has been on a mission to transform from an application into a platform. To that end it made three announcements last year: Zoom Apps development tools, the Zoom Apps marketplace and a $100 million development fund to invest in some of the more promising startups building tools on top of their platform. Today, at the closing bell, the company announced it has made its first round of investments.

Ross Mayfield, product lead for Zoom Apps and integrations, spoke to TechCrunch about the round of investments. “We’re in the process of creating this ecosystem. We felt it important, particularly to focus on the seed stage and A stage of partnering with entrepreneurs to create great things on this platform. And I think what you see in the first batch of more than a dozen investments is representative of something that’s going to be a significant ongoing undertaking,” he explained.

He said while they aren’t announcing exact investment amounts, they are writing checks for between $250,000 and $2.5 million. They are teaming with other investment partners, rather than leading the rounds, but that doesn’t mean they aren’t working with these startups using internal resources for advice and executive backing, beyond the money.

“Every one of these investments has an executive or senior sponsor within the company. So there’s another person inside that knows the lay of the land, can help them advance and spend more personal time with them,” Mayfield said.

The company is also running several Zoom chat channels for the startups receiving investments to learn from one another and the Zoom Apps team. “We have a shared chat channel between the startup and my team. We have a channel called Announcements and a channel called Help, and another one that the startups created called Community,” he said.

Every week they use these channels to hold a developer office hour, a business office hour (which Mayfield runs) and a community hour, where the startups can gather and talk amongst themselves about whatever they want.

Among the specific categories receiving funding are collaboration and productivity, community and charity, DE&I and PeopleOps, and gaming and entertainment. In the collaboration and productivity category, Warmly is a sales tool that provides background and information about each person participating in the meeting ahead of time, while allowing the meeting organizer to create customized Zoom backgrounds for each event.

Another is Fathom, which alleviates the need to take notes during a meeting, but it’s more than recording and transcription. “It gives you this really simple interface where you can just tag moments. And then, as a result you have this transcript of the video recording, and you can click on those tagged moments as highlights, and then share a clip of the meeting highlights to Salesforce, Slack and other tools,” Mayfield said.

Pledge enables individuals or organizations to request and collect donations inside a Zoom meeting instantly, and Canvas is a hiring and interview tool that helps companies build diverse teams with data that helps them set and meet DEI goals.

These and the other companies represent the first tranche of investments from this fund, and Mayfield says the company intends to continue looking for startups using the Zoom platform to build their startup or integrate with Zoom.

He says that every company starts as a feature, then becomes a product and then aspires to be a line of products. The trick is getting there.  The goal of the investment program and the entire set of Zoom Apps tools is about helping these companies take the first step.

“The art of being an entrepreneur is working with that risk in the absence of resources and pushing at the frontier of what you know.” Zoom is trying to be a role model, a mentor and an investor on that journey.