Transcript
Welcome to a special edition of the Strive podcast series. I'm your host, Chris Mirzwa. What's special about today? We're coming to you live from New York City at Shift 2025. And I am very lucky to be joined by two fantastic guests. First, Asif Dromi. Thank you for being here with Monday.com and Ben Herzberg, who is with Commvault and now part of our Solutions Marketing Group, but very importantly, former chief scientist of Satori. For those that are new, what is Strive all about? We talk about security, technology, resilience, everything IT in a virtual environment. But I got to tell you something, there's nothing virtual about Midtown Manhattan this week. This is the real deal, and we're here. Thank you for being with us. So what are we talking about today? We're going to talk about how Monday.com won a very large opportunity, and, of course, that always comes with unique challenges. In this case, they had to stand up a full new data room, and they had to do it with security and compliance in mind. And how they did that? With, of course, Satori, with Snowflake, with Terraforms, and goodness knows a number of other architectural tools. We're going to explore that and talk about lessons learned. So, Asif, if I can start. First off, thank you again for being here. You came a long way. You may have won the longest distance award coming from Israel, so congratulations on that. So basically, I come from Dubai, so it's two hours more. Oh, even further. You definitely win. We'll have a prize for you right after this. So, that said, can you kind of take us back to where all this started? A little bit about Monday.com and the opportunity and how this all evolved. Sure. So, at Monday, Monday is a special creature. We measure everything. Monday is a data-driven company from day one. And data for us is not an option. It's a must. And like each good story, it starts with a need. It's a big need that we need to support a new kind of data, data that is subject to GDPR compliance. And, okay, so we need to support GDPR. What does it mean? You know, it's a privacy policy. We need to support that the data will be at Europe and et cetera. But this was new for us. And there's a lot of challenges. We need to support, like as I said, that the data will be at Europe. But also we need to support that each employee at Monday will be able to access only the relevant data for him. And, of course, everything will be secure and managed. But this was like the big challenges for us. And that you do on every opportunity. It's core to the business, as you mentioned. Was there something unique about this opportunity that even raised the stakes higher that required sort of more thought along that line? Yes. So the data is like, as I said, new kind of data. But this data was super relevant for a lot of areas in the company. The analysts need this data. Developers need this data to understand if everything works well in the product. The leaderships need to understand what is the relevant KPIs, if they need to push some products more or maybe to go back with some products. And all the company really needs this data. And also they need it yesterday. So this was a big challenge. And we need to deliver a solution quickly as possible. So, all right, tight timeline and complexity, two magical ingredients that don't always mix together. So if I can, Ben, you have an opportunity to meet with lots of clients. Clearly you have a great relationship here with Asif and Monday.com. How often do you see this? How unique was this? So this is definitely not unique. We are working with many data-driven companies. Bigger, smaller than Monday.com. The common ground is that they have sensitive data that they're working with. And they need to actually work with this data. So if a company only needs, like 10 years ago, if a company only needed a special BI team to be able to crunch the data. And that's not a big challenge. But nowadays you want a company with thousands of employees. Thousands of employees need access to data. And you need to do it in a controlled way. So you need basically three things for that. You need visibility of where your sensitive data is. Who is able to do what with that data? Who is actually doing what with the data? And so on. And control. So you need to be able to set fine-grained access control over the data. So each person gets only what they need. And for the purpose they need that data for. And third, they need the proof, the evidence. So they need everything to be ready for compliance. Because compliance is a big driver here. So we see that a lot. And we are very happy to help companies like Monday.com and others win with data. Love it. Okay, so maybe you could stay in the Wayback Machine when this was happening. And how you balanced the overall company objective while maintaining security and compliance. How did you kind of balance both of those pieces? So our solution was to build a new data warehouse at Europe. A separate data warehouse. That, of course, supports all the GDPR needs. And we also need to manage all the permissions and access management. But it's not so easy. If you are a company with 5 employees, 10 employees, 15 employees. So snowflake management is really easy. So just do it. But in case that you work at Monday. And you have thousands of different customers. And you have multiple BI tools. It's much harder. It's a big mess. It's like you have one role that connects to another role that connects to another role. And you're not able to understand who has permission for what. If it's okay that this person has permissions to sensitive data. And you also don't have visibility to understand. Okay, one person queries from one tool or second tool or third tool. It's a big mess. So thank you, Ben, for giving us Satori. It makes our lives much easier. Now we're able to manage all the permissions and all the access management securely in one place. I'm able to also set up the things in an easy way. So this works really, really well for us. I had to do it with Satori. And, you know, it's not just to create new Snowflake and Satori. We build something beautiful with Terraform from day one. We build. Who is not familiar with Terraform? It's an easy way to manage infrastructure with code. So instead of, like, create Snowflake objects and create Satori objects, we just build our own model that merges, like, all the Satori objects and Snowflake objects in one model. And it works like magic. We're able to create new databases and all the relevant things in one place easily. It's scalable. And, like, if you have some requirement or you need to do a change, it's really simple. So for me, it was like magic. And appropriately wrapped in the compliance piece with the Terraform. So, Ben, that's a great point. Back to your previous question, or when we were chatting, you said it's almost geometrically expanding the complexity, right, around this. So how does that work? So I think that Asif touched on a good point in here, that having data security is not enough to have something that theoretically can do something. It's very important to make your data security in an operationalized way. So you can actually support it while you scale. And when you have more users and more use cases and more data and more AI applications and so on and so forth, it's very important to have a tool, a platform that can do that and support operationalizing data security. With Terraform, with REST API, with other concepts that we built into Satori, some of that we will discuss tomorrow in our session. So to that end, since one of the big things that we want folks to take away is best practices, maybe you could just highlight a couple of the key things that you would recommend folks do, like the Terraform wrapper, which sounds like it's working fantastically and scalable for you all. How often are you seeing people do that? Is that like a leading edge best practice right now? It's pretty often that companies, not only in Terraform, but they use Satori as a platform that's integrated with other tools, like Slack, like Jira, like ServiceNow, like many different tools depending on what they want to achieve. It was very important for us when we designed and built Satori to do so. If I had to give companies, I would say that from the companies looking at this podcast, or the people from companies looking at this podcast, about 100% of them have flagship AI projects, for example. And I would say if I had one tip to give, it's to think of it as a house of cards. You want to get AI ready fast, but for that you need other things in place. You need to cover the data governance in a good way and data management, so you need to make sure you have quality, secure data with proper access control, with proper visibility, and then you will be much quicker when you have those flagship projects around AI analytics and so on. It's like a crawl, walk, run, but you need to make sure that you're doing the basics in a good way. Yeah, you've got to build the foundation first. Ben, remember me, we talked about how we solve the problem and the solution, but I also want to add that we do it in less than two weeks. It was like everyone was shocked. We were able to give the business the ability to keep forward. We provided the leadership, the relevant KPIs, the data, the developers, the data, and I think this is one of the main things that with Terraform and Satori, we were able to provide a good solution really, really fast. I have to ask, as we wrap up, just like Ben, fantastic on what is state of mind and how to build these repeatable and secure. What advice would you give? There's got to be somebody there who's in a similar project, in a similar challenge. What would be a couple pieces of advice you'd give? I think if you are a data engineer and you need to build a new infrastructure, don't rush to create new databases and new roles and just flow with the infrastructures. It will be much worse to handle it later. I think that my advice is think good about your needs and what is the solution that you need to provide and build it from scratch, organize as possible. Organize as possible, do it right, without mistakes, and I think your life will be much easier. Fantastic, and congratulations on the two weeks. There's a shocking number, I'm sure, if people are listening, they're writing, going, did you really say two weeks? Less than two weeks. I don't have to say five days. That's very impressive. I want to say first, Asif, thank you for coming. Thank you for your business, and thank you for the trust in Commvault. I mean, that means everything to us, so thank you. And Ben, thank you for being such a great partner with Satori and now, of course, all in the family. And being the chief scientist, you're probably going to have a number of people after this picking your brain, so get ready for a huge LinkedIn spike. I hope you're ready for that. So you too, Asif, get ready. You may need more storage on LinkedIn. So that said, again, thank you to my guests. Thank you to everybody who's tuned in for this STRIVE podcast, the special live edition. And I think I'd like to close by saying this. When you listen to Asif and his story and the timeline they were able to execute in, while not everything is built the same and not everybody's challenge is the same, I would encourage you to go over our brand new readyverse.com site. We have just launched that. It has an enormous amount of information, and it's being refreshed constantly. We're focused on providing the community, you, with the latest information on resilience and looking at attack vectors and making sure we have the best people focused on the best articles, videos, and white papers for you to pursue your own resilience. So, gentlemen, thank you, and thank you for joining us today.
