Today’s enterprise organizations are using some form of multi-cloud infrastructure, and the numbers don’t lie. According to Flexera’s 2020 State of the Cloud report, an average of 2.2 public clouds are being used per enterprise company. And in a different report from the Everest Group, 58% of enterprise workloads are on hybrid or private cloud. The sheer increase in multi-cloud usage illustrates it’s growing popularity across enterprises.

I was really stoked to deliver a session at Microsoft Ignite with my long-time friend and fellow Head Geek™, Tom LaRock, on the topic of migrating an on-premises SQL Server database to the Azure cloud. You can watch the session on demand here. In addition, Microsoft MVP and SQL Server expert David Klee provides an excellent recap on each of the major elements Tom and I discussed.

To many businesses, the pace of innovation and speed to market has been hindered by the legacy infrastructure. This is mainly due to the closed structures and inflexible old-school architectural formats that they follow. The decades-old infrastructure hesitates to scale up with the growing business demands and realize advanced cloud-based technologies.

I believe that the evolution to hybrid cloud is inevitable. Not because it’s grabbing headlines, but because it mirrors the industry’s history of new technology adoption. Take the evolution of virtualization, for example. Going back 20 years give or take, virtual machines popularized by VMware, KVM, and Hyper-V started to gain traction.

SQL is great, but sometimes you may need something else. By and large, the prevalent type of data that data engineers deal with on a regular basis is relational. Tables in a data warehouse, transactional data in Online Transactional Processing (OLTP) databases — they can all be queried and accessed using SQL. But does it mean that NoSQL is irrelevant for data engineering?

Chances are if you’re reading this, you are (or are thinking about) moving to cloud. While cloud migration isn’t a new term and many people are migrating, there are a few things you should know before taking the leap. Migrating your database to the cloud is worth the hours of planning, sorting through data and running tests because if it’s not done right, it may come with more bad than good.

Last year, we released native tracing for AWS Lambda through Datadog APM to provide deep visibility into serverless functions and surface performance issues such as cold starts and errors, without any added latency. But Lambda functions are only one piece of the puzzle in a rapidly growing serverless ecosystem, which includes message queues, data streams, notification services, and more.

If you feel intimidated by Kubernetes’ complexity but still need to modernize your business applications with containers, rest assured you’re not the only one. The container orchestration platform solves many problems but also creates new ones, so read on to find out about a new approach that can help you get just the benefits.

Cloud API logs are a significant blind spot for many organizations and often factor into large-scale, publicly announced data breaches. They pose several challenges to security teams: For all of these reasons, cloud API logs are resistant to conventional threat detection and hunting techniques.

Each day, more and more companies consider opting for cloud-based solutions, and they almost always end up adopting them to some extent. While the increasing popularity of cloud services may be a significant factor in accelerating the adoption rate of cloud-based solutions, some individuals remain skeptical of migrating their applications to the cloud due to unfamiliar territory.