The latest News and Information on Cloud monitoring, security and related technologies.
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.
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?
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.
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.
When you are running cloud-based services as part of your overall business operations, it becomes necessary to monitor your cloud operations for evaluating the usage and efficiency of the cloud services, applications, and infrastructure. Cloud monitoring also lets you watch for threats and be mindful of cyber-attacks. Here is a brief rundown on how best to monitor cloud services and some tips to make it more efficient and useful.
