Operations | Monitoring | ITSM | DevOps | Cloud

Every enterprise collects and stores massive amounts of security and observability data but struggles to get value outside of operations and security teams. These datasets can offer enormous value to business operations and enterprise reporting teams if they have access to the data in their toolsets. BizOps needs to optimize batch planning and the enterprise reporting teams need to reconcile how many assets the enterprise owns versus the number it has under support contracts.

Gartner® has published the 2022 Magic Quadrant™ for APM and Observability, an annual report that evaluates vendors in this category. We’re honored that Datadog has been recognized as a “Leader” within this Magic Quadrant report for the second consecutive year, with the highest position for Ability to Execute.

The pace of change in the automotive industry is at an unprecedented level. Not only are cars quickly switching from fossil fuel to electric, but the vehicle itself also is playing an ever-increasing role in advanced driver-assistance systems (ADAS) to improve driving comfort, efficiency, and safety.

The main goal of optimization in Django projects is to make it fast to perform database queries by ensuring that your projects run by making the best use of system resources. A properly optimized database will reduce the response time hence a better user experience. In this 4 part series, you will learn how to optimize the different areas of your Django application. This part will focus on optimizing the database for speed in Django applications.

The fact that data centers have evolved a lot is undeniable. This has enabled storage evolution and the execution of online applications. Now we often talk about hybrid clouds. *Yes, we don’t even take the time to explain what digital clouds are anymore and we even assume that everyone has their own, small but they have them.But when it comes to doing things big, it’s unavoidable to mention the giant Google Cloud®!

The IT Operations space has a ton of recent advancements, and arguably the most elusive Observability unicorn for many organizations has got to be "AIOps," perhaps with "proactive monitoring" coming in as a close second place. You may be thinking.

As systems become more complex and distributed, the total amount of machine data put off by those systems continues to skyrocket. While teams may need access to an ever-increasing scope of machine data to gain insights into their increasingly complicated systems, that same need to access an increasingly large amount of data also creates cost concerns. Those concerns can grow into cost emergencies quickly.

Every month, our team works on two major fronts: shipping new features asked by users and iterating on shipped features to make them better for existing users. Last month, our team worked closely with users to ship a lot of product improvements both in UI and backend performance. Alongside that, we have been working on metrics builder and log management, two major feature upgrades to SigNoz.

Given the strategic importance of the cloud and size of cloud expenditures, it’s critical for enterprises to have solid controls in place to manage it all. According to our latest research, however, while most organizations agree with that sentiment, very few have put it into practice. There are distinct but related disciplines that come into play: FinOps and cloud governance. In this two-part series, we explore current state of each.