Datadog has made a name for itself as a popular cloud-native application performance monitoring tool, measuring a system’s health and status based on the telemetry data it generates. This telemetry includes machine-generated data, such as logs, metrics and traces. Cloud based applications and infrastructure generate millions (even billions) of logs – and analyzing them can generate a wealth of insights for DevOps, security, product teams and more.

Is your organization currently relying on Amazon CloudWatch for log management and log analytics in the cloud? While CloudWatch delivers on many promises for AWS infrastructure monitoring, it isn’t the only log analytics solution – and may not even be your best option. Fast-growing organizations should consider supplementing CloudWatch with innovative alternatives offering better performance at scale, superior cost economics, reduced complexity and enhanced data access in the cloud.

Armed with a Ph.D. from UC San Diego, our guest started off with internships at Google and Microsoft before gaining valuable experience as a VP and a highly sought-after consultant for startups and SMBs. Now he’s one of the world’s foremost experts on wrangling vast data sets and maximizing efficiency.

How can you derive value from data? One answer is to generate alerts based on the data. Alerts help your team stay on top of a variety of potential challenges – like application performance issues, security risks, disruptions to the CI/CD delivery chain and beyond. ChaosSearch’s flexible alerting system makes it easy to generate alerts relevant to your organization’s needs.

If you’re an engineer, it’s probably easy enough to appreciate the technical value of DevOps. DevOps makes software delivery faster, increases agility, improves collaboration and more. That being said, this is likely not the case for business professionals. They don’t always see the value of DevOps as clearly from their perspective. After all, even if you adopt the best DevOps tools and design optimal DevOps processes, there’s no guarantee that DevOps will drive business value.

Today, virtually everyone who manages infrastructure or applications relies on logging to understand what is happening within their environments. But some teams do logging better than others. Although there is no one right – or wrong – approach to log management, there are a variety of logging mistakes that engineers commonly make when deciding what to log, how to log it, and how to work with their log data.

ChaosSearch activates your cloud object storage for analytics at scale via multi-API access, with no data movement, no sharding nor re-indexing, and no data retention trade-offs. To help engineers and IT leaders experience the power of ChaosSearch for themselves, we’ve made it easier than ever to get started with our free trial experience.

The cybersecurity talent shortage is real. As of December 2021, a job-tracking database from the U.S. Commerce Department showed nearly 600,000 unfilled cybersecurity positions. And a 2021 study found that 57% of cybersecurity professionals worked at organizations that have been directly impacted by the cybersecurity talent shortage. Even so, many organizations want to “shift security left” or build security best practices earlier into the software development lifecycle (SDLC).

IT is messy stuff. Enterprise applications and devices rely on a web of interdependent clouds, networks, and containers. IT operations (ITOps), development operations (DevOps), and cloud operations (CloudOps) engineers work hard to manage this mess. If they succeed, they create a stable, agile IT environment that makes their enterprise more productive. If they fail, their enterprise becomes less productive.

Does your team know how to use data analytics to their advantage? For the vast majority of companies, the answer may be “no.” According to Accenture, only 21% of people are confident in their data literacy skills, and just 32% of companies have realized tangible, measurable value from their data. While the definition of data literacy varies depending on who you ask, at its core, the term means equipping anyone in your organization to know how to use data in a business context.