Operations | Monitoring | ITSM | DevOps | Cloud

At Datadog, we have always been deeply involved with open source software—producing it, using it, and contributing to it. Our Agent, tracers, SDKs, and libraries have been open source from the beginning, giving our customers the flexibility to extend our tools for their own needs. The transparency of our open source components also allows them to fully audit the Datadog software that is running on their systems. But our commitment to open source only starts there.

Data growth has significantly out-pacing budgets; the products we use, have to do more. This is where optimization comes into play. Generally, optimization is associated with reduction which may be intimidating…what if something important is reduced? How can you identify what should be reduced? Reduction isn’t about removing context, but about removing repetitive data, meaningless fields, or even flattening JSON.

The observability and cybersecurity sector is chock full of providers from startups like StateStack and Coralogix to established organizations like Datadog, Sumo Logic and Splunk, offering solutions with capabilities of various depth and breadth that are solving the tough problems of application reliability and security.

Traditional data center networking can’t meet the needs of today’s AI workload communication. We need a different networking paradigm to meet these new challenges. In this blog post, learn about the technical changes happening in data center networking from the silicon to the hardware to the cables in between.

The shift from traditional monitoring to observability is widespread, and necessary. It's the way we make sense of increasingly complex and distributed systems. But when we capture all this data at scale... what do we do with it all? If this data itself had inherent value, we’d all be rich. But in the real world data does not provide us value until we can act on what it tells us.

PromCon, the annual Prometheus community conference, is around the corner, and this year I’ll have exciting news to share from the Prometheus Java community: The highly anticipated 1.0.0 version of the Prometheus Java client library is here! At Grafana Labs, we’re big proponents of Prometheus. And as a maintainer of the Prometheus Java client library, I highly appreciate the support, as it helps us to drive innovation in the Prometheus community.

A zero-day vulnerability (CVE-2023-5129) in the WebP image library is being actively exploited, putting major browsers and scores of additional apps at risk.

Percepio Tracealyzer is available for many popular real-time operating systems (RTOS), including FreeRTOS, Zephyr, and Azure RTOS ThreadX, and also for Linux. But what if you want to use it for another RTOS, one that Percepio doesn’t provide an integration for? Then you’ve been out of luck—until now.

The business challenges organizations face today are enormous: increased efficiency, lower costs, supply chain resilience, revenue growth, talent retention, and digital fragmentation. A modern enterprise needs an adaptable operating model to support its business goals. This requires a range of data, analytical, and AI capabilities to reach the desired business outcomes—from simple to cutting edge.

While the cloud is recognized as more secure than on-premises servers and infrastructures, it does come with the often talked about shared responsibility model. Cloud providers are responsible for security ‘of’ the cloud, while their clients are responsible for security ‘in’ the cloud. It’s ‘differently secure’, rather than the traditionally secure organizations have been used to when working with on-premises environments.