Operations | Monitoring | ITSM | DevOps | Cloud

Imagine you’re the protector of a castle. Your walls are tall, the gates are strong, and the guards are well-trained. But what if an intruder was still able to slip past your defenses? Even with the best security tools, not every threat will be caught. Threat hunting is the proactive approach to finding attackers that might have bypassed your defenses.

The Business Activity Monitoring (BAM) module is designed to shift support “left,” meaning it empowers support operators to identify and address issues earlier in the process by providing them with a business-friendly view of the underlying complex infrastructure. This makes it easier for operators to understand and manage critical processes without needing to have expert skills in the technical complexities of Azure.

In today’s fast-paced and competitive markets, staying ahead isn’t just a luxury—it’s a necessity. However, keeping tabs on every move your competitors make can be overwhelming. This is where competitive intelligence (CI) plays a crucial role. CI involves tracking your competitors’ strategies, pricing models, and trends to gain insights that allow you to make informed business decisions.

Dealing with disruptions from third-party providers can really disrupt your business operations. As our IT infrastructures become more complex, managing these outages can be quite a headache. If you're a site reliability engineer (SRE) looking for a smoother way to handle these incidents, you'll want to check out the new Rootly and IsDown integration. Rootly is an incident management system that seriously speeds up business response times.

Observability means you know what’s happening in your software systems, because they tell you. They tell you with telemetry: data emitted just for the people developing and operating the software. You already have telemetry–every log is a data point about something that happened. Structured logs or trace spans are even better, containing many pieces of data correlated in the same record. But you want to start from what you have, then improve it as you improve the software.

As the number of distinct sources generating logs across systems and applications grows, teams face the challenge of normalizing log data at scale. This challenge can manifest when you’re simply looking to leverage logs “off-the-shelf” for investigations, dashboards, or reports–especially when you don’t control the content and structure of certain logs (like those collected from third-party applications and platforms).

Chances are, you've heard one of the main promises of serverless compute: "you only pay for what you use". While convenient when starting a new project, once you start to get continuous usage on that compute, you start to realize you're paying a hefty premium for that convenience. If you're using AWS Lambda like I am, chances are that "for what you use" part isn't completely true either.

In 2020, we introduced the GitHub data source plugin for Grafana, helping organizations visualize and gain deeper insights into their use of the popular version control and collaboration platform. Since then, thousands of users have installed the data source, and we’ve been working hard to extend its capabilities and make it even easier to use.

Discover the key differences between Datadog and Grafana to find the ideal monitoring tool that fits your needs and budget.