Operations | Monitoring | ITSM | DevOps | Cloud

In an era where digital infrastructures are increasingly hybrid, the ability to efficiently monitor, analyze, and act on vast amounts of operational data is a significant challenge. According to Gartner, the surge in data volumes, with some workloads producing petabytes of telemetry annually, has led to heightened complexity and soaring costs—potentially exceeding $10 million annually for large enterprises.

The Domain Name System (DNS) is often described as the address book of the Internet. A and AAAA records map a human-friendly hostname like honeybadger.io to some machine-friendly IP address like 104.198.14.52. Other types of DNS records also exist; in particular, CNAME records are records that map a hostname to some other hostname, thereby delegating IP resolution to the latter.

In the IT infrastructure serving increasingly digitized enterprises, the criticality of network quality of service is more than evident to ensure connectivity to everyone at any time. System and network administrators need to understand which technology enables efficient, reliable, and lowest latency data transmission between IT applications and services.

No matter how well businesses run, team leads, or project managers are always searching for ways to run business operations faster and more efficiently. Even when projects and management plan effectively, processes can still become stuck, face delays, or data becomes disorganized.

As organizations continue to become more reliant on distributed and hybrid workforces, the need for comprehensive data collection across every endpoint—servers, applications, desktops, and laptops—has never been more critical. But let’s be real: agents can be a total headache. That’s where Cribl Edge comes in, now with support for desktops and laptops (in preview)!

Organizations generate, collect, and store vast amounts of telemetry data. With this data comes the growing responsibility to ensure compliance with various regulations, from GDPR to HIPPA. Data compliance ensures data is handled, stored, and processed according to laws and standards protecting personal information. But what makes compliance regulations scary is that it’s ever-changing and rules vary across industries, making it complex to manage.

Amazon Web Services (AWS) offers several native tools for reporting and cost optimization. Among them is AWS Budgets, a service that enables users to set spending and usage limits on their AWS resources. It also schedules reports with regular updates on actual or forecasted costs, ensuring users are informed of usage. However, AWS Budgets is a budgeting tool and has limitations when it comes to comprehensive AWS cost control.

Ever need to do some math during policy evaluation? Sometimes configuration settings are based on available resources. For example, what if you want to calculate the size of shared buffers to be 25% of your available memory? Let’s write some policy. First, we need to figure out how much memory we have. Let’s parse this out from /proc/meminfo: So, we have 65505464 kB of memory in total. Knowing that we can use eval() to calculate what 25% is. eval() can also be used to test truthfulness.