Operations | Monitoring | ITSM | DevOps | Cloud

Getting the right people working in the CoPE is crucial to success because these change agents must limber up the organization and promote the flexibility necessary to perform resilience. We’ll look for teammates who share enough in common to work well together, but who don’t necessarily perfectly overlap so that they can play off each other’s strengths.

The more customers I talk to, the more I see a trend toward wanting a low-cost vendor-agnostic data lake. Customers want the freedom to store their data long-term and typically look to object stores from AWS, Azure, and Google Cloud. To optimize for data access, users will partition their data into directories to optimize for use cases such as Cribl Replay and Cribl Search. Only relevant files will be accessed for rehydration or search by partitioning data.

To win the space race, aerospace and aviation companies must be fast. The end-to-end cycle of testing, visualizing test data, and making improvements demands swiftness, especially when a single launch yields billions of data points. It starts with real-time access to data. Real-time data analysis with nanosecond precision is crucial for monitoring environmental and habitat conditions when lives are at stake. Speeding up the iteration pipeline is essential but not sufficient. Cost efficiency matters too.

The internet is basically just a bunch of websites calling each other. You make a call to some service, that service calls you back, and then that service goes down and ruins your afternoon. Requests, our latest addition to Insights, is a place to see, understand, track, and improve the behavior of outgoing HTTP requests.

Azure Structured Query Language (SQL) has 18 different deployment options, service tiers, compute models, and two different pricing models: vCores and Database Transaction Units (DTU). Because of these complexities, it’s nearly impossible to project monthly budgets! This guide will explain the common Azure SQL pricing configurations and offer tips on optimizing your cloud budget.

Republicans and Democrats don’t agree on much, but when it comes to generative AI, they’ve managed to find 32 billion points of agreement. On May 15, a bipartisan group of senators unveiled a roadmap that would have the U.S. government spending $32 billion annually by 2026 to drive AI-related innovation. The U.S. isn’t alone; AI spending in India is growing at an annual average rate of 31.5%, and will exceed $5 billion by 2027.

The cloud offers on-demand computing resources, the ability to increase or reduce usage as needed, and the flexibility to pay only for what you use. But if you’ve been building on the cloud for some time, you know that the last part isn’t exactly straightforward. For example, leaving aggressive product features, engineering sessions, or testing projects unchecked can quickly waste thousands, even millions of dollars in a matter of days.

The business of observability is all about data: what you’re observing in the data, how you’re visualizing it, what it indicates about the state of your environment, and how to address issues that may occur. Creating your own perspective for observability, and understanding what you’re seeing, can be difficult.

The FCC recently published a proposal to require nine major US internet service providers to deploy RPKI Route Origin Validation (ROV). In this post, we’ll look at the proposal and where the nine service providers currently stand with respect to ROV.