Operations | Monitoring | ITSM | DevOps | Cloud

We’ve all been there. You’re working through some rather frustrating blockers during an incident only to discover that you don’t own the dependency at fault. Or, you’ve been pounding away at an issue when a fellow engineer reaches out and asks if your service is affected by some particularly gnarly database failure they’re seeing. But then what? Do you merge efforts and work in parallel or head for a coffee break while the issue gets attacked upstream?

A fairly common claim among website uptime monitoring services is that downtime costs $5600 per minute. Chances are, you'll have one of two reactions to this claim: The reality of what downtime costs your business lies somewhere in between. As a company that runs 3.6 million uptime checks per week, we have a bit of insight into the cost of downtime, so if you're curious - read on.

GitLab is a DevSecOps platform that helps engineering teams automate software delivery. Using GitLab, teams can easily collaborate on projects and quickly deliver application code with robust CI/CD, security, and testing features. Datadog’s GitLab integration enables you to monitor your GitLab instances alongside the rest of your infrastructure by collecting GitLab metrics, logs, and service checks.

With the growing utilization of AI, modern business applications rely more and more on machine learning (ML) models. But the complexity of these models poses significant challenges to data scientists, engineers, and MLOps teams seeking to maintain and optimize performance.

In Elasticsearch 8.8, we’re introducing the reroute processor in technical preview that makes it possible to send documents, such as logs, to different data streams, according to flexible routing rules. When using Elastic Observability, this gives you more granular control over your data with regard to retention, permissions, and processing with all the potential benefits of the data stream naming scheme. While optimized for data streams, the reroute processor also works with classic indices.

Application Programming Interfaces (APIs) are a crucial building block in modern software development, allowing applications to communicate with each other and share data consistently. APIs are used to exchange data inside and between organizations, and the widespread adoption of microservices and asynchronous patterns boosted API adoption inside the application itself.

Data is like the oxygen that fuels the digital revolution. While critical and readily available, data becomes dangerous when misused. Leaders and users alike are becoming concerned with how organizations can protect data, especially personal information. It’s a complex and dynamic challenge, making it harder than ever to share data to the extent needed to facilitate innovation and research. To meet these challenges, many organizations are leveraging federated data systems.