In the August episode of This Month in Datadog, Jeremy shares how you can make more informed cloud cost decisions, gain insights into your LiteLLM-powered applications, and secure Kubernetes infrastructure with Datadog Workload Protection. Later in the episode, Danny puts the spotlight on Datadog Kubernetes Autoscaling, which helps you deliver cost savings without sacrificing performance.
Also, you’ll learn about our upcoming Datadog Summits, free events where you can grow your skills, network with peers, or learn about the latest innovations in AI, monitoring, security, and more.
New features
Balance costs and performance with Datadog Kubernetes Autoscaling
Overprovisioned workloads are a challenge for every organization. With Datadog Kubernetes Autoscaling, you’ll get scaling recommendations and automations to help you reduce costs without sacrificing performance. Learn more about Datadog Kubernetes Autoscaling in this blog post.
Make more informed spending decisions with new Cloud Cost Management features
Datadog has introduced two new features to bring spending under control. When costs spike unexpectedly, it can be hard to pinpoint the cause. Cloud Cost Anomalies automatically surfaces who or what is driving AWS cost anomalies so you can respond quickly. Additionally, now you can add budgets to dashboards, which helps FinOps and engineering teams track their spending, stay aligned, and act before costs grow out of hand.
To learn more, read our release notes about Cloud Cost Anomalies and adding budgets to dashboards.
Monitor and optimize LiteLLM-powered applications with our LiteLLM integration
Managing requests across multiple LLM providers can make it difficult to monitor application performance and reliability. With Datadog’s native LiteLLM integration, you can capture LLM requests, trace activity across your stack, and gain visibility into your LiteLLM-powered applications. There’s a lot more to get to, so be sure to read our blog post on our integration with LiteLLM.
Gain visibility into Kubernetes user sessions with Datadog Workload Protection
Tracking user activity in Kubernetes can be challenging, especially when dealing with remote activity and user accounts. With Datadog Workload Protection, which already detects threats in Amazon EC2 instances and Docker containers, you can now gain visibility into Kubernetes user sessions. This capability lets you track remote users with privileged access, spot suspicious activity like excessive pod or cluster activity in a short period of time, and strengthen the security of your Kubernetes workloads. To learn more, read our blog post on Workload Protection.
Additional updates
Other features and updates released this month include:
- Start collaborating more quickly during incidents by launching Google Meet calls directly from Datadog
- Resolve errors faster by identifying which team owns the affected code
- Easily manage Agent configurations by defining policies with Terraform
- Measure the availability of your frontend application with metrics included in RUM without Limits
- Prevent critical issues from slipping through the cracks with monitor notification rules
See you next month
This Month in Datadog is a monthly roundup of our latest features, product announcements, events, and more. Subscribe to our YouTube channel to get notified when future episodes go live.
In the meantime, check out our release notes for a full list of new features and updates, or see them in action by logging onto the Datadog platform or signing up for a 14-day free trial.
See you next month!
