Operations | Monitoring | ITSM | DevOps | Cloud

datadog

Unify your OpenTelemetry and Datadog experience with the embedded OTel Collector in the Agent

Jun 26, 2024 By Lutao Xie In Datadog
OpenTelemetry (OTel) is an open source, vendor-neutral observability solution that consists of a suite of components—including APIs, SDKs, and the OTel Collector—that allow teams to monitor their applications and services in a standardized format. OTel defines this data via the OpenTelemetry Protocol (OTLP), a standard for the encoding and transfer of telemetry data that organizations can use to collect, process, and export telemetry and route it to observability backends, such as Datadog.
Read Post
datadog

Monitor, troubleshoot, improve, and secure your LLM applications with Datadog LLM Observability

Jun 26, 2024 By Thomas Sobolik In Datadog
Organizations across all industries are racing to adopt LLMs and integrate generative AI into their offerings. LLMs have been demonstrably useful for intelligent assistants, AIOps, and natural language query interfaces, among many other use cases. However, running them in production and at an enterprise scale presents many challenges.
Read Post
datadog

Track the status of all your SLOs in Datadog

Jun 24, 2024 By Meghan Jordan In Datadog
Service level objectives, or SLOs, are a key part of the site reliability engineering toolkit. SLOs provide a framework for defining clear targets around application performance, which ultimately help teams provide a consistent customer experience, balance feature development with platform stability, and improve communication with internal and external users.
Read Post
datadog

Best practices for managing your SLOs with Datadog

Jun 24, 2024 By Mark Azer In Datadog
Collaboration and communication are critical to the successful implementation of service level objectives. Development and operational teams need to evaluate the impact of their work against established service reliability targets in order to improve their end user experience. Datadog simplifies cross-team collaboration by enabling everyone in your organization to track, manage, and monitor the status of all of their SLOs and error budgets in one place.
Read Post
datadog

SLOs 101: How to establish and define service level objectives

Jun 24, 2024 By Mark Azer In Datadog
In recent years, organizations have increasingly adopted service level objectives, or SLOs, as a fundamental part of their site reliability engineering (SRE) practice. Best practices around SLOs have been pioneered by Google—the Google SRE book and a webinar that we jointly hosted with Google both provide great introductions to this concept. In essence, SLOs are rooted in the idea that service reliability and user happiness go hand in hand.
Read Post
datadog

Troubleshoot infrastructure faster with Recent Changes

Jun 21, 2024 By Sriram Raman In Datadog
Infrastructure changes often trigger incidents, but troubleshooting these incidents is challenging when responders have to navigate through multiple tools to correlate telemetry with configuration changes. This lack of unified observability leads to longer mean time to resolution (MTTR), greater operational stress, and ultimately, negative business outcomes.
Read Post
datadog

Troubleshoot infrastructure issues faster with Resource Changes

Jun 21, 2024 By Sriram Raman In Datadog
Infrastructure changes often trigger incidents, but troubleshooting these incidents is challenging when responders have to navigate through multiple tools to correlate telemetry with configuration changes. This lack of unified observability leads to longer mean time to resolution (MTTR), greater operational stress, and ultimately, negative business outcomes.
Read Post
datadog

Diagnose runtime and code inefficiencies in production by using Continuous Profiler's timeline view

Jun 20, 2024 By Guillaume Turbat In Datadog
When you face issues like reduced throughput or latency spikes in your production applications, determining the cause isn’t always straightforward. These kinds of performance problems might not arise for simple reasons such as under-provisioned resources; often, the root of the problem lies deep within an application’s runtime execution.
Read Post
datadog

Troubleshoot and optimize data processing workloads with Data Jobs Monitoring

Jun 20, 2024 By Fionce Siow In Datadog
Data is central to any business: it powers mission-critical applications, informs business decisions, and supports the growing adoption of AI/ML models. As a result, data volumes are only increasing, and teams rely on engines like Apache Spark and managed platforms like Databricks or Amazon EMR to process this data at scale.
Read Post

Copyright © 2026 OpsMatters™. All rights reserved.