Operations | Monitoring | ITSM | DevOps | Cloud

datadog

Analyze cloud costs with flexible spreadsheets in Datadog Sheets

May 6, 2026 By Katherine Broner In Datadog
Cloud cost data is most useful when teams can adapt it to their own reporting and planning needs. In addition to viewing cost breakdowns, FinOps teams often need to calculate forecasts, reshape datasets, and present tailored views to finance and leadership teams. In many workflows, those steps happen outside the observability platform. Once the data is exported, it quickly becomes outdated and requires repeated manual updates.
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How to Measure your Most Expensive Milliseconds

May 6, 2026 By Datadog In Datadog
In the fast-paced world of mobile development, reliability rarely fails with a loud crash; instead, it degrades quietly through micro-regressions that erode user trust and engagement. While most companies track backend health and API latency, they often fly blind regarding the actual screen-level responsiveness that defines the true user experience. When Expedia Group underwent a major technical evolution, the team realized they lacked a consistent baseline to compare performance across platforms, leaving them unable to validate improvements before rollout.
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Monitor and optimize Supabase query performance with Datadog Database Monitoring

May 4, 2026 By Kyra Abbu In Datadog
Built on Postgres, Supabase is an open source, all-in-one backend platform for developers who want to ship applications without managing infrastructure. This makes it especially popular with frontend developers and vibe coders who may have little to no database expertise. Datadog's Supabase integration provides high-level infrastructure metrics, but developers also need query-level visibility to easily diagnose, optimize, and trace performance issues back to their source.
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This Month in Datadog - April 2026

May 4, 2026 By Datadog In Datadog
In the latest episode of This Month in Datadog, Jeremy shares how to run autonomous Cloud SIEM investigations, remediate vulnerabilities with auto-generated fixes, and use natural language to explore Datadog. Later, Sumedha Mehta spotlights the Datadog MCP Server, which gives AI agents real-time access to Datadog’s observability data. Then, Chetan Sharma walks through Datadog Experiments, which measures how product changes impact the user journey.
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Add dynamically updating context to logs with Reference Tables and Observability Pipelines

May 1, 2026 By Micah Kim In Datadog
Security and platform engineering teams rely on context-rich logs to investigate threats, prioritize incidents, and meet compliance requirements. Context is often stored separately from applications that generate logs, in sources like threat intelligence feeds in Snowflake, asset lists in Amazon S3, ownership data in ServiceNow CMDB, and risk scores produced in Databricks.
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Test network paths with TCP, UDP, and ICMP in Datadog

Apr 23, 2026 By Addie Beach In Datadog
When developers and SREs design application tests, they often prioritize user workflows and API availability. Extending that suite with network tests that match your app’s traffic protocols can reveal whether issues originate in the network or application layer. In this post, we’ll explore how you can design effective network tests using the Transmission Control Protocol (TCP), User Datagram Protocol (UDP), or Internet Control Message Protocol (ICMP), including.
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The product signal latency gap slowing your growth

Apr 23, 2026 By Adam Virani In Datadog
Organizations often call product managers the CEOs of the product. But PMs know that’s a myth. When a CEO wants a status report, they get one immediately. They don’t need to negotiate for engineering time, reconcile conflicting project priorities, or wait for a data scientist to find a gap in their schedule. For most PMs, simply understanding the state of the product is where growth can stall.
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Turn developer feedback into operational insight with Datadog Forms and Sheets

Apr 22, 2026 By Reva Ranka In Datadog
Engineering organizations rely heavily on developer feedback to improve internal platforms, tooling, and processes. However, that feedback is often scattered across disconnected systems such as external forms, spreadsheets, chat threads, and documentation tools. Because these systems are separate from operational data, teams struggle to correlate developer sentiment with measurable performance or reliability outcomes.
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Identify and fix code issues faster with Datadog's Azure DevOps Source Code integration

Apr 21, 2026 By Eric Metaj In Datadog
Developers and SREs who rely on Microsoft Azure DevOps often face fragmented workflows when investigating issues or reviewing code quality. Troubleshooting an error can require jumping between observability tools and source code repositories as you manually connect traces, stack frames, and commits. At the same time, security vulnerabilities, misconfigurations, and flaky tests may go undetected until later stages of the software delivery life cycle (SDLC), where they are more costly to fix.
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Bringing observability data hosting to the UK on AWS

Apr 21, 2026 By Geoffrey Carlisle In Datadog
UK organizations are increasingly required to design systems that account for data residency requirements, ensuring that operational data remains within national boundaries. Many teams already run their applications on AWS infrastructure in the UK, but telemetry data can still be processed outside the region, creating gaps in visibility. Datadog’s upcoming UK availability zone solves this by keeping telemetry data in the same region as the workloads that generate it.
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